A design strategy for autonomous systems

NASA Technical Reports Server (NTRS)

Forster, Pete

1989-01-01

Some solutions to crucial issues regarding the competent performance of an autonomously operating robot are identified; namely, that of handling multiple and variable data sources containing overlapping information and maintaining coherent operation while responding adequately to changes in the environment. Support for the ideas developed for the construction of such behavior are extracted from speculations in the study of cognitive psychology, an understanding of the behavior of controlled mechanisms, and the development of behavior-based robots in a few robot research laboratories. The validity of these ideas is supported by some simple simulation experiments in the field of mobile robot navigation and guidance.

Open Issues in Evolutionary Robotics.

PubMed

Silva, Fernando; Duarte, Miguel; Correia, Luís; Oliveira, Sancho Moura; Christensen, Anders Lyhne

2016-01-01

One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applicability of evolutionary robotics techniques for the synthesis of behavioral control, researchers have consistently been faced with a number of issues preventing the widespread adoption of evolutionary robotics for engineering purposes. In this article, we review and discuss the open issues in evolutionary robotics. First, we analyze the benefits and challenges of simulation-based evolution and subsequent deployment of controllers versus evolution on real robotic hardware. Second, we discuss specific evolutionary computation issues that have plagued evolutionary robotics: (1) the bootstrap problem, (2) deception, and (3) the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks. Finally, we address the absence of standard research practices in the field. We also discuss promising avenues of research. Our underlying motivation is the reduction of the current gap between evolutionary robotics and mainstream robotics, and the establishment of evolutionary robotics as a canonical approach for the engineering of autonomous robots.

Electroencephalography(EEG)-based instinctive brain-control of a quadruped locomotion robot.

PubMed

Jia, Wenchuan; Huang, Dandan; Luo, Xin; Pu, Huayan; Chen, Xuedong; Bai, Ou

2012-01-01

Artificial intelligence and bionic control have been applied in electroencephalography (EEG)-based robot system, to execute complex brain-control task. Nevertheless, due to technical limitations of the EEG decoding, the brain-computer interface (BCI) protocol is often complex, and the mapping between the EEG signal and the practical instructions lack of logic associated, which restrict the user's actual use. This paper presents a strategy that can be used to control a quadruped locomotion robot by user's instinctive action, based on five kinds of movement related neurophysiological signal. In actual use, the user drives or imagines the limbs/wrists action to generate EEG signal to adjust the real movement of the robot according to his/her own motor reflex of the robot locomotion. This method is easy for real use, as the user generates the brain-control signal through the instinctive reaction. By adopting the behavioral control of learning and evolution based on the proposed strategy, complex movement task may be realized by instinctive brain-control.

Adaptive Tracking Control for Robots With an Interneural Computing Scheme.

PubMed

Tsai, Feng-Sheng; Hsu, Sheng-Yi; Shih, Mau-Hsiang

2018-04-01

Adaptive tracking control of mobile robots requires the ability to follow a trajectory generated by a moving target. The conventional analysis of adaptive tracking uses energy minimization to study the convergence and robustness of the tracking error when the mobile robot follows a desired trajectory. However, in the case that the moving target generates trajectories with uncertainties, a common Lyapunov-like function for energy minimization may be extremely difficult to determine. Here, to solve the adaptive tracking problem with uncertainties, we wish to implement an interneural computing scheme in the design of a mobile robot for behavior-based navigation. The behavior-based navigation adopts an adaptive plan of behavior patterns learning from the uncertainties of the environment. The characteristic feature of the interneural computing scheme is the use of neural path pruning with rewards and punishment interacting with the environment. On this basis, the mobile robot can be exploited to change its coupling weights in paths of neural connections systematically, which can then inhibit or enhance the effect of flow elimination in the dynamics of the evolutionary neural network. Such dynamical flow translation ultimately leads to robust sensory-to-motor transformations adapting to the uncertainties of the environment. A simulation result shows that the mobile robot with the interneural computing scheme can perform fault-tolerant behavior of tracking by maintaining suitable behavior patterns at high frequency levels.

Evolution of Signaling in a Multi-Robot System: Categorization and Communication

NASA Astrophysics Data System (ADS)

Ampatzis, Christos; Tuci, Elio; Trianni, Vito; Dorigo, Marco

We use Evolutionary Robotics to design robot controllers in which decision-making mechanisms to switch from solitary to social behavior are integrated with the mechanisms that underpin the sensory-motor repertoire of the robots. In particular, we study the evolution of behavioral and communicative skills in a categorization task. The individual decision-making structures are based on the integration over time of sensory information. The mechanisms for switching from solitary to social behavior and the ways in which the robots can affect each other's behavior are not predetermined by the experimenter, but are aspects of our model designed by artificial evolution. Our results show that evolved robots manage to cooperate and collectively discriminate between different environments by developing a simple communication protocol based on sound signaling. Communication emerges in the absence of explicit selective pressure coded in the fitness function. The evolution of communication is neither trivial nor obvious; for a meaningful signaling system to evolve, evolution must produce both appropriate signals and appropriate reactions to signals. The use of communication proves to be adaptive for the group, even if, in principle, non-cooperating robots can be equally successful with cooperating robots.

Autonomous Shepherding Behaviors of Multiple Target Steering Robots.

PubMed

Lee, Wonki; Kim, DaeEun

2017-11-25

This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots' position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach.

Optimized Assistive Human-Robot Interaction Using Reinforcement Learning.

PubMed

Modares, Hamidreza; Ranatunga, Isura; Lewis, Frank L; Popa, Dan O

2016-03-01

An intelligent human-robot interaction (HRI) system with adjustable robot behavior is presented. The proposed HRI system assists the human operator to perform a given task with minimum workload demands and optimizes the overall human-robot system performance. Motivated by human factor studies, the presented control structure consists of two control loops. First, a robot-specific neuro-adaptive controller is designed in the inner loop to make the unknown nonlinear robot behave like a prescribed robot impedance model as perceived by a human operator. In contrast to existing neural network and adaptive impedance-based control methods, no information of the task performance or the prescribed robot impedance model parameters is required in the inner loop. Then, a task-specific outer-loop controller is designed to find the optimal parameters of the prescribed robot impedance model to adjust the robot's dynamics to the operator skills and minimize the tracking error. The outer loop includes the human operator, the robot, and the task performance details. The problem of finding the optimal parameters of the prescribed robot impedance model is transformed into a linear quadratic regulator (LQR) problem which minimizes the human effort and optimizes the closed-loop behavior of the HRI system for a given task. To obviate the requirement of the knowledge of the human model, integral reinforcement learning is used to solve the given LQR problem. Simulation results on an x - y table and a robot arm, and experimental implementation results on a PR2 robot confirm the suitability of the proposed method.

Controlling the autonomy of a reconnaissance robot

NASA Astrophysics Data System (ADS)

Dalgalarrondo, Andre; Dufourd, Delphine; Filliat, David

2004-09-01

In this paper, we present our research on the control of a mobile robot for indoor reconnaissance missions. Based on previous work concerning our robot control architecture HARPIC, we have developed a man machine interface and software components that allow a human operator to control a robot at different levels of autonomy. This work aims at studying how a robot could be helpful in indoor reconnaissance and surveillance missions in hostile environment. In such missions, since a soldier faces many threats and must protect himself while looking around and holding his weapon, he cannot devote his attention to the teleoperation of the robot. Moreover, robots are not yet able to conduct complex missions in a fully autonomous mode. Thus, in a pragmatic way, we have built a software that allows dynamic swapping between control modes (manual, safeguarded and behavior-based) while automatically performing map building and localization of the robot. It also includes surveillance functions like movement detection and is designed for multirobot extensions. We first describe the design of our agent-based robot control architecture and discuss the various ways to control and interact with a robot. The main modules and functionalities implementing those ideas in our architecture are detailed. More precisely, we show how we combine manual controls, obstacle avoidance, wall and corridor following, way point and planned travelling. Some experiments on a Pioneer robot equipped with various sensors are presented. Finally, we suggest some promising directions for the development of robots and user interfaces for hostile environment and discuss our planned future improvements.

Collective Behaviors of Mobile Robots Beyond the Nearest Neighbor Rules With Switching Topology.

PubMed

Ning, Boda; Han, Qing-Long; Zuo, Zongyu; Jin, Jiong; Zheng, Jinchuan

2018-05-01

This paper is concerned with the collective behaviors of robots beyond the nearest neighbor rules, i.e., dispersion and flocking, when robots interact with others by applying an acute angle test (AAT)-based interaction rule. Different from a conventional nearest neighbor rule or its variations, the AAT-based interaction rule allows interactions with some far-neighbors and excludes unnecessary nearest neighbors. The resulting dispersion and flocking hold the advantages of scalability, connectivity, robustness, and effective area coverage. For the dispersion, a spring-like controller is proposed to achieve collision-free coordination. With switching topology, a new fixed-time consensus-based energy function is developed to guarantee the system stability. An upper bound of settling time for energy consensus is obtained, and a uniform time interval is accordingly set so that energy distribution is conducted in a fair manner. For the flocking, based on a class of generalized potential functions taking nonsmooth switching into account, a new controller is proposed to ensure that the same velocity for all robots is eventually reached. A co-optimizing problem is further investigated to accomplish additional tasks, such as enhancing communication performance, while maintaining the collective behaviors of mobile robots. Simulation results are presented to show the effectiveness of the theoretical results.

Model learning for robot control: a survey.

PubMed

Nguyen-Tuong, Duy; Peters, Jan

2011-11-01

Models are among the most essential tools in robotics, such as kinematics and dynamics models of the robot's own body and controllable external objects. It is widely believed that intelligent mammals also rely on internal models in order to generate their actions. However, while classical robotics relies on manually generated models that are based on human insights into physics, future autonomous, cognitive robots need to be able to automatically generate models that are based on information which is extracted from the data streams accessible to the robot. In this paper, we survey the progress in model learning with a strong focus on robot control on a kinematic as well as dynamical level. Here, a model describes essential information about the behavior of the environment and the influence of an agent on this environment. In the context of model-based learning control, we view the model from three different perspectives. First, we need to study the different possible model learning architectures for robotics. Second, we discuss what kind of problems these architecture and the domain of robotics imply for the applicable learning methods. From this discussion, we deduce future directions of real-time learning algorithms. Third, we show where these scenarios have been used successfully in several case studies.

Distributed multirobot sensing and tracking: a behavior-based approach

NASA Astrophysics Data System (ADS)

Parker, Lynne E.

1995-09-01

An important issue that arises in the automation of many large-scale surveillance and reconnaissance tasks is that of tracking the movements of (or maintaining passive contact with) objects navigating in a bounded area of interest. Oftentimes in these problems, the area to be monitored will move over time or will not permit fixed sensors, thus requiring a team of mobile sensors--or robots--to monitor the area collectively. In these situations, the robots must not only have mechanisms for determining how to track objects and how to fuse information from neighboring robots, but they must also have distributed control strategies for ensuring that the entire area of interest is continually covered to the greatest extent possible. This paper focuses on the distributed control issue by describing a proposed decentralized control mechanism that allows a team of robots to collectively track and monitor objects in an uncluttered area of interest. The approach is based upon an extension to the ALLIANCE behavior-based architecture that generalizes from the domain of loosely-coupled, independent applications to the domain of strongly cooperative applications, in which the action selection of a robot is dependent upon the actions selected by its teammates. We conclude the paper be describing our ongoing implementation of the proposed approach on a team of four mobile robots.

Autonomous Shepherding Behaviors of Multiple Target Steering Robots

PubMed Central

Lee, Wonki; Kim, DaeEun

2017-01-01

This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots’ position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach. PMID:29186836

An Architecture for Controlling Multiple Robots

NASA Technical Reports Server (NTRS)

Aghazarian, Hrand; Pirjanian, Paolo; Schenker, Paul; Huntsberger, Terrance

2004-01-01

The Control Architecture for Multirobot Outpost (CAMPOUT) is a distributed-control architecture for coordinating the activities of multiple robots. In the CAMPOUT, multiple-agent activities and sensor-based controls are derived as group compositions and involve coordination of more basic controllers denoted, for present purposes, as behaviors. The CAMPOUT provides basic mechanistic concepts for representation and execution of distributed group activities. One considers a network of nodes that comprise behaviors (self-contained controllers) augmented with hyper-links, which are used to exchange information between the nodes to achieve coordinated activities. Group behavior is guided by a scripted plan, which encodes a conditional sequence of single-agent activities. Thus, higher-level functionality is composed by coordination of more basic behaviors under the downward task decomposition of a multi-agent planner

State Estimation for Tensegrity Robots

NASA Technical Reports Server (NTRS)

Caluwaerts, Ken; Bruce, Jonathan; Friesen, Jeffrey M.; Sunspiral, Vytas

2016-01-01

Tensegrity robots are a class of compliant robots that have many desirable traits when designing mass efficient systems that must interact with uncertain environments. Various promising control approaches have been proposed for tensegrity systems in simulation. Unfortunately, state estimation methods for tensegrity robots have not yet been thoroughly studied. In this paper, we present the design and evaluation of a state estimator for tensegrity robots. This state estimator will enable existing and future control algorithms to transfer from simulation to hardware. Our approach is based on the unscented Kalman filter (UKF) and combines inertial measurements, ultra wideband time-of-flight ranging measurements, and actuator state information. We evaluate the effectiveness of our method on the SUPERball, a tensegrity based planetary exploration robotic prototype. In particular, we conduct tests for evaluating both the robot's success in estimating global position in relation to fixed ranging base stations during rolling maneuvers as well as local behavior due to small-amplitude deformations induced by cable actuation.

Integrating sensorimotor systems in a robot model of cricket behavior

NASA Astrophysics Data System (ADS)

Webb, Barbara H.; Harrison, Reid R.

2000-10-01

The mechanisms by which animals manage sensorimotor integration and coordination of different behaviors can be investigated in robot models. In previous work the first author has build a robot that localizes sound based on close modeling of the auditory and neural system in the cricket. It is known that the cricket combines its response to sound with other sensorimotor activities such as an optomotor reflex and reactions to mechanical stimulation for the antennae and cerci. Behavioral evidence suggests some ways these behaviors may be integrated. We have tested the addition of an optomotor response, using an analog VLSI circuit developed by the second author, to the sound localizing behavior and have shown that it can, as in the cricket, improve the directness of the robot's path to sound. In particular it substantially improves behavior when the robot is subject to a motor disturbance. Our aim is to better understand how the insect brain functions in controlling complex combinations of behavior, with the hope that this will also suggest novel mechanisms for sensory integration on robots.

Evolutionary Fuzzy Control and Navigation for Two Wheeled Robots Cooperatively Carrying an Object in Unknown Environments.

PubMed

Juang, Chia-Feng; Lai, Min-Ge; Zeng, Wan-Ting

2015-09-01

This paper presents a method that allows two wheeled, mobile robots to navigate unknown environments while cooperatively carrying an object. In the navigation method, a leader robot and a follower robot cooperatively perform either obstacle boundary following (OBF) or target seeking (TS) to reach a destination. The two robots are controlled by fuzzy controllers (FC) whose rules are learned through an adaptive fusion of continuous ant colony optimization and particle swarm optimization (AF-CACPSO), which avoids the time-consuming task of manually designing the controllers. The AF-CACPSO-based evolutionary fuzzy control approach is first applied to the control of a single robot to perform OBF. The learning approach is then applied to achieve cooperative OBF with two robots, where an auxiliary FC designed with the AF-CACPSO is used to control the follower robot. For cooperative TS, a rule for coordination of the two robots is developed. To navigate cooperatively, a cooperative behavior supervisor is introduced to select between cooperative OBF and cooperative TS. The performance of the AF-CACPSO is verified through comparisons with various population-based optimization algorithms for the OBF learning problem. Simulations and experiments verify the effectiveness of the approach for cooperative navigation of two robots.

A bio-inspired auditory perception model for amplitude-frequency clustering (keynote Paper)

NASA Astrophysics Data System (ADS)

Arena, Paolo; Fortuna, Luigi; Frasca, Mattia; Ganci, Gaetana; Patane, Luca

2005-06-01

In this paper a model for auditory perception is introduced. This model is based on a network of integrate-and-fire and resonate-and-fire neurons and is aimed to control the phonotaxis behavior of a roving robot. The starting point is the model of phonotaxis in Gryllus Bimaculatus: the model consists of four integrate-and-fire neurons and is able of discriminating the calling song of male cricket and orienting the robot towards the sound source. This paper aims to extend the model to include an amplitude-frequency clustering. The proposed spiking network shows different behaviors associated with different characteristics of the input signals (amplitude and frequency). The behavior implemented on the robot is similar to the cricket behavior, where some frequencies are associated with the calling song of male crickets, while other ones indicate the presence of predators. Therefore, the whole model for auditory perception is devoted to control different responses (attractive or repulsive) depending on the input characteristics. The performance of the control system has been evaluated with several experiments carried out on a roving robot.

Progress in EEG-Based Brain Robot Interaction Systems

PubMed Central

Li, Mengfan; Niu, Linwei; Xian, Bin; Zeng, Ming; Chen, Genshe

2017-01-01

The most popular noninvasive Brain Robot Interaction (BRI) technology uses the electroencephalogram- (EEG-) based Brain Computer Interface (BCI), to serve as an additional communication channel, for robot control via brainwaves. This technology is promising for elderly or disabled patient assistance with daily life. The key issue of a BRI system is to identify human mental activities, by decoding brainwaves, acquired with an EEG device. Compared with other BCI applications, such as word speller, the development of these applications may be more challenging since control of robot systems via brainwaves must consider surrounding environment feedback in real-time, robot mechanical kinematics, and dynamics, as well as robot control architecture and behavior. This article reviews the major techniques needed for developing BRI systems. In this review article, we first briefly introduce the background and development of mind-controlled robot technologies. Second, we discuss the EEG-based brain signal models with respect to generating principles, evoking mechanisms, and experimental paradigms. Subsequently, we review in detail commonly used methods for decoding brain signals, namely, preprocessing, feature extraction, and feature classification, and summarize several typical application examples. Next, we describe a few BRI applications, including wheelchairs, manipulators, drones, and humanoid robots with respect to synchronous and asynchronous BCI-based techniques. Finally, we address some existing problems and challenges with future BRI techniques. PMID:28484488

Development of a multisensor-based bio-botanic robot and its implementation using a self-designed embedded board.

PubMed

Chang, Chung-Liang; Sie, Ming-Fong; Shie, Jin-Long

2011-01-01

This paper presents the design concept of a bio-botanic robot which demonstrates its behavior based on plant growth. Besides, it can reflect the different phases of plant growth depending on the proportional amounts of light, temperature and water. The mechanism design is made up of a processed aluminum base, spring, polydimethylsiloxane (PDMS) and actuator to constitute the plant base and plant body. The control system consists of two micro-controllers and a self-designed embedded development board where the main controller transmits the values of the environmental sensing module within the embedded board to a sub-controller. The sub-controller determines the growth stage, growth height, and time and transmits its decision value to the main controller. Finally, based on the data transmitted by the sub-controller, the main controller controls the growth phase of the bio-botanic robot using a servo motor and leaf actuator. The research result not only helps children realize the variation of plant growth but also is entertainment-educational through its demonstration of the growth process of the bio-botanic robot in a short time.

Comparative Study of SSVEP- and P300-Based Models for the Telepresence Control of Humanoid Robots.

PubMed

Zhao, Jing; Li, Wei; Li, Mengfan

2015-01-01

In this paper, we evaluate the control performance of SSVEP (steady-state visual evoked potential)- and P300-based models using Cerebot-a mind-controlled humanoid robot platform. Seven subjects with diverse experience participated in experiments concerning the open-loop and closed-loop control of a humanoid robot via brain signals. The visual stimuli of both the SSVEP- and P300- based models were implemented on a LCD computer monitor with a refresh frequency of 60 Hz. Considering the operation safety, we set the classification accuracy of a model over 90.0% as the most important mandatory for the telepresence control of the humanoid robot. The open-loop experiments demonstrated that the SSVEP model with at most four stimulus targets achieved the average accurate rate about 90%, whereas the P300 model with the six or more stimulus targets under five repetitions per trial was able to achieve the accurate rates over 90.0%. Therefore, the four SSVEP stimuli were used to control four types of robot behavior; while the six P300 stimuli were chosen to control six types of robot behavior. Both of the 4-class SSVEP and 6-class P300 models achieved the average success rates of 90.3% and 91.3%, the average response times of 3.65 s and 6.6 s, and the average information transfer rates (ITR) of 24.7 bits/min 18.8 bits/min, respectively. The closed-loop experiments addressed the telepresence control of the robot; the objective was to cause the robot to walk along a white lane marked in an office environment using live video feedback. Comparative studies reveal that the SSVEP model yielded faster response to the subject's mental activity with less reliance on channel selection, whereas the P300 model was found to be suitable for more classifiable targets and required less training. To conclude, we discuss the existing SSVEP and P300 models for the control of humanoid robots, including the models proposed in this paper.

Comparative Study of SSVEP- and P300-Based Models for the Telepresence Control of Humanoid Robots

PubMed Central

Li, Mengfan

2015-01-01

In this paper, we evaluate the control performance of SSVEP (steady-state visual evoked potential)- and P300-based models using Cerebot—a mind-controlled humanoid robot platform. Seven subjects with diverse experience participated in experiments concerning the open-loop and closed-loop control of a humanoid robot via brain signals. The visual stimuli of both the SSVEP- and P300- based models were implemented on a LCD computer monitor with a refresh frequency of 60 Hz. Considering the operation safety, we set the classification accuracy of a model over 90.0% as the most important mandatory for the telepresence control of the humanoid robot. The open-loop experiments demonstrated that the SSVEP model with at most four stimulus targets achieved the average accurate rate about 90%, whereas the P300 model with the six or more stimulus targets under five repetitions per trial was able to achieve the accurate rates over 90.0%. Therefore, the four SSVEP stimuli were used to control four types of robot behavior; while the six P300 stimuli were chosen to control six types of robot behavior. Both of the 4-class SSVEP and 6-class P300 models achieved the average success rates of 90.3% and 91.3%, the average response times of 3.65 s and 6.6 s, and the average information transfer rates (ITR) of 24.7 bits/min 18.8 bits/min, respectively. The closed-loop experiments addressed the telepresence control of the robot; the objective was to cause the robot to walk along a white lane marked in an office environment using live video feedback. Comparative studies reveal that the SSVEP model yielded faster response to the subject’s mental activity with less reliance on channel selection, whereas the P300 model was found to be suitable for more classifiable targets and required less training. To conclude, we discuss the existing SSVEP and P300 models for the control of humanoid robots, including the models proposed in this paper. PMID:26562524

Fuzzy logic based robotic controller

NASA Technical Reports Server (NTRS)

Attia, F.; Upadhyaya, M.

1994-01-01

Existing Proportional-Integral-Derivative (PID) robotic controllers rely on an inverse kinematic model to convert user-specified cartesian trajectory coordinates to joint variables. These joints experience friction, stiction, and gear backlash effects. Due to lack of proper linearization of these effects, modern control theory based on state space methods cannot provide adequate control for robotic systems. In the presence of loads, the dynamic behavior of robotic systems is complex and nonlinear, especially where mathematical modeling is evaluated for real-time operators. Fuzzy Logic Control is a fast emerging alternative to conventional control systems in situations where it may not be feasible to formulate an analytical model of the complex system. Fuzzy logic techniques track a user-defined trajectory without having the host computer to explicitly solve the nonlinear inverse kinematic equations. The goal is to provide a rule-based approach, which is closer to human reasoning. The approach used expresses end-point error, location of manipulator joints, and proximity to obstacles as fuzzy variables. The resulting decisions are based upon linguistic and non-numerical information. This paper presents a solution to the conventional robot controller which is independent of computationally intensive kinematic equations. Computer simulation results of this approach as obtained from software implementation are also discussed.

Generic, scalable and decentralized fault detection for robot swarms.

PubMed

Tarapore, Danesh; Christensen, Anders Lyhne; Timmis, Jon

2017-01-01

Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system's capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation.

Generic, scalable and decentralized fault detection for robot swarms

PubMed Central

Christensen, Anders Lyhne; Timmis, Jon

2017-01-01

Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system’s capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation. PMID:28806756

Progress Report for the Robotic Intelligence Evaluation. Program Year 1: Developing Test Methodology for Anti-Rollover Systems

DTIC Science & Technology

2006-06-01

Scientific Research. 5PAM-Crash is a trademark of the ESI Group . 6MATLAB and SIMULINK are registered trademarks of the MathWorks. 14 maneuvers...Laboratory (ARL) to develop methodologies to evaluate robotic behavior algorithms that control the actions of individual robots or groups of robots...methodologies to evaluate robotic behavior algorithms that control the actions of individual robots or groups of robots acting as a team to perform a

Acquisition of Autonomous Behaviors by Robotic Assistants

NASA Technical Reports Server (NTRS)

Peters, R. A., II; Sarkar, N.; Bodenheimer, R. E.; Brown, E.; Campbell, C.; Hambuchen, K.; Johnson, C.; Koku, A. B.; Nilas, P.; Peng, J.

2005-01-01

Our research achievements under the NASA-JSC grant contributed significantly in the following areas. Multi-agent based robot control architecture called the Intelligent Machine Architecture (IMA) : The Vanderbilt team received a Space Act Award for this research from NASA JSC in October 2004. Cognitive Control and the Self Agent : Cognitive control in human is the ability to consciously manipulate thoughts and behaviors using attention to deal with conflicting goals and demands. We have been updating the IMA Self Agent towards this goal. If opportunity arises, we would like to work with NASA to empower Robonaut to do cognitive control. Applications 1. SES for Robonaut, 2. Robonaut Fault Diagnostic System, 3. ISAC Behavior Generation and Learning, 4. Segway Research.

Coordination of Distributed Fuzzy Behaviors in Mobile Robot Control

NASA Technical Reports Server (NTRS)

Tunstel, E.

1995-01-01

This presentation describes an approach to behavior coordination and conflict resolution within the context of a hierarchical architecture of fuzzy behaviors. Coordination is achieved using weighted decision-making based on behavioral degrees of applicability. This strategy is appropriate for fuzzy control of systems that can be represented by hierarchical or decentralized structures.

Affordance Templates for Shared Robot Control

NASA Technical Reports Server (NTRS)

Hart, Stephen; Dinh, Paul; Hambuchen, Kim

2014-01-01

This paper introduces the Affordance Template framework used to supervise task behaviors on the NASA-JSC Valkyrie robot at the 2013 DARPA Robotics Challenge (DRC) Trials. This framework provides graphical interfaces to human supervisors that are adjustable based on the run-time environmental context (e.g., size, location, and shape of objects that the robot must interact with, etc.). Additional improvements, described below, inject degrees of autonomy into instantiations of affordance templates at run-time in order to enable efficient human supervision of the robot for accomplishing tasks.

Towards autonomous locomotion: CPG-based control of smooth 3D slithering gait transition of a snake-like robot.

PubMed

Bing, Zhenshan; Cheng, Long; Chen, Guang; Röhrbein, Florian; Huang, Kai; Knoll, Alois

2017-04-04

Snake-like robots with 3D locomotion ability have significant advantages of adaptive travelling in diverse complex terrain over traditional legged or wheeled mobile robots. Despite numerous developed gaits, these snake-like robots suffer from unsmooth gait transitions by changing the locomotion speed, direction, and body shape, which would potentially cause undesired movement and abnormal torque. Hence, there exists a knowledge gap for snake-like robots to achieve autonomous locomotion. To address this problem, this paper presents the smooth slithering gait transition control based on a lightweight central pattern generator (CPG) model for snake-like robots. First, based on the convergence behavior of the gradient system, a lightweight CPG model with fast computing time was designed and compared with other widely adopted CPG models. Then, by reshaping the body into a more stable geometry, the slithering gait was modified, and studied based on the proposed CPG model, including the gait transition of locomotion speed, moving direction, and body shape. In contrast to sinusoid-based method, extensive simulations and prototype experiments finally demonstrated that smooth slithering gait transition can be effectively achieved using the proposed CPG-based control method without generating undesired locomotion and abnormal torque.

Autonomous Mobile Platform for Research in Cooperative Robotics

NASA Technical Reports Server (NTRS)

Daemi, Ali; Pena, Edward; Ferguson, Paul

1998-01-01

This paper describes the design and development of a platform for research in cooperative mobile robotics. The structure and mechanics of the vehicles are based on R/C cars. The vehicle is rendered mobile by a DC motor and servo motor. The perception of the robot's environment is achieved using IR sensors and a central vision system. A laptop computer processes images from a CCD camera located above the testing area to determine the position of objects in sight. This information is sent to each robot via RF modem. Each robot is operated by a Motorola 68HC11E micro-controller, and all actions of the robots are realized through the connections of IR sensors, modem, and motors. The intelligent behavior of each robot is based on a hierarchical fuzzy-rule based approach.

A biologically inspired meta-control navigation system for the Psikharpax rat robot.

PubMed

Caluwaerts, K; Staffa, M; N'Guyen, S; Grand, C; Dollé, L; Favre-Félix, A; Girard, B; Khamassi, M

2012-06-01

A biologically inspired navigation system for the mobile rat-like robot named Psikharpax is presented, allowing for self-localization and autonomous navigation in an initially unknown environment. The ability of parts of the model (e.g. the strategy selection mechanism) to reproduce rat behavioral data in various maze tasks has been validated before in simulations. But the capacity of the model to work on a real robot platform had not been tested. This paper presents our work on the implementation on the Psikharpax robot of two independent navigation strategies (a place-based planning strategy and a cue-guided taxon strategy) and a strategy selection meta-controller. We show how our robot can memorize which was the optimal strategy in each situation, by means of a reinforcement learning algorithm. Moreover, a context detector enables the controller to quickly adapt to changes in the environment-recognized as new contexts-and to restore previously acquired strategy preferences when a previously experienced context is recognized. This produces adaptivity closer to rat behavioral performance and constitutes a computational proposition of the role of the rat prefrontal cortex in strategy shifting. Moreover, such a brain-inspired meta-controller may provide an advancement for learning architectures in robotics.

Robotic intelligence kernel

DOEpatents

Bruemmer, David J [Idaho Falls, ID

2009-11-17

A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

Development of a Multisensor-Based Bio-Botanic Robot and Its Implementation Using a Self-Designed Embedded Board

PubMed Central

Chang, Chung-Liang; Sie, Ming-Fong; Shie, Jin-Long

2011-01-01

This paper presents the design concept of a bio-botanic robot which demonstrates its behavior based on plant growth. Besides, it can reflect the different phases of plant growth depending on the proportional amounts of light, temperature and water. The mechanism design is made up of a processed aluminum base, spring, polydimethylsiloxane (PDMS) and actuator to constitute the plant base and plant body. The control system consists of two micro-controllers and a self-designed embedded development board where the main controller transmits the values of the environmental sensing module within the embedded board to a sub-controller. The sub-controller determines the growth stage, growth height, and time and transmits its decision value to the main controller. Finally, based on the data transmitted by the sub-controller, the main controller controls the growth phase of the bio-botanic robot using a servo motor and leaf actuator. The research result not only helps children realize the variation of plant growth but also is entertainment-educational through its demonstration of the growth process of the bio-botanic robot in a short time. PMID:22247684

Modeling of Continuum Manipulators Using Pythagorean Hodograph Curves.

PubMed

Singh, Inderjeet; Amara, Yacine; Melingui, Achille; Mani Pathak, Pushparaj; Merzouki, Rochdi

2018-05-10

Research on continuum manipulators is increasingly developing in the context of bionic robotics because of their many advantages over conventional rigid manipulators. Due to their soft structure, they have inherent flexibility, which makes it a huge challenge to control them with high performances. Before elaborating a control strategy of such robots, it is essential to reconstruct first the behavior of the robot through development of an approximate behavioral model. This can be kinematic or dynamic depending on the conditions of operation of the robot itself. Kinematically, two types of modeling methods exist to describe the robot behavior; quantitative methods describe a model-based method, and qualitative methods describe a learning-based method. In kinematic modeling of continuum manipulator, the assumption of constant curvature is often considered to simplify the model formulation. In this work, a quantitative modeling method is proposed, based on the Pythagorean hodograph (PH) curves. The aim is to obtain a three-dimensional reconstruction of the shape of the continuum manipulator with variable curvature, allowing the calculation of its inverse kinematic model (IKM). It is noticed that the performances of the PH-based kinematic modeling of continuum manipulators are considerable regarding position accuracy, shape reconstruction, and time/cost of the model calculation, than other kinematic modeling methods, for two cases: free load manipulation and variable load manipulation. This modeling method is applied to the compact bionic handling assistant (CBHA) manipulator for validation. The results are compared with other IKMs developed in case of CBHA manipulator.

Survival of falling robots

NASA Astrophysics Data System (ADS)

Cameron, Jonathan M.; Arkin, Ronald C.

1992-02-01

As mobile robots are used in more uncertain and dangerous environments, it will become important to design them so that they can survive falls. In this paper, we examine a number of mechanisms and strategies that animals use to withstand these potentially catastrophic events and extend them to the design of robots. A brief survey of several aspects of how common cats survive falls provides an understanding of the issues involved in preventing traumatic injury during a falling event. After outlining situations in which robots might fall, a number of factors affecting their survival are described. From this background, several robot design guidelines are derived. These include recommendations for the physical structure of the robot as well as requirements for the robot control architecture. A control architecture is proposed based on reactive control techniques and action-oriented perception that is geared to support this form of survival behavior.

Survival of falling robots

NASA Technical Reports Server (NTRS)

Cameron, Jonathan M.; Arkin, Ronald C.

1992-01-01

As mobile robots are used in more uncertain and dangerous environments, it will become important to design them so that they can survive falls. In this paper, we examine a number of mechanisms and strategies that animals use to withstand these potentially catastrophic events and extend them to the design of robots. A brief survey of several aspects of how common cats survive falls provides an understanding of the issues involved in preventing traumatic injury during a falling event. After outlining situations in which robots might fall, a number of factors affecting their survival are described. From this background, several robot design guidelines are derived. These include recommendations for the physical structure of the robot as well as requirements for the robot control architecture. A control architecture is proposed based on reactive control techniques and action-oriented perception that is geared to support this form of survival behavior.

Using qualitative maps to direct reactive robots

NASA Technical Reports Server (NTRS)

Bertin, Randolph; Pendleton, Tom

1992-01-01

The principal advantage of mobile robots is that they are able to go to specific locations to perform useful tasks rather than have the tasks brought to them. It is important therefore that the robot be used to reach desired locations efficiently and reliably. A mobile robot whose environment extends significantly beyond its sensory horizon must maintain a representation of the environment, a map, in order to attain these efficiency and reliability requirements. We believe that qualitative mapping methods provide useful and robust representation schemes and that such maps may be used to direct the actions of a reactively controlled robot. In this paper we describe our experience in employing qualitative maps to direct, through the selection of desired control strategies, a reactive-behavior based robot. This mapping capability represents the development of one aspect of a successful deliberative/reactive hybrid control architecture.

A Human-Robot Co-Manipulation Approach Based on Human Sensorimotor Information.

PubMed

Peternel, Luka; Tsagarakis, Nikos; Ajoudani, Arash

2017-07-01

This paper aims to improve the interaction and coordination between the human and the robot in cooperative execution of complex, powerful, and dynamic tasks. We propose a novel approach that integrates online information about the human motor function and manipulability properties into the hybrid controller of the assistive robot. Through this human-in-the-loop framework, the robot can adapt to the human motor behavior and provide the appropriate assistive response in different phases of the cooperative task. We experimentally evaluate the proposed approach in two human-robot co-manipulation tasks that require specific complementary behavior from the two agents. Results suggest that the proposed technique, which relies on a minimum degree of task-level pre-programming, can achieve an enhanced physical human-robot interaction performance and deliver appropriate level of assistance to the human operator.

Intelligent behavior generator for autonomous mobile robots using planning-based AI decision making and supervisory control logic

NASA Astrophysics Data System (ADS)

Shah, Hitesh K.; Bahl, Vikas; Martin, Jason; Flann, Nicholas S.; Moore, Kevin L.

2002-07-01

In earlier research the Center for Self-Organizing and Intelligent Systems (CSOIS) at Utah State University (USU) have been funded by the US Army Tank-Automotive and Armaments Command's (TACOM) Intelligent Mobility Program to develop and demonstrate enhanced mobility concepts for unmanned ground vehicles (UGVs). One among the several out growths of this work has been the development of a grammar-based approach to intelligent behavior generation for commanding autonomous robotic vehicles. In this paper we describe the use of this grammar for enabling autonomous behaviors. A supervisory task controller (STC) sequences high-level action commands (taken from the grammar) to be executed by the robot. It takes as input a set of goals and a partial (static) map of the environment and produces, from the grammar, a flexible script (or sequence) of the high-level commands that are to be executed by the robot. The sequence is derived by a planning function that uses a graph-based heuristic search (A* -algorithm). Each action command has specific exit conditions that are evaluated by the STC following each task completion or interruption (in the case of disturbances or new operator requests). Depending on the system's state at task completion or interruption (including updated environmental and robot sensor information), the STC invokes a reactive response. This can include sequencing the pending tasks or initiating a re-planning event, if necessary. Though applicable to a wide variety of autonomous robots, an application of this approach is demonstrated via simulations of ODIS, an omni-directional inspection system developed for security applications.

Folk-Psychological Interpretation of Human vs. Humanoid Robot Behavior: Exploring the Intentional Stance toward Robots.

PubMed

Thellman, Sam; Silvervarg, Annika; Ziemke, Tom

2017-01-01

People rely on shared folk-psychological theories when judging behavior. These theories guide people's social interactions and therefore need to be taken into consideration in the design of robots and other autonomous systems expected to interact socially with people. It is, however, not yet clear to what degree the mechanisms that underlie people's judgments of robot behavior overlap or differ from the case of human or animal behavior. To explore this issue, participants ( N = 90) were exposed to images and verbal descriptions of eight different behaviors exhibited either by a person or a humanoid robot. Participants were asked to rate the intentionality, controllability and desirability of the behaviors, and to judge the plausibility of seven different types of explanations derived from a recently proposed psychological model of lay causal explanation of human behavior. Results indicate: substantially similar judgments of human and robot behavior, both in terms of (1a) ascriptions of intentionality/controllability/desirability and in terms of (1b) plausibility judgments of behavior explanations; (2a) high level of agreement in judgments of robot behavior - (2b) slightly lower but still largely similar to agreement over human behaviors; (3) systematic differences in judgments concerning the plausibility of goals and dispositions as explanations of human vs. humanoid behavior. Taken together, these results suggest that people's intentional stance toward the robot was in this case very similar to their stance toward the human.

Robust Behavior-Based Control for Distributed Multi-Robot Collection Tasks

DTIC Science & Technology

2000-01-01

Department, University of Southern California, Los Angeles, CA 90089-0781 USA (e-mail: mataric @usc.edu) For a given task environment and set of robots...Press: Cambridge, Mas- sachusetts. [17] Richard T. Vaughan, Kasper Sty, Gaurav S. Sukhatme, and Maja J Mataric, \\Whistling in the dark : Cooperative

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot.

PubMed

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

PubMed Central

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world. PMID:26528176

Virtual spring damper method for nonholonomic robotic swarm self-organization and leader following

NASA Astrophysics Data System (ADS)

Wiech, Jakub; Eremeyev, Victor A.; Giorgio, Ivan

2018-04-01

In this paper, we demonstrate a method for self-organization and leader following of nonholonomic robotic swarm based on spring damper mesh. By self-organization of swarm robots we mean the emergence of order in a swarm as the result of interactions among the single robots. In other words the self-organization of swarm robots mimics some natural behavior of social animals like ants among others. The dynamics of two-wheel robot is derived, and a relation between virtual forces and robot control inputs is defined in order to establish stable swarm formation. Two cases of swarm control are analyzed. In the first case the swarm cohesion is achieved by virtual spring damper mesh connecting nearest neighboring robots without designated leader. In the second case we introduce a swarm leader interacting with nearest and second neighbors allowing the swarm to follow the leader. The paper ends with numeric simulation for performance evaluation of the proposed control method.

Bio-inspired vision based robot control using featureless estimations of time-to-contact.

PubMed

Zhang, Haijie; Zhao, Jianguo

2017-01-31

Marvelous vision based dynamic behaviors of insects and birds such as perching, landing, and obstacle avoidance have inspired scientists to propose the idea of time-to-contact, which is defined as the time for a moving observer to contact an object or surface if the current velocity is maintained. Since with only a vision sensor, time-to-contact can be directly estimated from consecutive images, it is widely used for a variety of robots to fulfill various tasks such as obstacle avoidance, docking, chasing, perching and landing. However, most of existing methods to estimate the time-to-contact need to extract and track features during the control process, which is time-consuming and cannot be applied to robots with limited computation power. In this paper, we adopt a featureless estimation method, extend this method to more general settings with angular velocities, and improve the estimation results using Kalman filtering. Further, we design an error based controller with gain scheduling strategy to control the motion of mobile robots. Experiments for both estimation and control are conducted using a customized mobile robot platform with low-cost embedded systems. Onboard experimental results demonstrate the effectiveness of the proposed approach, with the robot being controlled to successfully dock in front of a vertical wall. The estimation and control methods presented in this paper can be applied to computation-constrained miniature robots for agile locomotion such as landing, docking, or navigation.

DCF(Registered)-A JAUS and TENA Compliant Agent-Based Framework for Test and Evaluation of Unmanned Vehicles

DTIC Science & Technology

2011-03-01

functions of the vignette editor include visualizing the state of the UAS team, creating T&E scenarios, monitoring the UAS team performance, and...These behaviors are then executed by the robot sequentially (Figure 2). A state machine mission editor allows mission builders to use behaviors from the...include control, robotics, distributed applications, multimedia applications, databases, design patterns, and software engineering. Mr. Lenzi is the

Robotics and neuroscience: a rhythmic interaction.

PubMed

Ronsse, Renaud; Lefèvre, Philippe; Sepulchre, Rodolphe

2008-05-01

At the crossing between motor control neuroscience and robotics system theory, the paper presents a rhythmic experiment that is amenable both to handy laboratory implementation and simple mathematical modeling. The experiment is based on an impact juggling task, requiring the coordination of two upper-limb effectors and some phase-locking with the trajectories of one or several juggled objects. We describe the experiment, its implementation and the mathematical model used for the analysis. Our underlying research focuses on the role of sensory feedback in rhythmic tasks. In a robotic implementation of our experiment, we study the minimum feedback that is required to achieve robust control. A limited source of feedback, measuring only the impact times, is shown to give promising results. A second field of investigation concerns the human behavior in the same impact juggling task. We study how a variation of the tempo induces a transition between two distinct control strategies with different sensory feedback requirements. Analogies and differences between the robotic and human behaviors are obviously of high relevance in such a flexible setup.

An autonomous satellite architecture integrating deliberative reasoning and behavioural intelligence

NASA Technical Reports Server (NTRS)

Lindley, Craig A.

1993-01-01

This paper describes a method for the design of autonomous spacecraft, based upon behavioral approaches to intelligent robotics. First, a number of previous spacecraft automation projects are reviewed. A methodology for the design of autonomous spacecraft is then presented, drawing upon both the European Space Agency technological center (ESTEC) automation and robotics methodology and the subsumption architecture for autonomous robots. A layered competency model for autonomous orbital spacecraft is proposed. A simple example of low level competencies and their interaction is presented in order to illustrate the methodology. Finally, the general principles adopted for the control hardware design of the AUSTRALIS-1 spacecraft are described. This system will provide an orbital experimental platform for spacecraft autonomy studies, supporting the exploration of different logical control models, different computational metaphors within the behavioral control framework, and different mappings from the logical control model to its physical implementation.

Adaptive and Resilient Soft Tensegrity Robots.

PubMed

Rieffel, John; Mouret, Jean-Baptiste

2018-04-17

Living organisms intertwine soft (e.g., muscle) and hard (e.g., bones) materials, giving them an intrinsic flexibility and resiliency often lacking in conventional rigid robots. The emerging field of soft robotics seeks to harness these same properties to create resilient machines. The nature of soft materials, however, presents considerable challenges to aspects of design, construction, and control-and up until now, the vast majority of gaits for soft robots have been hand-designed through empirical trial-and-error. This article describes an easy-to-assemble tensegrity-based soft robot capable of highly dynamic locomotive gaits and demonstrating structural and behavioral resilience in the face of physical damage. Enabling this is the use of a machine learning algorithm able to discover effective gaits with a minimal number of physical trials. These results lend further credence to soft-robotic approaches that seek to harness the interaction of complex material dynamics to generate a wealth of dynamical behaviors.

Mobile robots IV; Proceedings of the Meeting, Philadelphia, PA, Nov. 6, 7, 1989

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolfe, W.J.; Chun, W.H.

1990-01-01

The present conference on mobile robot systems discusses high-speed machine perception based on passive sensing, wide-angle optical ranging, three-dimensional path planning for flying/crawling robots, navigation of autonomous mobile intelligence in an unstructured natural environment, mechanical models for the locomotion of a four-articulated-track robot, a rule-based command language for a semiautonomous Mars rover, and a computer model of the structured light vision system for a Mars rover. Also discussed are optical flow and three-dimensional information for navigation, feature-based reasoning trail detection, a symbolic neural-net production system for obstacle avoidance and navigation, intelligent path planning for robot navigation in an unknown environment,more » behaviors from a hierarchical control system, stereoscopic TV systems, the REACT language for autonomous robots, and a man-amplifying exoskeleton.« less

Improving the transparency of a rehabilitation robot by exploiting the cyclic behaviour of walking.

PubMed

van Dijk, W; van der Kooij, H; Koopman, B; van Asseldonk, E H F; van der Kooij, H

2013-06-01

To promote active participation of neurological patients during robotic gait training, controllers, such as "assist as needed" or "cooperative control", are suggested. Apart from providing support, these controllers also require that the robot should be capable of resembling natural, unsupported, walking. This means that they should have a transparent mode, where the interaction forces between the human and the robot are minimal. Traditional feedback-control algorithms do not exploit the cyclic nature of walking to improve the transparency of the robot. The purpose of this study was to improve the transparent mode of robotic devices, by developing two controllers that use the rhythmic behavior of gait. Both controllers use adaptive frequency oscillators and kernel-based non-linear filters. Kernelbased non-linear filters can be used to estimate signals and their time derivatives, as a function of the gait phase. The first controller learns the motor angle, associated with a certain joint angle pattern, and acts as a feed-forward controller to improve the torque tracking (including the zero-torque mode). The second controller learns the state of the mechanical system and compensates for the dynamical effects (e.g. the acceleration of robot masses). Both controllers have been tested separately and in combination on a small subject population. Using the feedforward controller resulted in an improved torque tracking of at least 52 percent at the hip joint, and 61 percent at the knee joint. When both controllers were active simultaneously, the interaction power between the robot and the human leg was reduced by at least 40 percent at the thigh, and 43 percent at the shank. These results indicate that: if a robotic task is cyclic, the torque tracking and transparency can be improved by exploiting the predictions of adaptive frequency oscillator and kernel-based nonlinear filters.

Adaptive control strategies for flexible robotic arm

NASA Technical Reports Server (NTRS)

Bialasiewicz, Jan T.

1993-01-01

The motivation of this research came about when a neural network direct adaptive control scheme was applied to control the tip position of a flexible robotic arm. Satisfactory control performance was not attainable due to the inherent non-minimum phase characteristics of the flexible robotic arm tip. Most of the existing neural network control algorithms are based on the direct method and exhibit very high sensitivity if not unstable closed-loop behavior. Therefore a neural self-tuning control (NSTC) algorithm is developed and applied to this problem and showed promising results. Simulation results of the NSTC scheme and the conventional self-tuning (STR) control scheme are used to examine performance factors such as control tracking mean square error, estimation mean square error, transient response, and steady state response.

ALLIANCE: An architecture for fault tolerant, cooperative control of heterogeneous mobile robots

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parker, L.E.

1995-02-01

This research addresses the problem of achieving fault tolerant cooperation within small- to medium-sized teams of heterogeneous mobile robots. The author describes a novel behavior-based, fully distributed architecture, called ALLIANCE, that utilizes adaptive action selection to achieve fault tolerant cooperative control in robot missions involving loosely coupled, largely independent tasks. The robots in this architecture possess a variety of high-level functions that they can perform during a mission, and must at all times select an appropriate action based on the requirements of the mission, the activities of other robots, the current environmental conditions, and their own internal states. Since suchmore » cooperative teams often work in dynamic and unpredictable environments, the software architecture allows the team members to respond robustly and reliably to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. After presenting ALLIANCE, the author describes in detail experimental results of an implementation of this architecture on a team of physical mobile robots performing a cooperative box pushing demonstration. These experiments illustrate the ability of ALLIANCE to achieve adaptive, fault-tolerant cooperative control amidst dynamic changes in the capabilities of the robot team.« less

Generic robot architecture

DOEpatents

Bruemmer, David J [Idaho Falls, ID; Few, Douglas A [Idaho Falls, ID

2010-09-21

The present invention provides methods, computer readable media, and apparatuses for a generic robot architecture providing a framework that is easily portable to a variety of robot platforms and is configured to provide hardware abstractions, abstractions for generic robot attributes, environment abstractions, and robot behaviors. The generic robot architecture includes a hardware abstraction level and a robot abstraction level. The hardware abstraction level is configured for developing hardware abstractions that define, monitor, and control hardware modules available on a robot platform. The robot abstraction level is configured for defining robot attributes and provides a software framework for building robot behaviors from the robot attributes. Each of the robot attributes includes hardware information from at least one hardware abstraction. In addition, each robot attribute is configured to substantially isolate the robot behaviors from the at least one hardware abstraction.

Folk-Psychological Interpretation of Human vs. Humanoid Robot Behavior: Exploring the Intentional Stance toward Robots

PubMed Central

Thellman, Sam; Silvervarg, Annika; Ziemke, Tom

2017-01-01

People rely on shared folk-psychological theories when judging behavior. These theories guide people’s social interactions and therefore need to be taken into consideration in the design of robots and other autonomous systems expected to interact socially with people. It is, however, not yet clear to what degree the mechanisms that underlie people’s judgments of robot behavior overlap or differ from the case of human or animal behavior. To explore this issue, participants (N = 90) were exposed to images and verbal descriptions of eight different behaviors exhibited either by a person or a humanoid robot. Participants were asked to rate the intentionality, controllability and desirability of the behaviors, and to judge the plausibility of seven different types of explanations derived from a recently proposed psychological model of lay causal explanation of human behavior. Results indicate: substantially similar judgments of human and robot behavior, both in terms of (1a) ascriptions of intentionality/controllability/desirability and in terms of (1b) plausibility judgments of behavior explanations; (2a) high level of agreement in judgments of robot behavior – (2b) slightly lower but still largely similar to agreement over human behaviors; (3) systematic differences in judgments concerning the plausibility of goals and dispositions as explanations of human vs. humanoid behavior. Taken together, these results suggest that people’s intentional stance toward the robot was in this case very similar to their stance toward the human. PMID:29184519

Intelligent robots for planetary exploration and construction

NASA Technical Reports Server (NTRS)

Albus, James S.

1992-01-01

Robots capable of practical applications in planetary exploration and construction will require realtime sensory-interactive goal-directed control systems. A reference model architecture based on the NIST Real-time Control System (RCS) for real-time intelligent control systems is suggested. RCS partitions the control problem into four basic elements: behavior generation (or task decomposition), world modeling, sensory processing, and value judgment. It clusters these elements into computational nodes that have responsibility for specific subsystems, and arranges these nodes in hierarchical layers such that each layer has characteristic functionality and timing. Planetary exploration robots should have mobility systems that can safely maneuver over rough surfaces at high speeds. Walking machines and wheeled vehicles with dynamic suspensions are candidates. The technology of sensing and sensory processing has progressed to the point where real-time autonomous path planning and obstacle avoidance behavior is feasible. Map-based navigation systems will support long-range mobility goals and plans. Planetary construction robots must have high strength-to-weight ratios for lifting and positioning tools and materials in six degrees-of-freedom over large working volumes. A new generation of cable-suspended Stewart platform devices and inflatable structures are suggested for lifting and positioning materials and structures, as well as for excavation, grading, and manipulating a variety of tools and construction machinery.

Robotic Planetary Drill Tests

NASA Technical Reports Server (NTRS)

Glass, Brian J.; Thompson, S.; Paulsen, G.

2010-01-01

Several proposed or planned planetary science missions to Mars and other Solar System bodies over the next decade require subsurface access by drilling. This paper discusses the problems of remote robotic drilling, an automation and control architecture based loosely on observed human behaviors in drilling on Earth, and an overview of robotic drilling field test results using this architecture since 2005. Both rotary-drag and rotary-percussive drills are targeted. A hybrid diagnostic approach incorporates heuristics, model-based reasoning and vibration monitoring with neural nets. Ongoing work leads to flight-ready drilling software.

Robotic Fish to Aid Animal Behavior Studies and Informal Science Learning

NASA Astrophysics Data System (ADS)

Phamduy, Paul

The application of robotic fish in the fields of animal behavior and informal science learning are new and relatively untapped. In the context of animal behavior studies, robotic fish offers a consistent and customizable stimulus that could contribute to dissect the determinants of social behavior. In the realm of informal science learning, robotic fish are gaining momentum for the possibility of educating the general public simultaneously on fish physiology and underwater robotics. In this dissertation, the design and development of a number of robotic fish platforms and prototypes and their application in animal behavioral studies and informal science learning settings are presented. Robotic platforms for animal behavioral studies focused on the utilization replica or same scale prototypes. A novel robotic fish platform, featuring a three-dimensional swimming multi-linked robotic fish, was developed with three control modes varying in the level of robot autonomy offered. This platform was deployed at numerous science festivals and science centers, to obtain data on visitor engagement and experience.

Emotional metacontrol of attention: Top-down modulation of sensorimotor processes in a robotic visual search task.

PubMed

Belkaid, Marwen; Cuperlier, Nicolas; Gaussier, Philippe

2017-01-01

Emotions play a significant role in internal regulatory processes. In this paper, we advocate four key ideas. First, novelty detection can be grounded in the sensorimotor experience and allow higher order appraisal. Second, cognitive processes, such as those involved in self-assessment, influence emotional states by eliciting affects like boredom and frustration. Third, emotional processes such as those triggered by self-assessment influence attentional processes. Last, close emotion-cognition interactions implement an efficient feedback loop for the purpose of top-down behavior regulation. The latter is what we call 'Emotional Metacontrol'. We introduce a model based on artificial neural networks. This architecture is used to control a robotic system in a visual search task. The emotional metacontrol intervenes to bias the robot visual attention during active object recognition. Through a behavioral and statistical analysis, we show that this mechanism increases the robot performance and fosters the exploratory behavior to avoid deadlocks.

Experiments with a small behaviour controlled planetary rover

NASA Technical Reports Server (NTRS)

Miller, David P.; Desai, Rajiv S.; Gat, Erann; Ivlev, Robert; Loch, John

1993-01-01

A series of experiments that were performed on the Rocky 3 robot is described. Rocky 3 is a small autonomous rover capable of navigating through rough outdoor terrain to a predesignated area, searching that area for soft soil, acquiring a soil sample, and depositing the sample in a container at its home base. The robot is programmed according to a reactive behavior control paradigm using the ALFA programming language. This style of programming produces robust autonomous performance while requiring significantly less computational resources than more traditional mobile robot control systems. The code for Rocky 3 runs on an eight bit processor and uses about ten k of memory.

Experimental Robot Model Adjustments Based on Force–Torque Sensor Information

PubMed Central

2018-01-01

The computational complexity of humanoid robot balance control is reduced through the application of simplified kinematics and dynamics models. However, these simplifications lead to the introduction of errors that add to other inherent electro-mechanic inaccuracies and affect the robotic system. Linear control systems deal with these inaccuracies if they operate around a specific working point but are less precise if they do not. This work presents a model improvement based on the Linear Inverted Pendulum Model (LIPM) to be applied in a non-linear control system. The aim is to minimize the control error and reduce robot oscillations for multiple working points. The new model, named the Dynamic LIPM (DLIPM), is used to plan the robot behavior with respect to changes in the balance status denoted by the zero moment point (ZMP). Thanks to the use of information from force–torque sensors, an experimental procedure has been applied to characterize the inaccuracies and introduce them into the new model. The experiments consist of balance perturbations similar to those of push-recovery trials, in which step-shaped ZMP variations are produced. The results show that the responses of the robot with respect to balance perturbations are more precise and the mechanical oscillations are reduced without comprising robot dynamics. PMID:29534477

Development of safe mechanism for surgical robots using equilibrium point control method.

PubMed

Park, Shinsuk; Lim, Hokjin; Kim, Byeong-sang; Song, Jae-bok

2006-01-01

This paper introduces a novel mechanism for surgical robotic systems to generate human arm-like compliant motion. The mechanism is based on the idea of the equilibrium point control hypothesis which claims that multi-joint limb movements are achieved by shifting the limbs' equilibrium positions defined by neuromuscular activity. The equilibrium point control can be implemented on a robot manipulator by installing two actuators at each joint of the manipulator, one to control the joint position, and the other to control the joint stiffness. This double-actuator mechanism allows us to arbitrarily manipulate the stiffness (or impedance) of a robotic manipulator as well as its position. Also, the force at the end-effector can be estimated based on joint stiffness and joint angle changes without using force transducers. A two-link manipulator and a three-link manipulator with the double-actuator units have been developed, and experiments and simulation results show the potential of the proposed approach. By creating the human arm-like behavior, this mechanism can improve the performance of robot manipulators to execute stable and safe movement in surgical environments by using a simple control scheme.

Improving Grasp Skills Using Schema Structured Learning

NASA Technical Reports Server (NTRS)

Platt, Robert; Grupen, ROderic A.; Fagg, Andrew H.

2006-01-01

Abstract In the control-based approach to robotics, complex behavior is created by sequencing and combining control primitives. While it is desirable for the robot to autonomously learn the correct control sequence, searching through the large number of potential solutions can be time consuming. This paper constrains this search to variations of a generalized solution encoded in a framework known as an action schema. A new algorithm, SCHEMA STRUCTURED LEARNING, is proposed that repeatedly executes variations of the generalized solution in search of instantiations that satisfy action schema objectives. This approach is tested in a grasping task where Dexter, the UMass humanoid robot, learns which reaching and grasping controllers maximize the probability of grasp success.

Explanation Capabilities for Behavior-Based Robot Control

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance L.

2012-01-01

A recent study that evaluated issues associated with remote interaction with an autonomous vehicle within the framework of grounding found that missing contextual information led to uncertainty in the interpretation of collected data, and so introduced errors into the command logic of the vehicle. As the vehicles became more autonomous through the activation of additional capabilities, more errors were made. This is an inefficient use of the platform, since the behavior of remotely located autonomous vehicles didn't coincide with the "mental models" of human operators. One of the conclusions of the study was that there should be a way for the autonomous vehicles to describe what action they choose and why. Robotic agents with enough self-awareness to dynamically adjust the information conveyed back to the Operations Center based on a detail level component analysis of requests could provide this description capability. One way to accomplish this is to map the behavior base of the robot into a formal mathematical framework called a cost-calculus. A cost-calculus uses composition operators to build up sequences of behaviors that can then be compared to what is observed using well-known inference mechanisms.

Biologically-inspired adaptive obstacle negotiation behavior of hexapod robots

PubMed Central

Goldschmidt, Dennis; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Neurobiological studies have shown that insects are able to adapt leg movements and posture for obstacle negotiation in changing environments. Moreover, the distance to an obstacle where an insect begins to climb is found to be a major parameter for successful obstacle negotiation. Inspired by these findings, we present an adaptive neural control mechanism for obstacle negotiation behavior in hexapod robots. It combines locomotion control, backbone joint control, local leg reflexes, and neural learning. While the first three components generate locomotion including walking and climbing, the neural learning mechanism allows the robot to adapt its behavior for obstacle negotiation with respect to changing conditions, e.g., variable obstacle heights and different walking gaits. By successfully learning the association of an early, predictive signal (conditioned stimulus, CS) and a late, reflex signal (unconditioned stimulus, UCS), both provided by ultrasonic sensors at the front of the robot, the robot can autonomously find an appropriate distance from an obstacle to initiate climbing. The adaptive neural control was developed and tested first on a physical robot simulation, and was then successfully transferred to a real hexapod robot, called AMOS II. The results show that the robot can efficiently negotiate obstacles with a height up to 85% of the robot's leg length in simulation and 75% in a real environment. PMID:24523694

Modular architecture for robotics and teleoperation

DOEpatents

Anderson, Robert J.

1996-12-03

Systems and methods for modularization and discretization of real-time robot, telerobot and teleoperation systems using passive, network based control laws. Modules consist of network one-ports and two-ports. Wave variables and position information are passed between modules. The behavior of each module is decomposed into uncoupled linear-time-invariant, and coupled, nonlinear memoryless elements and then are separately discretized.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pin, F.G.; Bender, S.R.

Most fuzzy logic-based reasoning schemes developed for robot control are fully reactive, i.e., the reasoning modules consist of fuzzy rule bases that represent direct mappings from the stimuli provided by the perception systems to the responses implemented by the motion controllers. Due to their totally reactive nature, such reasoning systems can encounter problems such as infinite loops and limit cycles. In this paper, we proposed an approach to remedy these problems by adding a memory and memory-related behaviors to basic reactive systems. Three major types of memory behaviors are addressed: memory creation, memory management, and memory utilization. These are firstmore » presented, and examples of their implementation for the recognition of limit cycles during the navigation of an autonomous robot in a priori unknown environments are then discussed.« less

Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot

PubMed Central

Pasma, Jantsje H.; Assländer, Lorenz; van Kordelaar, Joost; de Kam, Digna; Mergner, Thomas; Schouten, Alfred C.

2018-01-01

The Independent Channel (IC) model is a commonly used linear balance control model in the frequency domain to analyze human balance control using system identification and parameter estimation. The IC model is a rudimentary and noise-free description of balance behavior in the frequency domain, where a stable model representation is not guaranteed. In this study, we conducted firstly time-domain simulations with added noise, and secondly robot experiments by implementing the IC model in a real-world robot (PostuRob II) to test the validity and stability of the model in the time domain and for real world situations. Balance behavior of seven healthy participants was measured during upright stance by applying pseudorandom continuous support surface rotations. System identification and parameter estimation were used to describe the balance behavior with the IC model in the frequency domain. The IC model with the estimated parameters from human experiments was implemented in Simulink for computer simulations including noise in the time domain and robot experiments using the humanoid robot PostuRob II. Again, system identification and parameter estimation were used to describe the simulated balance behavior. Time series, Frequency Response Functions, and estimated parameters from human experiments, computer simulations, and robot experiments were compared with each other. The computer simulations showed similar balance behavior and estimated control parameters compared to the human experiments, in the time and frequency domain. Also, the IC model was able to control the humanoid robot by keeping it upright, but showed small differences compared to the human experiments in the time and frequency domain, especially at high frequencies. We conclude that the IC model, a descriptive model in the frequency domain, can imitate human balance behavior also in the time domain, both in computer simulations with added noise and real world situations with a humanoid robot. This provides further evidence that the IC model is a valid description of human balance control. PMID:29615886

Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot.

PubMed

Pasma, Jantsje H; Assländer, Lorenz; van Kordelaar, Joost; de Kam, Digna; Mergner, Thomas; Schouten, Alfred C

2018-01-01

The Independent Channel (IC) model is a commonly used linear balance control model in the frequency domain to analyze human balance control using system identification and parameter estimation. The IC model is a rudimentary and noise-free description of balance behavior in the frequency domain, where a stable model representation is not guaranteed. In this study, we conducted firstly time-domain simulations with added noise, and secondly robot experiments by implementing the IC model in a real-world robot (PostuRob II) to test the validity and stability of the model in the time domain and for real world situations. Balance behavior of seven healthy participants was measured during upright stance by applying pseudorandom continuous support surface rotations. System identification and parameter estimation were used to describe the balance behavior with the IC model in the frequency domain. The IC model with the estimated parameters from human experiments was implemented in Simulink for computer simulations including noise in the time domain and robot experiments using the humanoid robot PostuRob II. Again, system identification and parameter estimation were used to describe the simulated balance behavior. Time series, Frequency Response Functions, and estimated parameters from human experiments, computer simulations, and robot experiments were compared with each other. The computer simulations showed similar balance behavior and estimated control parameters compared to the human experiments, in the time and frequency domain. Also, the IC model was able to control the humanoid robot by keeping it upright, but showed small differences compared to the human experiments in the time and frequency domain, especially at high frequencies. We conclude that the IC model, a descriptive model in the frequency domain, can imitate human balance behavior also in the time domain, both in computer simulations with added noise and real world situations with a humanoid robot. This provides further evidence that the IC model is a valid description of human balance control.

Design and control of active vision based mechanisms for intelligent robots

NASA Technical Reports Server (NTRS)

Wu, Liwei; Marefat, Michael M.

1994-01-01

In this paper, we propose a design of an active vision system for intelligent robot application purposes. The system has the degrees of freedom of pan, tilt, vergence, camera height adjustment, and baseline adjustment with a hierarchical control system structure. Based on this vision system, we discuss two problems involved in the binocular gaze stabilization process: fixation point selection and vergence disparity extraction. A hierarchical approach to determining point of fixation from potential gaze targets using evaluation function representing human visual behavior to outside stimuli is suggested. We also characterize different visual tasks in two cameras for vergence control purposes, and a phase-based method based on binarized images to extract vergence disparity for vergence control is presented. A control algorithm for vergence control is discussed.

Evolving mobile robots able to display collective behaviors.

PubMed

Baldassarre, Gianluca; Nolfi, Stefano; Parisi, Domenico

2003-01-01

We present a set of experiments in which simulated robots are evolved for the ability to aggregate and move together toward a light target. By developing and using quantitative indexes that capture the structural properties of the emerged formations, we show that evolved individuals display interesting behavioral patterns in which groups of robots act as a single unit. Moreover, evolved groups of robots with identical controllers display primitive forms of situated specialization and play different behavioral functions within the group according to the circumstances. Overall, the results presented in the article demonstrate that evolutionary techniques, by exploiting the self-organizing behavioral properties that emerge from the interactions between the robots and between the robots and the environment, are a powerful method for synthesizing collective behavior.

A multitasking behavioral control system for the Robotic All Terrain Lunar Exploration Rover (RATLER)

NASA Technical Reports Server (NTRS)

Klarer, P.

1994-01-01

An alternative methodology for designing an autonomous navigation and control system is discussed. This generalized hybrid system is based on a less sequential and less anthropomorphic approach than that used in the more traditional artificial intelligence (AI) technique. The architecture is designed to allow both synchronous and asynchronous operations between various behavior modules. This is accomplished by intertask communications channels which implement each behavior module and each interconnection node as a stand-alone task. The proposed design architecture allows for construction of hybrid systems which employ both subsumption and traditional AI techniques as well as providing for a teleoperator's interface. Implementation of the architecture is planned for the prototype Robotic All Terrain Lunar Explorer Rover (RATLER) which is described briefly.

Gesteme-free context-aware adaptation of robot behavior in human-robot cooperation.

PubMed

Nessi, Federico; Beretta, Elisa; Gatti, Cecilia; Ferrigno, Giancarlo; De Momi, Elena

2016-11-01

Cooperative robotics is receiving greater acceptance because the typical advantages provided by manipulators are combined with an intuitive usage. In particular, hands-on robotics may benefit from the adaptation of the assistant behavior with respect to the activity currently performed by the user. A fast and reliable classification of human activities is required, as well as strategies to smoothly modify the control of the manipulator. In this scenario, gesteme-based motion classification is inadequate because it needs the observation of a wide signal percentage and the definition of a rich vocabulary. In this work, a system able to recognize the user's current activity without a vocabulary of gestemes, and to accordingly adapt the manipulator's dynamic behavior is presented. An underlying stochastic model fits variations in the user's guidance forces and the resulting trajectories of the manipulator's end-effector with a set of Gaussian distribution. The high-level switching between these distributions is captured with hidden Markov models. The dynamic of the KUKA light-weight robot, a torque-controlled manipulator, is modified with respect to the classified activity using sigmoidal-shaped functions. The presented system is validated over a pool of 12 näive users in a scenario that addresses surgical targeting tasks on soft tissue. The robot's assistance is adapted in order to obtain a stiff behavior during activities that require critical accuracy constraint, and higher compliance during wide movements. Both the ability to provide the correct classification at each moment (sample accuracy) and the capability of correctly identify the correct sequence of activity (sequence accuracy) were evaluated. The proposed classifier is fast and accurate in all the experiments conducted (80% sample accuracy after the observation of ∼450ms of signal). Moreover, the ability of recognize the correct sequence of activities, without unwanted transitions is guaranteed (sequence accuracy ∼90% when computed far away from user desired transitions). Finally, the proposed activity-based adaptation of the robot's dynamic does not lead to a not smooth behavior (high smoothness, i.e. normalized jerk score <0.01). The provided system is able to dynamic assist the operator during cooperation in the presented scenario. Copyright © 2016 Elsevier B.V. All rights reserved.

A multitasking behavioral control system for the Robotic All-Terrain Lunar Exploration Rover (RATLER)

NASA Technical Reports Server (NTRS)

Klarer, Paul

1993-01-01

An approach for a robotic control system which implements so called 'behavioral' control within a realtime multitasking architecture is proposed. The proposed system would attempt to ameliorate some of the problems noted by some researchers when implementing subsumptive or behavioral control systems, particularly with regard to multiple processor systems and realtime operations. The architecture is designed to allow synchronous operations between various behavior modules by taking advantage of a realtime multitasking system's intertask communications channels, and by implementing each behavior module and each interconnection node as a stand-alone task. The potential advantages of this approach over those previously described in the field are discussed. An implementation of the architecture is planned for a prototype Robotic All Terrain Lunar Exploration Rover (RATLER) currently under development and is briefly described.

LABRADOR: a learning autonomous behavior-based robot for adaptive detection and object retrieval

NASA Astrophysics Data System (ADS)

Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

2013-01-01

As part of the TARDEC-funded CANINE (Cooperative Autonomous Navigation in a Networked Environment) Program, iRobot developed LABRADOR (Learning Autonomous Behavior-based Robot for Adaptive Detection and Object Retrieval). LABRADOR was based on the rugged, man-portable, iRobot PackBot unmanned ground vehicle (UGV) equipped with an explosives ordnance disposal (EOD) manipulator arm and a custom gripper. For LABRADOR, we developed a vision-based object learning and recognition system that combined a TLD (track-learn-detect) filter based on object shape features with a color-histogram-based object detector. Our vision system was able to learn in real-time to recognize objects presented to the robot. We also implemented a waypoint navigation system based on fused GPS, IMU (inertial measurement unit), and odometry data. We used this navigation capability to implement autonomous behaviors capable of searching a specified area using a variety of robust coverage strategies - including outward spiral, random bounce, random waypoint, and perimeter following behaviors. While the full system was not integrated in time to compete in the CANINE competition event, we developed useful perception, navigation, and behavior capabilities that may be applied to future autonomous robot systems.

A Lower Limb Rehabilitation Robot in Sitting Position with a Review of Training Activities.

PubMed

Eiammanussakul, Trinnachoke; Sangveraphunsiri, Viboon

2018-01-01

Robots for stroke rehabilitation at the lower limbs in sitting/lying position have been developed extensively. Some of them have been applied in clinics and shown the potential of the recovery of poststroke patients who suffer from hemiparesis. These robots were developed to provide training at different joints of lower limbs with various activities and modalities. This article reviews the training activities that were realized by rehabilitation robots in literature, in order to offer insights for developing a novel robot suitable for stroke rehabilitation. The control system of the lower limb rehabilitation robot in sitting position that was introduced in the previous work is discussed in detail to demonstrate the behavior of the robot while training a subject. The nonlinear impedance control law, based on active assistive control strategy, is able to define the response of the robot with more specifications while the passivity property and the robustness of the system is verified. A preliminary experiment is conducted on a healthy subject to show that the robot is able to perform active assistive exercises with various training activities and assist the subject to complete the training with desired level of assistance.

Self-Organized Behavior Generation for Musculoskeletal Robots.

PubMed

Der, Ralf; Martius, Georg

2017-01-01

With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors "waiting" to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics.

Self-Organized Behavior Generation for Musculoskeletal Robots

PubMed Central

Der, Ralf; Martius, Georg

2017-01-01

With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors “waiting” to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics. PMID:28360852

Behavioral similarity measurement based on image processing for robots that use imitative learning

NASA Astrophysics Data System (ADS)

Sterpin B., Dante G.; Martinez S., Fernando; Jacinto G., Edwar

2017-02-01

In the field of the artificial societies, particularly those are based on memetics, imitative behavior is essential for the development of cultural evolution. Applying this concept for robotics, through imitative learning, a robot can acquire behavioral patterns from another robot. Assuming that the learning process must have an instructor and, at least, an apprentice, the fact to obtain a quantitative measurement for their behavioral similarity, would be potentially useful, especially in artificial social systems focused on cultural evolution. In this paper the motor behavior of both kinds of robots, for two simple tasks, is represented by 2D binary images, which are processed in order to measure their behavioral similarity. The results shown here were obtained comparing some similarity measurement methods for binary images.

Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

PubMed Central

Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M.L.; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

2017-01-01

The term ‘synergy’ – from the Greek synergia – means ‘working together’. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project “The Hand Embodied” (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies. PMID:26923030

Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands.

PubMed

Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M L; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

2016-07-01

The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project "The Hand Embodied" (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies. Copyright © 2016 Elsevier B.V. All rights reserved.

Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

NASA Astrophysics Data System (ADS)

Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M. L.; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

2016-07-01

The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project ;The Hand Embodied; (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.

External force/velocity control for an autonomous rehabilitation robot

NASA Astrophysics Data System (ADS)

Saekow, Peerayuth; Neranon, Paramin; Smithmaitrie, Pruittikorn

2018-01-01

Stroke is a primary cause of death and the leading cause of permanent disability in adults. There are many stroke survivors, who live with a variety of levels of disability and always need rehabilitation activities on daily basis. Several studies have reported that usage of rehabilitation robotic devices shows the better improvement outcomes in upper-limb stroke patients than the conventional therapy-nurses or therapists actively help patients with exercise-based rehabilitation. This research focuses on the development of an autonomous robotic trainer designed to guide a stroke patient through an upper-limb rehabilitation task. The robotic device was designed and developed to automate the reaching exercise as mentioned. The designed robotic system is made up of a four-wheel omni-directional mobile robot, an ATI Gamma multi-axis force/torque sensor used to measure contact force and a microcontroller real-time operating system. Proportional plus Integral control was adapted to control the overall performance and stability of the autonomous assistive robot. External force control was successfully implemented to establish the behavioral control strategy for the robot force and velocity control scheme. In summary, the experimental results indicated satisfactorily stable performance of the robot force and velocity control can be considered acceptable. The gain tuning for proportional integral (PI) velocity control algorithms was suitably estimated using the Ziegler-Nichols method in which the optimized proportional and integral gains are 0.45 and 0.11, respectively. Additionally, the PI external force control gains were experimentally tuned using the trial and error method based on a set of experiments which allow a human participant moves the robot along the constrained circular path whilst attempting to minimize the radial force. The performance was analyzed based on the root mean square error (E_RMS) of the radial forces, in which the lower the variation in radial forces, the better the performance of the system. The outstanding performance of the tests as specified by the E_RMS of the radial force was observed with proportional and integral gains of Kp = 0.7 and Ki = 0.75, respectively.

Towards Assessing the Human Trajectory Planning Horizon

PubMed Central

Nitsch, Verena; Meinzer, Dominik; Wollherr, Dirk

2016-01-01

Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a shared environment. For locomotion, these environments resemble traversable areas which are shared between multiple agents like humans and robots. The seamless integration of mobile robots into these environments requires accurate predictions of human locomotion. This work considers optimal control and model predictive control approaches for accurate trajectory prediction and proposes to integrate aspects of human behavior to improve their performance. Recently developed models are not able to reproduce accurately trajectories that result from sudden avoidance maneuvers. Particularly, the human locomotion behavior when handling disturbances from other agents poses a problem. The goal of this work is to investigate whether humans alter their trajectory planning horizon, in order to resolve abruptly emerging collision situations. By modeling humans as model predictive controllers, the influence of the planning horizon is investigated in simulations. Based on these results, an experiment is designed to identify, whether humans initiate a change in their locomotion planning behavior while moving in a complex environment. The results support the hypothesis, that humans employ a shorter planning horizon to avoid collisions that are triggered by unexpected disturbances. Observations presented in this work are expected to further improve the generalizability and accuracy of prediction methods based on dynamic models. PMID:27936015

Towards Assessing the Human Trajectory Planning Horizon.

PubMed

Carton, Daniel; Nitsch, Verena; Meinzer, Dominik; Wollherr, Dirk

2016-01-01

Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a shared environment. For locomotion, these environments resemble traversable areas which are shared between multiple agents like humans and robots. The seamless integration of mobile robots into these environments requires accurate predictions of human locomotion. This work considers optimal control and model predictive control approaches for accurate trajectory prediction and proposes to integrate aspects of human behavior to improve their performance. Recently developed models are not able to reproduce accurately trajectories that result from sudden avoidance maneuvers. Particularly, the human locomotion behavior when handling disturbances from other agents poses a problem. The goal of this work is to investigate whether humans alter their trajectory planning horizon, in order to resolve abruptly emerging collision situations. By modeling humans as model predictive controllers, the influence of the planning horizon is investigated in simulations. Based on these results, an experiment is designed to identify, whether humans initiate a change in their locomotion planning behavior while moving in a complex environment. The results support the hypothesis, that humans employ a shorter planning horizon to avoid collisions that are triggered by unexpected disturbances. Observations presented in this work are expected to further improve the generalizability and accuracy of prediction methods based on dynamic models.

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect.

PubMed

Ando, Noriyasu; Emoto, Shuhei; Kanzaki, Ryohei

2016-12-19

Robotic odor source localization has been a challenging area and one to which biological knowledge has been expected to contribute, as finding odor sources is an essential task for organism survival. Insects are well-studied organisms with regard to odor tracking, and their behavioral strategies have been applied to mobile robots for evaluation. This "bottom-up" approach is a fundamental way to develop biomimetic robots; however, the biological analyses and the modeling of behavioral mechanisms are still ongoing. Therefore, it is still unknown how such a biological system actually works as the controller of a robotic platform. To answer this question, we have developed an insect-controlled robot in which a male adult silkmoth (Bombyx mori) drives a robot car in response to odor stimuli; this can be regarded as a prototype of a future insect-mimetic robot. In the cockpit of the robot, a tethered silkmoth walked on an air-supported ball and an optical sensor measured the ball rotations. These rotations were translated into the movement of the two-wheeled robot. The advantage of this "hybrid" approach is that experimenters can manipulate any parameter of the robot, which enables the evaluation of the odor-tracking capability of insects and provides useful suggestions for robotic odor-tracking. Furthermore, these manipulations are non-invasive ways to alter the sensory-motor relationship of a pilot insect and will be a useful technique for understanding adaptive behaviors.

Training a Network of Electronic Neurons for Control of a Mobile Robot

NASA Astrophysics Data System (ADS)

Vromen, T. G. M.; Steur, E.; Nijmeijer, H.

An adaptive training procedure is developed for a network of electronic neurons, which controls a mobile robot driving around in an unknown environment while avoiding obstacles. The neuronal network controls the angular velocity of the wheels of the robot based on the sensor readings. The nodes in the neuronal network controller are clusters of neurons rather than single neurons. The adaptive training procedure ensures that the input-output behavior of the clusters is identical, even though the constituting neurons are nonidentical and have, in isolation, nonidentical responses to the same input. In particular, we let the neurons interact via a diffusive coupling, and the proposed training procedure modifies the diffusion interaction weights such that the neurons behave synchronously with a predefined response. The working principle of the training procedure is experimentally validated and results of an experiment with a mobile robot that is completely autonomously driving in an unknown environment with obstacles are presented.

Understanding of Android-Based Robotic and Game Structure

NASA Astrophysics Data System (ADS)

Phongtraychack, A.; Syryamkin, V.

2018-05-01

The development of an android with impressive lifelike appearance and behavior has been a long-standing goal in robotics and a new and exciting approach of smartphone-based robotics for research and education. Recent years have been progressive for many technologies, which allowed creating such androids. There are different examples including the autonomous Erica android system capable of conversational interaction and speech synthesis technologies. The behavior of Android-based robot could be running on the phone as the robot performed a task outdoors. In this paper, we present an overview and understanding of the platform of Android-based robotic and game structure for research and education.

Designing and implementing nervous system simulations on LEGO robots.

PubMed

Blustein, Daniel; Rosenthal, Nikolai; Ayers, Joseph

2013-05-25

We present a method to use the commercially available LEGO Mindstorms NXT robotics platform to test systems level neuroscience hypotheses. The first step of the method is to develop a nervous system simulation of specific reflexive behaviors of an appropriate model organism; here we use the American Lobster. Exteroceptive reflexes mediated by decussating (crossing) neural connections can explain an animal's taxis towards or away from a stimulus as described by Braitenberg and are particularly well suited for investigation using the NXT platform.(1) The nervous system simulation is programmed using LabVIEW software on the LEGO Mindstorms platform. Once the nervous system is tuned properly, behavioral experiments are run on the robot and on the animal under identical environmental conditions. By controlling the sensory milieu experienced by the specimens, differences in behavioral outputs can be observed. These differences may point to specific deficiencies in the nervous system model and serve to inform the iteration of the model for the particular behavior under study. This method allows for the experimental manipulation of electronic nervous systems and serves as a way to explore neuroscience hypotheses specifically regarding the neurophysiological basis of simple innate reflexive behaviors. The LEGO Mindstorms NXT kit provides an affordable and efficient platform on which to test preliminary biomimetic robot control schemes. The approach is also well suited for the high school classroom to serve as the foundation for a hands-on inquiry-based biorobotics curriculum.

Learning classifier systems for single and multiple mobile robots in unstructured environments

NASA Astrophysics Data System (ADS)

Bay, John S.

1995-12-01

The learning classifier system (LCS) is a learning production system that generates behavioral rules via an underlying discovery mechanism. The LCS architecture operates similarly to a blackboard architecture; i.e., by posted-message communications. But in the LCS, the message board is wiped clean at every time interval, thereby requiring no persistent shared resource. In this paper, we adapt the LCS to the problem of mobile robot navigation in completely unstructured environments. We consider the model of the robot itself, including its sensor and actuator structures, to be part of this environment, in addition to the world-model that includes a goal and obstacles at unknown locations. This requires a robot to learn its own I/O characteristics in addition to solving its navigation problem, but results in a learning controller that is equally applicable, unaltered, in robots with a wide variety of kinematic structures and sensing capabilities. We show the effectiveness of this LCS-based controller through both simulation and experimental trials with a small robot. We then propose a new architecture, the Distributed Learning Classifier System (DLCS), which generalizes the message-passing behavior of the LCS from internal messages within a single agent to broadcast massages among multiple agents. This communications mode requires little bandwidth and is easily implemented with inexpensive, off-the-shelf hardware. The DLCS is shown to have potential application as a learning controller for multiple intelligent agents.

A cognitive robotics system: the symbolic and sub-symbolic robotic intelligence control system (SS-RICS)

NASA Astrophysics Data System (ADS)

Kelley, Troy D.; Avery, Eric

2010-04-01

This paper will detail the progress on the development of the Symbolic and Subsymbolic Robotics Intelligence Control System (SS-RICS). The system is a goal oriented production system, based loosely on the cognitive architecture, the Adaptive Control of Thought-Rational (ACT-R) some additions and changes. We have found that in order to simulate complex cognition on a robot, many aspects of cognition (long term memory (LTM), perception) needed to be in place before any generalized intelligent behavior can be produced. In working with ACT-R, we found that it was a good instantiation of working memory, but that we needed to add other aspects of cognition including LTM and perception to have a complete cognitive system. Our progress to date will be noted and the challenges that remain will be addressed.

Interacting With Robots to Investigate the Bases of Social Interaction.

PubMed

Sciutti, Alessandra; Sandini, Giulio

2017-12-01

Humans show a great natural ability at interacting with each other. Such efficiency in joint actions depends on a synergy between planned collaboration and emergent coordination, a subconscious mechanism based on a tight link between action execution and perception. This link supports phenomena as mutual adaptation, synchronization, and anticipation, which cut drastically the delays in the interaction and the need of complex verbal instructions and result in the establishment of joint intentions, the backbone of social interaction. From a neurophysiological perspective, this is possible, because the same neural system supporting action execution is responsible of the understanding and the anticipation of the observed action of others. Defining which human motion features allow for such emergent coordination with another agent would be crucial to establish more natural and efficient interaction paradigms with artificial devices, ranging from assistive and rehabilitative technology to companion robots. However, investigating the behavioral and neural mechanisms supporting natural interaction poses substantial problems. In particular, the unconscious processes at the basis of emergent coordination (e.g., unintentional movements or gazing) are very difficult-if not impossible-to restrain or control in a quantitative way for a human agent. Moreover, during an interaction, participants influence each other continuously in a complex way, resulting in behaviors that go beyond experimental control. In this paper, we propose robotics technology as a potential solution to this methodological problem. Robots indeed can establish an interaction with a human partner, contingently reacting to his actions without losing the controllability of the experiment or the naturalness of the interactive scenario. A robot could represent an "interactive probe" to assess the sensory and motor mechanisms underlying human-human interaction. We discuss this proposal with examples from our research with the humanoid robot iCub, showing how an interactive humanoid robot could be a key tool to serve the investigation of the psychological and neuroscientific bases of social interaction.

An Intelligent Agent-Controlled and Robot-Based Disassembly Assistant

NASA Astrophysics Data System (ADS)

Jungbluth, Jan; Gerke, Wolfgang; Plapper, Peter

2017-09-01

One key for successful and fluent human-robot-collaboration in disassembly processes is equipping the robot system with higher autonomy and intelligence. In this paper, we present an informed software agent that controls the robot behavior to form an intelligent robot assistant for disassembly purposes. While the disassembly process first depends on the product structure, we inform the agent using a generic approach through product models. The product model is then transformed to a directed graph and used to build, share and define a coarse disassembly plan. To refine the workflow, we formulate “the problem of loosening a connection and the distribution of the work” as a search problem. The created detailed plan consists of a sequence of actions that are used to call, parametrize and execute robot programs for the fulfillment of the assistance. The aim of this research is to equip robot systems with knowledge and skills to allow them to be autonomous in the performance of their assistance to finally improve the ergonomics of disassembly workstations.

Using robots to understand animal cognition.

PubMed

Frohnwieser, Anna; Murray, John C; Pike, Thomas W; Wilkinson, Anna

2016-01-01

In recent years, robotic animals and humans have been used to answer a variety of questions related to behavior. In the case of animal behavior, these efforts have largely been in the field of behavioral ecology. They have proved to be a useful tool for this enterprise as they allow the presentation of naturalistic social stimuli whilst providing the experimenter with full control of the stimulus. In interactive experiments, the behavior of robots can be controlled in a manner that is impossible with real animals, making them ideal instruments for the study of social stimuli in animals. This paper provides an overview of the current state of the field and considers the impact that the use of robots could have on fundamental questions related to comparative psychology: namely, perception, spatial cognition, social cognition, and early cognitive development. We make the case that the use of robots to investigate these key areas could have an important impact on the field of animal cognition. © 2016 Society for the Experimental Analysis of Behavior.

A multitasking behavioral control system for the Robotic All Terrain Lunar Exploration Rover (RATLER)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klarer, P.

1994-03-01

The design of a multitasking behavioral control system for the Robotic All Terrain Lunar Exploration Rover (RATLER) is described. The control system design attempts to ameliorate some of the problems noted by some researchers when implementing subsumption or behavioral control systems, particularly with regard to multiple processor systems and real-time operations. The architecture is designed to allow both synchronous and asynchronous operations between various behavior modules by taking advantage of intertask communications channels, and by implementing each behavior module and each interconnection node as a stand-alone task. The potential advantages of this approach over those previously described in the fieldmore » are discussed. An implementation of the architecture is planned for a prototype Robotic All Terrain Lunar Exploration Rover (RATLER) currently under development, and is briefly described.« less

Emotional metacontrol of attention: Top-down modulation of sensorimotor processes in a robotic visual search task

PubMed Central

Cuperlier, Nicolas; Gaussier, Philippe

2017-01-01

Emotions play a significant role in internal regulatory processes. In this paper, we advocate four key ideas. First, novelty detection can be grounded in the sensorimotor experience and allow higher order appraisal. Second, cognitive processes, such as those involved in self-assessment, influence emotional states by eliciting affects like boredom and frustration. Third, emotional processes such as those triggered by self-assessment influence attentional processes. Last, close emotion-cognition interactions implement an efficient feedback loop for the purpose of top-down behavior regulation. The latter is what we call ‘Emotional Metacontrol’. We introduce a model based on artificial neural networks. This architecture is used to control a robotic system in a visual search task. The emotional metacontrol intervenes to bias the robot visual attention during active object recognition. Through a behavioral and statistical analysis, we show that this mechanism increases the robot performance and fosters the exploratory behavior to avoid deadlocks. PMID:28934291

Distributed recurrent neural forward models with synaptic adaptation and CPG-based control for complex behaviors of walking robots

PubMed Central

Dasgupta, Sakyasingha; Goldschmidt, Dennis; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain a variety of movements, the neural mechanisms generate movements while making appropriate predictions crucial for achieving adaptation. Such predictions or planning ahead can be achieved by way of internal models that are grounded in the overall behavior of the animal. Inspired by these findings, we present here, an artificial bio-inspired walking system which effectively combines biomechanics (in terms of the body and leg structures) with the underlying neural mechanisms. The neural mechanisms consist of (1) central pattern generator based control for generating basic rhythmic patterns and coordinated movements, (2) distributed (at each leg) recurrent neural network based adaptive forward models with efference copies as internal models for sensory predictions and instantaneous state estimations, and (3) searching and elevation control for adapting the movement of an individual leg to deal with different environmental conditions. Using simulations we show that this bio-inspired approach with adaptive internal models allows the walking robot to perform complex locomotive behaviors as observed in insects, including walking on undulated terrains, crossing large gaps, leg damage adaptations, as well as climbing over high obstacles. Furthermore, we demonstrate that the newly developed recurrent network based approach to online forward models outperforms the adaptive neuron forward models, which have hitherto been the state of the art, to model a subset of similar walking behaviors in walking robots. PMID:26441629

See You See Me: the Role of Eye Contact in Multimodal Human-Robot Interaction.

PubMed

Xu, Tian Linger; Zhang, Hui; Yu, Chen

2016-05-01

We focus on a fundamental looking behavior in human-robot interactions - gazing at each other's face. Eye contact and mutual gaze between two social partners are critical in smooth human-human interactions. Therefore, investigating at what moments and in what ways a robot should look at a human user's face as a response to the human's gaze behavior is an important topic. Toward this goal, we developed a gaze-contingent human-robot interaction system, which relied on momentary gaze behaviors from a human user to control an interacting robot in real time. Using this system, we conducted an experiment in which human participants interacted with the robot in a joint attention task. In the experiment, we systematically manipulated the robot's gaze toward the human partner's face in real time and then analyzed the human's gaze behavior as a response to the robot's gaze behavior. We found that more face looks from the robot led to more look-backs (to the robot's face) from human participants and consequently created more mutual gaze and eye contact between the two. Moreover, participants demonstrated more coordinated and synchronized multimodal behaviors between speech and gaze when more eye contact was successfully established and maintained.

Application of a model of instrumental conditioning to mobile robot control

NASA Astrophysics Data System (ADS)

Saksida, Lisa M.; Touretzky, D. S.

1997-09-01

Instrumental conditioning is a psychological process whereby an animal learns to associate its actions with their consequences. This type of learning is exploited in animal training techniques such as 'shaping by successive approximations,' which enables trainers to gradually adjust the animal's behavior by giving strategically timed reinforcements. While this is similar in principle to reinforcement learning, the real phenomenon includes many subtle effects not considered in the machine learning literature. In addition, a good deal of domain information is utilized by an animal learning a new task; it does not start from scratch every time it learns a new behavior. For these reasons, it is not surprising that mobile robot learning algorithms have yet to approach the sophistication and robustness of animal learning. A serious attempt to model instrumental learning could prove fruitful for improving machine learning techniques. In the present paper, we develop a computational theory of shaping at a level appropriate for controlling mobile robots. The theory is based on a series of mechanisms for 'behavior editing,' in which pre-existing behaviors, either innate or previously learned, can be dramatically changed in magnitude, shifted in direction, or otherwise manipulated so as to produce new behavioral routines. We have implemented our theory on Amelia, an RWI B21 mobile robot equipped with a gripper and color video camera. We provide results from training Amelia on several tasks, all of which were constructed as variations of one innate behavior, object-pursuit.

Robotic comfort zones

NASA Astrophysics Data System (ADS)

Likhachev, Maxim; Arkin, Ronald C.

2000-10-01

The paper investigates how the psychological notion of comfort can be useful in the design of robotic systems. A review of the existing study of human comfort, especially regarding its presence in infants, is conducted with the goal being to determine the relevant characteristics for mapping it onto the robotics domain. Focus is place on the identification of the salient features in the environment that affect the comfort level. Factors involved include current state familiarity, working conditions, the amount and location of available resources, etc. As part of our newly developed comfort function theory, the notion of an object as a psychological attachment for a robot is also introduced, as espoused in Bowlby's theory of attachment. The output space of the comfort function and its dependency on the comfort level are analyzed. The results of the derivation of this comfort function are then presented in terms of the impact they have on robotic behavior. Justification for the use of the comfort function are then presented in terms of the impact they have on robotic behavior. Justification for the use of the comfort function in the domain of robotics is presented with relevance for real-world operations. Also, a transformation of the theoretical discussion into a mathematical framework suitable for implementation within a behavior-based control system is presented. The paper concludes with results of simulation studies and real robot experiments using the derived comfort function.

Variants of guided self-organization for robot control.

PubMed

Martius, Georg; Herrmann, J Michael

2012-09-01

Autonomous robots can generate exploratory behavior by self-organization of the sensorimotor loop. We show that the behavioral manifold that is covered in this way can be modified in a goal-dependent way without reducing the self-induced activity of the robot. We present three strategies for guided self-organization, namely by using external rewards, a problem-specific error function, or assumptions about the symmetries of the desired behavior. The strategies are analyzed for two different robots in a physically realistic simulation.

A GPU-accelerated cortical neural network model for visually guided robot navigation.

PubMed

Beyeler, Michael; Oros, Nicolas; Dutt, Nikil; Krichmar, Jeffrey L

2015-12-01

Humans and other terrestrial animals use vision to traverse novel cluttered environments with apparent ease. On one hand, although much is known about the behavioral dynamics of steering in humans, it remains unclear how relevant perceptual variables might be represented in the brain. On the other hand, although a wealth of data exists about the neural circuitry that is concerned with the perception of self-motion variables such as the current direction of travel, little research has been devoted to investigating how this neural circuitry may relate to active steering control. Here we present a cortical neural network model for visually guided navigation that has been embodied on a physical robot exploring a real-world environment. The model includes a rate based motion energy model for area V1, and a spiking neural network model for cortical area MT. The model generates a cortical representation of optic flow, determines the position of objects based on motion discontinuities, and combines these signals with the representation of a goal location to produce motor commands that successfully steer the robot around obstacles toward the goal. The model produces robot trajectories that closely match human behavioral data. This study demonstrates how neural signals in a model of cortical area MT might provide sufficient motion information to steer a physical robot on human-like paths around obstacles in a real-world environment, and exemplifies the importance of embodiment, as behavior is deeply coupled not only with the underlying model of brain function, but also with the anatomical constraints of the physical body it controls. Copyright © 2015 Elsevier Ltd. All rights reserved.

Image Mapping and Visual Attention on the Sensory Ego-Sphere

NASA Technical Reports Server (NTRS)

Fleming, Katherine Achim; Peters, Richard Alan, II

2012-01-01

The Sensory Ego-Sphere (SES) is a short-term memory for a robot in the form of an egocentric, tessellated, spherical, sensory-motor map of the robot s locale. Visual attention enables fast alignment of overlapping images without warping or position optimization, since an attentional point (AP) on the composite typically corresponds to one on each of the collocated regions in the images. Such alignment speeds analysis of the multiple images of the area. Compositing and attention were performed two ways and compared: (1) APs were computed directly on the composite and not on the full-resolution images until the time of retrieval; and (2) the attentional operator was applied to all incoming imagery. It was found that although the second method was slower, it produced consistent and, thereby, more useful APs. The SES is an integral part of a control system that will enable a robot to learn new behaviors based on its previous experiences, and that will enable it to recombine its known behaviors in such a way as to solve related, but novel, task problems with apparent creativity. The approach is to combine sensory-motor data association and dimensionality reduction to learn navigation and manipulation tasks as sequences of basic behaviors that can be implemented with a small set of closed-loop controllers. Over time, the aggregate of behaviors and their transition probabilities form a stochastic network. Then given a task, the robot finds a path in the network that leads from its current state to the goal. The SES provides a short-term memory for the cognitive functions of the robot, association of sensory and motor data via spatio-temporal coincidence, direction of the attention of the robot, navigation through spatial localization with respect to known or discovered landmarks, and structured data sharing between the robot and human team members, the individuals in multi-robot teams, or with a C3 center.

Resource allocation and supervisory control architecture for intelligent behavior generation

NASA Astrophysics Data System (ADS)

Shah, Hitesh K.; Bahl, Vikas; Moore, Kevin L.; Flann, Nicholas S.; Martin, Jason

2003-09-01

In earlier research the Center for Self-Organizing and Intelligent Systems (CSOIS) at Utah State University (USU) was funded by the US Army Tank-Automotive and Armaments Command's (TACOM) Intelligent Mobility Program to develop and demonstrate enhanced mobility concepts for unmanned ground vehicles (UGVs). As part of our research, we presented the use of a grammar-based approach to enabling intelligent behaviors in autonomous robotic vehicles. With the growth of the number of available resources on the robot, the variety of the generated behaviors and the need for parallel execution of multiple behaviors to achieve reaction also grew. As continuation of our past efforts, in this paper, we discuss the parallel execution of behaviors and the management of utilized resources. In our approach, available resources are wrapped with a layer (termed services) that synchronizes and serializes access to the underlying resources. The controlling agents (called behavior generating agents) generate behaviors to be executed via these services. The agents are prioritized and then, based on their priority and the availability of requested services, the Control Supervisor decides on a winner for the grant of access to services. Though the architecture is applicable to a variety of autonomous vehicles, we discuss its application on T4, a mid-sized autonomous vehicle developed for security applications.

BGen: A UML Behavior Network Generator Tool

NASA Technical Reports Server (NTRS)

Huntsberger, Terry; Reder, Leonard J.; Balian, Harry

2010-01-01

BGen software was designed for autogeneration of code based on a graphical representation of a behavior network used for controlling automatic vehicles. A common format used for describing a behavior network, such as that used in the JPL-developed behavior-based control system, CARACaS ["Control Architecture for Robotic Agent Command and Sensing" (NPO-43635), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 40] includes a graph with sensory inputs flowing through the behaviors in order to generate the signals for the actuators that drive and steer the vehicle. A computer program to translate Unified Modeling Language (UML) Freeform Implementation Diagrams into a legacy C implementation of Behavior Network has been developed in order to simplify the development of C-code for behavior-based control systems. UML is a popular standard developed by the Object Management Group (OMG) to model software architectures graphically. The C implementation of a Behavior Network is functioning as a decision tree.

Structuring Formal Control Systems Specifications for Reuse: Surviving Hardware Changes

NASA Technical Reports Server (NTRS)

Thompson, Jeffrey M.; Heimdahl, Mats P. E.; Erickson, Debra M.

2000-01-01

Formal capture and analysis of the required behavior of control systems have many advantages. For instance, it encourages rigorous requirements analysis, the required behavior is unambiguously defined, and we can assure that various safety properties are satisfied. Formal modeling is, however, a costly and time consuming process and if one could reuse the formal models over a family of products, significant cost savings would be realized. In an ongoing project we are investigating how to structure state-based models to achieve a high level of reusability within product families. In this paper we discuss a high-level structure of requirements models that achieves reusability of the desired control behavior across varying hardware platforms in a product family. The structuring approach is demonstrated through a case study in the mobile robotics domain where the desired robot behavior is reused on two diverse platforms-one commercial mobile platform and one build in-house. We use our language RSML (-e) to capture the control behavior for reuse and our tool NIMBUS to demonstrate how the formal specification can be validated and used as a prototype on the two platforms.

Symbolic dynamic filtering and language measure for behavior identification of mobile robots.

PubMed

Mallapragada, Goutham; Ray, Asok; Jin, Xin

2012-06-01

This paper presents a procedure for behavior identification of mobile robots, which requires limited or no domain knowledge of the underlying process. While the features of robot behavior are extracted by symbolic dynamic filtering of the observed time series, the behavior patterns are classified based on language measure theory. The behavior identification procedure has been experimentally validated on a networked robotic test bed by comparison with commonly used tools, namely, principal component analysis for feature extraction and Bayesian risk analysis for pattern classification.

Active avoidance: escape and dodging behaviors for reactive control

NASA Astrophysics Data System (ADS)

Arkin, Ronald C.; Carter, William M.

1992-03-01

New methods for producing avoidance behavior among moving obstacles within the context of reactive robotic control are described. These specifically include escape and dodging behaviors. Dodging is concerned with the avoidance of a ballistic projectile while escape is more useful within the context of chase. The motivation and formulation of these new reactive behaviors are presented. Simulation results of a robot in a cluttered and moving world are also provided.

Deriving neural network controllers from neuro-biological data: implementation of a single-leg stick insect controller.

PubMed

von Twickel, Arndt; Büschges, Ansgar; Pasemann, Frank

2011-02-01

This article presents modular recurrent neural network controllers for single legs of a biomimetic six-legged robot equipped with standard DC motors. Following arguments of Ekeberg et al. (Arthropod Struct Dev 33:287-300, 2004), completely decentralized and sensori-driven neuro-controllers were derived from neuro-biological data of stick-insects. Parameters of the controllers were either hand-tuned or optimized by an evolutionary algorithm. Employing identical controller structures, qualitatively similar behaviors were achieved for robot and for stick insect simulations. For a wide range of perturbing conditions, as for instance changing ground height or up- and downhill walking, swing as well as stance control were shown to be robust. Behavioral adaptations, like varying locomotion speeds, could be achieved by changes in neural parameters as well as by a mechanical coupling to the environment. To a large extent the simulated walking behavior matched biological data. For example, this was the case for body support force profiles and swing trajectories under varying ground heights. The results suggest that the single-leg controllers are suitable as modules for hexapod controllers, and they might therefore bridge morphological- and behavioral-based approaches to stick insect locomotion control.

A small, cheap, and portable reconnaissance robot

NASA Astrophysics Data System (ADS)

Kenyon, Samuel H.; Creary, D.; Thi, Dan; Maynard, Jeffrey

2005-05-01

While there is much interest in human-carriable mobile robots for defense/security applications, existing examples are still too large/heavy, and there are not many successful small human-deployable mobile ground robots, especially ones that can survive being thrown/dropped. We have developed a prototype small short-range teleoperated indoor reconnaissance/surveillance robot that is semi-autonomous. It is self-powered, self-propelled, spherical, and meant to be carried and thrown by humans into indoor, yet relatively unstructured, dynamic environments. The robot uses multiple channels for wireless control and feedback, with the potential for inter-robot communication, swarm behavior, or distributed sensor network capabilities. The primary reconnaissance sensor for this prototype is visible-spectrum video. This paper focuses more on the software issues, both the onboard intelligent real time control system and the remote user interface. The communications, sensor fusion, intelligent real time controller, etc. are implemented with onboard microcontrollers. We based the autonomous and teleoperation controls on a simple finite state machine scripting layer. Minimal localization and autonomous routines were designed to best assist the operator, execute whatever mission the robot may have, and promote its own survival. We also discuss the advantages and pitfalls of an inexpensive, rapidly-developed semi-autonomous robotic system, especially one that is spherical, and the importance of human-robot interaction as considered for the human-deployment and remote user interface.

Homeostasis lighting control based on relationship between lighting environment and human behavior

NASA Astrophysics Data System (ADS)

Ueda, Risa; Mita, Akira

2015-03-01

Although each person has own preferences, living spaces which can respond to various preferences and needs have not become reality. Focusing on the lighting environments which influence on the impression of living spaces, this research aims to offer comfortable lighting environments for each resident by a flexible control. This research examines the relationship between lighting environments and human behaviors considering colored lights. In accord with the relationship, this research proposes an illuminance-color control system which flexibly changes spatial environments responding to human conditions. Firstly, the psychological evaluation was conducted in order to build human models for various environments. As a result, preferred lighting environments for each examinee were determined for particular behaviors. Moreover, satisfaction levels of lighting environments were calculated by using seven types of impression of the environments as parameters. The results were summarized as human models. Secondly, this research proposed "Homeostasis Lighting Control System", which employs the human models. Homeostasis lighting control system embodies the algorithm of homeostasis, which is one of the functions of the physiological adaptation. Human discomfort feelings are obtained automatically by the sensor agent robot. The system can offer comfortable lighting environments without controlling environments by residents autonomously based on the information from the robot. This research takes into accounts both illuminance and color. The robot communicates with the server which contains human models, then the system corresponds to individuals. Combining these three systems, the proposed system can effectively control the lighting environment. At last, the feasibility of the proposed system was verified by simulation experiments.

Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pin, Francois G.

2002-06-01

Robotic tasks are typically defined in Task Space (e.g., the 3-D World), whereas robots are controlled in Joint Space (motors). The transformation from Task Space to Joint Space must consider the task objectives (e.g., high precision, strength optimization, torque optimization), the task constraints (e.g., obstacles, joint limits, non-holonomic constraints, contact or tool task constraints), and the robot kinematics configuration (e.g., tools, type of joints, mobile platform, manipulator, modular additions, locked joints). Commercially available robots are optimized for a specific set of tasks, objectives and constraints and, therefore, their control codes are extremely specific to a particular set of conditions. Thus,more » there exist a multiplicity of codes, each handling a particular set of conditions, but none suitable for use on robots with widely varying tasks, objectives, constraints, or environments. On the other hand, most DOE missions and tasks are typically ''batches of one''. Attempting to use commercial codes for such work requires significant personnel and schedule costs for re-programming or adding code to the robots whenever a change in task objective, robot configuration, number and type of constraint, etc. occurs. The objective of our project is to develop a ''generic code'' to implement this Task-space to Joint-Space transformation that would allow robot behavior adaptation, in real time (at loop rate), to changes in task objectives, number and type of constraints, modes of controls, kinematics configuration (e.g., new tools, added module). Our specific goal is to develop a single code for the general solution of under-specified systems of algebraic equations that is suitable for solving the inverse kinematics of robots, is useable for all types of robots (mobile robots, manipulators, mobile manipulators, etc.) with no limitation on the number of joints and the number of controlled Task-Space variables, can adapt to real time changes in number and type of constraints and in task objectives, and can adapt to changes in kinematics configurations (change of module, change of tool, joint failure adaptation, etc.).« less

Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm

DTIC Science & Technology

2016-04-01

cheap, disposable swarms of robots that can accomplish these tasks quickly and with- out much human supervision. While there has been a lot of work...have shown that swarms of robots so dumb that they have no computational power–they can’t even add or subtract, and have no memory can still collec...behaviors can be achieved using swarms of computation-free robots . Our work starts with the simple robot model proposed in [6] and adds a form of

Boundaries Control Collective Dynamics of Inertial Self-Propelled Robots.

PubMed

Deblais, A; Barois, T; Guerin, T; Delville, P H; Vaudaine, R; Lintuvuori, J S; Boudet, J F; Baret, J C; Kellay, H

2018-05-04

Simple ingredients, such as well-defined interactions and couplings for the velocity and orientation of self-propelled objects, are sufficient to produce complex collective behavior in assemblies of such entities. Here, we use assemblies of rodlike robots made motile through self-vibration. When confined in circular arenas, dilute assemblies of these rods act as a gas. Increasing the surface fraction leads to a collective behavior near the boundaries: polar clusters emerge while, in the bulk, gaslike behavior is retained. The coexistence between a gas and surface clusters is a direct consequence of inertial effects as shown by our simulations. A theoretical model, based on surface mediated transport accounts for this coexistence and illustrates the exact role of the boundaries. Our study paves the way towards the control of collective behavior: By using deformable but free to move arenas, we demonstrate that the surface induced clusters can lead to directed motion, while the topology of the surface states can be controlled by biasing the motility of the particles.

Boundaries Control Collective Dynamics of Inertial Self-Propelled Robots

NASA Astrophysics Data System (ADS)

Deblais, A.; Barois, T.; Guerin, T.; Delville, P. H.; Vaudaine, R.; Lintuvuori, J. S.; Boudet, J. F.; Baret, J. C.; Kellay, H.

2018-05-01

Simple ingredients, such as well-defined interactions and couplings for the velocity and orientation of self-propelled objects, are sufficient to produce complex collective behavior in assemblies of such entities. Here, we use assemblies of rodlike robots made motile through self-vibration. When confined in circular arenas, dilute assemblies of these rods act as a gas. Increasing the surface fraction leads to a collective behavior near the boundaries: polar clusters emerge while, in the bulk, gaslike behavior is retained. The coexistence between a gas and surface clusters is a direct consequence of inertial effects as shown by our simulations. A theoretical model, based on surface mediated transport accounts for this coexistence and illustrates the exact role of the boundaries. Our study paves the way towards the control of collective behavior: By using deformable but free to move arenas, we demonstrate that the surface induced clusters can lead to directed motion, while the topology of the surface states can be controlled by biasing the motility of the particles.

Morphological computation of multi-gaited robot locomotion based on free vibration.

PubMed

Reis, Murat; Yu, Xiaoxiang; Maheshwari, Nandan; Iida, Fumiya

2013-01-01

In recent years, there has been increasing interest in the study of gait patterns in both animals and robots, because it allows us to systematically investigate the underlying mechanisms of energetics, dexterity, and autonomy of adaptive systems. In particular, for morphological computation research, the control of dynamic legged robots and their gait transitions provides additional insights into the guiding principles from a synthetic viewpoint for the emergence of sensible self-organizing behaviors in more-degrees-of-freedom systems. This article presents a novel approach to the study of gait patterns, which makes use of the intrinsic mechanical dynamics of robotic systems. Each of the robots consists of a U-shaped elastic beam and exploits free vibration to generate different locomotion patterns. We developed a simplified physics model of these robots, and through experiments in simulation and real-world robotic platforms, we show three distinctive mechanisms for generating different gait patterns in these robots.

Reducing software mass through behavior control. [of planetary roving robots

NASA Technical Reports Server (NTRS)

Miller, David P.

1992-01-01

Attention is given to the tradeoff between communication and computation as regards a planetary rover (both these subsystems are very power-intensive, and both can be the major driver of the rover's power subsystem, and therefore the minimum mass and size of the rover). Software techniques that can be used to reduce the requirements on both communciation and computation, allowing the overall robot mass to be greatly reduced, are discussed. Novel approaches to autonomous control, called behavior control, employ an entirely different approach, and for many tasks will yield a similar or superior level of autonomy to traditional control techniques, while greatly reducing the computational demand. Traditional systems have several expensive processes that operate serially, while behavior techniques employ robot capabilities that run in parallel. Traditional systems make extensive world models, while behavior control systems use minimal world models or none at all.

From the laboratory to the soldier: providing tactical behaviors for Army robots

NASA Astrophysics Data System (ADS)

Knichel, David G.; Bruemmer, David J.

2008-04-01

The Army Future Combat System (FCS) Operational Requirement Document has identified a number of advanced robot tactical behavior requirements to enable the Future Brigade Combat Team (FBCT). The FBCT advanced tactical behaviors include Sentinel Behavior, Obstacle Avoidance Behavior, and Scaled Levels of Human-Machine control Behavior. The U.S. Army Training and Doctrine Command, (TRADOC) Maneuver Support Center (MANSCEN) has also documented a number of robotic behavior requirements for the Army non FCS forces such as the Infantry Brigade Combat Team (IBCT), Stryker Brigade Combat Team (SBCT), and Heavy Brigade Combat Team (HBCT). The general categories of useful robot tactical behaviors include Ground/Air Mobility behaviors, Tactical Mission behaviors, Manned-Unmanned Teaming behaviors, and Soldier-Robot Interface behaviors. Many DoD research and development centers are achieving the necessary components necessary for artificial tactical behaviors for ground and air robots to include the Army Research Laboratory (ARL), U.S. Army Research, Development and Engineering Command (RDECOM), Space and Naval Warfare (SPAWAR) Systems Center, US Army Tank-Automotive Research, Development and Engineering Center (TARDEC) and non DoD labs such as Department of Energy (DOL). With the support of the Joint Ground Robotics Enterprise (JGRE) through DoD and non DoD labs the Army Maneuver Support Center has recently concluded successful field trails of ground and air robots with specialized tactical behaviors and sensors to enable semi autonomous detection, reporting, and marking of explosive hazards to include Improvised Explosive Devices (IED) and landmines. A specific goal of this effort was to assess how collaborative behaviors for multiple unmanned air and ground vehicles can reduce risks to Soldiers and increase efficiency for on and off route explosive hazard detection, reporting, and marking. This paper discusses experimental results achieved with a robotic countermine system that utilizes autonomous behaviors and a mixed-initiative control scheme to address the challenges of detecting and marking buried landmines. Emerging requirements for robotic countermine operations are outlined as are the technologies developed under this effort to address them. A first experiment shows that the resulting system was able to find and mark landmines with a very low level of human involvement. In addition, the data indicates that the robotic system is able to decrease the time to find mines and increase the detection accuracy and reliability. Finally, the paper presents current efforts to incorporate new countermine sensors and port the resulting behaviors to two fielded military systems for rigorous assessing.

Designing and Implementing Nervous System Simulations on LEGO Robots

PubMed Central

Blustein, Daniel; Rosenthal, Nikolai; Ayers, Joseph

2013-01-01

We present a method to use the commercially available LEGO Mindstorms NXT robotics platform to test systems level neuroscience hypotheses. The first step of the method is to develop a nervous system simulation of specific reflexive behaviors of an appropriate model organism; here we use the American Lobster. Exteroceptive reflexes mediated by decussating (crossing) neural connections can explain an animal's taxis towards or away from a stimulus as described by Braitenberg and are particularly well suited for investigation using the NXT platform.1 The nervous system simulation is programmed using LabVIEW software on the LEGO Mindstorms platform. Once the nervous system is tuned properly, behavioral experiments are run on the robot and on the animal under identical environmental conditions. By controlling the sensory milieu experienced by the specimens, differences in behavioral outputs can be observed. These differences may point to specific deficiencies in the nervous system model and serve to inform the iteration of the model for the particular behavior under study. This method allows for the experimental manipulation of electronic nervous systems and serves as a way to explore neuroscience hypotheses specifically regarding the neurophysiological basis of simple innate reflexive behaviors. The LEGO Mindstorms NXT kit provides an affordable and efficient platform on which to test preliminary biomimetic robot control schemes. The approach is also well suited for the high school classroom to serve as the foundation for a hands-on inquiry-based biorobotics curriculum. PMID:23728477

FOCU:S--future operator control unit: soldier

NASA Astrophysics Data System (ADS)

O'Brien, Barry J.; Karan, Cem; Young, Stuart H.

2009-05-01

The U.S. Army Research Laboratory's (ARL) Computational and Information Sciences Directorate (CISD) has long been involved in autonomous asset control, specifically as it relates to small robots. Over the past year, CISD has been making strides in the implementation of three areas of small robot autonomy, namely platform autonomy, Soldier-robot interface, and tactical behaviors. It is CISD's belief that these three areas must be considered as a whole in order to provide Soldiers with useful capabilities. In addressing the Soldier-robot interface aspect, CISD has begun development on a unique dismounted controller called the Future Operator Control Unit: Soldier (FOCU:S) that is based on an Apple iPod Touch. The iPod Touch's small form factor, unique touch-screen input device, and the presence of general purpose computing applications such as a web browser combine to give this device the potential to be a disruptive technology. Setting CISD's implementation apart from other similar iPod or iPhone-based devices is the ARL software that allows multiple robotic platforms to be controlled from a single OCU. The FOCU:S uses the same Agile Computing Infrastructure (ACI) that all other assets in the ARL robotic control system use, enabling automated asset discovery on any type of network. Further, a custom ad hoc routing implementation allows the FOCU:S to communicate with the ARL ad hoc communications system and enables it to extend the range of the network. This paper will briefly describe the current robotic control architecture employed by ARL and provide short descriptions of existing capabilities. Further, the paper will discuss FOCU:S specific software developed for the iPod Touch, including unique capabilities enabled by the device's unique hardware.

Control of humanoid robot via motion-onset visual evoked potentials

PubMed Central

Li, Wei; Li, Mengfan; Zhao, Jing

2015-01-01

This paper investigates controlling humanoid robot behavior via motion-onset specific N200 potentials. In this study, N200 potentials are induced by moving a blue bar through robot images intuitively representing robot behaviors to be controlled with mind. We present the individual impact of each subject on N200 potentials and discuss how to deal with individuality to obtain a high accuracy. The study results document the off-line average accuracy of 93% for hitting targets across over five subjects, so we use this major component of the motion-onset visual evoked potential (mVEP) to code people's mental activities and to perform two types of on-line operation tasks: navigating a humanoid robot in an office environment with an obstacle and picking-up an object. We discuss the factors that affect the on-line control success rate and the total time for completing an on-line operation task. PMID:25620918

Micromanipulation and microfabrication for optical microrobotics

NASA Astrophysics Data System (ADS)

Palima, Darwin; Bañas, Andrew Rafael; Vizsnyiczai, Gaszton; Kelemen, Lóránd; Aabo, Thomas; Ormos, Pál.; Glückstad, Jesper

2012-10-01

Robotics can use optics feedback in vision-based control of intelligent robotic guidance systems. With light's miniscule momentum, shrinking robots down to the microscale regime creates opportunities for exploiting optical forces and torques in microrobotic actuation and control. Indeed, the literature on optical trapping and micromanipulation attests to the possibilities for optical microrobotics. This work presents an optical microrobotics perspective on the optical microfabrication and micromanipulation work that we performed. We designed different three-dimensional microstructures and fabricated them by two-photon polymerization. These microstructures were then handled using our biophotonics workstation (BWS) for proof-of-principle demonstrations of optical actuation, akin to 6DOF actuation of robotic micromanipulators. Furthermore, we also show an example of dynamic behavior of the trapped microstructure that can be achieved when using static traps in the BWS. This can be generalized, in the future, towards a structural shaping optimization strategy for optimally controlling microstructures to complement approaches based on lightshaping. We also show that light channeled to microfabricated, free-standing waveguides can be used not only to redirect light for targeted delivery of optical energy but can also for targeted delivery of optical force, which can serve to further extend the manipulation arms in optical robotics. Moreover, light deflection with waveguide also creates a recoil force on the waveguide, which can be exploited for controlling the optical force.

Ionic polymer-metal composite enabled robotic manta ray

NASA Astrophysics Data System (ADS)

Chen, Zheng; Um, Tae I.; Bart-Smith, Hilary

2011-04-01

The manta ray, Manta birostris, demonstrates excellent swimming capabilities; generating highly efficient thrust via flapping of dorsally flattened pectoral fins. In this paper, we present an underwater robot that mimics the swimming behavior of the manta ray. An assembly-based fabrication method is developed to create the artificial pectoral fins, which are capable of generating oscillatory with a large twisting angle between leading and trailing edges. Ionic polymer-metal composite (IPMC) actuators are used as artificial muscles in the fin. Each fin consists of four IPMC beams bonded with a compliant poly(dimethylsiloxane) (PDMS) membrane. By controlling each individual IPMC strips, we are able to generate complex flapping motions. The fin is characterized in terms of tip deflection, tip blocking force, twist angle, and power consumption. Based on the characteristics of the artificial pectoral fin, a small size and free-swimming robotic manta ray is developed. The robot consists of two artificial pectoral fins, a rigid body, and an on-board control unit with a lithium ion rechargeable battery. Experimental results show that the robot swam at a speed of up to 0.055 body length per second (BL/sec).

Distributed flow sensing for closed-loop speed control of a flexible fish robot.

PubMed

Zhang, Feitian; Lagor, Francis D; Yeo, Derrick; Washington, Patrick; Paley, Derek A

2015-10-23

Flexibility plays an important role in fish behavior by enabling high maneuverability for predator avoidance and swimming in turbulent flow. This paper presents a novel flexible fish robot equipped with distributed pressure sensors for flow sensing. The body of the robot is molded from soft, hyperelastic material, which provides flexibility. Its Joukowski-foil shape is conducive to modeling the fluid analytically. A quasi-steady potential-flow model is adopted for real-time flow estimation, whereas a discrete-time vortex-shedding flow model is used for higher-fidelity simulation. The dynamics for the flexible fish robot yield a reduced model for one-dimensional swimming. A recursive Bayesian filter assimilates pressure measurements to estimate flow speed, angle of attack, and foil camber. The closed-loop speed-control strategy combines an inverse-mapping feedforward controller based on an average model derived for periodic actuation of angle-of-attack and a proportional-integral feedback controller utilizing the estimated flow information. Simulation and experimental results are presented to show the effectiveness of the estimation and control strategy. The paper provides a systematic approach to distributed flow sensing for closed-loop speed control of a flexible fish robot by regulating the flapping amplitude.

Motion and Emotional Behavior Design for Pet Robot Dog

NASA Astrophysics Data System (ADS)

Cheng, Chi-Tai; Yang, Yu-Ting; Miao, Shih-Heng; Wong, Ching-Chang

A pet robot dog with two ears, one mouth, one facial expression plane, and one vision system is designed and implemented so that it can do some emotional behaviors. Three processors (Inter® Pentium® M 1.0 GHz, an 8-bit processer 8051, and embedded soft-core processer NIOS) are used to control the robot. One camera, one power detector, four touch sensors, and one temperature detector are used to obtain the information of the environment. The designed robot with 20 DOF (degrees of freedom) is able to accomplish the walking motion. A behavior system is built on the implemented pet robot so that it is able to choose a suitable behavior for different environmental situation. From the practical test, we can see that the implemented pet robot dog can do some emotional interaction with the human.

Impedance control in a wave-based teleoperator for rehabilitation motor therapies assisted by robots.

PubMed

Mendoza, Marco; Bonilla, Isela; González-Galván, Emilio; Reyes, Fernando

2016-01-01

This paper presents an improved wave-based bilateral teleoperation scheme for rehabilitation therapies assisted by robot manipulators. The main feature of this bilateral teleoperator is that both robot manipulators, master and slave, are controlled by impedance. Thus, a pair of motion-based adaptive impedance controllers are integrated into a wave-based configuration, in order to guarantee a stable human-robot interaction and to compensate the position drift, characteristic of the available schemes of bilateral teleoperation. Moreover, the teleoperator stability, in the presence of time delays in the communication channel, is guaranteed because the wave-variable approach is included to encode the force and velocity signals. It should be noted that the proposed structure enables the implementation of several teleoperator schemes, from passive therapies, without the intervention of a human operator on the master side, to fully active therapies where both manipulators interact with humans in a stable manner. The suitable performance of the proposed teleoperator is verified through some results obtained from the simulation of the passive and active-constrained modes, by considering typical tasks in motor-therapy rehabilitation, where an improved behavior is observed when compared to implementations of the classical wave-based approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Control of autonomous robot using neural networks

NASA Astrophysics Data System (ADS)

Barton, Adam; Volna, Eva

2017-07-01

The aim of the article is to design a method of control of an autonomous robot using artificial neural networks. The introductory part describes control issues from the perspective of autonomous robot navigation and the current mobile robots controlled by neural networks. The core of the article is the design of the controlling neural network, and generation and filtration of the training set using ART1 (Adaptive Resonance Theory). The outcome of the practical part is an assembled Lego Mindstorms EV3 robot solving the problem of avoiding obstacles in space. To verify models of an autonomous robot behavior, a set of experiments was created as well as evaluation criteria. The speed of each motor was adjusted by the controlling neural network with respect to the situation in which the robot was found.

Extended Task Space Control for Robotic Manipulators

NASA Technical Reports Server (NTRS)

Backes, Paul G. (Inventor); Long, Mark K. (Inventor)

1996-01-01

The invention is a method of operating a robot in successive sampling intervals to perform a task, the robot having joints and joint actuators with actuator control loops, by decomposing the task into behavior forces, accelerations, velocities and positions of plural behaviors to be exhibited by the robot simultaneously, computing actuator accelerations of the joint actuators for the current sampling interval from both behavior forces, accelerations velocities and positions of the current sampling interval and actuator velocities and positions of the previous sampling interval, computing actuator velocities and positions of the joint actuators for the current sampling interval from the actuator velocities and positions of the previous sampling interval, and, finally, controlling the actuators in accordance with the actuator accelerations, velocities and positions of the current sampling interval. The actuator accelerations, velocities and positions of the current sampling interval are stored for use during the next sampling interval.

Robotic Billiards: Understanding Humans in Order to Counter Them.

PubMed

Nierhoff, Thomas; Leibrandt, Konrad; Lorenz, Tamara; Hirche, Sandra

2016-08-01

Ongoing technological advances in the areas of computation, sensing, and mechatronics enable robotic-based systems to interact with humans in the real world. To succeed against a human in a competitive scenario, a robot must anticipate the human behavior and include it in its own planning framework. Then it can predict the next human move and counter it accordingly, thus not only achieving overall better performance but also systematically exploiting the opponent's weak spots. Pool is used as a representative scenario to derive a model-based planning and control framework where not only the physics of the environment but also a model of the opponent is considered. By representing the game of pool as a Markov decision process and incorporating a model of the human decision-making based on studies, an optimized policy is derived. This enables the robot to include the opponent's typical game style into its tactical considerations when planning a stroke. The results are validated in simulations and real-life experiments with an anthropomorphic robot playing pool against a human.

Adaptive categorization of ART networks in robot behavior learning using game-theoretic formulation.

PubMed

Fung, Wai-keung; Liu, Yun-hui

2003-12-01

Adaptive Resonance Theory (ART) networks are employed in robot behavior learning. Two of the difficulties in online robot behavior learning, namely, (1) exponential memory increases with time, (2) difficulty for operators to specify learning tasks accuracy and control learning attention before learning. In order to remedy the aforementioned difficulties, an adaptive categorization mechanism is introduced in ART networks for perceptual and action patterns categorization in this paper. A game-theoretic formulation of adaptive categorization for ART networks is proposed for vigilance parameter adaptation for category size control on the categories formed. The proposed vigilance parameter update rule can help improving categorization performance in the aspect of category number stability and solve the problem of selecting initial vigilance parameter prior to pattern categorization in traditional ART networks. Behavior learning using physical robot is conducted to demonstrate the effectiveness of the proposed adaptive categorization mechanism in ART networks.

Energetic Passivity of the Human Ankle Joint.

PubMed

Lee, Hyunglae; Hogan, Neville

2016-12-01

Understanding the passive or nonpassive behavior of the neuromuscular system is important to design and control robots that physically interact with humans, since it provides quantitative information to secure coupled stability while maximizing performance. This has become more important than ever apace with the increasing demand for robotic technologies in neurorehabilitation. This paper presents a quantitative characterization of passive and nonpassive behavior of the ankle of young healthy subjects, which provides a baseline for future studies in persons with neurological impairments and information for future developments of rehabilitation robots, such as exoskeletal devices and powered prostheses. Measurements using a wearable ankle robot actuating 2 degrees-of-freedom of the ankle combined with curl analysis and passivity analysis enabled characterization of both quasi-static and steady-state dynamic behavior of the ankle, unavailable from single DOF studies. Despite active neuromuscular control over a wide range of muscle activation, in young healthy subjects passive or dissipative ankle behavior predominated.

HiMoP: A three-component architecture to create more human-acceptable social-assistive robots : Motivational architecture for assistive robots.

PubMed

Rodríguez-Lera, Francisco J; Matellán-Olivera, Vicente; Conde-González, Miguel Á; Martín-Rico, Francisco

2018-05-01

Generation of autonomous behavior for robots is a general unsolved problem. Users perceive robots as repetitive tools that do not respond to dynamic situations. This research deals with the generation of natural behaviors in assistive service robots for dynamic domestic environments, particularly, a motivational-oriented cognitive architecture to generate more natural behaviors in autonomous robots. The proposed architecture, called HiMoP, is based on three elements: a Hierarchy of needs to define robot drives; a set of Motivational variables connected to robot needs; and a Pool of finite-state machines to run robot behaviors. The first element is inspired in Alderfer's hierarchy of needs, which specifies the variables defined in the motivational component. The pool of finite-state machine implements the available robot actions, and those actions are dynamically selected taking into account the motivational variables and the external stimuli. Thus, the robot is able to exhibit different behaviors even under similar conditions. A customized version of the "Speech Recognition and Audio Detection Test," proposed by the RoboCup Federation, has been used to illustrate how the architecture works and how it dynamically adapts and activates robots behaviors taking into account internal variables and external stimuli.

Soft Dielectric Elastomer Oscillators Driving Bioinspired Robots.

PubMed

Henke, E-F Markus; Schlatter, Samuel; Anderson, Iain A

2017-12-01

Entirely soft robots with animal-like behavior and integrated artificial nervous systems will open up totally new perspectives and applications. To produce them, we must integrate control and actuation in the same soft structure. Soft actuators (e.g., pneumatic and hydraulic) exist but electronics are hard and stiff and remotely located. We present novel soft, electronics-free dielectric elastomer oscillators, which are able to drive bioinspired robots. As a demonstrator, we present a robot that mimics the crawling motion of the caterpillar, with an integrated artificial nervous system, soft actuators and without any conventional stiff electronic parts. Supplied with an external DC voltage, the robot autonomously generates all signals that are necessary to drive its dielectric elastomer actuators, and it translates an in-plane electromechanical oscillation into a crawling locomotion movement. Therefore, all functional and supporting parts are made of polymer materials and carbon. Besides the basic design of this first electronic-free, biomimetic robot, we present prospects to control the general behavior of such robots. The absence of conventional stiff electronics and the exclusive use of polymeric materials will provide a large step toward real animal-like robots, compliant human machine interfaces, and a new class of distributed, neuron-like internal control for robotic systems.

Continuum Reconfigurable Parallel Robots for Surgery: Shape Sensing and State Estimation with Uncertainty.

PubMed

Anderson, Patrick L; Mahoney, Arthur W; Webster, Robert J

2017-07-01

This paper examines shape sensing for a new class of surgical robot that consists of parallel flexible structures that can be reconfigured inside the human body. Known as CRISP robots, these devices provide access to the human body through needle-sized entry points, yet can be configured into truss-like structures capable of dexterous movement and large force application. They can also be reconfigured as needed during a surgical procedure. Since CRISP robots are elastic, they will deform when subjected to external forces or other perturbations. In this paper, we explore how to combine sensor information with mechanics-based models for CRISP robots to estimate their shapes under applied loads. The end result is a shape sensing framework for CRISP robots that will enable future research on control under applied loads, autonomous motion, force sensing, and other robot behaviors.

Intrinsic interactive reinforcement learning - Using error-related potentials for real world human-robot interaction.

PubMed

Kim, Su Kyoung; Kirchner, Elsa Andrea; Stefes, Arne; Kirchner, Frank

2017-12-14

Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in dynamic environments based on feedback. Explicit human feedback during robot RL is advantageous, since an explicit reward function can be easily adapted. However, it is very demanding and tiresome for a human to continuously and explicitly generate feedback. Therefore, the development of implicit approaches is of high relevance. In this paper, we used an error-related potential (ErrP), an event-related activity in the human electroencephalogram (EEG), as an intrinsically generated implicit feedback (rewards) for RL. Initially we validated our approach with seven subjects in a simulated robot learning scenario. ErrPs were detected online in single trial with a balanced accuracy (bACC) of 91%, which was sufficient to learn to recognize gestures and the correct mapping between human gestures and robot actions in parallel. Finally, we validated our approach in a real robot scenario, in which seven subjects freely chose gestures and the real robot correctly learned the mapping between gestures and actions (ErrP detection (90% bACC)). In this paper, we demonstrated that intrinsically generated EEG-based human feedback in RL can successfully be used to implicitly improve gesture-based robot control during human-robot interaction. We call our approach intrinsic interactive RL.

The trade-off between morphology and control in the co-optimized design of robots.

PubMed

Rosendo, Andre; von Atzigen, Marco; Iida, Fumiya

2017-01-01

Conventionally, robot morphologies are developed through simulations and calculations, and different control methods are applied afterwards. Assuming that simulations and predictions are simplified representations of our reality, how sure can roboticists be that the chosen morphology is the most adequate for the possible control choices in the real-world? Here we study the influence of the design parameters in the creation of a robot with a Bayesian morphology-control (MC) co-optimization process. A robot autonomously creates child robots from a set of possible design parameters and uses Bayesian Optimization (BO) to infer the best locomotion behavior from real world experiments. Then, we systematically change from an MC co-optimization to a control-only (C) optimization, which better represents the traditional way that robots are developed, to explore the trade-off between these two methods. We show that although C processes can greatly improve the behavior of poor morphologies, such agents are still outperformed by MC co-optimization results with as few as 25 iterations. Our findings, on one hand, suggest that BO should be used in the design process of robots for both morphological and control parameters to reach optimal performance, and on the other hand, point to the downfall of current design methods in face of new search techniques.

The trade-off between morphology and control in the co-optimized design of robots

PubMed Central

Iida, Fumiya

2017-01-01

Conventionally, robot morphologies are developed through simulations and calculations, and different control methods are applied afterwards. Assuming that simulations and predictions are simplified representations of our reality, how sure can roboticists be that the chosen morphology is the most adequate for the possible control choices in the real-world? Here we study the influence of the design parameters in the creation of a robot with a Bayesian morphology-control (MC) co-optimization process. A robot autonomously creates child robots from a set of possible design parameters and uses Bayesian Optimization (BO) to infer the best locomotion behavior from real world experiments. Then, we systematically change from an MC co-optimization to a control-only (C) optimization, which better represents the traditional way that robots are developed, to explore the trade-off between these two methods. We show that although C processes can greatly improve the behavior of poor morphologies, such agents are still outperformed by MC co-optimization results with as few as 25 iterations. Our findings, on one hand, suggest that BO should be used in the design process of robots for both morphological and control parameters to reach optimal performance, and on the other hand, point to the downfall of current design methods in face of new search techniques. PMID:29023482

Behavior-based multi-robot collaboration for autonomous construction tasks

NASA Technical Reports Server (NTRS)

Stroupe, Ashley; Huntsberger, Terry; Okon, Avi; Aghazarian, Hrand; Robinson, Matthew

2005-01-01

The Robot Construction Crew (RCC) is a heterogeneous multi-robot system for autonomous construction of a structure through assembly of Long components. The two robot team demonstrates component placement into an existing structure in a realistic environment. The task requires component acquisition, cooperative transport, and cooperative precision manipulation. A behavior-based architecture provides adaptability. The RCC approach minimizes computation, power, communication, and sensing for applicability to space-related construction efforts, but the techniques are applicable to terrestrial construction tasks.

Mergeable nervous systems for robots.

PubMed

Mathews, Nithin; Christensen, Anders Lyhne; O'Grady, Rehan; Mondada, Francesco; Dorigo, Marco

2017-09-12

Robots have the potential to display a higher degree of lifetime morphological adaptation than natural organisms. By adopting a modular approach, robots with different capabilities, shapes, and sizes could, in theory, construct and reconfigure themselves as required. However, current modular robots have only been able to display a limited range of hardwired behaviors because they rely solely on distributed control. Here, we present robots whose bodies and control systems can merge to form entirely new robots that retain full sensorimotor control. Our control paradigm enables robots to exhibit properties that go beyond those of any existing machine or of any biological organism: the robots we present can merge to form larger bodies with a single centralized controller, split into separate bodies with independent controllers, and self-heal by removing or replacing malfunctioning body parts. This work takes us closer to robots that can autonomously change their size, form and function.Robots that can self-assemble into different morphologies are desired to perform tasks that require different physical capabilities. Mathews et al. design robots whose bodies and control systems can merge and split to form new robots that retain full sensorimotor control and act as a single entity.

Decentralized control scheme for myriapod robot inspired by adaptive and resilient centipede locomotion.

PubMed

Yasui, Kotaro; Sakai, Kazuhiko; Kano, Takeshi; Owaki, Dai; Ishiguro, Akio

2017-01-01

Recently, myriapods have attracted the attention of engineers because mobile robots that mimic them potentially have the capability of producing highly stable, adaptive, and resilient behaviors. The major challenge here is to develop a control scheme that can coordinate their numerous legs in real time, and an autonomous decentralized control could be the key to solve this problem. Therefore, we focus on real centipedes and aim to design a decentralized control scheme for myriapod robots by drawing inspiration from behavioral experiments on centipede locomotion under unusual conditions. In the behavioral experiments, we observed the response to the removal of a part of the terrain and to amputation of several legs. Further, we determined that the ground reaction force is significant for generating rhythmic leg movements; the motion of each leg is likely affected by a sensory input from its neighboring legs. Thus, we constructed a two-dimensional model wherein a simple local reflexive mechanism was implemented in each leg. We performed simulations by using this model and demonstrated that the myriapod robot could move adaptively to changes in the environment and body properties. Our findings will shed new light on designing adaptive and resilient myriapod robots that can function under various circumstances.

Development and control of a magnetorheological haptic device for robot assisted surgery.

PubMed

Shokrollahi, Elnaz; Goldenberg, Andrew A; Drake, James M; Eastwood, Kyle W; Kang, Matthew

2017-07-01

A prototype magnetorheological (MR) fluid-based actuator has been designed for tele-robotic surgical applications. This device is capable of generating forces up to 47 N, with input currents ranging from 0 to 1.5 A. We begin by outlining the physical design of the device, and then discuss a novel nonlinear model of the device's behavior. The model was developed using the Hammerstein-Wiener (H-W) nonlinear black-box technique and is intended to accurately capture the hysteresis behavior of the MR-fluid. Several experiments were conducted on the device to collect estimation and validation datasets to construct the model and assess its performance. Different estimating functions were used to construct the model, and their effectiveness is assessed based on goodness-of-fit and final-prediction-error measurements. A sigmoid network was found to have a goodness-of-fit of 95%. The model estimate was then used to tune a PID controller. Two control schemes were proposed to eliminate the hysteresis behavior present in the MR fluid device. One method uses a traditional force feedback control loop and the other is based on measuring the magnetic field using a Hall-effect sensor embedded within the device. The Hall-effect sensor scheme was found to be superior in terms of cost, simplicity and real-time control performance compared to the force control strategy.

The sixth generation robot in space

NASA Technical Reports Server (NTRS)

Butcher, A.; Das, A.; Reddy, Y. V.; Singh, H.

1990-01-01

The knowledge based simulator developed in the artificial intelligence laboratory has become a working test bed for experimenting with intelligent reasoning architectures. With this simulator, recently, small experiments have been done with an aim to simulate robot behavior to avoid colliding paths. An automatic extension of such experiments to intelligently planning robots in space demands advanced reasoning architectures. One such architecture for general purpose problem solving is explored. The robot, seen as a knowledge base machine, goes via predesigned abstraction mechanism for problem understanding and response generation. The three phases in one such abstraction scheme are: abstraction for representation, abstraction for evaluation, and abstraction for resolution. Such abstractions require multimodality. This multimodality requires the use of intensional variables to deal with beliefs in the system. Abstraction mechanisms help in synthesizing possible propagating lattices for such beliefs. The machine controller enters into a sixth generation paradigm.

Planning in subsumption architectures

NASA Technical Reports Server (NTRS)

Chalfant, Eugene C.

1994-01-01

A subsumption planner using a parallel distributed computational paradigm based on the subsumption architecture for control of real-world capable robots is described. Virtual sensor state space is used as a planning tool to visualize the robot's anticipated effect on its environment. Decision sequences are generated based on the environmental situation expected at the time the robot must commit to a decision. Between decision points, the robot performs in a preprogrammed manner. A rudimentary, domain-specific partial world model contains enough information to extrapolate the end results of the rote behavior between decision points. A collective network of predictors operates in parallel with the reactive network forming a recurrrent network which generates plans as a hierarchy. Details of a plan segment are generated only when its execution is imminent. The use of the subsumption planner is demonstrated by a simple maze navigation problem.

Novel compliant actuator for wearable robotics applications.

PubMed

Claros, M; Soto, R; Rodríguez, J J; Cantú, C; Contreras-Vidal, José L

2013-01-01

In the growing fields of wearable robotics, rehabilitation robotics, prosthetics, and walking robots, variable impedance and force actuators are being designed and implemented because of their ability to dynamically modulate the intrinsic viscoelastic properties such as stiffness and damping. This modulation is crucial to achieve an efficient and safe human-robot interaction that could lead to electronically generate useful emergent dynamical behaviors. In this work we propose a novel actuation system in which is implemented a control scheme based on equilibrium forces for an active joint capable to provide assistance/resistance as needed and also achieve minimal mechanical impedance when tracking the movement of the user limbs. The actuation system comprises a DC motor with a built in speed reducer, two force-sensing resistors (FSR), a mechanism which transmits to the FSRs the torque developed in the joint and a controller which regulate the amount of energy that is delivered to the DC motor. The proposed system showed more impedance reduction, by the effect of the controlled contact forces, compared with the ones in the reviewed literature.

Software and electronic developments for TUG - T60 robotic telescope

NASA Astrophysics Data System (ADS)

Parmaksizoglu, M.; Dindar, M.; Kirbiyik, H.; Helhel, S.

2014-12-01

A robotic telescope is a telescope that can make observations without hands-on human control. Its low level behavior is automatic and computer-controlled. Robotic telescopes usually run under the control of a scheduler, which provides high-level control by selecting astronomical targets for observation. TUBITAK National Observatory (TUG) T60 Robotic Telescope is controlled by open source OCAAS software, formally named TALON. This study introduces the improvements on TALON software, new electronic and mechanic designs. The designs and software improvements were implemented in the T60 telescope control software and tested on the real system successfully.

Using arm and hand gestures to command robots during stealth operations

NASA Astrophysics Data System (ADS)

Stoica, Adrian; Assad, Chris; Wolf, Michael; You, Ki Sung; Pavone, Marco; Huntsberger, Terry; Iwashita, Yumi

2012-06-01

Command of support robots by the warfighter requires intuitive interfaces to quickly communicate high degree-offreedom (DOF) information while leaving the hands unencumbered. Stealth operations rule out voice commands and vision-based gesture interpretation techniques, as they often entail silent operations at night or in other low visibility conditions. Targeted at using bio-signal inputs to set navigation and manipulation goals for the robot (say, simply by pointing), we developed a system based on an electromyography (EMG) "BioSleeve", a high density sensor array for robust, practical signal collection from forearm muscles. The EMG sensor array data is fused with inertial measurement unit (IMU) data. This paper describes the BioSleeve system and presents initial results of decoding robot commands from the EMG and IMU data using a BioSleeve prototype with up to sixteen bipolar surface EMG sensors. The BioSleeve is demonstrated on the recognition of static hand positions (e.g. palm facing front, fingers upwards) and on dynamic gestures (e.g. hand wave). In preliminary experiments, over 90% correct recognition was achieved on five static and nine dynamic gestures. We use the BioSleeve to control a team of five LANdroid robots in individual and group/squad behaviors. We define a gesture composition mechanism that allows the specification of complex robot behaviors with only a small vocabulary of gestures/commands, and we illustrate it with a set of complex orders.

Using Arm and Hand Gestures to Command Robots during Stealth Operations

NASA Technical Reports Server (NTRS)

Stoica, Adrian; Assad, Chris; Wolf, Michael; You, Ki Sung; Pavone, Marco; Huntsberger, Terry; Iwashita, Yumi

2012-01-01

Command of support robots by the warfighter requires intuitive interfaces to quickly communicate high degree-of-freedom (DOF) information while leaving the hands unencumbered. Stealth operations rule out voice commands and vision-based gesture interpretation techniques, as they often entail silent operations at night or in other low visibility conditions. Targeted at using bio-signal inputs to set navigation and manipulation goals for the robot (say, simply by pointing), we developed a system based on an electromyography (EMG) "BioSleeve", a high density sensor array for robust, practical signal collection from forearm muscles. The EMG sensor array data is fused with inertial measurement unit (IMU) data. This paper describes the BioSleeve system and presents initial results of decoding robot commands from the EMG and IMU data using a BioSleeve prototype with up to sixteen bipolar surface EMG sensors. The BioSleeve is demonstrated on the recognition of static hand positions (e.g. palm facing front, fingers upwards) and on dynamic gestures (e.g. hand wave). In preliminary experiments, over 90% correct recognition was achieved on five static and nine dynamic gestures. We use the BioSleeve to control a team of five LANdroid robots in individual and group/squad behaviors. We define a gesture composition mechanism that allows the specification of complex robot behaviors with only a small vocabulary of gestures/commands, and we illustrate it with a set of complex orders.

Self-organization via active exploration in robotic applications. Phase 2: Hybrid hardware prototype

NASA Technical Reports Server (NTRS)

Oegmen, Haluk

1993-01-01

In many environments human-like intelligent behavior is required from robots to assist and/or replace human operators. The purpose of these robots is to reduce human time and effort in various tasks. Thus the robot should be robust and as autonomous as possible in order to eliminate or to keep to a strict minimum its maintenance and external control. Such requirements lead to the following properties: fault tolerance, self organization, and intelligence. A good insight into implementing these properties in a robot can be gained by considering human behavior. In the first phase of this project, a neural network architecture was developed that captures some fundamental aspects of human categorization, habit, novelty, and reinforcement behavior. The model, called FRONTAL, is a 'cognitive unit' regulating the exploratory behavior of the robot. In the second phase of the project, FRONTAL was interfaced with an off-the-shelf robotic arm and a real-time vision system. The components of this robotic system, a review of FRONTAL, and simulation studies are presented in this report.

Formation Control over Delayed Communication Network

NASA Astrophysics Data System (ADS)

Secchi, Cristian; Fantuzzi, Cesare

In this Chapter we address the problem of formation control of a group of robots that exchange information over a communication network characterized by a non negligible delay. We consider the Virtual Body Artificial Potential approach for stabilizing a group of robots at a desired formation. We show that it is possible to model the controlled group of robots as a port-Hamiltonian system and we exploit the scattering framework to achieve a passive behavior of the controlled system and to stabilize the robots in the desired formation independently of any communication delay.

SLAM algorithm applied to robotics assistance for navigation in unknown environments.

PubMed

Cheein, Fernando A Auat; Lopez, Natalia; Soria, Carlos M; di Sciascio, Fernando A; Pereira, Fernando Lobo; Carelli, Ricardo

2010-02-17

The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous). The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI). In this paper, a sequential Extended Kalman Filter (EKF) feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents. The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how to use the MCI. The SLAM results have shown a consistent reconstruction of the environment. The obtained map was stored inside the Muscle-Computer Interface. The integration of a highly demanding processing algorithm (SLAM) with a MCI and the communication between both in real time have shown to be consistent and successful. The metric map generated by the mobile robot would allow possible future autonomous navigation without direct control of the user, whose function could be relegated to choose robot destinations. Also, the mobile robot shares the same kinematic model of a motorized wheelchair. This advantage can be exploited for wheelchair autonomous navigation.

Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller

PubMed Central

Cyr, André; Boukadoum, Mounir; Thériault, Frédéric

2014-01-01

In this paper, we investigate the operant conditioning (OC) learning process within a bio-inspired paradigm, using artificial spiking neural networks (ASNN) to act as robot brain controllers. In biological agents, OC results in behavioral changes learned from the consequences of previous actions, based on progressive prediction adjustment from rewarding or punishing signals. In a neurorobotics context, virtual and physical autonomous robots may benefit from a similar learning skill when facing unknown and unsupervised environments. In this work, we demonstrate that a simple invariant micro-circuit can sustain OC in multiple learning scenarios. The motivation for this new OC implementation model stems from the relatively complex alternatives that have been described in the computational literature and recent advances in neurobiology. Our elementary kernel includes only a few crucial neurons, synaptic links and originally from the integration of habituation and spike-timing dependent plasticity as learning rules. Using several tasks of incremental complexity, our results show that a minimal neural component set is sufficient to realize many OC procedures. Hence, with the proposed OC module, designing learning tasks with an ASNN and a bio-inspired robot context leads to simpler neural architectures for achieving complex behaviors. PMID:25120464

Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller.

PubMed

Cyr, André; Boukadoum, Mounir; Thériault, Frédéric

2014-01-01

In this paper, we investigate the operant conditioning (OC) learning process within a bio-inspired paradigm, using artificial spiking neural networks (ASNN) to act as robot brain controllers. In biological agents, OC results in behavioral changes learned from the consequences of previous actions, based on progressive prediction adjustment from rewarding or punishing signals. In a neurorobotics context, virtual and physical autonomous robots may benefit from a similar learning skill when facing unknown and unsupervised environments. In this work, we demonstrate that a simple invariant micro-circuit can sustain OC in multiple learning scenarios. The motivation for this new OC implementation model stems from the relatively complex alternatives that have been described in the computational literature and recent advances in neurobiology. Our elementary kernel includes only a few crucial neurons, synaptic links and originally from the integration of habituation and spike-timing dependent plasticity as learning rules. Using several tasks of incremental complexity, our results show that a minimal neural component set is sufficient to realize many OC procedures. Hence, with the proposed OC module, designing learning tasks with an ASNN and a bio-inspired robot context leads to simpler neural architectures for achieving complex behaviors.

Tandem Stance Avoidance Using Adaptive and Asymmetric Admittance Control for Fall Prevention.

PubMed

Nakagawa, Shotaro; Hasegawa, Yasuhisa; Fukuda, Toshio; Kondo, Izumi; Tanimoto, Masanori; Di, Pei; Huang, Jian; Huang, Qiang

2016-05-01

Fall prevention is one of the most important functions of walking assistance devices for user's safety. It is preferable that these devices prevent the user from being in the state where the risk of falling is high rather than helping them recovering from falling motion. During turning, when the user is in the tandem stance, a state where both legs form a line along walking direction, a support base that is surrounded by two legs becomes small, and a stability margin becomes small. This paper therefore aims to prevent the tandem stance by using nonwearable robot "intelligent cane" for the elderly or physically challenged person. Generally, the behavior of the lower limb follows the upper body turning. This paper therefore introduces a cane robot control method which constrains the behavior of user's upper body. By adjusting an admittance parameter of the robot according to the positions of a support leg, the robot resists to turn while a support leg is on the same side of the turning direction. A swing leg on the turning direction side therefore freely moves to the turning direction, while a swing leg on the opposite direction side of turning hardly move to the turning direction.

Can a Soft Robotic Probe Use Stiffness Control Like a Human Finger to Improve Efficacy of Haptic Perception?

PubMed

Sornkarn, Nantachai; Nanayakkara, Thrishantha

2017-01-01

When humans are asked to palpate a soft tissue to locate a hard nodule, they regulate the stiffness, speed, and force of the finger during examination. If we understand the relationship between these behavioral variables and haptic information gain (transfer entropy) during manual probing, we can improve the efficacy of soft robotic probes for soft tissue palpation, such as in tumor localization in minimally invasive surgery. Here, we recorded the muscle co-contraction activity of the finger using EMG sensors to address the question as to whether joint stiffness control during manual palpation plays an important role in the haptic information gain. To address this question, we used a soft robotic probe with a controllable stiffness joint and a force sensor mounted at the base to represent the function of the tendon in a biological finger. Then, we trained a Markov chain using muscle co-contraction patterns of human subjects, and used it to control the stiffness of the soft robotic probe in the same soft tissue palpation task. The soft robotic experiments showed that haptic information gain about the depth of the hard nodule can be maximized by varying the internal stiffness of the soft probe.

Linear Temporal Logic (LTL) Based Monitoring of Smart Manufacturing Systems.

PubMed

Heddy, Gerald; Huzaifa, Umer; Beling, Peter; Haimes, Yacov; Marvel, Jeremy; Weiss, Brian; LaViers, Amy

2015-01-01

The vision of Smart Manufacturing Systems (SMS) includes collaborative robots that can adapt to a range of scenarios. This vision requires a classification of multiple system behaviors, or sequences of movement, that can achieve the same high-level tasks. Likewise, this vision presents unique challenges regarding the management of environmental variables in concert with discrete, logic-based programming. Overcoming these challenges requires targeted performance and health monitoring of both the logical controller and the physical components of the robotic system. Prognostics and health management (PHM) defines a field of techniques and methods that enable condition-monitoring, diagnostics, and prognostics of physical elements, functional processes, overall systems, etc. PHM is warranted in this effort given that the controller is vulnerable to program changes, which propagate in unexpected ways, logical runtime exceptions, sensor failure, and even bit rot. The physical component's health is affected by the wear and tear experienced by machines constantly in motion. The controller's source of faults is inherently discrete, while the latter occurs in a manner that builds up continuously over time. Such a disconnect poses unique challenges for PHM. This paper presents a robotic monitoring system that captures and resolves this disconnect. This effort leverages supervisory robotic control and model checking with linear temporal logic (LTL), presenting them as a novel monitoring system for PHM. This methodology has been demonstrated in a MATLAB-based simulator for an industry inspired use-case in the context of PHM. Future work will use the methodology to develop adaptive, intelligent control strategies to evenly distribute wear on the joints of the robotic arms, maximizing the life of the system.

Measuring information transfer in a soft robotic arm.

PubMed

Nakajima, K; Schmidt, N; Pfeifer, R

2015-05-13

Soft robots can exhibit diverse behaviors with simple types of actuation by partially outsourcing control to the morphological and material properties of their soft bodies, which is made possible by the tight coupling between control, body, and environment. In this paper, we present a method that will quantitatively characterize these diverse spatiotemporal dynamics of a soft body based on the information-theoretic approach. In particular, soft bodies have the ability to propagate the effect of actuation through the entire body, with a certain time delay, due to their elasticity. Our goal is to capture this delayed interaction in a quantitative manner based on a measure called momentary information transfer. We extend this measure to soft robotic applications and demonstrate its power using a physical soft robotic platform inspired by the octopus. Our approach is illustrated in two ways. First, we statistically characterize the delayed actuation propagation through the body as a strength of information transfer. Second, we capture this information propagation directly as local information dynamics. As a result, we show that our approach can successfully characterize the spatiotemporal dynamics of the soft robotic platform, explicitly visualizing how information transfers through the entire body with delays. Further extension scenarios of our approach are discussed for soft robotic applications in general.

Market-Based Coordination and Auditing Mechanisms for Self-Interested Multi-Robot Systems

ERIC Educational Resources Information Center

Ham, MyungJoo

2009-01-01

We propose market-based coordinated task allocation mechanisms, which allocate complex tasks that require synchronized and collaborated services of multiple robot agents to robot agents, and an auditing mechanism, which ensures proper behaviors of robot agents by verifying inter-agent activities, for self-interested, fully-distributed, and…

Mobile robots for localizing gas emission sources on landfill sites: is bio-inspiration the way to go?

PubMed

Hernandez Bennetts, Victor; Lilienthal, Achim J; Neumann, Patrick P; Trincavelli, Marco

2011-01-01

Roboticists often take inspiration from animals for designing sensors, actuators, or algorithms that control the behavior of robots. Bio-inspiration is motivated with the uncanny ability of animals to solve complex tasks like recognizing and manipulating objects, walking on uneven terrains, or navigating to the source of an odor plume. In particular the task of tracking an odor plume up to its source has nearly exclusively been addressed using biologically inspired algorithms and robots have been developed, for example, to mimic the behavior of moths, dung beetles, or lobsters. In this paper we argue that biomimetic approaches to gas source localization are of limited use, primarily because animals differ fundamentally in their sensing and actuation capabilities from state-of-the-art gas-sensitive mobile robots. To support our claim, we compare actuation and chemical sensing available to mobile robots to the corresponding capabilities of moths. We further characterize airflow and chemosensor measurements obtained with three different robot platforms (two wheeled robots and one flying micro-drone) in four prototypical environments and show that the assumption of a constant and unidirectional airflow, which is the basis of many gas source localization approaches, is usually far from being valid. This analysis should help to identify how underlying principles, which govern the gas source tracking behavior of animals, can be usefully "translated" into gas source localization approaches that fully take into account the capabilities of mobile robots. We also describe the requirements for a reference application, monitoring of gas emissions at landfill sites with mobile robots, and discuss an engineered gas source localization approach based on statistics as an alternative to biologically inspired algorithms.

Mobile Robots for Localizing Gas Emission Sources on Landfill Sites: Is Bio-Inspiration the Way to Go?

PubMed Central

Hernandez Bennetts, Victor; Lilienthal, Achim J.; Neumann, Patrick P.; Trincavelli, Marco

2011-01-01

Roboticists often take inspiration from animals for designing sensors, actuators, or algorithms that control the behavior of robots. Bio-inspiration is motivated with the uncanny ability of animals to solve complex tasks like recognizing and manipulating objects, walking on uneven terrains, or navigating to the source of an odor plume. In particular the task of tracking an odor plume up to its source has nearly exclusively been addressed using biologically inspired algorithms and robots have been developed, for example, to mimic the behavior of moths, dung beetles, or lobsters. In this paper we argue that biomimetic approaches to gas source localization are of limited use, primarily because animals differ fundamentally in their sensing and actuation capabilities from state-of-the-art gas-sensitive mobile robots. To support our claim, we compare actuation and chemical sensing available to mobile robots to the corresponding capabilities of moths. We further characterize airflow and chemosensor measurements obtained with three different robot platforms (two wheeled robots and one flying micro-drone) in four prototypical environments and show that the assumption of a constant and unidirectional airflow, which is the basis of many gas source localization approaches, is usually far from being valid. This analysis should help to identify how underlying principles, which govern the gas source tracking behavior of animals, can be usefully “translated” into gas source localization approaches that fully take into account the capabilities of mobile robots. We also describe the requirements for a reference application, monitoring of gas emissions at landfill sites with mobile robots, and discuss an engineered gas source localization approach based on statistics as an alternative to biologically inspired algorithms. PMID:22319493

Robust Agent Control of an Autonomous Robot with Many Sensors and Actuators

DTIC Science & Technology

1993-05-01

Overview 22 3.1 Issues of Controller Design ........................ 22 3.2 Robot Behavior Control Philosophy .................. 23 3.3 Overview of the... designed and built by our lab as an 9 Figure 1.1- Hannibal. 10 experimental platform to explore planetary micro-rover control issues (Angle 1991). When... designing the robot, careful consideration was given to mobility, sensing, and robustness issues. Much has been said concerning the advan- tages of

A problem of optimal control and observation for distributed homogeneous multi-agent system

NASA Astrophysics Data System (ADS)

Kruglikov, Sergey V.

2017-12-01

The paper considers the implementation of a algorithm for controlling a distributed complex of several mobile multi-robots. The concept of a unified information space of the controlling system is applied. The presented information and mathematical models of participants and obstacles, as real agents, and goals and scenarios, as virtual agents, create the base forming the algorithmic and software background for computer decision support system. The controlling scheme assumes the indirect management of the robotic team on the basis of optimal control and observation problem predicting intellectual behavior in a dynamic, hostile environment. A basic content problem is a compound cargo transportation by a group of participants in the case of a distributed control scheme in the terrain with multiple obstacles.

Sozzy: a hormone-driven autonomous vacuum cleaner

NASA Astrophysics Data System (ADS)

Yamamoto, Masaki

1994-02-01

Domestic robots are promising examples of the application of robotics to personal life. There have been many approaches in this field, but no successful results exist. The problem is that domestic environments are more difficult for robots than other environments, such as factory floors or office floors. Consequently, conventional approaches using a model of human intelligence to design robots have not been successful. In this paper, we report on a prototyped domestic vacuum-cleaning robot that is designed to be able to handle complex environments. The control software is composed of two layers, both of which are generally inspired by behaviors of living creatures. The first layer corresponds to a dynamically reconfigurable system of behaviors implemented in the subsumption architecture. The ability of the robot to support alternate configurations of its behaviors provides the robot with increased robustness. We have conveniently labeled particular configurations as specific `emotions' according to the interpretation of observers of the robot's behavior. The second layer simulates the hormone system. The hormone system is modeled using state variables, increased or decreased by stimuli from the environment. The hormone condition selects the robot's most suitable emotion, according to the changing environments. The robot hardware is built of off-the-shelf parts, such as an embedded CPU, inexpensive home-appliance sensors, and small motors. These parts keep the total building cost to a minimum. The robot also has a vacuum cleaning function to demonstrate its capability to perform useful tasks. We tested the robot in our laboratory, and successfully videotaped its robust behaviors. We also confirmed the hormone system to enhance the robot's plasticity and lifelike quality.

From self-assessment to frustration, a small step toward autonomy in robotic navigation

PubMed Central

Jauffret, Adrien; Cuperlier, Nicolas; Tarroux, Philippe; Gaussier, Philippe

2013-01-01

Autonomy and self-improvement capabilities are still challenging in the fields of robotics and machine learning. Allowing a robot to autonomously navigate in wide and unknown environments not only requires a repertoire of robust strategies to cope with miscellaneous situations, but also needs mechanisms of self-assessment for guiding learning and for monitoring strategies. Monitoring strategies requires feedbacks on the behavior's quality, from a given fitness system in order to take correct decisions. In this work, we focus on how a second-order controller can be used to (1) manage behaviors according to the situation and (2) seek for human interactions to improve skills. Following an incremental and constructivist approach, we present a generic neural architecture, based on an on-line novelty detection algorithm that may be able to self-evaluate any sensory-motor strategies. This architecture learns contingencies between sensations and actions, giving the expected sensation from the previous perception. Prediction error, coming from surprising events, provides a measure of the quality of the underlying sensory-motor contingencies. We show how a simple second-order controller (emotional system) based on the prediction progress allows the system to regulate its behavior to solve complex navigation tasks and also succeeds in asking for help if it detects dead-lock situations. We propose that this model could be a key structure toward self-assessment and autonomy. We made several experiments that can account for such properties for two different strategies (road following and place cells based navigation) in different situations. PMID:24115931

Designing speech-based interfaces for telepresence robots for people with disabilities.

PubMed

Tsui, Katherine M; Flynn, Kelsey; McHugh, Amelia; Yanco, Holly A; Kontak, David

2013-06-01

People with cognitive and/or motor impairments may benefit from using telepresence robots to engage in social activities. To date, these robots, their user interfaces, and their navigation behaviors have not been designed for operation by people with disabilities. We conducted an experiment in which participants (n=12) used a telepresence robot in a scavenger hunt task to determine how they would use speech to command the robot. Based upon the results, we present design guidelines for speech-based interfaces for telepresence robots.

Engineering the evolution of self-organizing behaviors in swarm robotics: a case study.

PubMed

Trianni, Vito; Nolfi, Stefano

2011-01-01

Evolutionary robotics (ER) is a powerful approach for the automatic synthesis of robot controllers, as it requires little a priori knowledge about the problem to be solved in order to obtain good solutions. This is particularly true for collective and swarm robotics, in which the desired behavior of the group is an indirect result of the control and communication rules followed by each individual. However, the experimenter must make several arbitrary choices in setting up the evolutionary process, in order to define the correct selective pressures that can lead to the desired results. In some cases, only a deep understanding of the obtained results can point to the critical aspects that constrain the system, which can be later modified in order to re-engineer the evolutionary process towards better solutions. In this article, we discuss the problem of engineering the evolutionary machinery that can lead to the desired result in the swarm robotics context. We also present a case study about self-organizing synchronization in a swarm of robots, in which some arbitrarily chosen properties of the communication system hinder the scalability of the behavior to large groups. We show that by modifying the communication system, artificial evolution can synthesize behaviors that scale properly with the group size.

The Clinical Use of Robots for Individuals with Autism Spectrum Disorders: A Critical Review

PubMed Central

Diehl, Joshua J.; Schmitt, Lauren M.; Villano, Michael; Crowell, Charles R.

2011-01-01

We examined peer-reviewed studies in order to understand the current status of empirically-based evidence on the clinical applications of robots in the diagnosis and treatment of Autism Spectrum Disorders (ASD). Studies are organized into four broad categories: (a) the response of individuals with ASD to robots or robot-like behavior in comparison to human behavior, (b) the use of robots to elicit behaviors, (c) the use of robots to model, teach, and/or practice a skill, and (d) the use of robots to provide feedback on performance. A critical review of the literature revealed that most of the findings are exploratory and have methodological limitations that make it difficult to draw firm conclusions about the clinical utility of robots. Finally, we outline the research needed to determine the incremental validity of this technique. PMID:22125579

Task-level control for autonomous robots

NASA Technical Reports Server (NTRS)

Simmons, Reid

1994-01-01

Task-level control refers to the integration and coordination of planning, perception, and real-time control to achieve given high-level goals. Autonomous mobile robots need task-level control to effectively achieve complex tasks in uncertain, dynamic environments. This paper describes the Task Control Architecture (TCA), an implemented system that provides commonly needed constructs for task-level control. Facilities provided by TCA include distributed communication, task decomposition and sequencing, resource management, monitoring and exception handling. TCA supports a design methodology in which robot systems are developed incrementally, starting first with deliberative plans that work in nominal situations, and then layering them with reactive behaviors that monitor plan execution and handle exceptions. To further support this approach, design and analysis tools are under development to provide ways of graphically viewing the system and validating its behavior.

Engineering Sensorial Delay to Control Phototaxis and Emergent Collective Behaviors

NASA Astrophysics Data System (ADS)

Mijalkov, Mite; McDaniel, Austin; Wehr, Jan; Volpe, Giovanni

2016-01-01

Collective motions emerging from the interaction of autonomous mobile individuals play a key role in many phenomena, from the growth of bacterial colonies to the coordination of robotic swarms. For these collective behaviors to take hold, the individuals must be able to emit, sense, and react to signals. When dealing with simple organisms and robots, these signals are necessarily very elementary; e.g., a cell might signal its presence by releasing chemicals and a robot by shining light. An additional challenge arises because the motion of the individuals is often noisy; e.g., the orientation of cells can be altered by Brownian motion and that of robots by an uneven terrain. Therefore, the emphasis is on achieving complex and tunable behaviors from simple autonomous agents communicating with each other in robust ways. Here, we show that the delay between sensing and reacting to a signal can determine the individual and collective long-term behavior of autonomous agents whose motion is intrinsically noisy. We experimentally demonstrate that the collective behavior of a group of phototactic robots capable of emitting a radially decaying light field can be tuned from segregation to aggregation and clustering by controlling the delay with which they change their propulsion speed in response to the light intensity they measure. We track this transition to the underlying dynamics of this system, in particular, to the ratio between the robots' sensorial delay time and the characteristic time of the robots' random reorientation. Supported by numerics, we discuss how the same mechanism can be applied to control active agents, e.g., airborne drones, moving in a three-dimensional space. Given the simplicity of this mechanism, the engineering of sensorial delay provides a potentially powerful tool to engineer and dynamically tune the behavior of large ensembles of autonomous mobile agents; furthermore, this mechanism might already be at work within living organisms such as chemotactic cells.

Design and implementation of self-balancing coaxial two wheel robot based on HSIC

NASA Astrophysics Data System (ADS)

Hu, Tianlian; Zhang, Hua; Dai, Xin; Xia, Xianfeng; Liu, Ran; Qiu, Bo

2007-12-01

This thesis has studied the control problem concerning position and orientation control of self-balancing coaxial two wheel robot based on the human simulated intelligent control (HSIC) theory. Adopting Lagrange equation, the dynamic model of self-balancing coaxial two-wheel Robot is built up, and the Sensory-motor Intelligent Schemas (SMIS) of HSIC controller for the robot is designed by analyzing its movement and simulating the human controller. In robot's motion process, by perceiving position and orientation of the robot and using multi-mode control strategy based on characteristic identification, the HSIC controller enables the robot to control posture. Utilizing Matlab/Simulink, a simulation platform is established and a motion controller is designed and realized based on RT-Linux real-time operating system, employing high speed ARM9 processor S3C2440 as kernel of the motion controller. The effectiveness of the new design is testified by the experiment.

Towards an SEMG-based tele-operated robot for masticatory rehabilitation.

PubMed

Kalani, Hadi; Moghimi, Sahar; Akbarzadeh, Alireza

2016-08-01

This paper proposes a real-time trajectory generation for a masticatory rehabilitation robot based on surface electromyography (SEMG) signals. We used two Gough-Stewart robots. The first robot was used as a rehabilitation robot while the second robot was developed to model the human jaw system. The legs of the rehabilitation robot were controlled by the SEMG signals of a tele-operator to reproduce the masticatory motion in the human jaw, supposedly mounted on the moving platform, through predicting the location of a reference point. Actual jaw motions and the SEMG signals from the masticatory muscles were recorded and used as output and input, respectively. Three different methods, namely time-delayed neural networks, time delayed fast orthogonal search, and time-delayed Laguerre expansion technique, were employed and compared to predict the kinematic parameters. The optimal model structures as well as the input delays were obtained for each model and each subject through a genetic algorithm. Equations of motion were obtained by the virtual work method. Fuzzy method was employed to develop a fuzzy impedance controller. Moreover, a jaw model was developed to demonstrate the time-varying behavior of the muscle lengths during the rehabilitation process. The three modeling methods were capable of providing reasonably accurate estimations of the kinematic parameters, although the accuracy and training/validation speed of time-delayed fast orthogonal search were higher than those of the other two aforementioned methods. Also, during a simulation study, the fuzzy impedance scheme proved successful in controlling the moving platform for the accurate navigation of the reference point in the desired trajectory. SEMG has been widely used as a control command for prostheses and exoskeleton robots. However, in the current study by employing the proposed rehabilitation robot the complete continuous profile of the clenching motion was reproduced in the sagittal plane. Copyright © 2016. Published by Elsevier Ltd.

Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Editor)

1990-01-01

Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

Robotic Precursor Missions for Mars Habitats

NASA Technical Reports Server (NTRS)

Huntsberger, Terry; Pirjanian, Paolo; Schenker, Paul S.; Trebi-Ollennu, Ashitey; Das, Hari; Joshi, Sajay

2000-01-01

Infrastructure support for robotic colonies, manned Mars habitat, and/or robotic exploration of planetary surfaces will need to rely on the field deployment of multiple robust robots. This support includes such tasks as the deployment and servicing of power systems and ISRU generators, construction of beaconed roadways, and the site preparation and deployment of manned habitat modules. The current level of autonomy of planetary rovers such as Sojourner will need to be greatly enhanced for these types of operations. In addition, single robotic platforms will not be capable of complicated construction scenarios. Precursor robotic missions to Mars that involve teams of multiple cooperating robots to accomplish some of these tasks is a cost effective solution to the possible long timeline necessary for the deployment of a manned habitat. Ongoing work at JPL under the Mars Outpost Program in the area of robot colonies is investigating many of the technology developments necessary for such an ambitious undertaking. Some of the issues that are being addressed include behavior-based control systems for multiple cooperating robots (CAMPOUT), development of autonomous robotic systems for the rescue/repair of trapped or disabled robots, and the design and development of robotic platforms for construction tasks such as material transport and surface clearing.

Neural self-tuning adaptive control of non-minimum phase system

NASA Technical Reports Server (NTRS)

Ho, Long T.; Bialasiewicz, Jan T.; Ho, Hai T.

1993-01-01

The motivation of this research came about when a neural network direct adaptive control scheme was applied to control the tip position of a flexible robotic arm. Satisfactory control performance was not attainable due to the inherent non-minimum phase characteristics of the flexible robotic arm tip. Most of the existing neural network control algorithms are based on the direct method and exhibit very high sensitivity, if not unstable, closed-loop behavior. Therefore, a neural self-tuning control (NSTC) algorithm is developed and applied to this problem and showed promising results. Simulation results of the NSTC scheme and the conventional self-tuning (STR) control scheme are used to examine performance factors such as control tracking mean square error, estimation mean square error, transient response, and steady state response.

micROS: a morphable, intelligent and collective robot operating system.

PubMed

Yang, Xuejun; Dai, Huadong; Yi, Xiaodong; Wang, Yanzhen; Yang, Shaowu; Zhang, Bo; Wang, Zhiyuan; Zhou, Yun; Peng, Xuefeng

2016-01-01

Robots are developing in much the same way that personal computers did 40 years ago, and robot operating system is the critical basis. Current robot software is mainly designed for individual robots. We present in this paper the design of micROS, a morphable, intelligent and collective robot operating system for future collective and collaborative robots. We first present the architecture of micROS, including the distributed architecture for collective robot system as a whole and the layered architecture for every single node. We then present the design of autonomous behavior management based on the observe-orient-decide-act cognitive behavior model and the design of collective intelligence including collective perception, collective cognition, collective game and collective dynamics. We also give the design of morphable resource management, which first categorizes robot resources into physical, information, cognitive and social domains, and then achieve morphability based on self-adaptive software technology. We finally deploy micROS on NuBot football robots and achieve significant improvement in real-time performance.

See You See Me: the Role of Eye Contact in Multimodal Human-Robot Interaction

PubMed Central

XU, TIAN (LINGER); ZHANG, HUI; YU, CHEN

2016-01-01

We focus on a fundamental looking behavior in human-robot interactions – gazing at each other’s face. Eye contact and mutual gaze between two social partners are critical in smooth human-human interactions. Therefore, investigating at what moments and in what ways a robot should look at a human user’s face as a response to the human’s gaze behavior is an important topic. Toward this goal, we developed a gaze-contingent human-robot interaction system, which relied on momentary gaze behaviors from a human user to control an interacting robot in real time. Using this system, we conducted an experiment in which human participants interacted with the robot in a joint attention task. In the experiment, we systematically manipulated the robot’s gaze toward the human partner’s face in real time and then analyzed the human’s gaze behavior as a response to the robot’s gaze behavior. We found that more face looks from the robot led to more look-backs (to the robot’s face) from human participants and consequently created more mutual gaze and eye contact between the two. Moreover, participants demonstrated more coordinated and synchronized multimodal behaviors between speech and gaze when more eye contact was successfully established and maintained. PMID:28966875

Middle-ear microsurgery simulation to improve new robotic procedures.

PubMed

Kazmitcheff, Guillaume; Nguyen, Yann; Miroir, Mathieu; Péan, Fabien; Ferrary, Evelyne; Cotin, Stéphane; Sterkers, Olivier; Duriez, Christian

2014-01-01

Otological microsurgery is delicate and requires high dexterity in bad ergonomic conditions. To assist surgeons in these indications, a teleoperated system, called RobOtol, is developed. This robot enhances gesture accuracy and handiness and allows exploration of new procedures for middle ear surgery. To plan new procedures that exploit the capacities given by the robot, a surgical simulator is developed. The simulation reproduces with high fidelity the behavior of the anatomical structures and can also be used as a training tool for an easier control of the robot for surgeons. In the paper, we introduce the middle ear surgical simulation and then we perform virtually two challenging procedures with the robot. We show how interactive simulation can assist in analyzing the benefits of robotics in the case of complex manipulations or ergonomics studies and allow the development of innovative surgical procedures. New robot-based microsurgical procedures are investigated. The improvement offered by RobOtol is also evaluated and discussed.

Middle-Ear Microsurgery Simulation to Improve New Robotic Procedures

PubMed Central

Kazmitcheff, Guillaume; Nguyen, Yann; Miroir, Mathieu; Péan, Fabien; Ferrary, Evelyne; Cotin, Stéphane; Sterkers, Olivier; Duriez, Christian

2014-01-01

Otological microsurgery is delicate and requires high dexterity in bad ergonomic conditions. To assist surgeons in these indications, a teleoperated system, called RobOtol, is developed. This robot enhances gesture accuracy and handiness and allows exploration of new procedures for middle ear surgery. To plan new procedures that exploit the capacities given by the robot, a surgical simulator is developed. The simulation reproduces with high fidelity the behavior of the anatomical structures and can also be used as a training tool for an easier control of the robot for surgeons. In the paper, we introduce the middle ear surgical simulation and then we perform virtually two challenging procedures with the robot. We show how interactive simulation can assist in analyzing the benefits of robotics in the case of complex manipulations or ergonomics studies and allow the development of innovative surgical procedures. New robot-based microsurgical procedures are investigated. The improvement offered by RobOtol is also evaluated and discussed. PMID:25157373

The mechanical design of a humanoid robot with flexible skin sensor for use in psychiatric therapy

NASA Astrophysics Data System (ADS)

Burns, Alec; Tadesse, Yonas

2014-03-01

In this paper, a humanoid robot is presented for ultimate use in the rehabilitation of children with mental disorders, such as autism. Creating affordable and efficient humanoids could assist the therapy in psychiatric disability by offering multimodal communication between the humanoid and humans. Yet, the humanoid development needs a seamless integration of artificial muscles, sensors, controllers and structures. We have designed a human-like robot that has 15 DOF, 580 mm tall and 925 mm arm span using a rapid prototyping system. The robot has a human-like appearance and movement. Flexible sensors around the arm and hands for safe human-robot interactions, and a two-wheel mobile platform for maneuverability are incorporated in the design. The robot has facial features for illustrating human-friendly behavior. The mechanical design of the robot and the characterization of the flexible sensors are presented. Comprehensive study on the upper body design, mobile base, actuators selection, electronics, and performance evaluation are included in this paper.

A cognitive approach to classifying perceived behaviors

NASA Astrophysics Data System (ADS)

Benjamin, Dale Paul; Lyons, Damian

2010-04-01

This paper describes our work on integrating distributed, concurrent control in a cognitive architecture, and using it to classify perceived behaviors. We are implementing the Robot Schemas (RS) language in Soar. RS is a CSP-type programming language for robotics that controls a hierarchy of concurrently executing schemas. The behavior of every RS schema is defined using port automata. This provides precision to the semantics and also a constructive means of reasoning about the behavior and meaning of schemas. Our implementation uses Soar operators to build, instantiate and connect port automata as needed. Our approach is to use comprehension through generation (similar to NLSoar) to search for ways to construct port automata that model perceived behaviors. The generality of RS permits us to model dynamic, concurrent behaviors. A virtual world (Ogre) is used to test the accuracy of these automata. Soar's chunking mechanism is used to generalize and save these automata. In this way, the robot learns to recognize new behaviors.

Interaction dynamics of multiple mobile robots with simple navigation strategies

NASA Technical Reports Server (NTRS)

Wang, P. K. C.

1989-01-01

The global dynamic behavior of multiple interacting autonomous mobile robots with simple navigation strategies is studied. Here, the effective spatial domain of each robot is taken to be a closed ball about its mass center. It is assumed that each robot has a specified cone of visibility such that interaction with other robots takes place only when they enter its visibility cone. Based on a particle model for the robots, various simple homing and collision-avoidance navigation strategies are derived. Then, an analysis of the dynamical behavior of the interacting robots in unbounded spatial domains is made. The article concludes with the results of computer simulations studies of two or more interacting robots.

A Behavior-Based Strategy for Single and Multi-Robot Autonomous Exploration

PubMed Central

Cepeda, Jesus S.; Chaimowicz, Luiz; Soto, Rogelio; Gordillo, José L.; Alanís-Reyes, Edén A.; Carrillo-Arce, Luis C.

2012-01-01

In this paper, we consider the problem of autonomous exploration of unknown environments with single and multiple robots. This is a challenging task, with several potential applications. We propose a simple yet effective approach that combines a behavior-based navigation with an efficient data structure to store previously visited regions. This allows robots to safely navigate, disperse and efficiently explore the environment. A series of experiments performed using a realistic robotic simulator and a real testbed scenario demonstrate that our technique effectively distributes the robots over the environment and allows them to quickly accomplish their mission in large open spaces, narrow cluttered environments, dead-end corridors, as well as rooms with minimum exits.

The psychosocial effects of a companion robot: a randomized controlled trial.

PubMed

Robinson, Hayley; Macdonald, Bruce; Kerse, Ngaire; Broadbent, Elizabeth

2013-09-01

To investigate the psychosocial effects of the companion robot, Paro, in a rest home/hospital setting in comparison to a control group. Randomized controlled trial. Residents were randomized to the robot intervention group or a control group that attended normal activities instead of Paro sessions. Sessions took place twice a week for an hour over 12 weeks. Over the trial period, observations were conducted of residents' social behavior when interacting as a group with the robot. As a comparison, observations were also conducted of all the residents during general activities when the resident dog was or was not present. A residential care facility in Auckland, New Zealand. Forty residents in hospital and rest home care. Residents completed a baseline measure assessing cognitive status, loneliness, depression, and quality of life. At follow-up, residents completed a questionnaire assessing loneliness, depression, and quality of life. During observations, behavior was noted and collated for instances of talking and stroking the dog/robot. In comparison with the control group, residents who interacted with the robot had significant decreases in loneliness over the period of the trial. Both the resident dog and the seal robot made an impact on the social environment in comparison to when neither was present. Residents talked to and touched the robot significantly more than the resident dog. A greater number of residents were involved in discussion about the robot in comparison with the resident dog and conversation about the robot occurred more. Paro is a positive addition to this environment and has benefits for older people in nursing home care. Paro may be able to address some of the unmet needs of older people that a resident animal may not, particularly relating to loneliness. Copyright © 2013 American Medical Directors Association, Inc. Published by Elsevier Inc. All rights reserved.

Digital redesign of the control system for the Robotics Research Corporation model K-1607 robot

NASA Technical Reports Server (NTRS)

Carroll, Robert L.

1989-01-01

The analog control system for positioning each link of the Robotics Research Corporation Model K-1607 robot manipulator was redesigned for computer control. In order to accomplish the redesign, a linearized model of the dynamic behavior of the robot was developed. The parameters of the model were determined by examination of the input-output data collected in closed-loop operation of the analog control system. The robot manipulator possesses seven degrees of freedom in its motion. The analog control system installed by the manufacturer of the robot attempts to control the positioning of each link without feedback from other links. Constraints on the design of a digital control system include: the robot cannot be disassembled for measurement of parameters; the digital control system must not include filtering operations if possible, because of lack of computer capability; and criteria of goodness of control system performing is lacking. The resulting design employs sampled-data position and velocity feedback. The criteria of the design permits the control system gain margin and phase margin, measured at the same frequencies, to be the same as that provided by the analog control system.

Feasibility of Synergy-Based Exoskeleton Robot Control in Hemiplegia.

PubMed

Hassan, Modar; Kadone, Hideki; Ueno, Tomoyuki; Hada, Yasushi; Sankai, Yoshiyuki; Suzuki, Kenji

2018-06-01

Here, we present a study on exoskeleton robot control based on inter-limb locomotor synergies using a robot control method developed to target hemiparesis. The robot control is based on inter-limb locomotor synergies and kinesiological information from the non-paretic leg and a walking aid cane to generate motion patterns for the assisted leg. The developed synergy-based system was tested against an autonomous robot control system in five patients with hemiparesis and varying locomotor abilities. Three of the participants were able to walk using the robot. Results from these participants showed an improved spatial symmetry ratio and more consistent step length with the synergy-based method compared with that for the autonomous method, while the increase in the range of motion for the assisted joints was larger with the autonomous system. The kinematic synergy distribution of the participants walking without the robot suggests a relationship between each participant's synergy distribution and his/her ability to control the robot: participants with two independent synergies accounting for approximately 80% of the data variability were able to walk with the robot. This observation was not consistently apparent with conventional clinical measures such as the Brunnstrom stages. This paper contributes to the field of robot-assisted locomotion therapy by introducing the concept of inter-limb synergies, demonstrating performance differences between synergy-based and autonomous robot control, and investigating the range of disability in which the system is usable.

POINTER: Portable Intelligent Trainer for External Robotics

NASA Technical Reports Server (NTRS)

Kuiper, Hilbert; Rikken, Patrick J.

1994-01-01

Intelligent tutoring systems (ITS's) play an increasing role in training and education of people with different levels of skill and knowledge. As compared to conventional computer based training (CBT) an ITS provides more tailored instruction by trying to mimic the teaching behavior of a human instructor as much as possible and is therefore much more flexible. This paper starts with an introduction to ITS's, followed by the description of an ITS for training of an (astronaut) operator in monitoring and controlling robotic arm procedures. The robotic arm will be used for exchange of equipment between a space station and a space plane involving critical and accurate movements of the robotic arm. The ITS for this application, called Pointer, is developed by TNO Physics and Electronics Laboratory and is based upon an existing ITS that includes procedural training. Pointer has been developed on a workstation whereas the target platform was a portable computer. Therefore, a lot of attention had to be paid to scaling effects and keeping up with user friendliness of the much smaller user interface. Although the learning domain was the control of a robotic arm, it is clear that use of intelligent training technologies on a portable computer has many other applications (payload operations, operation control rooms, etc.). Training can occur at any time and place in an attractive and cost effective way.

Autonomous mobile robot teams

NASA Technical Reports Server (NTRS)

Agah, Arvin; Bekey, George A.

1994-01-01

This paper describes autonomous mobile robot teams performing tasks in unstructured environments. The behavior and the intelligence of the group is distributed, and the system does not include a central command base or leader. The novel concept of the Tropism-Based Cognitive Architecture is introduced, which is used by the robots in order to produce behavior transforming their sensory information to proper action. The results of a number of simulation experiments are presented. These experiments include worlds where the robot teams must locate, decompose, and gather objects, and defend themselves against hostile predators, while navigating around stationary and mobile obstacles.

Innovative Mobile Robot Method: Improving the Learning of Programming Languages in Engineering Degrees

ERIC Educational Resources Information Center

Ortiz, Octavio Ortiz; Pastor Franco, Juan Ángel; Alcover Garau, Pedro María; Herrero Martín, Ruth

2017-01-01

This paper describes a study of teaching a programming language in a C programming course by having students assemble and program a low-cost mobile robot. Writing their own programs to define the robot's behavior raised students' motivation. Working in small groups, students programmed the robots by using the control structures of structured…

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning.

PubMed

Chung, Michael Jae-Yoon; Friesen, Abram L; Fox, Dieter; Meltzoff, Andrew N; Rao, Rajesh P N

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration.

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning

PubMed Central

Chung, Michael Jae-Yoon; Friesen, Abram L.; Fox, Dieter; Meltzoff, Andrew N.; Rao, Rajesh P. N.

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration. PMID:26536366

I want what you've got: Cross platform portabiity and human-robot interaction assessment.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Julie L. Marble, Ph.D.*.; Douglas A. Few; David J. Bruemmer

2005-08-01

Human-robot interaction is a subtle, yet critical aspect of design that must be assessed during the development of both the human-robot interface and robot behaviors if the human-robot team is to effectively meet the complexities of the task environment. Testing not only ensures that the system can successfully achieve the tasks for which it was designed, but more importantly, usability testing allows the designers to understand how humans and robots can, will, and should work together to optimize workload distribution. A lack of human-centered robot interface design, the rigidity of sensor configuration, and the platform-specific nature of research robot developmentmore » environments are a few factors preventing robotic solutions from reaching functional utility in real word environments. Often the difficult engineering challenge of implementing adroit reactive behavior, reliable communication, trustworthy autonomy that combines with system transparency and usable interfaces is overlooked in favor of other research aims. The result is that many robotic systems never reach a level of functional utility necessary even to evaluate the efficacy of the basic system, much less result in a system that can be used in a critical, real-world environment. Further, because control architectures and interfaces are often platform specific, it is difficult or even impossible to make usability comparisons between them. This paper discusses the challenges inherent to the conduct of human factors testing of variable autonomy control architectures and across platforms within a complex, real-world environment. It discusses the need to compare behaviors, architectures, and interfaces within a structured environment that contains challenging real-world tasks, and the implications for system acceptance and trust of autonomous robotic systems for how humans and robots interact in true interactive teams.« less

Using the MEDiPORT humanoid robot to reduce procedural pain and distress in children with cancer: A pilot randomized controlled trial.

PubMed

Jibb, Lindsay A; Birnie, Kathryn A; Nathan, Paul C; Beran, Tanya N; Hum, Vanessa; Victor, J Charles; Stinson, Jennifer N

2018-06-12

Subcutaneous port needle insertions are painful and distressing for children with cancer. The interactive MEDiPORT robot has been programmed to implement psychological strategies to decrease pain and distress during this procedure. This study assessed the feasibility of a future MEDiPORT trial. The secondary aim was to determine the preliminary effectiveness of MEDiPORT in reducing child pain and distress during subcutaneous port accesses. This 5-month pilot randomized controlled trial used a web-based service to randomize 4- to 9-year-olds with cancer to the MEDiPORT cognitive-behavioral arm (robot using evidence-based cognitive-behavioral interventions) or active distraction arm (robot dancing and singing) while a nurse conducted a needle insertion. We assessed accrual and retention; technical difficulties; outcome measure completion by children, parents, and nurses; time taken to complete the study and clinical procedure; and child-, parent-, and nurse-rated acceptability. Descriptive analyses, with exploratory inferential testing of child pain and distress data, were used to address study aims. Forty children were randomized across study arms. Most (85%) eligible children participated and no children withdrew. Technical difficulties were more common in the cognitive-behavioral arm. Completion times for the study and needle insertion were acceptable and >96% of outcome measure items were completed. Overall, MEDiPORT and the study were acceptable to participants. There was no difference in pain between arms, but distress during the procedure was less pronounced in the active distraction arm. The MEDiPORT study appears feasible to implement as an adequately-powered effectiveness-assessing trial following modifications to the intervention and study protocol. ClinicalTrials.gov NCT02611739. © 2018 Wiley Periodicals, Inc.

SLAM algorithm applied to robotics assistance for navigation in unknown environments

PubMed Central

2010-01-01

Background The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous). The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI). Methods In this paper, a sequential Extended Kalman Filter (EKF) feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents. Results The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how to use the MCI. The SLAM results have shown a consistent reconstruction of the environment. The obtained map was stored inside the Muscle-Computer Interface. Conclusions The integration of a highly demanding processing algorithm (SLAM) with a MCI and the communication between both in real time have shown to be consistent and successful. The metric map generated by the mobile robot would allow possible future autonomous navigation without direct control of the user, whose function could be relegated to choose robot destinations. Also, the mobile robot shares the same kinematic model of a motorized wheelchair. This advantage can be exploited for wheelchair autonomous navigation. PMID:20163735

Hybrid FES-robot cooperative control of ambulatory gait rehabilitation exoskeleton.

PubMed

del-Ama, Antonio J; Gil-Agudo, Angel; Pons, José L; Moreno, Juan C

2014-03-04

Robotic and functional electrical stimulation (FES) approaches are used for rehabilitation of walking impairment of spinal cord injured individuals. Although devices are commercially available, there are still issues that remain to be solved. Control of hybrid exoskeletons aims at blending robotic exoskeletons and electrical stimulation to overcome the drawbacks of each approach while preserving their advantages. Hybrid actuation and control have a considerable potential for walking rehabilitation but there is a need of novel control strategies of hybrid systems that adequately manage the balance between FES and robotic controllers. Combination of FES and robotic control is a challenging issue, due to the non-linear behavior of muscle under stimulation and the lack of developments in the field of hybrid control. In this article, a cooperative control strategy of a hybrid exoskeleton is presented. This strategy is designed to overcome the main disadvantages of muscular stimulation: electromechanical delay and change in muscle performance over time, and to balance muscular and robotic actuation during walking.Experimental results in healthy subjects show the ability of the hybrid FES-robot cooperative control to balance power contribution between exoskeleton and muscle stimulation. The robotic exoskeleton decreases assistance while adequate knee kinematics are guaranteed. A new technique to monitor muscle performance is employed, which allows to estimate muscle fatigue and implement muscle fatigue management strategies. Kinesis is therefore the first ambulatory hybrid exoskeleton that can effectively balance robotic and FES actuation during walking. This represents a new opportunity to implement new rehabilitation interventions to induce locomotor activity in patients with paraplegia.Acronym list: 10 mWT: ten meters walking test; 6 MWT: six minutes walking test; FSM: finite-state machine; t-FSM: time-domain FSM; c-FSM: cycle-domain FSM; FES: functional electrical stimulation; HKAFO: hip-knee-ankle-foot orthosis; ILC: iterative error-based learning control; MFE: muscle fatigue estimator; NILC: Normalized stimulation output from ILC controller; PID: Proportional-Integral-derivative Control; PW: Stimulation pulse width; QUEST: Quebec User Evaluation of Satisfaction with assistive Technology; SCI: Spinal cord injury; TTI: torque-time integral; VAS: Visual Analog Scale.

Hybrid FES-robot cooperative control of ambulatory gait rehabilitation exoskeleton

PubMed Central

2014-01-01

Robotic and functional electrical stimulation (FES) approaches are used for rehabilitation of walking impairment of spinal cord injured individuals. Although devices are commercially available, there are still issues that remain to be solved. Control of hybrid exoskeletons aims at blending robotic exoskeletons and electrical stimulation to overcome the drawbacks of each approach while preserving their advantages. Hybrid actuation and control have a considerable potential for walking rehabilitation but there is a need of novel control strategies of hybrid systems that adequately manage the balance between FES and robotic controllers. Combination of FES and robotic control is a challenging issue, due to the non-linear behavior of muscle under stimulation and the lack of developments in the field of hybrid control. In this article, a cooperative control strategy of a hybrid exoskeleton is presented. This strategy is designed to overcome the main disadvantages of muscular stimulation: electromechanical delay and change in muscle performance over time, and to balance muscular and robotic actuation during walking. Experimental results in healthy subjects show the ability of the hybrid FES-robot cooperative control to balance power contribution between exoskeleton and muscle stimulation. The robotic exoskeleton decreases assistance while adequate knee kinematics are guaranteed. A new technique to monitor muscle performance is employed, which allows to estimate muscle fatigue and implement muscle fatigue management strategies. Kinesis is therefore the first ambulatory hybrid exoskeleton that can effectively balance robotic and FES actuation during walking. This represents a new opportunity to implement new rehabilitation interventions to induce locomotor activity in patients with paraplegia. Acronym list: 10mWT: ten meters walking test; 6MWT: six minutes walking test; FSM: finite-state machine; t-FSM: time-domain FSM; c-FSM: cycle-domain FSM; FES: functional electrical stimulation; HKAFO: hip-knee-ankle-foot orthosis; ILC: iterative error-based learning control; MFE: muscle fatigue estimator; NILC: Normalized stimulation output from ILC controller; PID: Proportional-Integral-derivative Control; PW: Stimulation pulse width; QUEST: Quebec User Evaluation of Satisfaction with assistive Technology; SCI: Spinal cord injury; TTI: torque-time integral; VAS: Visual Analog Scale. PMID:24594302

Distance-Based Behaviors for Low-Complexity Control in Multiagent Robotics

NASA Astrophysics Data System (ADS)

Pierpaoli, Pietro

Several biological examples show that living organisms cooperate to collectively accomplish tasks impossible for single individuals. More importantly, this coordination is often achieved with a very limited set of information. Inspired by these observations, research on autonomous systems has focused on the development of distributed control techniques for control and guidance of groups of autonomous mobile agents, or robots. From an engineering perspective, when coordination and cooperation is sought in large ensembles of robotic vehicles, a reduction in hardware and algorithms' complexity becomes mandatory from the very early stages of the project design. The research for solutions capable of lowering power consumption, cost and increasing reliability are thus worth investigating. In this work, we studied low-complexity techniques to achieve cohesion and control on swarms of autonomous robots. Starting from an inspiring example with two-agents, we introduced effects of neighbors' relative positions on control of an autonomous agent. The extension of this intuition addressed the control of large ensembles of autonomous vehicles, and was applied in the form of a herding-like technique. To this end, a low-complexity distance-based aggregation protocol was defined. We first showed that our protocol produced a cohesion aggregation among the agent while avoiding inter-agent collisions. Then, a feedback leader-follower architecture was introduced for the control of the swarm. We also described how proximity measures and probability of collisions with neighbors can also be used as source of information in highly populated environments.

Research on wheelchair robot control system based on EOG

NASA Astrophysics Data System (ADS)

Xu, Wang; Chen, Naijian; Han, Xiangdong; Sun, Jianbo

2018-04-01

The paper describes an intelligent wheelchair control system based on EOG. It can help disabled people improve their living ability. The system can acquire EOG signal from the user, detect the number of blink and the direction of glancing, and then send commands to the wheelchair robot via RS-232 to achieve the control of wheelchair robot. Wheelchair robot control system based on EOG is composed of processing EOG signal and human-computer interactive technology, which achieves a purpose of using conscious eye movement to control wheelchair robot.

Influence of robotic shoal size, configuration, and activity on zebrafish behavior in a free-swimming environment.

PubMed

Butail, Sachit; Polverino, Giovanni; Phamduy, Paul; Del Sette, Fausto; Porfiri, Maurizio

2014-12-15

In animal studies, robots have been recently used as a valid tool for testing a wide spectrum of hypotheses. These robots often exploit visual or auditory cues to modulate animal behavior. The propensity of zebrafish, a model organism in biological studies, toward fish with similar color patterns and shape has been leveraged to design biologically inspired robots that successfully attract zebrafish in preference tests. With an aim of extending the application of such robots to field studies, here, we investigate the response of zebrafish to multiple robotic fish swimming at different speeds and in varying arrangements. A soft real-time multi-target tracking and control system remotely steers the robots in circular trajectories during the experimental trials. Our findings indicate a complex behavioral response of zebrafish to biologically inspired robots. More robots produce a significant change in salient measures of stress, with a fast robot swimming alone causing more freezing and erratic activity than two robots swimming slowly together. In addition, fish spend more time in the proximity of a robot when they swim far apart than when the robots swim close to each other. Increase in the number of robots also significantly alters the degree of alignment of fish motion with a robot. Results from this study are expected to advance our understanding of robot perception by live animals and aid in hypothesis-driven studies in unconstrained free-swimming environments. Copyright © 2014 Elsevier B.V. All rights reserved.

Method and System for Controlling a Dexterous Robot Execution Sequence Using State Classification

NASA Technical Reports Server (NTRS)

Sanders, Adam M. (Inventor); Quillin, Nathaniel (Inventor); Platt, Robert J., Jr. (Inventor); Pfeiffer, Joseph (Inventor); Permenter, Frank Noble (Inventor)

2014-01-01

A robotic system includes a dexterous robot and a controller. The robot includes a plurality of robotic joints, actuators for moving the joints, and sensors for measuring a characteristic of the joints, and for transmitting the characteristics as sensor signals. The controller receives the sensor signals, and is configured for executing instructions from memory, classifying the sensor signals into distinct classes via the state classification module, monitoring a system state of the robot using the classes, and controlling the robot in the execution of alternative work tasks based on the system state. A method for controlling the robot in the above system includes receiving the signals via the controller, classifying the signals using the state classification module, monitoring the present system state of the robot using the classes, and controlling the robot in the execution of alternative work tasks based on the present system state.

Improving Emergency Response and Human-Robotic Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

David I. Gertman; David J. Bruemmer; R. Scott Hartley

2007-08-01

Preparedness for chemical, biological, and radiological/nuclear incidents at nuclear power plants (NPPs) includes the deployment of well trained emergency response teams. While teams are expected to do well, data from other domains suggests that the timeliness and accuracy associated with incident response can be improved through collaborative human-robotic interaction. Many incident response scenarios call for multiple, complex procedure-based activities performed by personnel wearing cumbersome personal protective equipment (PPE) and operating under high levels of stress and workload. While robotic assistance is postulated to reduce workload and exposure, limitations associated with communications and the robot’s ability to act independently have servedmore » to limit reliability and reduce our potential to exploit human –robotic interaction and efficacy of response. Recent work at the Idaho National Laboratory (INL) on expanding robot capability has the potential to improve human-system response during disaster management and recovery. Specifically, increasing the range of higher level robot behaviors such as autonomous navigation and mapping, evolving new abstractions for sensor and control data, and developing metaphors for operator control have the potential to improve state-of-the-art in incident response. This paper discusses these issues and reports on experiments underway intelligence residing on the robot to enhance emergency response.« less

Behavior-Based Multi-Robot Collaboration for Autonomous Construction Tasks

NASA Technical Reports Server (NTRS)

Stroupe, Ashley; Huntsberger, Terry; Okon, Avi; Aghazarian, Hrand; Robinson, Matthew

2005-01-01

We present a heterogeneous multi-robot system for autonomous construction of a structure through assembly of long components. Placement of a component within an existing structure in a realistic environment is demonstrated on a two-robot team. The task requires component acquisition, cooperative transport, and cooperative precision manipulation. Far adaptability, the system is designed as a behavior-based architecture. Far applicability to space-related construction efforts, computation, power, communication, and sensing are minimized, though the techniques developed are also applicable to terrestrial construction tasks.

Decentralized reinforcement-learning control and emergence of motion patterns

NASA Astrophysics Data System (ADS)

Svinin, Mikhail; Yamada, Kazuyaki; Okhura, Kazuhiro; Ueda, Kanji

1998-10-01

In this paper we propose a system for studying emergence of motion patterns in autonomous mobile robotic systems. The system implements an instance-based reinforcement learning control. Three spaces are of importance in formulation of the control scheme. They are the work space, the sensor space, and the action space. Important feature of our system is that all these spaces are assumed to be continuous. The core part of the system is a classifier system. Based on the sensory state space analysis, the control is decentralized and is specified at the lowest level of the control system. However, the local controllers are implicitly connected through the perceived environment information. Therefore, they constitute a dynamic environment with respect to each other. The proposed control scheme is tested under simulation for a mobile robot in a navigation task. It is shown that some patterns of global behavior--such as collision avoidance, wall-following, light-seeking--can emerge from the local controllers.

Modeling of dielectric elastomer oscillators for soft biomimetic applications.

PubMed

Henke, E-F M; Wilson, Katherine E; Anderson, I A

2018-06-26

Biomimetic, entirely soft robots with animal-like behavior and integrated artificial nervous systems will open up totally new perspectives and applications. However, until now, most presented studies on soft robots were limited to only partly soft designs, since all solutions at least needed conventional, stiff electronics to sense, process signals and activate actuators. We present a novel approach for a set up and the experimental validation of an artificial pace maker that is able to drive basic robotic structures and act as artificial central pattern generator. The structure is based on multi-functional dielectric elastomers (DEs). DE actuators, DE switches and DE resistors are combined to create complex DE oscillators (DEOs). Supplied with only one external DC voltage, the DEO autonomously generates oscillating signals that can be used to clock a robotic structure, control the cyclic motion of artificial muscles in bionic robots or make a whole robotic structure move. We present the basic functionality, derive a mathematical model for predicting the generated signal waveform and verify the model experimentally.

A soft body as a reservoir: case studies in a dynamic model of octopus-inspired soft robotic arm.

PubMed

Nakajima, Kohei; Hauser, Helmut; Kang, Rongjie; Guglielmino, Emanuele; Caldwell, Darwin G; Pfeifer, Rolf

2013-01-01

The behaviors of the animals or embodied agents are characterized by the dynamic coupling between the brain, the body, and the environment. This implies that control, which is conventionally thought to be handled by the brain or a controller, can partially be outsourced to the physical body and the interaction with the environment. This idea has been demonstrated in a number of recently constructed robots, in particular from the field of "soft robotics". Soft robots are made of a soft material introducing high-dimensionality, non-linearity, and elasticity, which often makes the robots difficult to control. Biological systems such as the octopus are mastering their complex bodies in highly sophisticated manners by capitalizing on their body dynamics. We will demonstrate that the structure of the octopus arm cannot only be exploited for generating behavior but also, in a sense, as a computational resource. By using a soft robotic arm inspired by the octopus we show in a number of experiments how control is partially incorporated into the physical arm's dynamics and how the arm's dynamics can be exploited to approximate non-linear dynamical systems and embed non-linear limit cycles. Future application scenarios as well as the implications of the results for the octopus biology are also discussed.

Method and apparatus for automatic control of a humanoid robot

NASA Technical Reports Server (NTRS)

Abdallah, Muhammad E (Inventor); Platt, Robert (Inventor); Wampler, II, Charles W. (Inventor); Sanders, Adam M (Inventor); Reiland, Matthew J (Inventor)

2013-01-01

A robotic system includes a humanoid robot having a plurality of joints adapted for force control with respect to an object acted upon by the robot, a graphical user interface (GUI) for receiving an input signal from a user, and a controller. The GUI provides the user with intuitive programming access to the controller. The controller controls the joints using an impedance-based control framework, which provides object level, end-effector level, and/or joint space-level control of the robot in response to the input signal. A method for controlling the robotic system includes receiving the input signal via the GUI, e.g., a desired force, and then processing the input signal using a host machine to control the joints via an impedance-based control framework. The framework provides object level, end-effector level, and/or joint space-level control of the robot, and allows for functional-based GUI to simplify implementation of a myriad of operating modes.

Piezoresistive pressure sensor array for robotic skin

NASA Astrophysics Data System (ADS)

Mirza, Fahad; Sahasrabuddhe, Ritvij R.; Baptist, Joshua R.; Wijesundara, Muthu B. J.; Lee, Woo H.; Popa, Dan O.

2016-05-01

Robots are starting to transition from the confines of the manufacturing floor to homes, schools, hospitals, and highly dynamic environments. As, a result, it is impossible to foresee all the probable operational situations of robots, and preprogram the robot behavior in those situations. Among human-robot interaction technologies, haptic communication is an intuitive physical interaction method that can help define operational behaviors for robots cooperating with humans. Multimodal robotic skin with distributed sensors can help robots increase perception capabilities of their surrounding environments. Electro-Hydro-Dynamic (EHD) printing is a flexible multi-modal sensor fabrication method because of its direct printing capability of a wide range of materials onto substrates with non-uniform topographies. In past work we designed interdigitated comb electrodes as a sensing element and printed piezoresistive strain sensors using customized EHD printable PEDOT:PSS based inks. We formulated a PEDOT:PSS derivative ink, by mixing PEDOT:PSS and DMSO. Bending induced characterization tests of prototyped sensors showed high sensitivity and sufficient stability. In this paper, we describe SkinCells, robot skin sensor arrays integrated with electronic modules. 4x4 EHD-printed arrays of strain sensors was packaged onto Kapton sheets and silicone encapsulant and interconnected to a custom electronic module that consists of a microcontroller, Wheatstone bridge with adjustable digital potentiometer, multiplexer, and serial communication unit. Thus, SkinCell's electronics can be used for signal acquisition, conditioning, and networking between sensor modules. Several SkinCells were loaded with controlled pressure, temperature and humidity testing apparatuses, and testing results are reported in this paper.

Linear Temporal Logic (LTL) Based Monitoring of Smart Manufacturing Systems

PubMed Central

Heddy, Gerald; Huzaifa, Umer; Beling, Peter; Haimes, Yacov; Marvel, Jeremy; Weiss, Brian; LaViers, Amy

2017-01-01

The vision of Smart Manufacturing Systems (SMS) includes collaborative robots that can adapt to a range of scenarios. This vision requires a classification of multiple system behaviors, or sequences of movement, that can achieve the same high-level tasks. Likewise, this vision presents unique challenges regarding the management of environmental variables in concert with discrete, logic-based programming. Overcoming these challenges requires targeted performance and health monitoring of both the logical controller and the physical components of the robotic system. Prognostics and health management (PHM) defines a field of techniques and methods that enable condition-monitoring, diagnostics, and prognostics of physical elements, functional processes, overall systems, etc. PHM is warranted in this effort given that the controller is vulnerable to program changes, which propagate in unexpected ways, logical runtime exceptions, sensor failure, and even bit rot. The physical component’s health is affected by the wear and tear experienced by machines constantly in motion. The controller’s source of faults is inherently discrete, while the latter occurs in a manner that builds up continuously over time. Such a disconnect poses unique challenges for PHM. This paper presents a robotic monitoring system that captures and resolves this disconnect. This effort leverages supervisory robotic control and model checking with linear temporal logic (LTL), presenting them as a novel monitoring system for PHM. This methodology has been demonstrated in a MATLAB-based simulator for an industry inspired use-case in the context of PHM. Future work will use the methodology to develop adaptive, intelligent control strategies to evenly distribute wear on the joints of the robotic arms, maximizing the life of the system. PMID:28730154

Unified Approach To Control Of Motions Of Mobile Robots

NASA Technical Reports Server (NTRS)

Seraji, Homayoun

1995-01-01

Improved computationally efficient scheme developed for on-line coordinated control of both manipulation and mobility of robots that include manipulator arms mounted on mobile bases. Present scheme similar to one described in "Coordinated Control of Mobile Robotic Manipulators" (NPO-19109). Both schemes based on configuration-control formalism. Present one incorporates explicit distinction between holonomic and nonholonomic constraints. Several other prior articles in NASA Tech Briefs discussed aspects of configuration-control formalism. These include "Increasing the Dexterity of Redundant Robots" (NPO-17801), "Redundant Robot Can Avoid Obstacles" (NPO-17852), "Configuration-Control Scheme Copes with Singularities" (NPO-18556), "More Uses for Configuration Control of Robots" (NPO-18607/NPO-18608).

Artificial consciousness, artificial emotions, and autonomous robots.

PubMed

Cardon, Alain

2006-12-01

Nowadays for robots, the notion of behavior is reduced to a simple factual concept at the level of the movements. On another hand, consciousness is a very cultural concept, founding the main property of human beings, according to themselves. We propose to develop a computable transposition of the consciousness concepts into artificial brains, able to express emotions and consciousness facts. The production of such artificial brains allows the intentional and really adaptive behavior for the autonomous robots. Such a system managing the robot's behavior will be made of two parts: the first one computes and generates, in a constructivist manner, a representation for the robot moving in its environment, and using symbols and concepts. The other part achieves the representation of the previous one using morphologies in a dynamic geometrical way. The robot's body will be seen for itself as the morphologic apprehension of its material substrata. The model goes strictly by the notion of massive multi-agent's organizations with a morphologic control.

A Low Cost Mobile Robot Based on Proportional Integral Derivative (PID) Control System and Odometer for Education

NASA Astrophysics Data System (ADS)

Haq, R.; Prayitno, H.; Dzulkiflih; Sucahyo, I.; Rahmawati, E.

2018-03-01

In this article, the development of a low cost mobile robot based on PID controller and odometer for education is presented. PID controller and odometer is applied for controlling mobile robot position. Two-dimensional position vector in cartesian coordinate system have been inserted to robot controller as an initial and final position. Mobile robot has been made based on differential drive and sensor magnetic rotary encoder which measured robot position from a number of wheel rotation. Odometry methode use data from actuator movements for predicting change of position over time. The mobile robot is examined to get final position with three different heading angle 30°, 45° and 60° by applying various value of KP, KD and KI constant.

A Novel Concept for Safe, Stiffness-Controllable Robot Links.

PubMed

Stilli, Agostino; Wurdemann, Helge A; Althoefer, Kaspar

2017-03-01

The recent decade has seen an astounding increase of interest and advancement in a new field of robotics, aimed at creating structures specifically for the safe interaction with humans. Softness, flexibility, and variable stiffness in robotics have been recognized as highly desirable characteristics for many applications. A number of solutions were proposed ranging from entirely soft robots (such as those composed mainly from soft materials such as silicone), via flexible continuum and snake-like robots, to rigid-link robots enhanced by joints that exhibit an elastic behavior either implemented in hardware or achieved purely by means of intelligent control. Although these are very good solutions paving the path to safe human-robot interaction, we propose here a new approach that focuses on creating stiffness controllability for the linkages between the robot joints. This article proposes a replacement for the traditionally rigid robot link-the new link is equipped with an additional capability of stiffness controllability. With this added feature, a robot can accurately carry out manipulation tasks (high stiffness), but can virtually instantaneously reduce its stiffness when a human is nearby or in contact with the robot. The key point of the invention described here is a robot link made of an airtight chamber formed by a soft and flexible, but high-strain resistant combination of a plastic mesh and silicone wall. Inflated with air to a high pressure, the mesh silicone chamber behaves like a rigid link; reducing the air pressure, softens the link and rendering the robot structure safe. This article investigates a number of link prototypes and shows the feasibility of the new concept. Stiffness tests have been performed, showing that a significant level of stiffness can be achieved-up to 40 N reaction force along the axial direction, for a 25-mm-diameter sample at 60 kPa, at an axial deformation of 5 mm. The results confirm that this novel concept to linkages for robot manipulators exhibits the beam-like behavior of traditional rigid links when fully pressurized and significantly reduced stiffness at low pressure. The proposed concept has the potential to easily create safe robots, augmenting traditional robot designs.

Information driven self-organization of complex robotic behaviors.

PubMed

Martius, Georg; Der, Ralf; Ay, Nihat

2013-01-01

Information theory is a powerful tool to express principles to drive autonomous systems because it is domain invariant and allows for an intuitive interpretation. This paper studies the use of the predictive information (PI), also called excess entropy or effective measure complexity, of the sensorimotor process as a driving force to generate behavior. We study nonlinear and nonstationary systems and introduce the time-local predicting information (TiPI) which allows us to derive exact results together with explicit update rules for the parameters of the controller in the dynamical systems framework. In this way the information principle, formulated at the level of behavior, is translated to the dynamics of the synapses. We underpin our results with a number of case studies with high-dimensional robotic systems. We show the spontaneous cooperativity in a complex physical system with decentralized control. Moreover, a jointly controlled humanoid robot develops a high behavioral variety depending on its physics and the environment it is dynamically embedded into. The behavior can be decomposed into a succession of low-dimensional modes that increasingly explore the behavior space. This is a promising way to avoid the curse of dimensionality which hinders learning systems to scale well.

Metabolic cost of level-ground walking with a robotic transtibial prosthesis combining push-off power and nonlinear damping behaviors: preliminary results.

PubMed

Yanggang Feng; Jinying Zhu; Qining Wang

2016-08-01

Recent advances in robotic technology are facilitating the development of robotic prostheses. Our previous studies proposed a lightweight robotic transtibial prosthesis with a damping control strategy. To improve the performance of power assistance, in this paper, we redesign the prosthesis and improve the control strategy by supplying extra push-off power. A male transtibial amputee subject volunteered to participate in the study. Preliminary experimental results show that the proposed prosthesis with push-off control improves energy expenditure by a percentage ranged from 9.72 % to 14.99 % for level-ground walking compared with the one using non-push-off control.

The other half of the embodied mind.

PubMed

Parisi, Domenico

2011-01-01

Embodied theories of mind tend to be theories of the cognitive half of the mind and to ignore its emotional half while a complete theory of the mind should account for both halves. Robots are a new way of expressing theories of the mind which are less ambiguous and more capable to generate specific and non-controversial predictions than verbally expressed theories. We outline a simple robotic model of emotional states as states of a sub-part of the neural network controlling the robot's behavior which has specific properties and which allows the robot to make faster and more correct motivational decisions, and we describe possible extensions of the model to account for social emotional states and for the expression of emotions that, unlike those of current "emotional" robots, are really "felt" by the robot in that they play a well-identified functional role in the robot's behavior.

The Other Half of the Embodied Mind

PubMed Central

Parisi, Domenico

2011-01-01

Embodied theories of mind tend to be theories of the cognitive half of the mind and to ignore its emotional half while a complete theory of the mind should account for both halves. Robots are a new way of expressing theories of the mind which are less ambiguous and more capable to generate specific and non-controversial predictions than verbally expressed theories. We outline a simple robotic model of emotional states as states of a sub-part of the neural network controlling the robot's behavior which has specific properties and which allows the robot to make faster and more correct motivational decisions, and we describe possible extensions of the model to account for social emotional states and for the expression of emotions that, unlike those of current “emotional” robots, are really “felt” by the robot in that they play a well-identified functional role in the robot's behavior. PMID:21687441

Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement

NASA Astrophysics Data System (ADS)

Liu, Dalong; Xu, Lijuan

2018-01-01

In order to improve the accuracy of robot pose positioning and control, this paper proposed a dynamic tracking measurement robot pose optimization control method based on the actual measurement of D-H parameters of the robot, the parameters is taken with feedback compensation of the robot, according to the geometrical parameters obtained by robot pose tracking measurement, improved multi sensor information fusion the extended Kalan filter method, with continuous self-optimal regression, using the geometric relationship between joint axes for kinematic parameters in the model, link model parameters obtained can timely feedback to the robot, the implementation of parameter correction and compensation, finally we can get the optimal attitude angle, realize the robot pose optimization control experiments were performed. 6R dynamic tracking control of robot joint robot with independent research and development is taken as experimental subject, the simulation results show that the control method improves robot positioning accuracy, and it has the advantages of versatility, simplicity, ease of operation and so on.

Bearing-based localization for leader-follower formation control

PubMed Central

Han, Qing; Ren, Shan; Lang, Hao; Zhang, Changliang

2017-01-01

The observability of the leader robot system and the leader-follower formation control are studied. First, the nonlinear observability is studied for when the leader robot observes landmarks. Second, the system is shown to be completely observable when the leader robot observes two different landmarks. When the leader robot system is observable, multi-robots can rapidly form and maintain a formation based on the bearing-only information that the follower robots observe from the leader robot. Finally, simulations confirm the effectiveness of the proposed formation control. PMID:28426706

A Behavior-Based Approach for Educational Robotics Activities

ERIC Educational Resources Information Center

De Cristoforis, P.; Pedre, S.; Nitsche, M.; Fischer, T.; Pessacg, F.; Di Pietro, C.

2013-01-01

Educational robotics proposes the use of robots as a teaching resource that enables inexperienced students to approach topics in fields unrelated to robotics. In recent years, these activities have grown substantially in elementary and secondary school classrooms and also in outreach experiences to interest students in science, technology,…

Multirobot Lunar Excavation and ISRU Using Artificial-Neural-Tissue Controllers

NASA Astrophysics Data System (ADS)

Thangavelautham, Jekanthan; Smith, Alexander; Abu El Samid, Nader; Ho, Alexander; Boucher, Dale; Richard, Jim; D'Eleuterio, Gabriele M. T.

2008-01-01

Automation of site preparation and resource utilization on the Moon with teams of autonomous robots holds considerable promise for establishing a lunar base. Such multirobot autonomous systems would require limited human support infrastructure, complement necessary manned operations and reduce overall mission risk. We present an Artificial Neural Tissue (ANT) architecture as a control system for autonomous multirobot excavation tasks. An ANT approach requires much less human supervision and pre-programmed human expertise than previous techniques. Only a single global fitness function and a set of allowable basis behaviors need be specified. An evolutionary (Darwinian) selection process is used to `breed' controllers for the task at hand in simulation and the fittest controllers are transferred onto hardware for further validation and testing. ANT facilitates `machine creativity', with the emergence of novel functionality through a process of self-organized task decomposition of mission goals. ANT based controllers are shown to exhibit self-organization, employ stigmergy (communication mediated through the environment) and make use of templates (unlabeled environmental cues). With lunar in-situ resource utilization (ISRU) efforts in mind, ANT controllers have been tested on a multirobot excavation task in which teams of robots with no explicit supervision can successfully avoid obstacles, interpret excavation blueprints, perform layered digging, avoid burying or trapping other robots and clear/maintain digging routes.

Optimization of power utilization in multimobile robot foraging behavior inspired by honeybees system.

PubMed

Ahmad, Faisul Arif; Ramli, Abd Rahman; Samsudin, Khairulmizam; Hashim, Shaiful Jahari

2014-01-01

Deploying large numbers of mobile robots which can interact with each other produces swarm intelligent behavior. However, mobile robots are normally running with finite energy resource, supplied from finite battery. The limitation of energy resource required human intervention for recharging the batteries. The sharing information among the mobile robots would be one of the potentials to overcome the limitation on previously recharging system. A new approach is proposed based on integrated intelligent system inspired by foraging of honeybees applied to multimobile robot scenario. This integrated approach caters for both working and foraging stages for known/unknown power station locations. Swarm mobile robot inspired by honeybee is simulated to explore and identify the power station for battery recharging. The mobile robots will share the location information of the power station with each other. The result showed that mobile robots consume less energy and less time when they are cooperating with each other for foraging process. The optimizing of foraging behavior would result in the mobile robots spending more time to do real work.

Optimization of Power Utilization in Multimobile Robot Foraging Behavior Inspired by Honeybees System

PubMed Central

Ahmad, Faisul Arif; Ramli, Abd Rahman; Samsudin, Khairulmizam; Hashim, Shaiful Jahari

2014-01-01

Deploying large numbers of mobile robots which can interact with each other produces swarm intelligent behavior. However, mobile robots are normally running with finite energy resource, supplied from finite battery. The limitation of energy resource required human intervention for recharging the batteries. The sharing information among the mobile robots would be one of the potentials to overcome the limitation on previously recharging system. A new approach is proposed based on integrated intelligent system inspired by foraging of honeybees applied to multimobile robot scenario. This integrated approach caters for both working and foraging stages for known/unknown power station locations. Swarm mobile robot inspired by honeybee is simulated to explore and identify the power station for battery recharging. The mobile robots will share the location information of the power station with each other. The result showed that mobile robots consume less energy and less time when they are cooperating with each other for foraging process. The optimizing of foraging behavior would result in the mobile robots spending more time to do real work. PMID:24949491

Effect of motor dynamics on nonlinear feedback robot arm control

NASA Technical Reports Server (NTRS)

Tarn, Tzyh-Jong; Li, Zuofeng; Bejczy, Antal K.; Yun, Xiaoping

1991-01-01

A nonlinear feedback robot controller that incorporates the robot manipulator dynamics and the robot joint motor dynamics is proposed. The manipulator dynamics and the motor dynamics are coupled to obtain a third-order-dynamic model, and differential geometric control theory is applied to produce a linearized and decoupled robot controller. The derived robot controller operates in the robot task space, thus eliminating the need for decomposition of motion commands into robot joint space commands. Computer simulations are performed to verify the feasibility of the proposed robot controller. The controller is further experimentally evaluated on the PUMA 560 robot arm. The experiments show that the proposed controller produces good trajectory tracking performances and is robust in the presence of model inaccuracies. Compared with a nonlinear feedback robot controller based on the manipulator dynamics only, the proposed robot controller yields conspicuously improved performance.

Turning and Radius Deviation Correction for a Hexapod Walking Robot Based on an Ant-Inspired Sensory Strategy

PubMed Central

Guo, Tong; Liu, Qiong; Zhu, Qianwei; Zhao, Xiangmo; Jin, Bo

2017-01-01

In order to find a common approach to plan the turning of a bio-inspired hexapod robot, a locomotion strategy for turning and deviation correction of a hexapod walking robot based on the biological behavior and sensory strategy of ants. A series of experiments using ants were carried out where the gait and the movement form of ants was studied. Taking the results of the ant experiments as inspiration by imitating the behavior of ants during turning, an extended turning algorithm based on arbitrary gait was proposed. Furthermore, after the observation of the radius adjustment of ants during turning, a radius correction algorithm based on the arbitrary gait of the hexapod robot was raised. The radius correction surface function was generated by fitting the correction data, which made it possible for the robot to move in an outdoor environment without the positioning system and environment model. The proposed algorithm was verified on the hexapod robot experimental platform. The turning and radius correction experiment of the robot with several gaits were carried out. The results indicated that the robot could follow the ideal radius and maintain stability, and the proposed ant-inspired turning strategy could easily make free turns with an arbitrary gait. PMID:29168742

Turning and Radius Deviation Correction for a Hexapod Walking Robot Based on an Ant-Inspired Sensory Strategy.

PubMed

Zhu, Yaguang; Guo, Tong; Liu, Qiong; Zhu, Qianwei; Zhao, Xiangmo; Jin, Bo

2017-11-23

Abstract : In order to find a common approach to plan the turning of a bio-inspired hexapod robot, a locomotion strategy for turning and deviation correction of a hexapod walking robot based on the biological behavior and sensory strategy of ants. A series of experiments using ants were carried out where the gait and the movement form of ants was studied. Taking the results of the ant experiments as inspiration by imitating the behavior of ants during turning, an extended turning algorithm based on arbitrary gait was proposed. Furthermore, after the observation of the radius adjustment of ants during turning, a radius correction algorithm based on the arbitrary gait of the hexapod robot was raised. The radius correction surface function was generated by fitting the correction data, which made it possible for the robot to move in an outdoor environment without the positioning system and environment model. The proposed algorithm was verified on the hexapod robot experimental platform. The turning and radius correction experiment of the robot with several gaits were carried out. The results indicated that the robot could follow the ideal radius and maintain stability, and the proposed ant-inspired turning strategy could easily make free turns with an arbitrary gait.

A new approach of active compliance control via fuzzy logic control for multifingered robot hand

NASA Astrophysics Data System (ADS)

Jamil, M. F. A.; Jalani, J.; Ahmad, A.

2016-07-01

Safety is a vital issue in Human-Robot Interaction (HRI). In order to guarantee safety in HRI, a model reference impedance control can be a very useful approach introducing a compliant control. In particular, this paper establishes a fuzzy logic compliance control (i.e. active compliance control) to reduce impact and forces during physical interaction between humans/objects and robots. Exploiting a virtual mass-spring-damper system allows us to determine a desired compliant level by understanding the behavior of the model reference impedance control. The performance of fuzzy logic compliant control is tested in simulation for a robotic hand known as the RED Hand. The results show that the fuzzy logic is a feasible control approach, particularly to control position and to provide compliant control. In addition, the fuzzy logic control allows us to simplify the controller design process (i.e. avoid complex computation) when dealing with nonlinearities and uncertainties.

Control of a 7-DOF Robotic Arm System With an SSVEP-Based BCI.

PubMed

Chen, Xiaogang; Zhao, Bing; Wang, Yijun; Xu, Shengpu; Gao, Xiaorong

2018-04-12

Although robot technology has been successfully used to empower people who suffer from motor disabilities to increase their interaction with their physical environment, it remains a challenge for individuals with severe motor impairment, who do not have the motor control ability to move robots or prosthetic devices by manual control. In this study, to mitigate this issue, a noninvasive brain-computer interface (BCI)-based robotic arm control system using gaze based steady-state visual evoked potential (SSVEP) was designed and implemented using a portable wireless electroencephalogram (EEG) system. A 15-target SSVEP-based BCI using a filter bank canonical correlation analysis (FBCCA) method allowed users to directly control the robotic arm without system calibration. The online results from 12 healthy subjects indicated that a command for the proposed brain-controlled robot system could be selected from 15 possible choices in 4[Formula: see text]s (i.e. 2[Formula: see text]s for visual stimulation and 2[Formula: see text]s for gaze shifting) with an average accuracy of 92.78%, resulting in a 15 commands/min transfer rate. Furthermore, all subjects (even naive users) were able to successfully complete the entire move-grasp-lift task without user training. These results demonstrated an SSVEP-based BCI could provide accurate and efficient high-level control of a robotic arm, showing the feasibility of a BCI-based robotic arm control system for hand-assistance.

Coordinated Control Of Mobile Robotic Manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun

1995-01-01

Computationally efficient scheme developed for on-line coordinated control of both manipulation and mobility of robots that include manipulator arms mounted on mobile bases. Applicable to variety of mobile robotic manipulators, including robots that move along tracks (typically, painting and welding robots), robots mounted on gantries and capable of moving in all three dimensions, wheeled robots, and compound robots (consisting of robots mounted on other robots). Theoretical basis discussed in several prior articles in NASA Tech Briefs, including "Increasing the Dexterity of Redundant Robots" (NPO-17801), "Redundant Robot Can Avoid Obstacles" (NPO-17852), "Configuration-Control Scheme Copes With Singularities" (NPO-18556), "More Uses for Configuration Control of Robots" (NPO-18607/NPO-18608).

Research on Robot Pose Control Technology Based on Kinematics Analysis Model

NASA Astrophysics Data System (ADS)

Liu, Dalong; Xu, Lijuan

2018-01-01

In order to improve the attitude stability of the robot, proposes an attitude control method of robot based on kinematics analysis model, solve the robot walking posture transformation, grasping and controlling the motion planning problem of robot kinematics. In Cartesian space analytical model, using three axis accelerometer, magnetometer and the three axis gyroscope for the combination of attitude measurement, the gyroscope data from Calman filter, using the four element method for robot attitude angle, according to the centroid of the moving parts of the robot corresponding to obtain stability inertia parameters, using random sampling RRT motion planning method, accurate operation to any position control of space robot, to ensure the end effector along a prescribed trajectory the implementation of attitude control. The accurate positioning of the experiment is taken using MT-R robot as the research object, the test robot. The simulation results show that the proposed method has better robustness, and higher positioning accuracy, and it improves the reliability and safety of robot operation.

Toward the Design of Personalized Continuum Surgical Robots.

PubMed

Morimoto, Tania K; Greer, Joseph D; Hawkes, Elliot W; Hsieh, Michael H; Okamura, Allison M

2018-05-31

Robot-assisted minimally invasive surgical systems enable procedures with reduced pain, recovery time, and scarring compared to traditional surgery. While these improvements benefit a large number of patients, safe access to diseased sites is not always possible for specialized patient groups, including pediatric patients, due to their anatomical differences. We propose a patient-specific design paradigm that leverages the surgeon's expertise to design and fabricate robots based on preoperative medical images. The components of the patient-specific robot design process are a virtual reality design interface enabling the surgeon to design patient-specific tools, 3-D printing of these tools with a biodegradable polyester, and an actuation and control system for deployment. The designed robot is a concentric tube robot, a type of continuum robot constructed from precurved, elastic, nesting tubes. We demonstrate the overall patient-specific design workflow, from preoperative images to physical implementation, for an example clinical scenario: nonlinear renal access to a pediatric kidney. We also measure the system's behavior as it is deployed through real and artificial tissue. System integration and successful benchtop experiments in ex vivo liver and in a phantom patient model demonstrate the feasibility of using a patient-specific design workflow to plan, fabricate, and deploy personalized, flexible continuum robots.

UM-PRS: An implementation of the procedural reasoning system for multirobot applications

NASA Technical Reports Server (NTRS)

Lee, Jaeho; Huber, Marcus J.; Durfee, Edmund H.; Kenny, Patrick G.

1994-01-01

The Procedural Reasoning System (PRS) is used in applications where predetermined situations might arise. The UM-PRS provides a reasoning system that represents robotic applications even in unpredictable domains, such as the robotic reconnaissance task domain outlined here. UM-PRS incorporates a changing context, rather than relying solely on a prearranged plan. The UM-PRS here provides representation important in the reasoning and interface between a mission plan and the executable map of an outdoor vehicle that changes its behavior based on what it comes in contact with in its environment. PRS is thus used in the dynamic control of such a vehicle, providing the basis for coordinating the joint task of multiple robotic vehicles by the their individual observations and representation.

A learning-based semi-autonomous controller for robotic exploration of unknown disaster scenes while searching for victims.

PubMed

Doroodgar, Barzin; Liu, Yugang; Nejat, Goldie

2014-12-01

Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing a human operator to cooperate and share such tasks with a rescue robot as navigation, exploration, and victim identification. In this paper, we present a unique hierarchical reinforcement learning-based semi-autonomous control architecture for rescue robots operating in cluttered and unknown urban search and rescue (USAR) environments. The aim of the controller is to enable a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A direction-based exploration technique is integrated in the controller to expand the search area of the robot via the classification of regions and the rubble piles within these regions. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed HRL-based semi-autonomous controller to unknown cluttered scenes with different sizes and varying types of configurations.

Drive Control System for Pipeline Crawl Robot Based on CAN Bus

NASA Astrophysics Data System (ADS)

Chen, H. J.; Gao, B. T.; Zhang, X. H.; Deng2, Z. Q.

2006-10-01

Drive control system plays important roles in pipeline robot. In order to inspect the flaw and corrosion of seabed crude oil pipeline, an original mobile pipeline robot with crawler drive unit, power and monitor unit, central control unit, and ultrasonic wave inspection device is developed. The CAN bus connects these different function units and presents a reliable information channel. Considering the limited space, a compact hardware system is designed based on an ARM processor with two CAN controllers. With made-to-order CAN protocol for the crawl robot, an intelligent drive control system is developed. The implementation of the crawl robot demonstrates that the presented drive control scheme can meet the motion control requirements of the underwater pipeline crawl robot.

Model identification and controller design of a fish-like robot

NASA Astrophysics Data System (ADS)

Ariyanto, Irfan; Kang, Taesam; Chan, Wai Leung; Lee, Youngjae

2007-04-01

Robotic fish is an interesting and prospective subject to develop. The simplest fish swimming mode to be mimicked for fish robots is the ostraciiform mode which only requires caudal fin flapping. An almost submerged ostraciiform fish robot was constructed to study its swimming characteristics. The swimming direction can be controlled by changing the mean angle of caudal fin oscillation. Experiments were conducted to study the behavior of the fish robot and in particular, the transfer function between swimming path angular rate and mean angle of the caudal fin oscillation were identified. Error to signal ratio quantity was used to determine how well the model fits with the experimental data. This identification model was used to design a 2-degree-of-freedom PID controller that meets some specific requirements to improve the steering performance.

A Segway RMP-based robotic transport system

NASA Astrophysics Data System (ADS)

Nguyen, Hoa G.; Kogut, Greg; Barua, Ripan; Burmeister, Aaron; Pezeshkian, Narek; Powell, Darren; Farrington, Nathan; Wimmer, Matt; Cicchetto, Brett; Heng, Chana; Ramirez, Velia

2004-12-01

In the area of logistics, there currently is a capability gap between the one-ton Army robotic Multifunction Utility/Logistics and Equipment (MULE) vehicle and a soldier"s backpack. The Unmanned Systems Branch at Space and Naval Warfare Systems Center (SPAWAR Systems Center, or SSC), San Diego, with the assistance of a group of interns from nearby High Tech High School, has demonstrated enabling technologies for a solution that fills this gap. A small robotic transport system has been developed based on the Segway Robotic Mobility Platform (RMP). We have demonstrated teleoperated control of this robotic transport system, and conducted two demonstrations of autonomous behaviors. Both demonstrations involved a robotic transporter following a human leader. In the first demonstration, the transporter used a vision system running a continuously adaptive mean-shift filter to track and follow a human. In the second demonstration, the separation between leader and follower was significantly increased using Global Positioning System (GPS) information. The track of the human leader, with a GPS unit in his backpack, was sent wirelessly to the transporter, also equipped with a GPS unit. The robotic transporter traced the path of the human leader by following these GPS breadcrumbs. We have additionally demonstrated a robotic medical patient transport capability by using the Segway RMP to power a mock-up of the Life Support for Trauma and Transport (LSTAT) patient care platform, on a standard NATO litter carrier. This paper describes the development of our demonstration robotic transport system and the various experiments conducted.

Coordinating teams of autonomous vehicles: an architectural perspective

NASA Astrophysics Data System (ADS)

Czichon, Cary; Peterson, Robert W.; Mettala, Erik G.; Vondrak, Ivo

2005-05-01

In defense-related robotics research, a mission level integration gap exists between mission tasks (tactical) performed by ground, sea, or air applications and elementary behaviors enacted by processing, communications, sensors, and weaponry resources (platform specific). The gap spans ensemble (heterogeneous team) behaviors, automatic MOE/MOP tracking, and tactical task modeling/simulation for virtual and mixed teams comprised of robotic and human combatants. This study surveys robotic system architectures, compares approaches for navigating problem/state spaces by autonomous systems, describes an architecture for an integrated, repository-based modeling, simulation, and execution environment, and outlines a multi-tiered scheme for robotic behavior components that is agent-based, platform-independent, and extendable via plug-ins. Tools for this integrated environment, along with a distributed agent framework for collaborative task performance are being developed by a U.S. Army funded SBIR project (RDECOM Contract N61339-04-C-0005).

Person-like intelligent systems architectures for robotic shared control and automated operations

NASA Technical Reports Server (NTRS)

Erickson, Jon D.; Aucoin, Paschal J., Jr.; Ossorio, Peter G.

1992-01-01

An approach to rendering robotic systems as 'personlike' as possible to achieve needed capabilities is outlined. Human characteristics such as knowledge, motivation, know-how, performance, achievement and individual differences corresponding to propensities and abilities can be supplied, within limits, with computing software and hardware to robotic systems provided with sufficiently rich sensory configurations. Pushing these limits is the developmental path for more and more personlike robotic systems. The portions of the Person Concept that appear to be most directly relevant to this effort are described in the following topics: reality concepts (the state-of-affairs system and descriptive formats, behavior as intentional action, individual persons (person characteristics), social patterns of behavior (social practices), and boundary conditions (status maxims). Personlike robotic themes and considerations for a technical development plan are also discussed.

Intelligent robot control using an adaptive critic with a task control center and dynamic database

NASA Astrophysics Data System (ADS)

Hall, E. L.; Ghaffari, M.; Liao, X.; Alhaj Ali, S. M.

2006-10-01

The purpose of this paper is to describe the design, development and simulation of a real time controller for an intelligent, vision guided robot. The use of a creative controller that can select its own tasks is demonstrated. This creative controller uses a task control center and dynamic database. The dynamic database stores both global environmental information and local information including the kinematic and dynamic models of the intelligent robot. The kinematic model is very useful for position control and simulations. However, models of the dynamics of the manipulators are needed for tracking control of the robot's motions. Such models are also necessary for sizing the actuators, tuning the controller, and achieving superior performance. Simulations of various control designs are shown. Also, much of the model has also been used for the actual prototype Bearcat Cub mobile robot. This vision guided robot was designed for the Intelligent Ground Vehicle Contest. A novel feature of the proposed approach is that the method is applicable to both robot arm manipulators and robot bases such as wheeled mobile robots. This generality should encourage the development of more mobile robots with manipulator capability since both models can be easily stored in the dynamic database. The multi task controller also permits wide applications. The use of manipulators and mobile bases with a high-level control are potentially useful for space exploration, certain rescue robots, defense robots, and medical robotics aids.

Behavior Selection of Mobile Robot Based on Integration of Multimodal Information

NASA Astrophysics Data System (ADS)

Chen, Bin; Kaneko, Masahide

Recently, biologically inspired robots have been developed to acquire the capacity for directing visual attention to salient stimulus generated from the audiovisual environment. On purpose to realize this behavior, a general method is to calculate saliency maps to represent how much the external information attracts the robot's visual attention, where the audiovisual information and robot's motion status should be involved. In this paper, we represent a visual attention model where three modalities, that is, audio information, visual information and robot's motor status are considered, while the previous researches have not considered all of them. Firstly, we introduce a 2-D density map, on which the value denotes how much the robot pays attention to each spatial location. Then we model the attention density using a Bayesian network where the robot's motion statuses are involved. Secondly, the information from both of audio and visual modalities is integrated with the attention density map in integrate-fire neurons. The robot can direct its attention to the locations where the integrate-fire neurons are fired. Finally, the visual attention model is applied to make the robot select the visual information from the environment, and react to the content selected. Experimental results show that it is possible for robots to acquire the visual information related to their behaviors by using the attention model considering motion statuses. The robot can select its behaviors to adapt to the dynamic environment as well as to switch to another task according to the recognition results of visual attention.

Towards Principled Experimental Study of Autonomous Mobile Robots

NASA Technical Reports Server (NTRS)

Gat, Erann

1995-01-01

We review the current state of research in autonomous mobile robots and conclude that there is an inadequate basis for predicting the reliability and behavior of robots operating in unengineered environments. We present a new approach to the study of autonomous mobile robot performance based on formal statistical analysis of independently reproducible experiments conducted on real robots. Simulators serve as models rather than experimental surrogates. We demonstrate three new results: 1) Two commonly used performance metrics (time and distance) are not as well correlated as is often tacitly assumed. 2) The probability distributions of these performance metrics are exponential rather than normal, and 3) a modular, object-oriented simulation accurately predicts the behavior of the real robot in a statistically significant manner.

Mitigating clogging and arrest in confined self-propelled systems

NASA Astrophysics Data System (ADS)

Savoie, William; Aguilar, Jeffrey; Monaenkova, Daria; Linevich, Vadim; Goldman, Daniel

Ensembles of self-propelling elements, like colloidal surfers, bacterial biofilms, and robot swarms can spontaneously form density heterogeneities. To understand how to prevent potentially catastrophic clogs in task-oriented active matter systems (like soil excavating robots), we present a robophysical study of excavation of granular media in a confined environment. We probe the efficacy of two social strategies observed in our studies of fire ants (S. invicta). The first behavior (denoted as unequal workload) prescribes to each excavator a different probability to enter the digging area. The second behavior (denoted as reversal\\x9D), is characterized by a probability to forfeit excavation when progress is sufficiently obstructed. For equal workload distribution and no reversal behavior, clogs at the digging site prevent excavation for sufficient numbers of robots. Measurements of aggregation relaxation times reveal how the strategies mitigate clogs. The unequal workload behavior reduces the tunnel density, decreasing the probability of clog formation. Reversal behavior, while allowing clogs to form, reduces aggregation relaxation time. We posit that application of social behaviors can be useful for swarm robot systems where global control and organization may not be possible.

Control of free-flying space robot manipulator systems

NASA Technical Reports Server (NTRS)

Cannon, Robert H., Jr.

1989-01-01

Control techniques for self-contained, autonomous free-flying space robots are being tested and developed. Free-flying space robots are envisioned as a key element of any successful long term presence in space. These robots must be capable of performing the assembly, maintenance, and inspection, and repair tasks that currently require astronaut extra-vehicular activity (EVA). Use of robots will provide economic savings as well as improved astronaut safety by reducing and in many cases, eliminating the need for human EVA. The focus of the work is to develop and carry out a set of research projects using laboratory models of satellite robots. These devices use air-cushion-vehicle (ACV) technology to simulate in two dimensions the drag-free, zero-g conditions of space. Current work is divided into six major projects or research areas. Fixed-base cooperative manipulation work represents our initial entry into multiple arm cooperation and high-level control with a sophisticated user interface. The floating-base cooperative manipulation project strives to transfer some of the technologies developed in the fixed-base work onto a floating base. The global control and navigation experiment seeks to demonstrate simultaneous control of the robot manipulators and the robot base position so that tasks can be accomplished while the base is undergoing a controlled motion. The multiple-vehicle cooperation project's goal is to demonstrate multiple free-floating robots working in teams to carry out tasks too difficult or complex for a single robot to perform. The Location Enhancement Arm Push-off (LEAP) activity's goal is to provide a viable alternative to expendable gas thrusters for vehicle propulsion wherein the robot uses its manipulators to throw itself from place to place. Because the successful execution of the LEAP technique requires an accurate model of the robot and payload mass properties, it was deemed an attractive testbed for adaptive control technology.

A soft body as a reservoir: case studies in a dynamic model of octopus-inspired soft robotic arm

PubMed Central

Nakajima, Kohei; Hauser, Helmut; Kang, Rongjie; Guglielmino, Emanuele; Caldwell, Darwin G.; Pfeifer, Rolf

2013-01-01

The behaviors of the animals or embodied agents are characterized by the dynamic coupling between the brain, the body, and the environment. This implies that control, which is conventionally thought to be handled by the brain or a controller, can partially be outsourced to the physical body and the interaction with the environment. This idea has been demonstrated in a number of recently constructed robots, in particular from the field of “soft robotics”. Soft robots are made of a soft material introducing high-dimensionality, non-linearity, and elasticity, which often makes the robots difficult to control. Biological systems such as the octopus are mastering their complex bodies in highly sophisticated manners by capitalizing on their body dynamics. We will demonstrate that the structure of the octopus arm cannot only be exploited for generating behavior but also, in a sense, as a computational resource. By using a soft robotic arm inspired by the octopus we show in a number of experiments how control is partially incorporated into the physical arm's dynamics and how the arm's dynamics can be exploited to approximate non-linear dynamical systems and embed non-linear limit cycles. Future application scenarios as well as the implications of the results for the octopus biology are also discussed. PMID:23847526

Object-based task-level control: A hierarchical control architecture for remote operation of space robots

NASA Technical Reports Server (NTRS)

Stevens, H. D.; Miles, E. S.; Rock, S. J.; Cannon, R. H.

1994-01-01

Expanding man's presence in space requires capable, dexterous robots capable of being controlled from the Earth. Traditional 'hand-in-glove' control paradigms require the human operator to directly control virtually every aspect of the robot's operation. While the human provides excellent judgment and perception, human interaction is limited by low bandwidth, delayed communications. These delays make 'hand-in-glove' operation from Earth impractical. In order to alleviate many of the problems inherent to remote operation, Stanford University's Aerospace Robotics Laboratory (ARL) has developed the Object-Based Task-Level Control architecture. Object-Based Task-Level Control (OBTLC) removes the burden of teleoperation from the human operator and enables execution of tasks not possible with current techniques. OBTLC is a hierarchical approach to control where the human operator is able to specify high-level, object-related tasks through an intuitive graphical user interface. Infrequent task-level command replace constant joystick operations, eliminating communications bandwidth and time delay problems. The details of robot control and task execution are handled entirely by the robot and computer control system. The ARL has implemented the OBTLC architecture on a set of Free-Flying Space Robots. The capability of the OBTLC architecture has been demonstrated by controlling the ARL Free-Flying Space Robots from NASA Ames Research Center.

Neuromodulation as a Robot Controller: A Brain Inspired Strategy for Controlling Autonomous Robots

DTIC Science & Technology

2009-09-01

To Appear in IEEE Robotics and Automation Magazine PREPRINT 1 Neuromodulation as a Robot Controller: A Brain Inspired Strategy for Controlling...Introduction We present a strategy for controlling autonomous robots that is based on principles of neuromodulation in the mammalian brain...object, ignore irrelevant distractions, and respond quickly and appropriately to the event [1]. There are separate neuromodulators that alter responses to

Causal network in a deafferented non-human primate brain.

PubMed

Balasubramanian, Karthikeyan; Takahashi, Kazutaka; Hatsopoulos, Nicholas G

2015-01-01

De-afferented/efferented neural ensembles can undergo causal changes when interfaced to neuroprosthetic devices. These changes occur via recruitment or isolation of neurons, alterations in functional connectivity within the ensemble and/or changes in the role of neurons, i.e., excitatory/inhibitory. In this work, emergence of a causal network and changes in the dynamics are demonstrated for a deafferented brain region exposed to BMI (brain-machine interface) learning. The BMI was controlling a robot for reach-and-grasp behavior. And, the motor cortical regions used for the BMI were deafferented due to chronic amputation, and ensembles of neurons were decoded for velocity control of the multi-DOF robot. A generalized linear model-framework based Granger causality (GLM-GC) technique was used in estimating the ensemble connectivity. Model selection was based on the AIC (Akaike Information Criterion).

Motor-Skill Learning in an Insect Inspired Neuro-Computational Control System

PubMed Central

Arena, Eleonora; Arena, Paolo; Strauss, Roland; Patané, Luca

2017-01-01

In nature, insects show impressive adaptation and learning capabilities. The proposed computational model takes inspiration from specific structures of the insect brain: after proposing key hypotheses on the direct involvement of the mushroom bodies (MBs) and on their neural organization, we developed a new architecture for motor learning to be applied in insect-like walking robots. The proposed model is a nonlinear control system based on spiking neurons. MBs are modeled as a nonlinear recurrent spiking neural network (SNN) with novel characteristics, able to memorize time evolutions of key parameters of the neural motor controller, so that existing motor primitives can be improved. The adopted control scheme enables the structure to efficiently cope with goal-oriented behavioral motor tasks. Here, a six-legged structure, showing a steady-state exponentially stable locomotion pattern, is exposed to the need of learning new motor skills: moving through the environment, the structure is able to modulate motor commands and implements an obstacle climbing procedure. Experimental results on a simulated hexapod robot are reported; they are obtained in a dynamic simulation environment and the robot mimicks the structures of Drosophila melanogaster. PMID:28337138

Controlling a robot with intention derived from motion.

PubMed

Crick, Christopher; Scassellati, Brian

2010-01-01

We present a novel, sophisticated intention-based control system for a mobile robot built from an extremely inexpensive webcam and radio-controlled toy vehicle. The system visually observes humans participating in various playground games and infers their goals and intentions through analyzing their spatiotemporal activity in relation to itself and each other, and then builds a coherent narrative out of the succession of these intentional states. Starting from zero information about the room, the rules of the games, or even which vehicle it controls, it learns rich relationships between players, their goals and intentions, probing uncertain situations with its own behavior. The robot is able to watch people playing various playground games, learn the roles and rules that apply to specific games, and participate in the play. The narratives it constructs capture essential information about the observed social roles and types of activity. After watching play for a short while, the system is able to participate appropriately in the games. We demonstrate how the system acts appropriately in scenarios such as chasing, follow-the-leader, and variants of tag. Copyright © 2009 Cognitive Science Society, Inc.

[Force-based local navigation in robot-assisted implantation bed anlage in the lateral skull base. An experimental study].

PubMed

Plinkert, P K; Federspil, P A; Plinkert, B; Henrich, D

2002-03-01

Excellent precision, miss of retiring, reproducibility are main characteristics of robots in the operating theatre. Because of these facts their use for surgery in the lateral scull base is of great interest. In recent experiments we determined process parameters for robot assisted reaming of a cochlea implant bed and for a mastoidectomy. These results suggested that optimizing parameters for thrilling with the robot is needed. Therefore we implemented a suitable reaming curve from the geometrical data of the implant and a force controlled process control for robot assisted reaming at the lateral scull base. Experiments were performed with an industrial robot on animal and human scull base specimen. Because of online force detection and feedback of sensory data the reaming with the robot was controlled. With increasing force values above a defined limit feed rates were automatically regulated. Furthermore we were able to detect contact of the thrill to dura mater by analyzing the force values. With the new computer program the desired implant bed was exactly prepared. Our examinations showed a successful reaming of an implant bed in the lateral scull base with a robot. Because of a force controlled reaming process locale navigation is possible and enables careful thrilling with a robot.

Some Novel Design Principles for Collective Behaviors in Mobile Robots

DOE Office of Scientific and Technical Information (OSTI.GOV)

OSBOURN, GORDON C.

2002-09-01

We present a set of novel design principles to aid in the development of complex collective behaviors in fleets of mobile robots. The key elements are: the use of a graph algorithm that we have created, with certain proven properties, that guarantee scalable local communications for fleets of arbitrary size; the use of artificial forces to simplify the design of motion control; the use of certain proximity values in the graph algorithm to simplify the sharing of robust navigation and sensor information among the robots. We describe these design elements and present a computer simulation that illustrates the behaviors readilymore » achievable with these design tools.« less

Assistive acting movement therapy devices with pneumatic rotary-type soft actuators.

PubMed

Wilkening, André; Baiden, David; Ivlev, Oleg

2012-12-01

Inherent compliance and assistive behavior are assumed to be essential properties for safe human-robot interaction. Rehabilitation robots demand the highest standards in this respect because the machine interacts directly with weak persons who are often sensitive to pain. Using novel soft fluidic actuators with rotary elastic chambers (REC actuators), compact, lightweight, and cost-effective therapeutic devices can be developed. This article describes modular design and control strategies for new assistive acting robotic devices for upper and lower extremities. Due to the inherent compliance and natural back-drivability of pneumatic REC actuators, these movement therapy devices provide gentle treatment, whereby the interaction forces between humans and the therapy device are estimated without the use of expensive force/torque sensors. An active model-based gravity compensation based on separated models of the robot and of the individual patient's extremity provides the basis for effective assistive control. The utilization of pneumatic actuators demands a special safety concept, which is merged with control algorithms to provide a sufficient level of safeness and to catch any possible system errors and/or emergency situations. A self-explanatory user interface allows for easy, intuitive handling. Prototypes are very comfortable for use due to several control routines that work in the background. Assistive devices have been tested extensively with several healthy persons; the knee/hip movement therapy device is now under clinical trials at the Clinic for Orthopaedics and Trauma Surgery at the Klinikum Stuttgart.

Robot Faces that Follow Gaze Facilitate Attentional Engagement and Increase Their Likeability.

PubMed

Willemse, Cesco; Marchesi, Serena; Wykowska, Agnieszka

2018-01-01

Gaze behavior of humanoid robots is an efficient mechanism for cueing our spatial orienting, but less is known about the cognitive-affective consequences of robots responding to human directional cues. Here, we examined how the extent to which a humanoid robot (iCub) avatar directed its gaze to the same objects as our participants affected engagement with the robot, subsequent gaze-cueing, and subjective ratings of the robot's characteristic traits. In a gaze-contingent eyetracking task, participants were asked to indicate a preference for one of two objects with their gaze while an iCub avatar was presented between the object photographs. In one condition, the iCub then shifted its gaze toward the object chosen by a participant in 80% of the trials (joint condition) and in the other condition it looked at the opposite object 80% of the time (disjoint condition). Based on the literature in human-human social cognition, we took the speed with which the participants looked back at the robot as a measure of facilitated reorienting and robot-preference, and found these return saccade onset times to be quicker in the joint condition than in the disjoint condition. As indicated by results from a subsequent gaze-cueing tasks, the gaze-following behavior of the robot had little effect on how our participants responded to gaze cues. Nevertheless, subjective reports suggested that our participants preferred the iCub following participants' gaze to the one with a disjoint attention behavior, rated it as more human-like and as more likeable. Taken together, our findings show a preference for robots who follow our gaze. Importantly, such subtle differences in gaze behavior are sufficient to influence our perception of humanoid agents, which clearly provides hints about the design of behavioral characteristics of humanoid robots in more naturalistic settings.

Research on the man in the loop control system of the robot arm based on gesture control

NASA Astrophysics Data System (ADS)

Xiao, Lifeng; Peng, Jinbao

2017-03-01

The Man in the loop control system of the robot arm based on gesture control research complex real-world environment, which requires the operator to continuously control and adjust the remote manipulator, as the background, completes the specific mission human in the loop entire system as the research object. This paper puts forward a kind of robot arm control system of Man in the loop based on gesture control, by robot arm control system based on gesture control and Virtual reality scene feedback to enhance immersion and integration of operator, to make operator really become a part of the whole control loop. This paper expounds how to construct a man in the loop control system of the robot arm based on gesture control. The system is a complex system of human computer cooperative control, but also people in the loop control problem areas. The new system solves the problems that the traditional method has no immersion feeling and the operation lever is unnatural, the adjustment time is long, and the data glove mode wears uncomfortable and the price is expensive.

Review of control strategies for robotic movement training after neurologic injury.

PubMed

Marchal-Crespo, Laura; Reinkensmeyer, David J

2009-06-16

There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies.

Review of control strategies for robotic movement training after neurologic injury

PubMed Central

Marchal-Crespo, Laura; Reinkensmeyer, David J

2009-01-01

There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies. PMID:19531254

Control strategies for effective robot assisted gait rehabilitation: the state of art and future prospects.

PubMed

Cao, Jinghui; Xie, Sheng Quan; Das, Raj; Zhu, Guo L

2014-12-01

A large number of gait rehabilitation robots, together with a variety of control strategies, have been developed and evaluated during the last decade. Initially, control strategies applied to rehabilitation robots were adapted from those applied to traditional industrial robots. However, these strategies cannot optimise effectiveness of gait rehabilitation. As a result, researchers have been investigating control strategies tailored for the needs of rehabilitation. Among these control strategies, assisted-as-needed (AAN) control is one of the most popular research topics in this field. AAN training strategies have gained the theoretical and practical evidence based backup from motor learning principles and clinical studies. Various approaches to AAN training have been proposed and investigated by research groups all around the world. This article presents a review on control algorithms of gait rehabilitation robots to summarise related knowledge and investigate potential trends of development. There are existing review papers on control strategies of rehabilitation robots. The review by Marchal-Crespo and Reinkensmeyer (2009) had a broad cover of control strategies of all kinds of rehabilitation robots. Hussain et al. (2011) had specifically focused on treadmill gait training robots and covered a limited number of control implementations on them. This review article encompasses more detailed information on control strategies for robot assisted gait rehabilitation, but is not limited to treadmill based training. It also investigates the potential to further develop assist-as-needed gait training based on assessments of patients' ability. In this paper, control strategies are generally divided into the trajectory tracking control and AAN control. The review covers these two basic categories, as well as other control algorithm and technologies derived from them, such as biofeedback control. Assessments on human gait ability are also included to investigate how to further develop implementations based on assist-as-needed concept. For the consideration of effectiveness, clinical studies on robotic gait rehabilitation are reviewed and analysed from the viewpoint of control algorithm. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Artificial Intelligence/Robotics Applications to Navy Aircraft Maintenance.

DTIC Science & Technology

1984-06-01

other automatic machinery such as presses, molding machines , and numerically-controlled machine tools, just as people do. A-36...Robotics Technologies 3 B. Relevant AI Technologies 4 1. Expert Systems 4 2. Automatic Planning 4 3. Natural Language 5 4. Machine Vision...building machines that imitate human behavior. Artificial intelligence is concerned with the functions of the brain, whereas robotics include, in

Physics-Based Robot Motion Planning in Dynamic Multi-Body Environments

DTIC Science & Technology

2010-05-10

be actuated by external influences and interactions, such as being carried or pushed. Foreign-controlled bodies are actively actuated, but by external...from the action space A. How this action is generated can strongly influence the overall behavior and performance of our planner and will be discussed in...evolving game-state and unpredictable player -input), an animator cannot manually adjust these controls in advance. The planning approaches introduced in

Semi-autonomous exploration of multi-floor buildings with a legged robot

NASA Astrophysics Data System (ADS)

Wenger, Garrett J.; Johnson, Aaron M.; Taylor, Camillo J.; Koditschek, Daniel E.

2015-05-01

This paper presents preliminary results of a semi-autonomous building exploration behavior using the hexapedal robot RHex. Stairwells are used in virtually all multi-floor buildings, and so in order for a mobile robot to effectively explore, map, clear, monitor, or patrol such buildings it must be able to ascend and descend stairwells. However most conventional mobile robots based on a wheeled platform are unable to traverse stairwells, motivating use of the more mobile legged machine. This semi-autonomous behavior uses a human driver to provide steering input to the robot, as would be the case in, e.g., a tele-operated building exploration mission. The gait selection and transitions between the walking and stair climbing gaits are entirely autonomous. This implementation uses an RGBD camera for stair acquisition, which offers several advantages over a previously documented detector based on a laser range finder, including significantly reduced acquisition time. The sensor package used here also allows for considerable expansion of this behavior. For example, complete automation of the building exploration task driven by a mapping algorithm and higher level planner is presently under development.

Social skills training for children with autism spectrum disorder using a robotic behavioral intervention system.

PubMed

Yun, Sang-Seok; Choi, JongSuk; Park, Sung-Kee; Bong, Gui-Young; Yoo, HeeJeong

2017-07-01

We designed a robot system that assisted in behavioral intervention programs of children with autism spectrum disorder (ASD). The eight-session intervention program was based on the discrete trial teaching protocol and focused on two basic social skills: eye contact and facial emotion recognition. The robotic interactions occurred in four modules: training element query, recognition of human activity, coping-mode selection, and follow-up action. Children with ASD who were between 4 and 7 years old and who had verbal IQ ≥ 60 were recruited and randomly assigned to the treatment group (TG, n = 8, 5.75 ± 0.89 years) or control group (CG, n = 7; 6.32 ± 1.23 years). The therapeutic robot facilitated the treatment intervention in the TG, and the human assistant facilitated the treatment intervention in the CG. The intervention procedures were identical in both groups. The primary outcome measures included parent-completed questionnaires, the Autism Diagnostic Observation Schedule (ADOS), and frequency of eye contact, which was measured with the partial interval recording method. After completing treatment, the eye contact percentages were significantly increased in both groups. For facial emotion recognition, the percentages of correct answers were increased in similar patterns in both groups compared to baseline (P > 0.05), with no difference between the TG and CG (P > 0.05). The subjects' ability to play, general behavioral and emotional symptoms were significantly diminished after treatment (p < 0.05). These results showed that the robot-facilitated and human-facilitated behavioral interventions had similar positive effects on eye contact and facial emotion recognition, which suggested that robots are useful mediators of social skills training for children with ASD. Autism Res 2017,. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 1306-1323. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Review on design and control aspects of ankle rehabilitation robots.

PubMed

Jamwal, Prashant K; Hussain, Shahid; Xie, Sheng Q

2015-03-01

Ankle rehabilitation robots can play an important role in improving outcomes of the rehabilitation treatment by assisting therapists and patients in number of ways. Consequently, few robot designs have been proposed by researchers which fall under either of the two categories, namely, wearable robots or platform-based robots. This paper presents a review of both kinds of ankle robots along with a brief analysis of their design, actuation and control approaches. While reviewing these designs it was observed that most of them are undesirably inspired by industrial robot designs. Taking note of the design concerns of current ankle robots, few improvements in the ankle robot designs have also been suggested. Conventional position control or force control approaches, being used in the existing ankle robots, have been reviewed. Apparently, opportunities of improvement also exist in the actuation as well as control of ankle robots. Subsequently, a discussion on most recent research in the development of novel actuators and advanced controllers based on appropriate physical and cognitive human-robot interaction has also been included in this review. Implications for Rehabilitation Ankle joint functions are restricted/impaired as a consequence of stroke or injury during sports or otherwise. Robots can help in reinstating functions faster and can also work as tool for recording rehabilitation data useful for further analysis. Evolution of ankle robots with respect to their design and control aspects has been discussed in the present paper and a novel design with futuristic control approach has been proposed.

Ratbot automatic navigation by electrical reward stimulation based on distance measurement in unknown environments.

PubMed

Gao, Liqiang; Sun, Chao; Zhang, Chen; Zheng, Nenggan; Chen, Weidong; Zheng, Xiaoxiang

2013-01-01

Traditional automatic navigation methods for bio-robots are constrained to configured environments and thus can't be applied to tasks in unknown environments. With no consideration of bio-robot's own innate living ability and treating bio-robots in the same way as mechanical robots, those methods neglect the intelligence behavior of animals. This paper proposes a novel ratbot automatic navigation method in unknown environments using only reward stimulation and distance measurement. By utilizing rat's habit of thigmotaxis and its reward-seeking behavior, this method is able to incorporate rat's intrinsic intelligence of obstacle avoidance and path searching into navigation. Experiment results show that this method works robustly and can successfully navigate the ratbot to a target in the unknown environment. This work might put a solid base for application of ratbots and also has significant implication of automatic navigation for other bio-robots as well.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thangavelautham, Jekanthan; Smith, Alexander; Abu El Samid, Nader

Automation of site preparation and resource utilization on the Moon with teams of autonomous robots holds considerable promise for establishing a lunar base. Such multirobot autonomous systems would require limited human support infrastructure, complement necessary manned operations and reduce overall mission risk. We present an Artificial Neural Tissue (ANT) architecture as a control system for autonomous multirobot excavation tasks. An ANT approach requires much less human supervision and pre-programmed human expertise than previous techniques. Only a single global fitness function and a set of allowable basis behaviors need be specified. An evolutionary (Darwinian) selection process is used to 'breed' controllersmore » for the task at hand in simulation and the fittest controllers are transferred onto hardware for further validation and testing. ANT facilitates 'machine creativity', with the emergence of novel functionality through a process of self-organized task decomposition of mission goals. ANT based controllers are shown to exhibit self-organization, employ stigmergy (communication mediated through the environment) and make use of templates (unlabeled environmental cues). With lunar in-situ resource utilization (ISRU) efforts in mind, ANT controllers have been tested on a multirobot excavation task in which teams of robots with no explicit supervision can successfully avoid obstacles, interpret excavation blueprints, perform layered digging, avoid burying or trapping other robots and clear/maintain digging routes.« less

ODYSSEUS autonomous walking robot: The leg/arm design

NASA Technical Reports Server (NTRS)

Bourbakis, N. G.; Maas, M.; Tascillo, A.; Vandewinckel, C.

1994-01-01

ODYSSEUS is an autonomous walking robot, which makes use of three wheels and three legs for its movement in the free navigation space. More specifically, it makes use of its autonomous wheels to move around in an environment where the surface is smooth and not uneven. However, in the case that there are small height obstacles, stairs, or small height unevenness in the navigation environment, the robot makes use of both wheels and legs to travel efficiently. In this paper we present the detailed hardware design and the simulated behavior of the extended leg/arm part of the robot, since it plays a very significant role in the robot actions (movements, selection of objects, etc.). In particular, the leg/arm consists of three major parts: The first part is a pipe attached to the robot base with a flexible 3-D joint. This pipe has a rotated bar as an extended part, which terminates in a 3-D flexible joint. The second part of the leg/arm is also a pipe similar to the first. The extended bar of the second part ends at a 2-D joint. The last part of the leg/arm is a clip-hand. It is used for selecting several small weight and size objects, and when it is in a 'closed' mode, it is used as a supporting part of the robot leg. The entire leg/arm part is controlled and synchronized by a microcontroller (68CH11) attached to the robot base.

Sensory Motor Coordination in Robonaut

NASA Technical Reports Server (NTRS)

Peters, Richard Alan, II

2003-01-01

As a participant of the year 2000 NASA Summer Faculty Fellowship Program, I worked with the engineers of the Dexterous Robotics Laboratory at NASA Johnson Space Center on the Robonaut project. The Robonaut is an articulated torso with two dexterous arms, left and right five-fingered hands, and a head with cameras mounted on an articulated neck. This advanced space robot, now driven only teleoperatively using VR gloves, sensors and helmets, is to be upgraded to a thinking system that can find, interact with and assist humans autonomously, allowing the Crew to work with Robonaut as a (junior) member of their team. Thus, the work performed this summer was toward the goal of enabling Robonaut to operate autonomously as an intelligent assistant to astronauts. Our underlying hypothesis is that a robot can develop intelligence if it learns a set of basic behaviors (i.e., reflexes - actions tightly coupled to sensing) and through experience learns how to sequence these to solve problems or to accomplish higher-level tasks. We describe our approach to the automatic acquisition of basic behaviors as learning sensory-motor coordination (SMC). Although research in the ontogenesis of animals development from the time of conception) supports the approach of learning SMC as the foundation for intelligent, autonomous behavior, we do not know whether it will prove viable for the development of autonomy in robots. The first step in testing the hypothesis is to determine if SMC can be learned by the robot. To do this, we have taken advantage of Robonaut's teleoperated control system. When a person teleoperates Robonaut, the person's own SMC causes the robot to act purposefully. If the sensory signals that the robot detects during teleoperation are recorded over several repetitions of the same task, it should be possible through signal analysis to identify the sensory-motor couplings that accompany purposeful motion. In this report, reasons for suspecting SMC as the basis for intelligent behavior will be reviewed. A robot control system for autonomous behavior that uses learned SMC will be proposed. Techniques for the extraction of salient parameters from sensory and motor data will be discussed. Experiments with Robonaut will be discussed and preliminary data presented.

Study on the intelligent decision making of soccer robot side-wall behavior

NASA Astrophysics Data System (ADS)

Zhang, Xiaochuan; Shao, Guifang; Tan, Zhi; Li, Zushu

2007-12-01

Side-wall is the static obstacle in soccer robot game, reasonably making use of the Side-wall can improve soccer robot competitive ability. As a kind of artificial life, the Side-wall processing strategy of soccer robot is influenced by many factors, such as game state, field region, attacking and defending situation and so on, each factor also has different influence degree, so, the Side-wall behavior selection is an intelligent selecting process. From the view point of human simulated, based on the idea of Side-wall processing priority[1], this paper builds the priority function for Side-wall processing, constructs the action predicative model for Side-wall obstacle, puts forward the Side-wall processing strategy, and forms the Side-wall behavior selection mechanism. Through the contrasting experiment between the strategy applied and none, proves that this strategy can improve the soccer robot capacity, it is feasible and effective, and has positive meaning for soccer robot stepped study.

Manifold traversing as a model for learning control of autonomous robots

NASA Technical Reports Server (NTRS)

Szakaly, Zoltan F.; Schenker, Paul S.

1992-01-01

This paper describes a recipe for the construction of control systems that support complex machines such as multi-limbed/multi-fingered robots. The robot has to execute a task under varying environmental conditions and it has to react reasonably when previously unknown conditions are encountered. Its behavior should be learned and/or trained as opposed to being programmed. The paper describes one possible method for organizing the data that the robot has learned by various means. This framework can accept useful operator input even if it does not fully specify what to do, and can combine knowledge from autonomous, operator assisted and programmed experiences.

Evolutionary robotics simulations help explain why reciprocity is rare in nature

PubMed Central

André, Jean-Baptiste; Nolfi, Stefano

2016-01-01

The relative rarity of reciprocity in nature, contrary to theoretical predictions that it should be widespread, is currently one of the major puzzles in social evolution theory. Here we use evolutionary robotics to solve this puzzle. We show that models based on game theory are misleading because they neglect the mechanics of behavior. In a series of experiments with simulated robots controlled by artificial neural networks, we find that reciprocity does not evolve, and show that this results from a general constraint that likely also prevents it from evolving in the wild. Reciprocity can evolve if it requires very few mutations, as is usually assumed in evolutionary game theoretic models, but not if, more realistically, it requires the accumulation of many adaptive mutations. PMID:27616139

A Null Space Control of Two Wheels Driven Mobile Manipulator Using Passivity Theory

NASA Astrophysics Data System (ADS)

Shibata, Tsuyoshi; Murakami, Toshiyuki

This paper describes a control strategy of null space motion of a two wheels driven mobile manipulator. Recently, robot is utilized in various industrial fields and it is preferable for the robot manipulator to have multiple degrees of freedom motion. Several studies of kinematics for null space motion have been proposed. However stability analysis of null space motion is not enough. Furthermore, these approaches apply to stable systems, but they do not apply unstable systems. Then, in this research, base of manipulator equips with two wheels driven mobile robot. This robot is called two wheels driven mobile manipulator, which becomes unstable system. In the proposed approach, a control design of null space uses passivity based stabilizing. A proposed controller is decided so that closed-loop system of robot dynamics satisfies passivity. This is passivity based control. Then, control strategy is that stabilizing of the robot system applies to work space observer based approach and null space control while keeping end-effector position. The validity of the proposed approach is verified by simulations and experiments of two wheels driven mobile manipulator.

The Clinical Use of Robots for Individuals with Autism Spectrum Disorders: A Critical Review

ERIC Educational Resources Information Center

Diehl, Joshua J.; Schmitt, Lauren M.; Villano, Michael; Crowell, Charles R.

2012-01-01

We examined peer-reviewed studies in order to understand the current status of empirically based evidence on the clinical applications of robots in the diagnosis and treatment of Autism Spectrum Disorders (ASD). Studies are organized into four broad categories: (a) the response of individuals with ASD to robots or robot-like behavior in comparison…

Physics-based approach to chemical source localization using mobile robotic swarms

NASA Astrophysics Data System (ADS)

Zarzhitsky, Dimitri

2008-07-01

Recently, distributed computation has assumed a dominant role in the fields of artificial intelligence and robotics. To improve system performance, engineers are combining multiple cooperating robots into cohesive collectives called swarms. This thesis illustrates the application of basic principles of physicomimetics, or physics-based design, to swarm robotic systems. Such principles include decentralized control, short-range sensing and low power consumption. We show how the application of these principles to robotic swarms results in highly scalable, robust, and adaptive multi-robot systems. The emergence of these valuable properties can be predicted with the help of well-developed theoretical methods. In this research effort, we have designed and constructed a distributed physicomimetics system for locating sources of airborne chemical plumes. This task, called chemical plume tracing (CPT), is receiving a great deal of attention due to persistent homeland security threats. For this thesis, we have created a novel CPT algorithm called fluxotaxis that is based on theoretical principles of fluid dynamics. Analytically, we show that fluxotaxis combines the essence, as well as the strengths, of the two most popular biologically-inspired CPT methods-- chemotaxis and anemotaxis. The chemotaxis strategy consists of navigating in the direction of the chemical density gradient within the plume, while the anemotaxis approach is based on an upwind traversal of the chemical cloud. Rigorous and extensive experimental evaluations have been performed in simulated chemical plume environments. Using a suite of performance metrics that capture the salient aspects of swarm-specific behavior, we have been able to evaluate and compare the three CPT algorithms. We demonstrate the improved performance of our fluxotaxis approach over both chemotaxis and anemotaxis in these realistic simulation environments, which include obstacles. To test our understanding of CPT on actual hardware, we have implemented chemotaxis on three laboratory-scale robots. Chemotaxis requires only chemical sensors; eventually, when small-scale anemometers capable of reliably detecting low air velocities become available, we plan to implement anemotaxis and fluxotaxis on the robots as well. Our chemotaxis robots use the physicomimetics control algorithm to arrange the team of vehicles into a triangular formation, which then traces an ethanol vapor plume to its source emitter. In agreement with our theoretical predictions, the swarm implementation shows a consistent gain in CPT performance as compared to a single-robot solution.

Real-time Cooperative Behavior for Tactical Mobile Robot Teams

DTIC Science & Technology

2001-02-01

control of multirobot missions. In particu- lar he used videogame scenarios to develop these skills, which might account for the intuition that those...to develop the following innovative research results for tacti- cal mobile robot teams: 1. A suite of new fault-tolerant reactive behaviors, 2. A...depicts the overall system architecture developed for this effort. It contains 3 major subsystems: Executive, Premission, and Runtime. The executive

The Unified Behavior Framework for the Simulation of Autonomous Agents

DTIC Science & Technology

2015-03-01

1980s, researchers have designed a variety of robot control architectures intending to imbue robots with some degree of autonomy. A recently developed ...Identification Friend or Foe viii THE UNIFIED BEHAVIOR FRAMEWORK FOR THE SIMULATION OF AUTONOMOUS AGENTS I. Introduction The development of autonomy has...room for research by utilizing methods like simulation and modeling that consume less time and fewer monetary resources. A recently developed reactive

Development of a control algorithm for the ultrasound scanning robot (NCCUSR) using ultrasound image and force feedback.

PubMed

Kim, Yeoun Jae; Seo, Jong Hyun; Kim, Hong Rae; Kim, Kwang Gi

2017-06-01

Clinicians who frequently perform ultrasound scanning procedures often suffer from musculoskeletal disorders, arthritis, and myalgias. To minimize their occurrence and to assist clinicians, ultrasound scanning robots have been developed worldwide. Although, to date, there is still no commercially available ultrasound scanning robot, many control methods have been suggested and researched. These control algorithms are either image based or force based. If the ultrasound scanning robot control algorithm was a combination of the two algorithms, it could benefit from the advantage of each one. However, there are no existing control methods for ultrasound scanning robots that combine force control and image analysis. Therefore, in this work, a control algorithm is developed for an ultrasound scanning robot using force feedback and ultrasound image analysis. A manipulator-type ultrasound scanning robot named 'NCCUSR' is developed and a control algorithm for this robot is suggested and verified. First, conventional hybrid position-force control is implemented for the robot and the hybrid position-force control algorithm is combined with ultrasound image analysis to fully control the robot. The control method is verified using a thyroid phantom. It was found that the proposed algorithm can be applied to control the ultrasound scanning robot and experimental outcomes suggest that the images acquired using the proposed control method can yield a rating score that is equivalent to images acquired directly by the clinicians. The proposed control method can be applied to control the ultrasound scanning robot. However, more work must be completed to verify the proposed control method in order to become clinically feasible. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Control strategies for robots in contact

NASA Astrophysics Data System (ADS)

Park, Jaeheung

In the field of robotics, there is a growing need to provide robots with the ability to interact with complex and unstructured environments. Operations in such environments pose significant challenges in terms of sensing, planning, and control. In particular, it is critical to design control algorithms that account for the dynamics of the robot and environment at multiple contacts. The work in this thesis focuses on the development of a control framework that addresses these issues. The approaches are based on the operational space control framework and estimation methods. By accounting for the dynamics of the robot and environment, modular and systematic methods are developed for robots interacting with the environment at multiple locations. The proposed force control approach demonstrates high performance in the presence of uncertainties. Building on this basic capability, new control algorithms have been developed for haptic teleoperation, multi-contact interaction with the environment, and whole body motion of non-fixed based robots. These control strategies have been experimentally validated through simulations and implementations on physical robots. The results demonstrate the effectiveness of the new control structure and its robustness to uncertainties. The contact control strategies presented in this thesis are expected to contribute to the needs in advanced controller design for humanoid and other complex robots interacting with their environments.

Information theory and robotics meet to study predator-prey interactions

NASA Astrophysics Data System (ADS)

Neri, Daniele; Ruberto, Tommaso; Cord-Cruz, Gabrielle; Porfiri, Maurizio

2017-07-01

Transfer entropy holds promise to advance our understanding of animal behavior, by affording the identification of causal relationships that underlie animal interactions. A critical step toward the reliable implementation of this powerful information-theoretic concept entails the design of experiments in which causal relationships could be systematically controlled. Here, we put forward a robotics-based experimental approach to test the validity of transfer entropy in the study of predator-prey interactions. We investigate the behavioral response of zebrafish to a fear-evoking robotic stimulus, designed after the morpho-physiology of the red tiger oscar and actuated along preprogrammed trajectories. From the time series of the positions of the zebrafish and the robotic stimulus, we demonstrate that transfer entropy correctly identifies the influence of the stimulus on the focal subject. Building on this evidence, we apply transfer entropy to study the interactions between zebrafish and a live red tiger oscar. The analysis of transfer entropy reveals a change in the direction of the information flow, suggesting a mutual influence between the predator and the prey, where the predator adapts its strategy as a function of the movement of the prey, which, in turn, adjusts its escape as a function of the predator motion. Through the integration of information theory and robotics, this study posits a new approach to study predator-prey interactions in freshwater fish.

[Low Fidelity Simulation of a Zero-Y Robot

NASA Technical Reports Server (NTRS)

Sweet, Adam

2001-01-01

The item to be cleared is a low-fidelity software simulation model of a hypothetical freeflying robot designed for use in zero gravity environments. This simulation model works with the HCC simulation system that was developed by Xerox PARC and NASA Ames Research Center. HCC has been previously cleared for distribution. When used with the HCC software, the model computes the location and orientation of the simulated robot over time. Failures (such as a broken motor) can be injected into the simulation to produce simulated behavior corresponding to the failure. Release of this simulation will allow researchers to test their software diagnosis systems by attempting to diagnose the simulated failure from the simulated behavior. This model does not contain any encryption software nor can it perform any control tasks that might be export controlled.

Jump stabilization and landing control by wing-spreading of a locust-inspired jumper.

PubMed

Beck, Avishai; Zaitsev, Valentin; Hanan, Uri Ben; Kosa, Gabor; Ayali, Amir; Weiss, Avi

2017-10-16

Bio-inspired robotics is a promising design strategy for mobile robots. Jumping is an energy efficient locomotion gait for traversing difficult terrain. Inspired by the jumping and flying behavior of the desert locust, we have recently developed a miniature jumping robot that can jump over 3.5 m high. However, much like the non-adult locust, it rotates while in the air and lands uncontrollably. Inspired by the winged adult locust, we have added spreading wings and a tail to the jumper. After the robot leaps, at the apex of the trajectory, the wings unfold and it glides to the ground. The advantages of this maneuver are the stabilization of the robot when airborne, the reduction of velocity at landing, the control of the landing angle and the potential to change the robot's orientation and control its flight trajectory. The new upgraded robot is capable of jumping to a still impressive height of 1.7 m eliminating airborne rotation and reducing landing velocity. Here, we analyze the dynamic and aerodynamic models of the robot, discuss the robot's design, and validate its ability to perform a jump-glide in a stable trajectory, land safely and change its orientation while in the air.

Optimal Digital Controller Design for a Servo Motor Taking Account of Intersample Behavior

NASA Astrophysics Data System (ADS)

Akiyoshi, Tatsuro; Imai, Jun; Funabiki, Shigeyuki

A continuous-time plant with discretized continuous-time controller do not yield stability if the sampling rate is lower than some certain level. Thus far, high functioning electronic control has made use of high cost hardwares which are needed to implement discretized continuous-time controllers, while low cost hardwares generally do not have high enough sampling rate. This technical note presents results comparing performance indices with and without intersample behavior, and some answer to the question how a low specification device can control a plant effectively. We consider a machine simulating wafer handling robots at semiconductor factories, which is an electromechanical system driven by a direct drive motor. We illustrate controller design for the robot with and without intersample behavior, and simulations and experimental results by using these controllers. Taking intersample behavior into account proves to be effective to make control performance better and enables it to choose relatively long sampling period. By controller design via performance index with intersample behavior, we can cope with situation where short enough sampling period may not be employed, and freedom of controller design might be widened especially on choice of sampling period.

Teaching Human Poses Interactively to a Social Robot

PubMed Central

Gonzalez-Pacheco, Victor; Malfaz, Maria; Fernandez, Fernando; Salichs, Miguel A.

2013-01-01

The main activity of social robots is to interact with people. In order to do that, the robot must be able to understand what the user is saying or doing. Typically, this capability consists of pre-programmed behaviors or is acquired through controlled learning processes, which are executed before the social interaction begins. This paper presents a software architecture that enables a robot to learn poses in a similar way as people do. That is, hearing its teacher's explanations and acquiring new knowledge in real time. The architecture leans on two main components: an RGB-D (Red-, Green-, Blue- Depth) -based visual system, which gathers the user examples, and an Automatic Speech Recognition (ASR) system, which processes the speech describing those examples. The robot is able to naturally learn the poses the teacher is showing to it by maintaining a natural interaction with the teacher. We evaluate our system with 24 users who teach the robot a predetermined set of poses. The experimental results show that, with a few training examples, the system reaches high accuracy and robustness. This method shows how to combine data from the visual and auditory systems for the acquisition of new knowledge in a natural manner. Such a natural way of training enables robots to learn from users, even if they are not experts in robotics. PMID:24048336

Teaching human poses interactively to a social robot.

PubMed

Gonzalez-Pacheco, Victor; Malfaz, Maria; Fernandez, Fernando; Salichs, Miguel A

2013-09-17

The main activity of social robots is to interact with people. In order to do that, the robot must be able to understand what the user is saying or doing. Typically, this capability consists of pre-programmed behaviors or is acquired through controlled learning processes, which are executed before the social interaction begins. This paper presents a software architecture that enables a robot to learn poses in a similar way as people do. That is, hearing its teacher's explanations and acquiring new knowledge in real time. The architecture leans on two main components: an RGB-D (Red-, Green-, Blue- Depth) -based visual system, which gathers the user examples, and an Automatic Speech Recognition (ASR) system, which processes the speech describing those examples. The robot is able to naturally learn the poses the teacher is showing to it by maintaining a natural interaction with the teacher. We evaluate our system with 24 users who teach the robot a predetermined set of poses. The experimental results show that, with a few training examples, the system reaches high accuracy and robustness. This method shows how to combine data from the visual and auditory systems for the acquisition of new knowledge in a natural manner. Such a natural way of training enables robots to learn from users, even if they are not experts in robotics.

Reversible Bending Behaviors of Photomechanical Soft Actuators Based on Graphene Nanocomposites.

PubMed

Niu, Dong; Jiang, Weitao; Liu, Hongzhong; Zhao, Tingting; Lei, Biao; Li, Yonghao; Yin, Lei; Shi, Yongsheng; Chen, Bangdao; Lu, Bingheng

2016-06-06

Photomechanical nanocomposites embedded with light-absorbing nanoparticles show promising applications in photoresponsive actuations. Near infrared (nIR)-responsive nanocomposites based photomechanical soft actuators can offer lightweight functional and underexploited entry into soft robotics, active optics, drug delivery, etc. A novel graphene-based photomechanical soft actuators, constituted by Polydimethylsiloxane (PDMS)/graphene-nanoplatelets (GNPs) layer (PDMS/GNPs) and pristine PDMS layer, have been constructed. Due to the mismatch of coefficient of thermal expansion of two layers induced by dispersion of GNPs, controllable and reversible bendings response to nIR light irradiation are observed. Interestingly, two different bending behaviors are observed when the nIR light comes from different sides, i.e., a gradual single-step photomechanical bending towards PDMS/GNPs layer when irradiation from PDMS side, while a dual-step bending (finally bending to the PDMS/GNPs side but with an strong and fast backlash at the time of light is on/off) when irradiation from PDMS/GNPs side. The two distinctive photomechanical bending behaviors are investigated in terms of heat transfer and thermal expansion, which reveals that the distinctive bending behaviors can be attributed to the differences in temperature gradients along the thickness when irradiation from different sides. In addition, the versatile photomechanical bending properties will provide alternative way for drug-delivery, soft robotics and microswitches, etc.

Reversible Bending Behaviors of Photomechanical Soft Actuators Based on Graphene Nanocomposites

PubMed Central

Niu, Dong; Jiang, Weitao; Liu, Hongzhong; Zhao, Tingting; Lei, Biao; Li, Yonghao; Yin, Lei; Shi, Yongsheng; Chen, Bangdao; Lu, Bingheng

2016-01-01

Photomechanical nanocomposites embedded with light-absorbing nanoparticles show promising applications in photoresponsive actuations. Near infrared (nIR)-responsive nanocomposites based photomechanical soft actuators can offer lightweight functional and underexploited entry into soft robotics, active optics, drug delivery, etc. A novel graphene-based photomechanical soft actuators, constituted by Polydimethylsiloxane (PDMS)/graphene-nanoplatelets (GNPs) layer (PDMS/GNPs) and pristine PDMS layer, have been constructed. Due to the mismatch of coefficient of thermal expansion of two layers induced by dispersion of GNPs, controllable and reversible bendings response to nIR light irradiation are observed. Interestingly, two different bending behaviors are observed when the nIR light comes from different sides, i.e., a gradual single-step photomechanical bending towards PDMS/GNPs layer when irradiation from PDMS side, while a dual-step bending (finally bending to the PDMS/GNPs side but with an strong and fast backlash at the time of light is on/off) when irradiation from PDMS/GNPs side. The two distinctive photomechanical bending behaviors are investigated in terms of heat transfer and thermal expansion, which reveals that the distinctive bending behaviors can be attributed to the differences in temperature gradients along the thickness when irradiation from different sides. In addition, the versatile photomechanical bending properties will provide alternative way for drug-delivery, soft robotics and microswitches, etc. PMID:27265380

E-Learning System for Learning Virtual Circuit Making with a Microcontroller and Programming to Control a Robot

ERIC Educational Resources Information Center

Takemura, Atsushi

2015-01-01

This paper proposes a novel e-Learning system for learning electronic circuit making and programming a microcontroller to control a robot. The proposed e-Learning system comprises a virtual-circuit-making function for the construction of circuits with a versatile, Arduino microcontroller and an educational system that can simulate behaviors of…

On learning navigation behaviors for small mobile robots with reservoir computing architectures.

PubMed

Antonelo, Eric Aislan; Schrauwen, Benjamin

2015-04-01

This paper proposes a general reservoir computing (RC) learning framework that can be used to learn navigation behaviors for mobile robots in simple and complex unknown partially observable environments. RC provides an efficient way to train recurrent neural networks by letting the recurrent part of the network (called reservoir) be fixed while only a linear readout output layer is trained. The proposed RC framework builds upon the notion of navigation attractor or behavior that can be embedded in the high-dimensional space of the reservoir after learning. The learning of multiple behaviors is possible because the dynamic robot behavior, consisting of a sensory-motor sequence, can be linearly discriminated in the high-dimensional nonlinear space of the dynamic reservoir. Three learning approaches for navigation behaviors are shown in this paper. The first approach learns multiple behaviors based on the examples of navigation behaviors generated by a supervisor, while the second approach learns goal-directed navigation behaviors based only on rewards. The third approach learns complex goal-directed behaviors, in a supervised way, using a hierarchical architecture whose internal predictions of contextual switches guide the sequence of basic navigation behaviors toward the goal.

Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning.

PubMed

Baykal, Cenk; Torres, Luis G; Alterovitz, Ron

2015-09-28

Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot's behavior and reachable workspace. Optimizing a robot's design by appropriately selecting tube parameters can improve the robot's effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot's configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy.

Developing Creative Behavior in Elementary School Students with Robotics

ERIC Educational Resources Information Center

Nemiro, Jill; Larriva, Cesar; Jawaharlal, Mariappan

2017-01-01

The School Robotics Initiative (SRI), a problem-based robotics program for elementary school students, was developed with the objective of reaching students early on to instill an interest in Science, Technology, Engineering, and Math disciplines. The purpose of this exploratory, observational study was to examine how the SRI fosters student…

Improving Collaborative Play Between Children with Autism Spectrum Disorders and Their Siblings: The Effectiveness of a Robot-Mediated Intervention Based on Lego® Therapy.

PubMed

Huskens, Bibi; Palmen, Annemiek; Van der Werff, Marije; Lourens, Tino; Barakova, Emilia

2015-11-01

The aim of the study was to investigate the effectiveness of a brief robot-mediated intervention based on Lego(®) therapy on improving collaborative behaviors (i.e., interaction initiations, responses, and play together) between children with ASD and their siblings during play sessions, in a therapeutic setting. A concurrent multiple baseline design across three child-sibling pairs was in effect. The robot-intervention resulted in no statistically significant changes in collaborative behaviors of the children with ASD. Despite limited effectiveness of the intervention, this study provides several practical implications and directions for future research.

Efficient Control Law Simulation for Multiple Mobile Robots

DOE Office of Scientific and Technical Information (OSTI.GOV)

Driessen, B.J.; Feddema, J.T.; Kotulski, J.D.

1998-10-06

In this paper we consider the problem of simulating simple control laws involving large numbers of mobile robots. Such simulation can be computationally prohibitive if the number of robots is large enough, say 1 million, due to the 0(N2 ) cost of each time step. This work therefore uses hierarchical tree-based methods for calculating the control law. These tree-based approaches have O(NlogN) cost per time step, thus allowing for efficient simulation involving a large number of robots. For concreteness, a decentralized control law which involves only the distance and bearing to the closest neighbor robot will be considered. The timemore » to calculate the control law for each robot at each time step is demonstrated to be O(logN).« less

Robot Deception and Squirrel Behavior: A Case Study in Bio-inspired Robotics

DTIC Science & Technology

2014-08-01

employed by doctors/ nurses among others. It is important to focus on this aspect when we consider a robot’s deceptive capabilities in human- robot ... Robot Deception and Squirrel Behavior: A Case Study in Bio-inspired Robotics Jaeeun Shim and Ronald C. Arkin Mobile Robot ...Abstract A common behavior in animals and human beings is deception. Deceptive behavior in robotics is potentially beneficial in several domains

Computer hardware and software for robotic control

NASA Technical Reports Server (NTRS)

Davis, Virgil Leon

1987-01-01

The KSC has implemented an integrated system that coordinates state-of-the-art robotic subsystems. It is a sensor based real-time robotic control system performing operations beyond the capability of an off-the-shelf robot. The integrated system provides real-time closed loop adaptive path control of position and orientation of all six axes of a large robot; enables the implementation of a highly configurable, expandable testbed for sensor system development; and makes several smart distributed control subsystems (robot arm controller, process controller, graphics display, and vision tracking) appear as intelligent peripherals to a supervisory computer coordinating the overall systems.

Neuromodelling based on evolutionary robotics: on the importance of motor control for spatial attention.

PubMed

Gigliotta, Onofrio; Bartolomeo, Paolo; Miglino, Orazio

2015-09-01

Mainstream approaches to modelling cognitive processes have typically focused on (1) reproducing their neural underpinning, without regard to sensory-motor systems and (2) producing a single, ideal computational model. Evolutionary robotics is an alternative possibility to bridge the gap between neural substrate and behavior by means of a sensory-motor apparatus, and a powerful tool to build a population of individuals rather than a single model. We trained 4 populations of neurorobots, equipped with a pan/tilt/zoom camera, and provided with different types of motor control in order to perform a cancellation task, often used to tap spatial cognition. Neurorobots' eye movements were controlled by (a) position, (b) velocity, (c) simulated muscles and (d) simulated muscles with fixed level of zoom. Neurorobots provided with muscle and velocity control showed better performances than those controlled in position. This is an interesting result since muscle control can be considered a particular type of position control. Finally, neurorobots provided with muscle control and zoom outperformed those without zooming ability.

An EMG Interface for the Control of Motion and Compliance of a Supernumerary Robotic Finger

PubMed Central

Hussain, Irfan; Spagnoletti, Giovanni; Salvietti, Gionata; Prattichizzo, Domenico

2016-01-01

In this paper, we propose a novel electromyographic (EMG) control interface to control motion and joints compliance of a supernumerary robotic finger. The supernumerary robotic fingers are a recently introduced class of wearable robotics that provides users additional robotic limbs in order to compensate or augment the existing abilities of natural limbs without substituting them. Since supernumerary robotic fingers are supposed to closely interact and perform actions in synergy with the human limbs, the control principles of extra finger should have similar behavior as human’s ones including the ability of regulating the compliance. So that, it is important to propose a control interface and to consider the actuators and sensing capabilities of the robotic extra finger compatible to implement stiffness regulation control techniques. We propose EMG interface and a control approach to regulate the compliance of the device through servo actuators. In particular, we use a commercial EMG armband for gesture recognition to be associated with the motion control of the robotic device and surface one channel EMG electrodes interface to regulate the compliance of the robotic device. We also present an updated version of a robotic extra finger where the adduction/abduction motion is realized through ball bearing and spur gears mechanism. We have validated the proposed interface with two sets of experiments related to compensation and augmentation. In the first set of experiments, different bimanual tasks have been performed with the help of the robotic device and simulating a paretic hand since this novel wearable system can be used to compensate the missing grasping abilities in chronic stroke patients. In the second set, the robotic extra finger is used to enlarge the workspace and manipulation capability of healthy hands. In both sets, the same EMG control interface has been used. The obtained results demonstrate that the proposed control interface is intuitive and can successfully be used, not only to control the motion of a supernumerary robotic finger but also to regulate its compliance. The proposed approach can be exploited also for the control of different wearable devices that has to actively cooperate with the human limbs. PMID:27891088

Analysis of Decentralized Variable Structure Control for Collective Search by Mobile Robots

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feddema, J.; Goldsmith, S.; Robinett, R.

1998-11-04

This paper presents an analysis of a decentralized coordination strategy for organizing and controlling a team of mobile robots performing collective search. The alpha-beta coordination strategy is a family of collective search algorithms that allow teams of communicating robots to implicitly coordinate their search activities through a division of labor based on self-selected roIes. In an alpha-beta team. alpha agents are motivated to improve their status by exploring new regions of the search space. Beta a~ents are conservative, and reiy on the alpha agents to provide advanced information on favorable regions of the search space. An agent selects its currentmore » role dynamically based on its current status value relative to the current status values of the other team members. Status is determined by some function of the agent's sensor readings, and is generally a measurement of source intensity at the agent's current location. Variations on the decision rules determining alpha and beta behavior produce different versions of the algorithm that lead to different global properties. The alpha-beta strategy is based on a simple finite-state machine that implements a form of Variable Structure Control (VSC). The VSC system changes the dynamics of the collective system by abruptly switching at defined states to alternative control laws . In VSC, Lyapunov's direct method is often used to design control surfaces which guide the system to a given goal. We introduce the alpha-beta aIgorithm and present an analysis of the equilibrium point and the global stability of the alpha-beta algorithm based on Lyapunov's method.« less

Analysis of decentralized variable structure control for collective search by mobile robots

NASA Astrophysics Data System (ADS)

Goldsmith, Steven Y.; Feddema, John T.; Robinett, Rush D., III

1998-10-01

This paper presents an analysis of a decentralized coordination strategy for organizing and controlling a team of mobile robots performing collective search. The alpha- beta coordination strategy is a family of collective search algorithms that allow teams of communicating robots to implicitly coordinate their search activities through a division of labor based on self-selected roles. In an alpha- beta team, alpha agents are motivated to improve their status by exploring new regions of the search space. Beta agents are conservative, and rely on the alpha agents to provide advanced information on favorable regions of the search space. An agent selects its current role dynamically based on its current status value relative to the current status values of the other team members. Status is determined by some function of the agent's sensor readings, and is generally a measurement of source intensity at the agent's current location. Variations on the decision rules determining alpha and beta behavior produce different versions of the algorithm that lead to different global properties. The alpha-beta strategy is based on a simple finite-state machine that implements a form of Variable Structure Control (VSC). The VSC system changes the dynamics of the collective system by abruptly switching at defined states to alternative control laws. In VSC, Lyapunov's direct method is often used to design control surfaces which guide the system to a given goal. We introduce the alpha- beta algorithm and present an analysis of the equilibrium point and the global stability of the alpha-beta algorithm based on Lyapunov's method.

Event-Based Control Strategy for Mobile Robots in Wireless Environments.

PubMed

Socas, Rafael; Dormido, Sebastián; Dormido, Raquel; Fabregas, Ernesto

2015-12-02

In this paper, a new event-based control strategy for mobile robots is presented. It has been designed to work in wireless environments where a centralized controller has to interchange information with the robots over an RF (radio frequency) interface. The event-based architectures have been developed for differential wheeled robots, although they can be applied to other kinds of robots in a simple way. The solution has been checked over classical navigation algorithms, like wall following and obstacle avoidance, using scenarios with a unique or multiple robots. A comparison between the proposed architectures and the classical discrete-time strategy is also carried out. The experimental results shows that the proposed solution has a higher efficiency in communication resource usage than the classical discrete-time strategy with the same accuracy.

Event-Based Control Strategy for Mobile Robots in Wireless Environments

PubMed Central

Socas, Rafael; Dormido, Sebastián; Dormido, Raquel; Fabregas, Ernesto

2015-01-01

In this paper, a new event-based control strategy for mobile robots is presented. It has been designed to work in wireless environments where a centralized controller has to interchange information with the robots over an RF (radio frequency) interface. The event-based architectures have been developed for differential wheeled robots, although they can be applied to other kinds of robots in a simple way. The solution has been checked over classical navigation algorithms, like wall following and obstacle avoidance, using scenarios with a unique or multiple robots. A comparison between the proposed architectures and the classical discrete-time strategy is also carried out. The experimental results shows that the proposed solution has a higher efficiency in communication resource usage than the classical discrete-time strategy with the same accuracy. PMID:26633412

Controlling Tensegrity Robots through Evolution using Friction based Actuation

NASA Technical Reports Server (NTRS)

Kothapalli, Tejasvi; Agogino, Adrian K.

2017-01-01

Traditional robotic structures have limitations in planetary exploration as their rigid structural joints are prone to damage in new and rough terrains. In contrast, robots based on tensegrity structures, composed of rods and tensile cables, offer a highly robust, lightweight, and energy efficient solution over traditional robots. In addition tensegrity robots can be highly configurable by rearranging their topology of rods, cables and motors. However, these highly configurable tensegrity robots pose a significant challenge for locomotion due to their complexity. This study investigates a control pattern for successful locomotion in tensegrity robots through an evolutionary algorithm. A twelve-rod hardware model is rapidly prototyped to utilize a new actuation method based on friction. A web-based physics simulation is created to model the twelve-rod tensegrity ball structure. Square-waves are used as control policies for the actuators of the tensegrity structure. Monte Carlo trials are run to find the most successful number of amplitudes for the square-wave control policy. From the results, an evolutionary algorithm is implemented to find the most optimized solution for locomotion of the twelve-rod tensegrity structure. The software pattern coupled with the new friction based actuation method can serve as the basis for highly efficient tensegrity robots in space exploration.

Cooperative intelligent robotics in space III; Proceedings of the Meeting, Boston, MA, Nov. 16-18, 1992

NASA Technical Reports Server (NTRS)

Erickson, Jon D. (Editor)

1992-01-01

The present volume on cooperative intelligent robotics in space discusses sensing and perception, Space Station Freedom robotics, cooperative human/intelligent robot teams, and intelligent space robotics. Attention is given to space robotics reasoning and control, ground-based space applications, intelligent space robotics architectures, free-flying orbital space robotics, and cooperative intelligent robotics in space exploration. Topics addressed include proportional proximity sensing for telerobots using coherent lasar radar, ground operation of the mobile servicing system on Space Station Freedom, teleprogramming a cooperative space robotic workcell for space stations, and knowledge-based task planning for the special-purpose dextrous manipulator. Also discussed are dimensions of complexity in learning from interactive instruction, an overview of the dynamic predictive architecture for robotic assistants, recent developments at the Goddard engineering testbed, and parallel fault-tolerant robot control.

Use of Robotic Pets in Providing Stimulation for Nursing Home Residents with Dementia.

PubMed

Naganuma, M; Ohkubo, E; Kato, N

2015-01-01

Trial experiments utilized robotic pets to facilitate self-reliance in nursing home residents. A remote-control robot modeled clear and meaningful behaviors to elderly residents. Special attention was paid to its effects on mental and social domains. Employing the robot as a gaze target and center of attention created a cue to initiate a communication channel between residents who normally show no interest in each other. The Sony AIBO robot in this study uses commercially available wireless equipment, and all its components are easily accessible to any medical or welfare institution interested in additional practice of these activities.

SVR versus neural-fuzzy network controllers for the sagittal balance of a biped robot.

PubMed

Ferreira, João P; Crisóstomo, Manuel M; Coimbra, A Paulo

2009-12-01

The real-time balance control of an eight-link biped robot using a zero moment point (ZMP) dynamic model is difficult due to the processing time of the corresponding equations. To overcome this limitation, two alternative intelligent computing control techniques were compared: one based on support vector regression (SVR) and another based on a first-order Takagi-Sugeno-Kang (TSK)-type neural-fuzzy (NF) network. Both methods use the ZMP error and its variation as inputs and the output is the correction of the robot's torso necessary for its sagittal balance. The SVR and the NF were trained based on simulation data and their performance was verified with a real biped robot. Two performance indexes are proposed to evaluate and compare the online performance of the two control methods. The ZMP is calculated by reading four force sensors placed under each robot's foot. The gait implemented in this biped is similar to a human gait that was acquired and adapted to the robot's size. Some experiments are presented and the results show that the implemented gait combined either with the SVR controller or with the TSK NF network controller can be used to control this biped robot. The SVR and the NF controllers exhibit similar stability, but the SVR controller runs about 50 times faster.

Locomotion training of legged robots using hybrid machine learning techniques

NASA Technical Reports Server (NTRS)

Simon, William E.; Doerschuk, Peggy I.; Zhang, Wen-Ran; Li, Andrew L.

1995-01-01

In this study artificial neural networks and fuzzy logic are used to control the jumping behavior of a three-link uniped robot. The biped locomotion control problem is an increment of the uniped locomotion control. Study of legged locomotion dynamics indicates that a hierarchical controller is required to control the behavior of a legged robot. A structured control strategy is suggested which includes navigator, motion planner, biped coordinator and uniped controllers. A three-link uniped robot simulation is developed to be used as the plant. Neurocontrollers were trained both online and offline. In the case of on-line training, a reinforcement learning technique was used to train the neurocontroller to make the robot jump to a specified height. After several hundred iterations of training, the plant output achieved an accuracy of 7.4%. However, when jump distance and body angular momentum were also included in the control objectives, training time became impractically long. In the case of off-line training, a three-layered backpropagation (BP) network was first used with three inputs, three outputs and 15 to 40 hidden nodes. Pre-generated data were presented to the network with a learning rate as low as 0.003 in order to reach convergence. The low learning rate required for convergence resulted in a very slow training process which took weeks to learn 460 examples. After training, performance of the neurocontroller was rather poor. Consequently, the BP network was replaced by a Cerebeller Model Articulation Controller (CMAC) network. Subsequent experiments described in this document show that the CMAC network is more suitable to the solution of uniped locomotion control problems in terms of both learning efficiency and performance. A new approach is introduced in this report, viz., a self-organizing multiagent cerebeller model for fuzzy-neural control of uniped locomotion is suggested to improve training efficiency. This is currently being evaluated for a possible patent by NASA, Johnson Space Center. An alternative modular approach is also developed which uses separate controllers for each stage of the running stride. A self-organizing fuzzy-neural controller controls the height, distance and angular momentum of the stride. A CMAC-based controller controls the movement of the leg from the time the foot leaves the ground to the time of landing. Because the leg joints are controlled at each time step during flight, movement is smooth and obstacles can be avoided. Initial results indicate that this approach can yield fast, accurate results.

Fish and robot dancing together: bluefin killifish females respond differently to the courtship of a robot with varying color morphs.

PubMed

Phamduy, P; Polverino, G; Fuller, R C; Porfiri, M

2014-09-01

The experimental integration of bioinspired robots in groups of social animals has become a valuable tool to understand the basis of social behavior and uncover the fundamental determinants of animal communication. In this study, we measured the preference of fertile female bluefin killifish (Lucania goodei) for robotic replicas whose aspect ratio, body size, motion pattern, and color morph were inspired by adult male killifish. The motion of the fish replica was controlled via a robotic platform, which simulated the typical courtship behavior observed in killifish males. The positional preferences of females were measured for three different color morphs (red, yellow, and blue). While variation in preference was high among females, females tend to spend more time in the vicinity of the yellow painted robot replicas. This preference may have emerged because the yellow robot replicas were very bright, particularly in the longer wavelengths (550–700 nm) compared to the red and blue replicas. These findings are in agreement with previous observations in mosquitofish and zebrafish on fish preference for artificially enhanced yellow pigmentation.

Experiments in advanced control concepts for space robotics - An overview of the Stanford Aerospace Robotics Laboratory

NASA Technical Reports Server (NTRS)

Hollars, M. G.; Cannon, R. H., Jr.; Alexander, H. L.; Morse, D. F.

1987-01-01

The Stanford University Aerospace Robotics Laboratory is actively developing and experimentally testing advanced robot control strategies for space robotic applications. Early experiments focused on control of very lightweight one-link manipulators and other flexible structures. The results are being extended to position and force control of mini-manipulators attached to flexible manipulators and multilink manipulators with flexible drive trains. Experimental results show that end-point sensing and careful dynamic modeling or adaptive control are key to the success of these control strategies. Free-flying space robot simulators that operate on an air cushion table have been built to test control strategies in which the dynamics of the base of the robot and the payload are important.

Robot vibration control using inertial damping forces

NASA Technical Reports Server (NTRS)

Lee, Soo Han; Book, Wayne J.

1991-01-01

This paper concerns the suppression of the vibration of a large flexible robot by inertial forces of a small robot which is located at the tip of the large robot. A controller for generating damping forces to a large robot is designed based on the two time scale model. The controller does not need to calculate the quasi-steady variables and is efficient in computation. Simulation results show the effectiveness of the inertial forces and the controller designed.

Robot vibration control using inertial damping forces

NASA Technical Reports Server (NTRS)

Lee, Soo Han; Book, Wayne J.

1989-01-01

The suppression is examined of the vibration of a large flexible robot by inertial forces of a small robot which is located at the tip of the large robot. A controller for generating damping forces to a large robot is designed based on the two time scale mode. The controller does not need to calculate the quasi-steady state variables and is efficient in computation. Simulation results show the effectiveness of the inertial forces and the controller designed.

Modeling and controlling a robotic convoy using guidance laws strategies.

PubMed

Belkhouche, Fethi; Belkhouche, Boumediene

2005-08-01

This paper deals with the problem of modeling and controlling a robotic convoy. Guidance laws techniques are used to provide a mathematical formulation of the problem. The guidance laws used for this purpose are the velocity pursuit, the deviated pursuit, and the proportional navigation. The velocity pursuit equations model the robot's path under various sensors based control laws. A systematic study of the tracking problem based on this technique is undertaken. These guidance laws are applied to derive decentralized control laws for the angular and linear velocities. For the angular velocity, the control law is directly derived from the guidance laws after considering the relative kinematics equations between successive robots. The second control law maintains the distance between successive robots constant by controlling the linear velocity. This control law is derived by considering the kinematics equations between successive robots under the considered guidance law. Properties of the method are discussed and proven. Simulation results confirm the validity of our approach, as well as the validity of the properties of the method. Index Terms-Guidance laws, relative kinematics equations, robotic convoy, tracking.

A Control Framework for Anthropomorphic Biped Walking Based on Stabilizing Feedforward Trajectories.

PubMed

Rezazadeh, Siavash; Gregg, Robert D

2016-10-01

Although dynamic walking methods have had notable successes in control of bipedal robots in the recent years, still most of the humanoid robots rely on quasi-static Zero Moment Point controllers. This work is an attempt to design a highly stable controller for dynamic walking of a human-like model which can be used both for control of humanoid robots and prosthetic legs. The method is based on using time-based trajectories that can induce a highly stable limit cycle to the bipedal robot. The time-based nature of the controller motivates its use to entrain a model of an amputee walking, which can potentially lead to a better coordination of the interaction between the prosthesis and the human. The simulations demonstrate the stability of the controller and its robustness against external perturbations.

Identification of two-phase flow regime based on electrical capacitance tomography and soft-sensing technique

NASA Astrophysics Data System (ADS)

Zhao, Ming-fu; Hu, Xin-Yu; Shao, Yun; Luo, Bin-bin; Wang, Xin

2008-10-01

This article analyses nowadays in common use of football robots in China, intended to improve the football robots' hardware platform system's capability, and designed a football robot which based on DSP core controller, and combined Fuzzy-PID control algorithm. The experiment showed, because of the advantages of DSP, such as quickly operation, various of interfaces, low power dissipation etc. It has great improvement on the football robot's performance of movement, controlling precision, real-time performance.

A fault-tolerant intelligent robotic control system

NASA Technical Reports Server (NTRS)

Marzwell, Neville I.; Tso, Kam Sing

1993-01-01

This paper describes the concept, design, and features of a fault-tolerant intelligent robotic control system being developed for space and commercial applications that require high dependability. The comprehensive strategy integrates system level hardware/software fault tolerance with task level handling of uncertainties and unexpected events for robotic control. The underlying architecture for system level fault tolerance is the distributed recovery block which protects against application software, system software, hardware, and network failures. Task level fault tolerance provisions are implemented in a knowledge-based system which utilizes advanced automation techniques such as rule-based and model-based reasoning to monitor, diagnose, and recover from unexpected events. The two level design provides tolerance of two or more faults occurring serially at any level of command, control, sensing, or actuation. The potential benefits of such a fault tolerant robotic control system include: (1) a minimized potential for damage to humans, the work site, and the robot itself; (2) continuous operation with a minimum of uncommanded motion in the presence of failures; and (3) more reliable autonomous operation providing increased efficiency in the execution of robotic tasks and decreased demand on human operators for controlling and monitoring the robotic servicing routines.

A Unified Approach to Motion Control of Motion Robots

NASA Technical Reports Server (NTRS)

Seraji, H.

1994-01-01

This paper presents a simple on-line approach for motion control of mobile robots made up of a manipulator arm mounted on a mobile base. The proposed approach is equally applicable to nonholonomic mobile robots, such as rover-mounted manipulators and to holonomic mobile robots such as tracked robots or compound manipulators. The computational efficiency of the proposed control scheme makes it particularly suitable for real-time implementation.

Differential-Drive Mobile Robot Control Design based-on Linear Feedback Control Law

NASA Astrophysics Data System (ADS)

Nurmaini, Siti; Dewi, Kemala; Tutuko, Bambang

2017-04-01

This paper deals with the problem of how to control differential driven mobile robot with simple control law. When mobile robot moves from one position to another to achieve a position destination, it always produce some errors. Therefore, a mobile robot requires a certain control law to drive the robot’s movement to the position destination with a smallest possible error. In this paper, in order to reduce position error, a linear feedback control is proposed with pole placement approach to regulate the polynoms desired. The presented work leads to an improved understanding of differential-drive mobile robot (DDMR)-based kinematics equation, which will assist to design of suitable controllers for DDMR movement. The result show by using the linier feedback control method with pole placement approach the position error is reduced and fast convergence is achieved.

Control of a 2 DoF robot using a brain-machine interface.

PubMed

Hortal, Enrique; Ubeda, Andrés; Iáñez, Eduardo; Azorín, José M

2014-09-01

In this paper, a non-invasive spontaneous Brain-Machine Interface (BMI) is used to control the movement of a planar robot. To that end, two mental tasks are used to manage the visual interface that controls the robot. The robot used is a PupArm, a force-controlled planar robot designed by the nBio research group at the Miguel Hernández University of Elche (Spain). Two control strategies are compared: hierarchical and directional control. The experimental test (performed by four users) consists of reaching four targets. The errors and time used during the performance of the tests are compared in both control strategies (hierarchical and directional control). The advantages and disadvantages of each method are shown after the analysis of the results. The hierarchical control allows an accurate approaching to the goals but it is slower than using the directional control which, on the contrary, is less precise. The results show both strategies are useful to control this planar robot. In the future, by adding an extra device like a gripper, this BMI could be used in assistive applications such as grasping daily objects in a realistic environment. In order to compare the behavior of the system taking into account the opinion of the users, a NASA Tasks Load Index (TLX) questionnaire is filled out after two sessions are completed. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Combating Terrorism Technical Support Office. 2008 Review

DTIC Science & Technology

2009-01-15

threat object displayed at the operator control unit of the robotic platform. Remote Utility Conversion Kit The Remote Utility Conversion Kit (RUCK) is a...three- dimensional and isometric simulations and games. Develop crowd models, adversarial behavior models, network-based simulations, mini-simulations...Craft-Littoral The modular unmanned surface craft-littoral ( MUSCL ) is a spin- off of EOD/LIC’s Unmanned Reconnaissance Observation Craft, developed

A self-paced motor imagery based brain-computer interface for robotic wheelchair control.

PubMed

Tsui, Chun Sing Louis; Gan, John Q; Hu, Huosheng

2011-10-01

This paper presents a simple self-paced motor imagery based brain-computer interface (BCI) to control a robotic wheelchair. An innovative control protocol is proposed to enable a 2-class self-paced BCI for wheelchair control, in which the user makes path planning and fully controls the wheelchair except for the automatic obstacle avoidance based on a laser range finder when necessary. In order for the users to train their motor imagery control online safely and easily, simulated robot navigation in a specially designed environment was developed. This allowed the users to practice motor imagery control with the core self-paced BCI system in a simulated scenario before controlling the wheelchair. The self-paced BCI can then be applied to control a real robotic wheelchair using a protocol similar to that controlling the simulated robot. Our emphasis is on allowing more potential users to use the BCI controlled wheelchair with minimal training; a simple 2-class self paced system is adequate with the novel control protocol, resulting in a better transition from offline training to online control. Experimental results have demonstrated the usefulness of the online practice under the simulated scenario, and the effectiveness of the proposed self-paced BCI for robotic wheelchair control.

Cloud-based robot remote control system for smart factory

NASA Astrophysics Data System (ADS)

Wu, Zhiming; Li, Lianzhong; Xu, Yang; Zhai, Jingmei

2015-12-01

With the development of internet technologies and the wide application of robots, there is a prospect (trend/tendency) of integration between network and robots. A cloud-based robot remote control system over networks for smart factory is proposed, which enables remote users to control robots and then realize intelligent production. To achieve it, a three-layer system architecture is designed including user layer, service layer and physical layer. Remote control applications running on the cloud server is developed on Microsoft Azure. Moreover, DIV+ CSS technologies are used to design human-machine interface to lower maintenance cost and improve development efficiency. Finally, an experiment is implemented to verify the feasibility of the program.

System design of a hand-held mobile robot for craniotomy.

PubMed

Kane, Gavin; Eggers, Georg; Boesecke, Robert; Raczkowsky, Jörg; Wörn, Heinz; Marmulla, Rüdiger; Mühling, Joachim

2009-01-01

This contribution reports the development and initial testing of a Mobile Robot System for Surgical Craniotomy, the Craniostar. A kinematic system based on a unicycle robot is analysed to provide local positioning through two spiked wheels gripping directly onto a patients skull. A control system based on a shared control system between both the Surgeon and Robot is employed in a hand-held design that is tested initially on plastic phantom and swine skulls. Results indicate that the system has substantially lower risk than present robotically assisted craniotomies, and despite being a hand-held mobile robot, the Craniostar is still capable of sub-millimetre accuracy in tracking along a trajectory and thus achieving an accurate transfer of pre-surgical plan to the operating room procedure, without the large impact of current medical robots based on modified industrial robots.

Formation control of robotic swarm using bounded artificial forces.

PubMed

Qin, Long; Zha, Yabing; Yin, Quanjun; Peng, Yong

2013-01-01

Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions.

Formation Control of Robotic Swarm Using Bounded Artificial Forces

PubMed Central

Zha, Yabing; Peng, Yong

2013-01-01

Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions. PMID:24453809

Generating Spatiotemporal Joint Torque Patterns from Dynamical Synchronization of Distributed Pattern Generators

PubMed Central

Pitti, Alexandre; Lungarella, Max; Kuniyoshi, Yasuo

2009-01-01

Pattern generators found in the spinal cord are no more seen as simple rhythmic oscillators for motion control. Indeed, they achieve flexible and dynamical coordination in interaction with the body and the environment dynamics giving to rise motor synergies. Discovering the mechanisms underlying the control of motor synergies constitutes an important research question not only for neuroscience but also for robotics: the motors coordination of high dimensional robotic systems is still a drawback and new control methods based on biological solutions may reduce their overall complexity. We propose to model the flexible combination of motor synergies in embodied systems via partial phase synchronization of distributed chaotic systems; for specific coupling strength, chaotic systems are able to phase synchronize their dynamics to the resonant frequencies of one external force. We take advantage of this property to explore and exploit the intrinsic dynamics of one specified embodied system. In two experiments with bipedal walkers, we show how motor synergies emerge when the controllers phase synchronize to the body's dynamics, entraining it to its intrinsic behavioral patterns. This stage is characterized by directed information flow from the sensors to the motors exhibiting the optimal situation when the body dynamics drive the controllers (mutual entrainment). Based on our results, we discuss the relevance of our findings for modeling the modular control of distributed pattern generators exhibited in the spinal cord, and for exploring the motor synergies in robots. PMID:20011216

An egocentric vision based assistive co-robot.

PubMed

Zhang, Jingzhe; Zhuang, Lishuo; Wang, Yang; Zhou, Yameng; Meng, Yan; Hua, Gang

2013-06-01

We present the prototype of an egocentric vision based assistive co-robot system. In this co-robot system, the user is wearing a pair of glasses with a forward looking camera, and is actively engaged in the control loop of the robot in navigational tasks. The egocentric vision glasses serve for two purposes. First, it serves as a source of visual input to request the robot to find a certain object in the environment. Second, the motion patterns computed from the egocentric video associated with a specific set of head movements are exploited to guide the robot to find the object. These are especially helpful for quadriplegic individuals who do not have needed hand functionality for interaction and control with other modalities (e.g., joystick). In our co-robot system, when the robot does not fulfill the object finding task in a pre-specified time window, it would actively solicit user controls for guidance. Then the users can use the egocentric vision based gesture interface to orient the robot towards the direction of the object. After that the robot will automatically navigate towards the object until it finds it. Our experiments validated the efficacy of the closed-loop design to engage the human in the loop.

A neuro-inspired spike-based PID motor controller for multi-motor robots with low cost FPGAs.

PubMed

Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control.

A Neuro-Inspired Spike-Based PID Motor Controller for Multi-Motor Robots with Low Cost FPGAs

PubMed Central

Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J.; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control. PMID:22666004

Affective and Engagement Issues in the Conception and Assessment of a Robot-Assisted Psychomotor Therapy for Persons with Dementia

PubMed Central

Rouaix, Natacha; Retru-Chavastel, Laure; Rigaud, Anne-Sophie; Monnet, Clotilde; Lenoir, Hermine; Pino, Maribel

2017-01-01

The interest in robot-assisted therapies (RAT) for dementia care has grown steadily in recent years. However, RAT using humanoid robots is still a novel practice for which the adhesion mechanisms, indications and benefits remain unclear. Also, little is known about how the robot's behavioral and affective style might promote engagement of persons with dementia (PwD) in RAT. The present study sought to investigate the use of a humanoid robot in a psychomotor therapy for PwD. We examined the robot's potential to engage participants in the intervention and its effect on their emotional state. A brief psychomotor therapy program involving the robot as the therapist's assistant was created. For this purpose, a corpus of social and physical behaviors for the robot and a “control software” for customizing the program and operating the robot were also designed. Particular attention was given to components of the RAT that could promote participant's engagement (robot's interaction style, personalization of contents). In the pilot assessment of the intervention nine PwD (7 women and 2 men, M age = 86 y/o) hospitalized in a geriatrics unit participated in four individual therapy sessions: one classic therapy (CT) session (patient- therapist) and three RAT sessions (patient-therapist-robot). Outcome criteria for the evaluation of the intervention included: participant's engagement, emotional state and well-being; satisfaction of the intervention, appreciation of the robot, and empathy-related behaviors in human-robot interaction (HRI). Results showed a high constructive engagement in both CT and RAT sessions. More positive emotional responses in participants were observed in RAT compared to CT. RAT sessions were better appreciated than CT sessions. The use of a social robot as a mediating tool appeared to promote the involvement of PwD in the therapeutic intervention increasing their immediate wellbeing and satisfaction. PMID:28713296

Affective and Engagement Issues in the Conception and Assessment of a Robot-Assisted Psychomotor Therapy for Persons with Dementia.

PubMed

Rouaix, Natacha; Retru-Chavastel, Laure; Rigaud, Anne-Sophie; Monnet, Clotilde; Lenoir, Hermine; Pino, Maribel

2017-01-01

The interest in robot-assisted therapies (RAT) for dementia care has grown steadily in recent years. However, RAT using humanoid robots is still a novel practice for which the adhesion mechanisms, indications and benefits remain unclear. Also, little is known about how the robot's behavioral and affective style might promote engagement of persons with dementia (PwD) in RAT. The present study sought to investigate the use of a humanoid robot in a psychomotor therapy for PwD. We examined the robot's potential to engage participants in the intervention and its effect on their emotional state. A brief psychomotor therapy program involving the robot as the therapist's assistant was created. For this purpose, a corpus of social and physical behaviors for the robot and a "control software" for customizing the program and operating the robot were also designed. Particular attention was given to components of the RAT that could promote participant's engagement (robot's interaction style, personalization of contents). In the pilot assessment of the intervention nine PwD (7 women and 2 men, M age = 86 y/o) hospitalized in a geriatrics unit participated in four individual therapy sessions: one classic therapy (CT) session (patient- therapist) and three RAT sessions (patient-therapist-robot). Outcome criteria for the evaluation of the intervention included: participant's engagement, emotional state and well-being; satisfaction of the intervention, appreciation of the robot, and empathy-related behaviors in human-robot interaction (HRI). Results showed a high constructive engagement in both CT and RAT sessions. More positive emotional responses in participants were observed in RAT compared to CT. RAT sessions were better appreciated than CT sessions. The use of a social robot as a mediating tool appeared to promote the involvement of PwD in the therapeutic intervention increasing their immediate wellbeing and satisfaction.

Online absolute pose compensation and steering control of industrial robot based on six degrees of freedom laser measurement

NASA Astrophysics Data System (ADS)

Yang, Juqing; Wang, Dayong; Fan, Baixing; Dong, Dengfeng; Zhou, Weihu

2017-03-01

In-situ intelligent manufacturing for large-volume equipment requires industrial robots with absolute high-accuracy positioning and orientation steering control. Conventional robots mainly employ an offline calibration technology to identify and compensate key robotic parameters. However, the dynamic and static parameters of a robot change nonlinearly. It is not possible to acquire a robot's actual parameters and control the absolute pose of the robot with a high accuracy within a large workspace by offline calibration in real-time. This study proposes a real-time online absolute pose steering control method for an industrial robot based on six degrees of freedom laser tracking measurement, which adopts comprehensive compensation and correction of differential movement variables. First, the pose steering control system and robot kinematics error model are constructed, and then the pose error compensation mechanism and algorithm are introduced in detail. By accurately achieving the position and orientation of the robot end-tool, mapping the computed Jacobian matrix of the joint variable and correcting the joint variable, the real-time online absolute pose compensation for an industrial robot is accurately implemented in simulations and experimental tests. The average positioning error is 0.048 mm and orientation accuracy is better than 0.01 deg. The results demonstrate that the proposed method is feasible, and the online absolute accuracy of a robot is sufficiently enhanced.

Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training

PubMed Central

2010-01-01

Background Manual body weight supported treadmill training and robot-aided treadmill training are frequently used techniques for the gait rehabilitation of individuals after stroke and spinal cord injury. Current evidence suggests that robot-aided gait training may be improved by making robotic behavior more patient-cooperative. In this study, we have investigated the immediate effects of patient-cooperative versus non-cooperative robot-aided gait training on individuals with incomplete spinal cord injury (iSCI). Methods Eleven patients with iSCI participated in a single training session with the gait rehabilitation robot Lokomat. The patients were exposed to four different training modes in random order: During both non-cooperative position control and compliant impedance control, fixed timing of movements was provided. During two variants of the patient-cooperative path control approach, free timing of movements was enabled and the robot provided only spatial guidance. The two variants of the path control approach differed in the amount of additional support, which was either individually adjusted or exaggerated. Joint angles and torques of the robot as well as muscle activity and heart rate of the patients were recorded. Kinematic variability, interaction torques, heart rate and muscle activity were compared between the different conditions. Results Patients showed more spatial and temporal kinematic variability, reduced interaction torques, a higher increase of heart rate and more muscle activity in the patient-cooperative path control mode with individually adjusted support than in the non-cooperative position control mode. In the compliant impedance control mode, spatial kinematic variability was increased and interaction torques were reduced, but temporal kinematic variability, heart rate and muscle activity were not significantly higher than in the position control mode. Conclusions Patient-cooperative robot-aided gait training with free timing of movements made individuals with iSCI participate more actively and with larger kinematic variability than non-cooperative, position-controlled robot-aided gait training. PMID:20828422

Research on robot mobile obstacle avoidance control based on visual information

NASA Astrophysics Data System (ADS)

Jin, Jiang

2018-03-01

Robots to detect obstacles and control robots to avoid obstacles has been a key research topic of robot control. In this paper, a scheme of visual information acquisition is proposed. By judging visual information, the visual information is transformed into the information source of path processing. In accordance with the established route, in the process of encountering obstacles, the algorithm real-time adjustment trajectory to meet the purpose of intelligent control of mobile robots. Simulation results show that, through the integration of visual sensing information, the obstacle information is fully obtained, while the real-time and accuracy of the robot movement control is guaranteed.

Robotic and Virtual Reality BCIs Using Spatial Tactile and Auditory Oddball Paradigms.

PubMed

Rutkowski, Tomasz M

2016-01-01

The paper reviews nine robotic and virtual reality (VR) brain-computer interface (BCI) projects developed by the author, in collaboration with his graduate students, within the BCI-lab research group during its association with University of Tsukuba, Japan. The nine novel approaches are discussed in applications to direct brain-robot and brain-virtual-reality-agent control interfaces using tactile and auditory BCI technologies. The BCI user intentions are decoded from the brainwaves in realtime using a non-invasive electroencephalography (EEG) and they are translated to a symbiotic robot or virtual reality agent thought-based only control. A communication protocol between the BCI output and the robot or the virtual environment is realized in a symbiotic communication scenario using an user datagram protocol (UDP), which constitutes an internet of things (IoT) control scenario. Results obtained from healthy users reproducing simple brain-robot and brain-virtual-agent control tasks in online experiments support the research goal of a possibility to interact with robotic devices and virtual reality agents using symbiotic thought-based BCI technologies. An offline BCI classification accuracy boosting method, using a previously proposed information geometry derived approach, is also discussed in order to further support the reviewed robotic and virtual reality thought-based control paradigms.

Robotic and Virtual Reality BCIs Using Spatial Tactile and Auditory Oddball Paradigms

PubMed Central

Rutkowski, Tomasz M.

2016-01-01

The paper reviews nine robotic and virtual reality (VR) brain–computer interface (BCI) projects developed by the author, in collaboration with his graduate students, within the BCI–lab research group during its association with University of Tsukuba, Japan. The nine novel approaches are discussed in applications to direct brain-robot and brain-virtual-reality-agent control interfaces using tactile and auditory BCI technologies. The BCI user intentions are decoded from the brainwaves in realtime using a non-invasive electroencephalography (EEG) and they are translated to a symbiotic robot or virtual reality agent thought-based only control. A communication protocol between the BCI output and the robot or the virtual environment is realized in a symbiotic communication scenario using an user datagram protocol (UDP), which constitutes an internet of things (IoT) control scenario. Results obtained from healthy users reproducing simple brain-robot and brain-virtual-agent control tasks in online experiments support the research goal of a possibility to interact with robotic devices and virtual reality agents using symbiotic thought-based BCI technologies. An offline BCI classification accuracy boosting method, using a previously proposed information geometry derived approach, is also discussed in order to further support the reviewed robotic and virtual reality thought-based control paradigms. PMID:27999538

Embodied cognition for autonomous interactive robots.

PubMed

Hoffman, Guy

2012-10-01

In the past, notions of embodiment have been applied to robotics mainly in the realm of very simple robots, and supporting low-level mechanisms such as dynamics and navigation. In contrast, most human-like, interactive, and socially adept robotic systems turn away from embodiment and use amodal, symbolic, and modular approaches to cognition and interaction. At the same time, recent research in Embodied Cognition (EC) is spanning an increasing number of complex cognitive processes, including language, nonverbal communication, learning, and social behavior. This article suggests adopting a modern EC approach for autonomous robots interacting with humans. In particular, we present three core principles from EC that may be applicable to such robots: (a) modal perceptual representation, (b) action/perception and action/cognition integration, and (c) a simulation-based model of top-down perceptual biasing. We describe a computational framework based on these principles, and its implementation on two physical robots. This could provide a new paradigm for embodied human-robot interaction based on recent psychological and neurological findings. Copyright © 2012 Cognitive Science Society, Inc.

Interfacing insect brain for space applications.

PubMed

Di Pino, Giovanni; Seidl, Tobias; Benvenuto, Antonella; Sergi, Fabrizio; Campolo, Domenico; Accoto, Dino; Maria Rossini, Paolo; Guglielmelli, Eugenio

2009-01-01

Insects exhibit remarkable navigation capabilities that current control architectures are still far from successfully mimic and reproduce. In this chapter, we present the results of a study on conceptualizing insect/machine hybrid controllers for improving autonomy of exploratory vehicles. First, the different principally possible levels of interfacing between insect and machine are examined followed by a review of current approaches towards hybridity and enabling technologies. Based on the insights of this activity, we propose a double hybrid control architecture which hinges around the concept of "insect-in-a-cockpit." It integrates both biological/artificial (insect/robot) modules and deliberative/reactive behavior. The basic assumption is that "low-level" tasks are managed by the robot, while the "insect intelligence" is exploited whenever high-level problem solving and decision making is required. Both neural and natural interfacing have been considered to achieve robustness and redundancy of exchanged information.

Robot Faces that Follow Gaze Facilitate Attentional Engagement and Increase Their Likeability

PubMed Central

Willemse, Cesco; Marchesi, Serena; Wykowska, Agnieszka

2018-01-01

Gaze behavior of humanoid robots is an efficient mechanism for cueing our spatial orienting, but less is known about the cognitive–affective consequences of robots responding to human directional cues. Here, we examined how the extent to which a humanoid robot (iCub) avatar directed its gaze to the same objects as our participants affected engagement with the robot, subsequent gaze-cueing, and subjective ratings of the robot’s characteristic traits. In a gaze-contingent eyetracking task, participants were asked to indicate a preference for one of two objects with their gaze while an iCub avatar was presented between the object photographs. In one condition, the iCub then shifted its gaze toward the object chosen by a participant in 80% of the trials (joint condition) and in the other condition it looked at the opposite object 80% of the time (disjoint condition). Based on the literature in human–human social cognition, we took the speed with which the participants looked back at the robot as a measure of facilitated reorienting and robot-preference, and found these return saccade onset times to be quicker in the joint condition than in the disjoint condition. As indicated by results from a subsequent gaze-cueing tasks, the gaze-following behavior of the robot had little effect on how our participants responded to gaze cues. Nevertheless, subjective reports suggested that our participants preferred the iCub following participants’ gaze to the one with a disjoint attention behavior, rated it as more human-like and as more likeable. Taken together, our findings show a preference for robots who follow our gaze. Importantly, such subtle differences in gaze behavior are sufficient to influence our perception of humanoid agents, which clearly provides hints about the design of behavioral characteristics of humanoid robots in more naturalistic settings. PMID:29459842

Externalising moods and psychological states in a cloud based system to enhance a pet-robot and child's interaction.

PubMed

Larriba, Ferran; Raya, Cristóbal; Angulo, Cecilio; Albo-Canals, Jordi; Díaz, Marta; Boldú, Roger

2016-07-15

This PATRICIA research project is about using pet robots to reduce pain and anxiety in hospitalized children. The study began 2 years ago and it is believed that the advances made in this project are significant. Patients, parents, nurses, psychologists, and engineers have adopted the Pleo robot, a baby dinosaur robotic pet, which works in different ways to assist children during hospitalization. Focus is spent on creating a wireless communication system with the Pleo in order to help the coordinator, who conducts therapy with the child, monitor, understand, and control Pleo's behavior at any moment. This article reports how this technological function is being developed and tested. Wireless communication between the Pleo and an Android device is achieved. The developed Android app allows the user to obtain any state of the robot without stopping its interaction with the patient. Moreover, information is sent to a cloud, so that robot moods, states and interactions can be shared among different robots. Pleo attachment was successful for more than 1 month, working with children in therapy, which makes the investment capable of positive therapeutic possibilities. This technical improvement in the Pleo addresses two key issues in social robotics: needing an enhanced response to maintain the attention and engagement of the child, and using the system as a platform to collect the states of the child's progress for clinical purposes.

Continuum robot arms inspired by cephalopods

NASA Astrophysics Data System (ADS)

Walker, Ian D.; Dawson, Darren M.; Flash, Tamar; Grasso, Frank W.; Hanlon, Roger T.; Hochner, Binyamin; Kier, William M.; Pagano, Christopher C.; Rahn, Christopher D.; Zhang, Qiming M.

2005-05-01

In this paper, we describe our recent results in the development of a new class of soft, continuous backbone ("continuum") robot manipulators. Our work is strongly motivated by the dexterous appendages found in cephalopods, particularly the arms and suckers of octopus, and the arms and tentacles of squid. Our ongoing investigation of these animals reveals interesting and unexpected functional aspects of their structure and behavior. The arrangement and dynamic operation of muscles and connective tissue observed in the arms of a variety of octopus species motivate the underlying design approach for our soft manipulators. These artificial manipulators feature biomimetic actuators, including artificial muscles based on both electro-active polymers (EAP) and pneumatic (McKibben) muscles. They feature a "clean" continuous backbone design, redundant degrees of freedom, and exhibit significant compliance that provides novel operational capacities during environmental interaction and object manipulation. The unusual compliance and redundant degrees of freedom provide strong potential for application to delicate tasks in cluttered and/or unstructured environments. Our aim is to endow these compliant robotic mechanisms with the diverse and dexterous grasping behavior observed in octopuses. To this end, we are conducting fundamental research into the manipulation tactics, sensory biology, and neural control of octopuses. This work in turn leads to novel approaches to motion planning and operator interfaces for the robots. The paper describes the above efforts, along with the results of our development of a series of continuum tentacle-like robots, demonstrating the unique abilities of biologically-inspired design.

A robotic approach to understanding the role and the mechanism of vicarious trial-and-error in a T-maze task.

PubMed

Matsuda, Eiko; Hubert, Julien; Ikegami, Takashi

2014-01-01

Vicarious trial-and-error (VTE) is a behavior observed in rat experiments that seems to suggest self-conflict. This behavior is seen mainly when the rats are uncertain about making a decision. The presence of VTE is regarded as an indicator of a deliberative decision-making process, that is, searching, predicting, and evaluating outcomes. This process is slower than automated decision-making processes, such as reflex or habituation, but it allows for flexible and ongoing control of behavior. In this study, we propose for the first time a robotic model of VTE to see if VTE can emerge just from a body-environment interaction and to show the underlying mechanism responsible for the observation of VTE and the advantages provided by it. We tried several robots with different parameters, and we have found that they showed three different types of VTE: high numbers of VTE at the beginning of learning, decreasing numbers afterward (similar VTE pattern to experiments with rats), low during the whole learning period, and high numbers all the time. Therefore, we were able to reproduce the phenomenon of VTE in a model robot using only a simple dynamical neural network with Hebbian learning, which suggests that VTE is an emergent property of a plastic and embodied neural network. From a comparison of the three types of VTE, we demonstrated that 1) VTE is associated with chaotic activity of neurons in our model and 2) VTE-showing robots were robust to environmental perturbations. We suggest that the instability of neuronal activity found in VTE allows ongoing learning to rebuild its strategy continuously, which creates robust behavior. Based on these results, we suggest that VTE is caused by a similar mechanism in biology and leads to robust decision making in an analogous way.

Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface

PubMed Central

Kim, Youngmoo E.

2017-01-01

Motor-imagery tasks are a popular input method for controlling brain-computer interfaces (BCIs), partially due to their similarities to naturally produced motor signals. The use of functional near-infrared spectroscopy (fNIRS) in BCIs is still emerging and has shown potential as a supplement or replacement for electroencephalography. However, studies often use only two or three motor-imagery tasks, limiting the number of available commands. In this work, we present the results of the first four-class motor-imagery-based online fNIRS-BCI for robot control. Thirteen participants utilized upper- and lower-limb motor-imagery tasks (left hand, right hand, left foot, and right foot) that were mapped to four high-level commands (turn left, turn right, move forward, and move backward) to control the navigation of a simulated or real robot. A significant improvement in classification accuracy was found between the virtual-robot-based BCI (control of a virtual robot) and the physical-robot BCI (control of the DARwIn-OP humanoid robot). Differences were also found in the oxygenated hemoglobin activation patterns of the four tasks between the first and second BCI. These results corroborate previous findings that motor imagery can be improved with feedback and imply that a four-class motor-imagery-based fNIRS-BCI could be feasible with sufficient subject training. PMID:28804712

Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface.

PubMed

Batula, Alyssa M; Kim, Youngmoo E; Ayaz, Hasan

2017-01-01

Motor-imagery tasks are a popular input method for controlling brain-computer interfaces (BCIs), partially due to their similarities to naturally produced motor signals. The use of functional near-infrared spectroscopy (fNIRS) in BCIs is still emerging and has shown potential as a supplement or replacement for electroencephalography. However, studies often use only two or three motor-imagery tasks, limiting the number of available commands. In this work, we present the results of the first four-class motor-imagery-based online fNIRS-BCI for robot control. Thirteen participants utilized upper- and lower-limb motor-imagery tasks (left hand, right hand, left foot, and right foot) that were mapped to four high-level commands (turn left, turn right, move forward, and move backward) to control the navigation of a simulated or real robot. A significant improvement in classification accuracy was found between the virtual-robot-based BCI (control of a virtual robot) and the physical-robot BCI (control of the DARwIn-OP humanoid robot). Differences were also found in the oxygenated hemoglobin activation patterns of the four tasks between the first and second BCI. These results corroborate previous findings that motor imagery can be improved with feedback and imply that a four-class motor-imagery-based fNIRS-BCI could be feasible with sufficient subject training.

Autonomous Motion Learning for Intra-Vehicular Activity Space Robot

NASA Astrophysics Data System (ADS)

Watanabe, Yutaka; Yairi, Takehisa; Machida, Kazuo

Space robots will be needed in the future space missions. So far, many types of space robots have been developed, but in particular, Intra-Vehicular Activity (IVA) space robots that support human activities should be developed to reduce human-risks in space. In this paper, we study the motion learning method of an IVA space robot with the multi-link mechanism. The advantage point is that this space robot moves using reaction force of the multi-link mechanism and contact forces from the wall as space walking of an astronaut, not to use a propulsion. The control approach is determined based on a reinforcement learning with the actor-critic algorithm. We demonstrate to clear effectiveness of this approach using a 5-link space robot model by simulation. First, we simulate that a space robot learn the motion control including contact phase in two dimensional case. Next, we simulate that a space robot learn the motion control changing base attitude in three dimensional case.

Pneumatic artificial muscle actuators for compliant robotic manipulators

NASA Astrophysics Data System (ADS)

Robinson, Ryan Michael

Robotic systems are increasingly being utilized in applications that require interaction with humans. In order to enable safe physical human-robot interaction, light weight and compliant manipulation are desirable. These requirements are problematic for many conventional actuation systems, which are often heavy, and typically use high stiffness to achieve high performance, leading to large impact forces upon collision. However, pneumatic artificial muscles (PAMs) are actuators that can satisfy these safety requirements while offering power-to-weight ratios comparable to those of conventional actuators. PAMs are extremely lightweight actuators that produce force in response to pressurization. These muscles demonstrate natural compliance, but have a nonlinear force-contraction profile that complicates modeling and control. This body of research presents solutions to the challenges associated with the implementation of PAMs as actuators in robotic manipulators, particularly with regard to modeling, design, and control. An existing PAM force balance model was modified to incorporate elliptic end geometry and a hyper-elastic constitutive relationship, dramatically improving predictions of PAM behavior at high contraction. Utilizing this improved model, two proof-of-concept PAM-driven manipulators were designed and constructed; design features included parallel placement of actuators and a tendon-link joint design. Genetic algorithm search heuristics were employed to determine an optimal joint geometry; allowing a manipulator to achieve a desired torque profile while minimizing the required PAM pressure. Performance of the manipulators was evaluated in both simulation and experiment employing various linear and nonlinear control strategies. These included output feedback techniques, such as proportional-integral-derivative (PID) and fuzzy logic, a model-based control for computed torque, and more advanced controllers, such as sliding mode, adaptive sliding mode, and adaptive neural network control. Results demonstrated the benefits of an accurate model in model-based control, and the advantages of adaptive neural network control when a model is unavailable or variations in payload are expected. Lastly, a variable recruitment strategy was applied to a group of parallel muscles actuating a common joint. Increased manipulator efficiency was observed when fewer PAMs were activated, justifying the use of variable recruitment strategies. Overall, this research demonstrates the benefits of pneumatic artificial muscles as actuators in robotics applications. It demonstrates that PAM-based manipulators can be well-modeled and can achieve high tracking accuracy over a wide range of payloads and inputs while maintaining natural compliance.

Kinematics Control and Analysis of Industrial Robot

NASA Astrophysics Data System (ADS)

Zhu, Tongbo; Cai, Fan; Li, Yongmei; Liu, Wei

2018-03-01

The robot’s development present situation, basic principle and control system are introduced briefly. Research is mainly focused on the study of the robot’s kinematics and motion control. The structural analysis of a planar articulated robot (SCARA) robot is presented,the coordinate system is established to obtain the position and orientation matrix of the end effector,a method of robot kinematics analysis based on homogeneous transformation method is proposed, and the kinematics solution of the robot is obtained.Establishment of industrial robot’s kinematics equation and formula for positive kinematics by example. Finally,the kinematic analysis of this robot was verified by examples.It provides a basis for structural design and motion control.It has active significance to promote the motion control of industrial robot.

Human-directed local autonomy for motion guidance and coordination in an intelligent manufacturing system

NASA Astrophysics Data System (ADS)

Alford, W. A.; Kawamura, Kazuhiko; Wilkes, Don M.

1997-12-01

This paper discusses the problem of integrating human intelligence and skills into an intelligent manufacturing system. Our center has jointed the Holonic Manufacturing Systems (HMS) Project, an international consortium dedicated to developing holonic systems technologies. One of our contributions to this effort is in Work Package 6: flexible human integration. This paper focuses on one activity, namely, human integration into motion guidance and coordination. Much research on intelligent systems focuses on creating totally autonomous agents. At the Center for Intelligent Systems (CIS), we design robots that interact directly with a human user. We focus on using the natural intelligence of the user to simplify the design of a robotic system. The problem is finding ways for the user to interact with the robot that are efficient and comfortable for the user. Manufacturing applications impose the additional constraint that the manufacturing process should not be disturbed; that is, frequent interacting with the user could degrade real-time performance. Our research in human-robot interaction is based on a concept called human directed local autonomy (HuDL). Under this paradigm, the intelligent agent selects and executes a behavior or skill, based upon directions from a human user. The user interacts with the robot via speech, gestures, or other media. Our control software is based on the intelligent machine architecture (IMA), an object-oriented architecture which facilitates cooperation and communication among intelligent agents. In this paper we describe our research testbed, a dual-arm humanoid robot and human user, and the use of this testbed for a human directed sorting task. We also discuss some proposed experiments for evaluating the integration of the human into the robot system. At the time of this writing, the experiments have not been completed.

An EMG-Based Control for an Upper-Limb Power-Assist Exoskeleton Robot.

PubMed

Kiguchi, K; Hayashi, Y

2012-08-01

Many kinds of power-assist robots have been developed in order to assist self-rehabilitation and/or daily life motions of physically weak persons. Several kinds of control methods have been proposed to control the power-assist robots according to user's motion intention. In this paper, an electromyogram (EMG)-based impedance control method for an upper-limb power-assist exoskeleton robot is proposed to control the robot in accordance with the user's motion intention. The proposed method is simple, easy to design, humanlike, and adaptable to any user. A neurofuzzy matrix modifier is applied to make the controller adaptable to any users. Not only the characteristics of EMG signals but also the characteristics of human body are taken into account in the proposed method. The effectiveness of the proposed method was evaluated by the experiments.

Simulation-based intelligent robotic agent for Space Station Freedom

NASA Technical Reports Server (NTRS)

Biegl, Csaba A.; Springfield, James F.; Cook, George E.; Fernandez, Kenneth R.

1990-01-01

A robot control package is described which utilizes on-line structural simulation of robot manipulators and objects in their workspace. The model-based controller is interfaced with a high level agent-independent planner, which is responsible for the task-level planning of the robot's actions. Commands received from the agent-independent planner are refined and executed in the simulated workspace, and upon successful completion, they are transferred to the real manipulators.

Dynamic modeling of parallel robots for computed-torque control implementation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Codourey, A.

1998-12-01

In recent years, increased interest in parallel robots has been observed. Their control with modern theory, such as the computed-torque method, has, however, been restrained, essentially due to the difficulty in establishing a simple dynamic model that can be calculated in real time. In this paper, a simple method based on the virtual work principle is proposed for modeling parallel robots. The mass matrix of the robot, needed for decoupling control strategies, does not explicitly appear in the formulation; however, it can be computed separately, based on kinetic energy considerations. The method is applied to the DELTA parallel robot, leadingmore » to a very efficient model that has been implemented in a real-time computed-torque control algorithm.« less

Intelligent control and cooperation for mobile robots

NASA Astrophysics Data System (ADS)

Stingu, Petru Emanuel

The topic discussed in this work addresses the current research being conducted at the Automation & Robotics Research Institute in the areas of UAV quadrotor control and heterogenous multi-vehicle cooperation. Autonomy can be successfully achieved by a robot under the following conditions: the robot has to be able to acquire knowledge about the environment and itself, and it also has to be able to reason under uncertainty. The control system must react quickly to immediate challenges, but also has to slowly adapt and improve based on accumulated knowledge. The major contribution of this work is the transfer of the ADP algorithms from the purely theoretical environment to the complex real-world robotic platforms that work in real-time and in uncontrolled environments. Many solutions are adopted from those present in nature because they have been proven to be close to optimal in very different settings. For the control of a single platform, reinforcement learning algorithms are used to design suboptimal controllers for a class of complex systems that can be conceptually split in local loops with simpler dynamics and relatively weak coupling to the rest of the system. Optimality is enforced by having a global critic but the curse of dimensionality is avoided by using local actors and intelligent pre-processing of the information used for learning the optimal controllers. The system model is used for constructing the structure of the control system, but on top of that the adaptive neural networks that form the actors use the knowledge acquired during normal operation to get closer to optimal control. In real-world experiments, efficient learning is a strong requirement for success. This is accomplished by using an approximation of the system model to focus the learning for equivalent configurations of the state space. Due to the availability of only local data for training, neural networks with local activation functions are implemented. For the control of a formation of robots subjected to dynamic communication constraints, game theory is used in addition to reinforcement learning. The nodes maintain an extra set of state variables about all the other nodes that they can communicate to. The more important are trust and predictability. They are a way to incorporate knowledge acquired in the past into the control decisions taken by each node. The trust variable provides a simple mechanism for the implementation of reinforcement learning. For robot formations, potential field based control algorithms are used to generate the control commands. The formation structure changes due to the environment and due to the decisions of the nodes. It is a problem of building a graph and coalitions by having distributed decisions but still reaching an optimal behavior globally.

Multidisciplinary approach for developing a new robotic system for domiciliary assistance to elderly people.

PubMed

Cavallo, F; Aquilano, M; Bonaccorsi, M; Mannari, I; Carrozza, M C; Dario, P

2011-01-01

This paper aims to show the effectiveness of a (inter / multi)disciplinary team, based on the technology developers, elderly care organizations, and designers, in developing the ASTRO robotic system for domiciliary assistance to elderly people. The main issues presented in this work concern the improvement of robot's behavior by means of a smart sensor network able to share information with the robot for localization and navigation, and the design of the robot's appearance and functionalities by means of a substantial analysis of users' requirements and attitude to robotic technology to improve acceptability and usability.

New diagnostic tool for robotic psychology and robotherapy studies.

PubMed

Libin, Elena; Libin, Alexander

2003-08-01

Robotic psychology and robotherapy as a new research area employs a systematic approach in studying psycho-physiological, psychological, and social aspects of person-robot communication. An analysis of the mechanisms underlying different forms of computer-mediated behavior requires both an adequate methodology and research tools. In the proposed article we discuss the concept, basic principles, structure, and contents of the newly designed Person-Robot Complex Interactive Scale (PRCIS), proposed for the purpose of investigating psychological specifics and therapeutic potentials of multilevel person-robot interactions. Assuming that human-robot communication has symbolic meaning, each interactive pattern evaluated via the newly developed scale is assigned certain psychological value associated with the person's past life experiences, likes and dislikes, emotional, cognitive, and behavioral traits or states. PRCIS includes (1) assessment of a person's individual style of communication with the robotic creature based on direct observations; (2) the participant's evaluation of his/her new experiences with an interactive robot and evaluation of its features, advantages and disadvantages, as well as past experiences with modern technology; and (3) the instructor's overall evaluation of the session.

Robotics technology discipline

NASA Technical Reports Server (NTRS)

Montemerlo, Melvin D.

1990-01-01

Viewgraphs on robotics technology discipline for Space Station Freedom are presented. Topics covered include: mechanisms; sensors; systems engineering processes for integrated robotics; man/machine cooperative control; 3D-real-time machine perception; multiple arm redundancy control; manipulator control from a movable base; multi-agent reasoning; and surfacing evolution technologies.

Parallel elastic elements improve energy efficiency on the STEPPR bipedal walking robot

DOE PAGES

Mazumdar, Anirban; Spencer, Steven J.; Hobart, Clinton; ...

2016-11-23

This study describes how parallel elastic elements can be used to reduce energy consumption in the electric motor driven, fully-actuated, STEPPR bipedal walking robot without compromising or significantly limiting locomotive behaviors. A physically motivated approach is used to illustrate how selectively-engaging springs for hip adduction and ankle flexion predict benefits for three different flat ground walking gaits: human walking, human-like robot walking and crouched robot walking. Based on locomotion data, springs are designed and substantial reductions in power consumption are demonstrated using a bench dynamometer. These lessons are then applied to STEPPR (Sandia Transmission-Efficient Prototype Promoting Research), a fully actuatedmore » bipedal robot designed to explore the impact of tailored joint mechanisms on walking efficiency. Featuring high-torque brushless DC motors, efficient low-ratio transmissions, and high fidelity torque control, STEPPR provides the ability to incorporate novel joint-level mechanisms without dramatically altering high level control. Unique parallel elastic designs are incorporated into STEPPR, and walking data shows that hip adduction and ankle flexion springs significantly reduce the required actuator energy at those joints for several gaits. These results suggest that parallel joint springs offer a promising means of supporting quasi-static joint torques due to body mass during walking, relieving motors of the need to support these torques and substantially improving locomotive energy efficiency.« less

Parallel elastic elements improve energy efficiency on the STEPPR bipedal walking robot

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mazumdar, Anirban; Spencer, Steven J.; Hobart, Clinton

This study describes how parallel elastic elements can be used to reduce energy consumption in the electric motor driven, fully-actuated, STEPPR bipedal walking robot without compromising or significantly limiting locomotive behaviors. A physically motivated approach is used to illustrate how selectively-engaging springs for hip adduction and ankle flexion predict benefits for three different flat ground walking gaits: human walking, human-like robot walking and crouched robot walking. Based on locomotion data, springs are designed and substantial reductions in power consumption are demonstrated using a bench dynamometer. These lessons are then applied to STEPPR (Sandia Transmission-Efficient Prototype Promoting Research), a fully actuatedmore » bipedal robot designed to explore the impact of tailored joint mechanisms on walking efficiency. Featuring high-torque brushless DC motors, efficient low-ratio transmissions, and high fidelity torque control, STEPPR provides the ability to incorporate novel joint-level mechanisms without dramatically altering high level control. Unique parallel elastic designs are incorporated into STEPPR, and walking data shows that hip adduction and ankle flexion springs significantly reduce the required actuator energy at those joints for several gaits. These results suggest that parallel joint springs offer a promising means of supporting quasi-static joint torques due to body mass during walking, relieving motors of the need to support these torques and substantially improving locomotive energy efficiency.« less

Tip-over prevention through heuristic reactive behaviors for unmanned ground vehicles

NASA Astrophysics Data System (ADS)

Talke, Kurt; Kelley, Leah; Longhini, Patrick; Catron, Garret

2014-06-01

Skid-steer teleoperated robots are commonly used by military and civilian crews to perform high-risk, dangerous and critical tasks such as bomb disposal. Their missions are often performed in unstructured environments with irregular terrain, such as inside collapsed buildings or on rough terrain covered with a variety of media, such as sand, brush, mud, rocks and debris. During such missions, it is often impractical if not impossible to send another robot or a human operator to right a toppled robot. As a consequence, a robot tip-over event usually results in mission failure. To make matters more complicated, such robots are often equipped with heavy payloads that raise their centers of mass and hence increase their instability. Should the robot be equipped with a manipulator arm or flippers, it may have a way to self-right. The majority of manipulator arms are not designed for and are likely to be damaged during self-righting procedures, however, which typically have a low success rate. Furthermore, those robots not equipped with manipulator arms or flippers have no self-righting capabilities. Additionally, due to the on-board camera frame of reference, the video feed may cause the robot to appear to be on at level ground, when it actually may be on a slope nearing tip-over. Finally, robot operators are often so focused on the mission at hand they are oblivious to their surroundings, similar to a kid playing a video game. While this may not be an issue in the living room, it is not a good scenario to experience on the battlefield. Our research seeks to remove tip-over monitoring from the already large list of tasks an operator must perform. An autonomous tip-over prevention behavior for a mobile robot with a static payload has been developed, implemented and experimentally validated on two different teleoperated robotic platforms. Suitable for use with both teleoperated and autonomous robots, the prevention behavior uses the force-angle stability measure, previously experimentally validated, to predict the likelihood of robot tip-over and trigger prevention behaviors. A unique heuristic approach to tip-over avoidance was investigated, wherein a set of evasive maneuvers that an expert teleoperator might take are activated when the tip-over-likelihood estimate passes a critical threshold. This control approach was validated on an iRobot Packbot as well as on a Segway RMP 440. The heuristic laws demonstrated the advantage of alerting operators to a tip-over scenario and gave them more time to correct the situation, as well as the ability to automatically initiate recovery on the y". This research shows promise in preventing dangerous scenarios that could damage a robot and/or compromise its mission, thus saving lives. It further provides a good foundation for follow-on development involving the expansion and integration of the prevention-control algorithms, to include movable payloads, environment manipulation, 2D or 3D look-ahead laser sensing and mapping, and adaptive path planning.

A Low-Cost EEG System-Based Hybrid Brain-Computer Interface for Humanoid Robot Navigation and Recognition

PubMed Central

Choi, Bongjae; Jo, Sungho

2013-01-01

This paper describes a hybrid brain-computer interface (BCI) technique that combines the P300 potential, the steady state visually evoked potential (SSVEP), and event related de-synchronization (ERD) to solve a complicated multi-task problem consisting of humanoid robot navigation and control along with object recognition using a low-cost BCI system. Our approach enables subjects to control the navigation and exploration of a humanoid robot and recognize a desired object among candidates. This study aims to demonstrate the possibility of a hybrid BCI based on a low-cost system for a realistic and complex task. It also shows that the use of a simple image processing technique, combined with BCI, can further aid in making these complex tasks simpler. An experimental scenario is proposed in which a subject remotely controls a humanoid robot in a properly sized maze. The subject sees what the surrogate robot sees through visual feedback and can navigate the surrogate robot. While navigating, the robot encounters objects located in the maze. It then recognizes if the encountered object is of interest to the subject. The subject communicates with the robot through SSVEP and ERD-based BCIs to navigate and explore with the robot, and P300-based BCI to allow the surrogate robot recognize their favorites. Using several evaluation metrics, the performances of five subjects navigating the robot were quite comparable to manual keyboard control. During object recognition mode, favorite objects were successfully selected from two to four choices. Subjects conducted humanoid navigation and recognition tasks as if they embodied the robot. Analysis of the data supports the potential usefulness of the proposed hybrid BCI system for extended applications. This work presents an important implication for the future work that a hybridization of simple BCI protocols provide extended controllability to carry out complicated tasks even with a low-cost system. PMID:24023953

A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.

PubMed

Choi, Bongjae; Jo, Sungho

2013-01-01

This paper describes a hybrid brain-computer interface (BCI) technique that combines the P300 potential, the steady state visually evoked potential (SSVEP), and event related de-synchronization (ERD) to solve a complicated multi-task problem consisting of humanoid robot navigation and control along with object recognition using a low-cost BCI system. Our approach enables subjects to control the navigation and exploration of a humanoid robot and recognize a desired object among candidates. This study aims to demonstrate the possibility of a hybrid BCI based on a low-cost system for a realistic and complex task. It also shows that the use of a simple image processing technique, combined with BCI, can further aid in making these complex tasks simpler. An experimental scenario is proposed in which a subject remotely controls a humanoid robot in a properly sized maze. The subject sees what the surrogate robot sees through visual feedback and can navigate the surrogate robot. While navigating, the robot encounters objects located in the maze. It then recognizes if the encountered object is of interest to the subject. The subject communicates with the robot through SSVEP and ERD-based BCIs to navigate and explore with the robot, and P300-based BCI to allow the surrogate robot recognize their favorites. Using several evaluation metrics, the performances of five subjects navigating the robot were quite comparable to manual keyboard control. During object recognition mode, favorite objects were successfully selected from two to four choices. Subjects conducted humanoid navigation and recognition tasks as if they embodied the robot. Analysis of the data supports the potential usefulness of the proposed hybrid BCI system for extended applications. This work presents an important implication for the future work that a hybridization of simple BCI protocols provide extended controllability to carry out complicated tasks even with a low-cost system.

How do walkers behave when crossing the way of a mobile robot that replicates human interaction rules?

PubMed

Vassallo, Christian; Olivier, Anne-Hélène; Souères, Philippe; Crétual, Armel; Stasse, Olivier; Pettré, Julien

2018-02-01

Previous studies showed the existence of implicit interaction rules shared by human walkers when crossing each other. Especially, each walker contributes to the collision avoidance task and the crossing order, as set at the beginning, is preserved along the interaction. This order determines the adaptation strategy: the first arrived increases his/her advance by slightly accelerating and changing his/her heading, whereas the second one slows down and moves in the opposite direction. In this study, we analyzed the behavior of human walkers crossing the trajectory of a mobile robot that was programmed to reproduce this human avoidance strategy. In contrast with a previous study, which showed that humans mostly prefer to give the way to a non-reactive robot, we observed similar behaviors between human-human avoidance and human-robot avoidance when the robot replicates the human interaction rules. We discuss this result in relation with the importance of controlling robots in a human-like way in order to ease their cohabitation with humans. Copyright © 2017 Elsevier B.V. All rights reserved.

Potential of robots as next-generation technology for clinical assessment of neurological disorders and upper-limb therapy.

PubMed

Scott, Stephen H; Dukelow, Sean P

2011-01-01

Robotic technologies have profoundly affected the identification of fundamental properties of brain function. This success is attributable to robots being able to control the position of or forces applied to limbs, and their inherent ability to easily, objectively, and reliably quantify sensorimotor behavior. Our general hypothesis is that these same attributes make robotic technologies ideal for clinically assessing sensory, motor, and cognitive impairments in stroke and other neurological disorders. Further, they provide opportunities for novel therapeutic strategies. The present opinionated review describes how robotic technologies combined with virtual/augmented reality systems can support a broad range of behavioral tasks to objectively quantify brain function. This information could potentially be used to provide more accurate diagnostic and prognostic information than is available from current clinical assessment techniques. The review also highlights the potential benefits of robots to provide upper-limb therapy. Although the capital cost of these technologies is substantial, it pales in comparison with the potential cost reductions to the overall healthcare system that improved assessment and therapeutic interventions offer.

A new scheme of force reflecting control

NASA Technical Reports Server (NTRS)

Kim, Won S.

1992-01-01

A new scheme of force reflecting control has been developed that incorporates position-error-based force reflection and robot compliance control. The operator is provided with a kinesthetic force feedback which is proportional to the position error between the operator-commanded and the actual position of the robot arm. Robot compliance control, which increases the effective compliance of the robot, is implemented by low pass filtering the outputs of the force/torque sensor mounted on the base of robot hand and using these signals to alter the operator's position command. This position-error-based force reflection scheme combined with shared compliance control has been implemented successfully to the Advanced Teleoperation system consisting of dissimilar master-slave arms. Stability measurements have demonstrated unprecedentedly high force reflection gains of up to 2 or 3, even though the slave arm is much stiffer than operator's hand holding the force reflecting hand controller. Peg-in-hole experiments were performed with eight different operating modes to evaluate the new force-reflecting control scheme. Best task performance resulted with this new control scheme.

Exploration of Planetary Terrains with a Legged Robot as a Scout Adjunct to a Rover

NASA Technical Reports Server (NTRS)

Colombano, Silvano; Kirchner, Frank; Spenneberg, Dirk; Hanratty, James

2004-01-01

The Scorpion robot is an innovative, biologically inspired 8-legged walking robot. It currently runs a novel approach to control which utilizes a central pattern generator (CPG) and local reflex action for each leg. From this starting point we are proposing to both extend the system's individual capabilities and its capacity to function as a "scout", cooperating with a larger wheeled rover. For this purpose we propose to develop a distributed system architecture that extends the system's capabilities both in the direction of high level planning and execution in collaboration with a rover, and in the direction of force-feedback based low level behaviors that will greatly enhance its ability to walk and climb in rough varied terrains. The final test of this improved ability will be a rappelling experiment where the Scorpion explores a steep cliff side in cooperation with a rover that serves as both anchor and planner/executive.

The Control Based on Internal Average Kinetic Energy in Complex Environment for Multi-robot System

NASA Astrophysics Data System (ADS)

Yang, Mao; Tian, Yantao; Yin, Xianghua

In this paper, reference trajectory is designed according to minimum energy consumed for multi-robot system, which nonlinear programming and cubic spline interpolation are adopted. The control strategy is composed of two levels, which lower-level is simple PD control and the upper-level is based on the internal average kinetic energy for multi-robot system in the complex environment with velocity damping. Simulation tests verify the effectiveness of this control strategy.

Adaptive control of space based robot manipulators

NASA Technical Reports Server (NTRS)

Walker, Michael W.; Wee, Liang-Boon

1991-01-01

For space based robots in which the base is free to move, motion planning and control is complicated by uncertainties in the inertial properties of the manipulator and its load. A new adaptive control method is presented for space based robots which achieves globally stable trajectory tracking in the presence of uncertainties in the inertial parameters of the system. A partition is made of the fifteen degree of freedom system dynamics into two parts: a nine degree of freedom invertible portion and a six degree of freedom noninvertible portion. The controller is then designed to achieve trajectory tracking of the invertible portion of the system. This portion consist of the manipulator joint positions and the orientation of the base. The motion of the noninvertible portion is bounded, but unpredictable. This portion consist of the position of the robot's base and the position of the reaction wheel.

Cosine Kuramoto Based Distribution of a Convoy with Limit-Cycle Obstacle Avoidance Through the Use of Simulated Agents

NASA Astrophysics Data System (ADS)

Howerton, William

This thesis presents a method for the integration of complex network control algorithms with localized agent specific algorithms for maneuvering and obstacle avoidance. This method allows for successful implementation of group and agent specific behaviors. It has proven to be robust and will work for a variety of vehicle platforms. Initially, a review and implementation of two specific algorithms will be detailed. The first, a modified Kuramoto model was developed by Xu [1] which utilizes tools from graph theory to efficiently perform the task of distributing agents. The second algorithm developed by Kim [2] is an effective method for wheeled robots to avoid local obstacles using a limit-cycle navigation method. The results of implementing these methods on a test-bed of wheeled robots will be presented. Control issues related to outside disturbances not anticipated in the original theory are then discussed. A novel method of using simulated agents to separate the task of distributing agents from agent specific velocity and heading commands has been developed and implemented to address these issues. This new method can be used to combine various behaviors and is not limited to a specific control algorithm.

Development of autonomous eating mechanism for biomimetic robots

NASA Astrophysics Data System (ADS)

Jeong, Kil-Woong; Cho, Ik-Jin; Lee, Yun-Jung

2005-12-01

Most of the recently developed robots are human friendly robots which imitate animals or humans such as entertainment robot, bio-mimetic robot and humanoid robot. Interest for these robots are being increased because the social trend is focused on health, welfare, and graying. Autonomous eating functionality is most unique and inherent behavior of pets and animals. Most of entertainment robots and pet robots make use of internal-type battery. Entertainment robots and pet robots with internal-type battery are not able to operate during charging the battery. Therefore, if a robot has an autonomous function for eating battery as its feeds, the robot is not only able to operate during recharging energy but also become more human friendly like pets. Here, a new autonomous eating mechanism was introduced for a biomimetic robot, called ELIRO-II(Eating LIzard RObot version 2). The ELIRO-II is able to find a food (a small battery), eat and evacuate by itself. This work describe sub-parts of the developed mechanism such as head-part, mouth-part, and stomach-part. In addition, control system of autonomous eating mechanism is described.

Nonparametric Online Learning Control for Soft Continuum Robot: An Enabling Technique for Effective Endoscopic Navigation

PubMed Central

Lee, Kit-Hang; Fu, Denny K.C.; Leong, Martin C.W.; Chow, Marco; Fu, Hing-Choi; Althoefer, Kaspar; Sze, Kam Yim; Yeung, Chung-Kwong

2017-01-01

Abstract Bioinspired robotic structures comprising soft actuation units have attracted increasing research interest. Taking advantage of its inherent compliance, soft robots can assure safe interaction with external environments, provided that precise and effective manipulation could be achieved. Endoscopy is a typical application. However, previous model-based control approaches often require simplified geometric assumptions on the soft manipulator, but which could be very inaccurate in the presence of unmodeled external interaction forces. In this study, we propose a generic control framework based on nonparametric and online, as well as local, training to learn the inverse model directly, without prior knowledge of the robot's structural parameters. Detailed experimental evaluation was conducted on a soft robot prototype with control redundancy, performing trajectory tracking in dynamically constrained environments. Advanced element formulation of finite element analysis is employed to initialize the control policy, hence eliminating the need for random exploration in the robot's workspace. The proposed control framework enabled a soft fluid-driven continuum robot to follow a 3D trajectory precisely, even under dynamic external disturbance. Such enhanced control accuracy and adaptability would facilitate effective endoscopic navigation in complex and changing environments. PMID:29251567

Nonparametric Online Learning Control for Soft Continuum Robot: An Enabling Technique for Effective Endoscopic Navigation.

PubMed

Lee, Kit-Hang; Fu, Denny K C; Leong, Martin C W; Chow, Marco; Fu, Hing-Choi; Althoefer, Kaspar; Sze, Kam Yim; Yeung, Chung-Kwong; Kwok, Ka-Wai

2017-12-01

Bioinspired robotic structures comprising soft actuation units have attracted increasing research interest. Taking advantage of its inherent compliance, soft robots can assure safe interaction with external environments, provided that precise and effective manipulation could be achieved. Endoscopy is a typical application. However, previous model-based control approaches often require simplified geometric assumptions on the soft manipulator, but which could be very inaccurate in the presence of unmodeled external interaction forces. In this study, we propose a generic control framework based on nonparametric and online, as well as local, training to learn the inverse model directly, without prior knowledge of the robot's structural parameters. Detailed experimental evaluation was conducted on a soft robot prototype with control redundancy, performing trajectory tracking in dynamically constrained environments. Advanced element formulation of finite element analysis is employed to initialize the control policy, hence eliminating the need for random exploration in the robot's workspace. The proposed control framework enabled a soft fluid-driven continuum robot to follow a 3D trajectory precisely, even under dynamic external disturbance. Such enhanced control accuracy and adaptability would facilitate effective endoscopic navigation in complex and changing environments.

A Modular Re-configurable Rover System

NASA Astrophysics Data System (ADS)

Bouloubasis, A.; McKee, G.; Active Robotics Lab

In this paper we present the novel concepts incorporated in a planetary surface exploration rover design that is currently under development. The Multitasking Rover (MTR) aims to demonstrate functionality that will cover many of the current and future needs such as rough-terrain mobility, modularity and upgradeability [1]. The rover system has enhanced mobility characteristics. It operates in conjunction with Science Packs (SPs) and Tool Packs (TPs) - modules attached to the main frame of the rover, which are either special tools or science instruments and alter the operation capabilities of the system. To date, each rover system design is very much task driven for example, the scenario of cooperative transportation of extended payloads [2], comprises two rovers each equipped with a manipulator dedicated to the task [3]. The MTR approach focuses mostly on modularity and upgradeability presenting at the same time a fair amount of internal re-configurability for the sake of rough terrain stability. The rover itself does not carry any scientific instruments or tools. To carry out the scenario mentioned above, the MTR would have to locate and pick-up a TP with the associated manipulator. After the completion of the task the TP could be put away to a storage location enabling the rover to utilize a different Pack. The rover will not only offer mobility to these modules, but also use them as tools, transforming its role and functionality. The advantage of this approach is that instead of sending a large number of rovers to perform a variety of tasks, a smaller number of MTRs could be deployed with a large number of SPs/TPs, offering multiples of the functionality at a reduced payload. Two SPs or TPs (or a combination of) can be carried and deployed. One of the key elements in the design of the four wheeled rover, lies within its suspension system. It comprises a linear actuator located within each leg and also an active differential linking the two shoulders. This novel design allows the MTR to lift, lower, roll or tilt its body. It also provides the ability to lift any of the legs by nearly 300mm, enhancing internal re-configurability and therefore rough terrain stability off the robotic vehicle. A modular software and control architecture will be used so that integration to, and operation through the MTR, of different Packs can be demonstrated. An on-board high-level controller [4] will communicate with a small network of micro-controllers through an RS485 bus. Additional processing power could be obtained through a Pack with equivalent or higher computational capabilities. 1 The nature of the system offers many opportunities for behavior based control. The control system must accommodate not only rover based behaviors like obstacle avoidance and vehicle stabilization, but also any additional behaviors that different Packs may introduce. The Ego-Behavior Architecture (EBA) [5] comprises a number of behaviors which operate autonomously and independent of each other. This facilitates the design and suits the operation of the MTR since it fulfills the need for uncomplicated assimilation of new behaviors in the existing architecture. Our work at the moment focuses on the design and construction of the mechanical and electronic systems for the MTR and an associated Pack. References [1] NASA, Human Exploration of Mars: The Reference Mission (Version 3.0 with June, 1998 Addendum) of the NASA Mars Exploration Study Team, Exploration Office, Advanced Development Office, Lyndon B. Johnson Space Center, Houston, TX 77058, June, 1998. [2] A. Trebi-Ollennu, H Das Nayer, H Aghazarian, A ganino, P Pirjanian, B Kennedy, T Huntsberger and P Schenker, Mars Rover Pair Cooperatively Transporting a Long Payload, in Proceedings of the 2002 IEEE International Conference on Robotics and Automation, May 2002, pp. 3136-3141. [3] A. K. Bouloubasis, G. T McKee, P. S. Schenker, A Behavior-Based Manipulator for Multi-Robot Transport Tasks, in proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2003, Taipei, Taiwan, September 2003, pp. 2287-2292. [4] www.gumstix.com [5] M. G. Lewis, P. M. Sharkey, A plug and play architecture for emergent behaviour in robot control, Proceedings Configuration an Control Aspects of Mechatronics, Ilmeneau, Germany, September 1997. 2

Research on Snake-Like Robot with Controllable Scales

NASA Astrophysics Data System (ADS)

Chen, Kailin; Zhao, Yuting; Chen, Shuping

The purpose of this paper is to propose a new structure for a snake-like robot. This type of snake-like robot is different from the normal snake-like robot because it has lots of controllable scales which have a large role in helping moving. Besides, a new form of robot gait named as linear motion mode is developed based on theoretical analysis for the new mechanical structure. Through simulation and analysis in simmechanics of matlab, we proved the validity of theories about the motion mode of snake-like robot. The proposed machine construction and control method for the designed motion is verified experimentally by the independent developed snake robot.

Vision-based stabilization of nonholonomic mobile robots by integrating sliding-mode control and adaptive approach

NASA Astrophysics Data System (ADS)

Cao, Zhengcai; Yin, Longjie; Fu, Yili

2013-01-01

Vision-based pose stabilization of nonholonomic mobile robots has received extensive attention. At present, most of the solutions of the problem do not take the robot dynamics into account in the controller design, so that these controllers are difficult to realize satisfactory control in practical application. Besides, many of the approaches suffer from the initial speed and torque jump which are not practical in the real world. Considering the kinematics and dynamics, a two-stage visual controller for solving the stabilization problem of a mobile robot is presented, applying the integration of adaptive control, sliding-mode control, and neural dynamics. In the first stage, an adaptive kinematic stabilization controller utilized to generate the command of velocity is developed based on Lyapunov theory. In the second stage, adopting the sliding-mode control approach, a dynamic controller with a variable speed function used to reduce the chattering is designed, which is utilized to generate the command of torque to make the actual velocity of the mobile robot asymptotically reach the desired velocity. Furthermore, to handle the speed and torque jump problems, the neural dynamics model is integrated into the above mentioned controllers. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, the simulation of the control law is implemented in perturbed case, and the results show that the control scheme can solve the stabilization problem effectively. The proposed control law can solve the speed and torque jump problems, overcome external disturbances, and provide a new solution for the vision-based stabilization of the mobile robot.

The research on visual industrial robot which adopts fuzzy PID control algorithm

NASA Astrophysics Data System (ADS)

Feng, Yifei; Lu, Guoping; Yue, Lulin; Jiang, Weifeng; Zhang, Ye

2017-03-01

The control system of six degrees of freedom visual industrial robot based on the control mode of multi-axis motion control cards and PC was researched. For the variable, non-linear characteristics of industrial robot`s servo system, adaptive fuzzy PID controller was adopted. It achieved better control effort. In the vision system, a CCD camera was used to acquire signals and send them to video processing card. After processing, PC controls the six joints` motion by motion control cards. By experiment, manipulator can operate with machine tool and vision system to realize the function of grasp, process and verify. It has influence on the manufacturing of the industrial robot.

Positive position control of robotic manipulators

NASA Technical Reports Server (NTRS)

Baz, A.; Gumusel, L.

1989-01-01

The present, simple and accurate position-control algorithm, which is applicable to fast-moving and lightly damped robot arms, is based on the positive position feedback (PPF) strategy and relies solely on position sensors to monitor joint angles of robotic arms to furnish stable position control. The optimized tuned filters, in the form of a set of difference equations, manipulate position signals for robotic system performance. Attention is given to comparisons between this PPF-algorithm controller's experimentally ascertained performance characteristics and those of a conventional proportional controller.

Stochastic receding horizon control: application to an octopedal robot

NASA Astrophysics Data System (ADS)

Shah, Shridhar K.; Tanner, Herbert G.

2013-06-01

Miniature autonomous systems are being developed under ARL's Micro Autonomous Systems and Technology (MAST). These systems can only be fitted with a small-size processor, and their motion behavior is inherently uncertain due to manufacturing and platform-ground interactions. One way to capture this uncertainty is through a stochastic model. This paper deals with stochastic motion control design and implementation for MAST- specific eight-legged miniature crawling robots, which have been kinematically modeled as systems exhibiting the behavior of a Dubin's car with stochastic noise. The control design takes the form of stochastic receding horizon control, and is implemented on a Gumstix Overo Fire COM with 720 MHz processor and 512 MB RAM, weighing 5.5 g. The experimental results show the effectiveness of this control law for miniature autonomous systems perturbed by stochastic noise.

Actuation control of a PiezoMEMS biomimetic robotic jellyfish

NASA Astrophysics Data System (ADS)

Alejandre, Alvaro; Olszewski, Oskar; Jackson, Nathan

2017-06-01

Biomimetic micro-robots try to mimic the motion of a living system in the form of a synthetically developed microfabricated device. Dynamic motion of living systems have evolved through the years, but trying to mimic these motions is challenging. Micro-robotics are particular challenging as the fabrication of devices and controlling the motion in 3 dimensions is difficult. However, micro-scale robotics have potential to be used in a wide range of applications. MEMS based robots that can move and function in a liquid environment is of particular interest. This paper describes the development of a piezoMEMS based device that mimics the movement of a jellyfish. The paper focuses on the development of a finite element model that investigates a method of controlling the individual piezoelectric beams in order to create a jet propulsion motion, consisting of a quick excitation pulse followed by a slow recovery pulse in order to maximize thrust and velocity. By controlling the individual beams or legs of the jellyfish robot the authors can control the robot to move precisely in 3 dimensions.

Implementation of robotic force control with position accommodation

NASA Technical Reports Server (NTRS)

Ryan, Michael J.

1992-01-01

As the need for robotic manipulation in fields such as manufacturing and telerobotics increases, so does the need for effective methods of controlling the interaction forces between the manipulators and their environment. Position Accommodation (PA) is a form of robotic force control where the nominal path of the manipulator is modified in response to forces and torques sensed at the tool-tip of the manipulator. The response is tailored such that the manipulator emulates a mechanical impedance to its environment. PA falls under the category of position-based robotic force control, and may be viewed as a form of Impedance Control. The practical implementations are explored of PA into an 18 degree-of-freedom robotic testbed consisting of two PUMA 560 arms mounted on two 3 DOF positioning platforms. Single and dual-arm architectures for PA are presented along with some experimental results. Characteristics of position-based force control are discussed, along with some of the limitations of PA.

A neural learning classifier system with self-adaptive constructivism for mobile robot control.

PubMed

Hurst, Jacob; Bull, Larry

2006-01-01

For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviors. This article examines the use of constructivism-inspired mechanisms within a neural learning classifier system architecture that exploits parameter self-adaptation as an approach to realize such behavior. The system uses a rule structure in which each rule is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in simulated mazes before moving to a mobile robot platform.

Robotics and local fusion

NASA Astrophysics Data System (ADS)

Emmerman, Philip J.

2005-05-01

Teams of robots or mixed teams of warfighters and robots on reconnaissance and other missions can benefit greatly from a local fusion station. A local fusion station is defined here as a small mobile processor with interfaces to enable the ingestion of multiple heterogeneous sensor data and information streams, including blue force tracking data. These data streams are fused and integrated with contextual information (terrain features, weather, maps, dynamic background features, etc.), and displayed or processed to provide real time situational awareness to the robot controller or to the robots themselves. These blue and red force fusion applications remove redundancies, lessen ambiguities, correlate, aggregate, and integrate sensor information with context such as high resolution terrain. Applications such as safety, team behavior, asset control, training, pattern analysis, etc. can be generated or enhanced by these fusion stations. This local fusion station should also enable the interaction between these local units and a global information world.

Gesture-Based Robot Control with Variable Autonomy from the JPL Biosleeve

NASA Technical Reports Server (NTRS)

Wolf, Michael T.; Assad, Christopher; Vernacchia, Matthew T.; Fromm, Joshua; Jethani, Henna L.

2013-01-01

This paper presents a new gesture-based human interface for natural robot control. Detailed activity of the user's hand and arm is acquired via a novel device, called the BioSleeve, which packages dry-contact surface electromyography (EMG) and an inertial measurement unit (IMU) into a sleeve worn on the forearm. The BioSleeve's accompanying algorithms can reliably decode as many as sixteen discrete hand gestures and estimate the continuous orientation of the forearm. These gestures and positions are mapped to robot commands that, to varying degrees, integrate with the robot's perception of its environment and its ability to complete tasks autonomously. This flexible approach enables, for example, supervisory point-to-goal commands, virtual joystick for guarded teleoperation, and high degree of freedom mimicked manipulation, all from a single device. The BioSleeve is meant for portable field use; unlike other gesture recognition systems, use of the BioSleeve for robot control is invariant to lighting conditions, occlusions, and the human-robot spatial relationship and does not encumber the user's hands. The BioSleeve control approach has been implemented on three robot types, and we present proof-of-principle demonstrations with mobile ground robots, manipulation robots, and prosthetic hands.

Automated Kinematics Equations Generation and Constrained Motion Planning Resolution for Modular and Reconfigurable Robots

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pin, Francois G.; Love, Lonnie L.; Jung, David L.

2004-03-29

Contrary to the repetitive tasks performed by industrial robots, the tasks in most DOE missions such as environmental restoration or Decontamination and Decommissioning (D&D) can be characterized as ''batches-of-one'', in which robots must be capable of adapting to changes in constraints, tools, environment, criteria and configuration. No commercially available robot control code is suitable for use with such widely varying conditions. In this talk we present our development of a ''generic code'' to allow real time (at loop rate) robot behavior adaptation to changes in task objectives, tools, number and type of constraints, modes of controls or kinematics configuration. Wemore » present the analytical framework underlying our approach and detail the design of its two major modules for the automatic generation of the kinematics equations when the robot configuration or tools change and for the motion planning under time-varying constraints. Sample problems illustrating the capabilities of the developed system are presented.« less

Modelling and Experiment Based on a Navigation System for a Cranio-Maxillofacial Surgical Robot.

PubMed

Duan, Xingguang; Gao, Liang; Wang, Yonggui; Li, Jianxi; Li, Haoyuan; Guo, Yanjun

2018-01-01

In view of the characteristics of high risk and high accuracy in cranio-maxillofacial surgery, we present a novel surgical robot system that can be used in a variety of surgeries. The surgical robot system can assist surgeons in completing biopsy of skull base lesions, radiofrequency thermocoagulation of the trigeminal ganglion, and radioactive particle implantation of skull base malignant tumors. This paper focuses on modelling and experimental analyses of the robot system based on navigation technology. Firstly, the transformation relationship between the subsystems is realized based on the quaternion and the iterative closest point registration algorithm. The hand-eye coordination model based on optical navigation is established to control the end effector of the robot moving to the target position along the planning path. The closed-loop control method, "kinematics + optics" hybrid motion control method, is presented to improve the positioning accuracy of the system. Secondly, the accuracy of the system model was tested by model experiments. And the feasibility of the closed-loop control method was verified by comparing the positioning accuracy before and after the application of the method. Finally, the skull model experiments were performed to evaluate the function of the surgical robot system. The results validate its feasibility and are consistent with the preoperative surgical planning.

Modelling and Experiment Based on a Navigation System for a Cranio-Maxillofacial Surgical Robot

PubMed Central

Duan, Xingguang; Gao, Liang; Li, Jianxi; Li, Haoyuan; Guo, Yanjun

2018-01-01

In view of the characteristics of high risk and high accuracy in cranio-maxillofacial surgery, we present a novel surgical robot system that can be used in a variety of surgeries. The surgical robot system can assist surgeons in completing biopsy of skull base lesions, radiofrequency thermocoagulation of the trigeminal ganglion, and radioactive particle implantation of skull base malignant tumors. This paper focuses on modelling and experimental analyses of the robot system based on navigation technology. Firstly, the transformation relationship between the subsystems is realized based on the quaternion and the iterative closest point registration algorithm. The hand-eye coordination model based on optical navigation is established to control the end effector of the robot moving to the target position along the planning path. The closed-loop control method, “kinematics + optics” hybrid motion control method, is presented to improve the positioning accuracy of the system. Secondly, the accuracy of the system model was tested by model experiments. And the feasibility of the closed-loop control method was verified by comparing the positioning accuracy before and after the application of the method. Finally, the skull model experiments were performed to evaluate the function of the surgical robot system. The results validate its feasibility and are consistent with the preoperative surgical planning. PMID:29599948

Fish robotics and hydrodynamics

NASA Astrophysics Data System (ADS)

Lauder, George

2010-11-01

Studying the fluid dynamics of locomotion in freely-swimming fishes is challenging due to difficulties in controlling fish behavior. To provide better control over fish-like propulsive systems we have constructed a variety of fish-like robotic test platforms that range from highly biomimetic models of fins, to simple physical models of body movements during aquatic locomotion. First, we have constructed a series of biorobotic models of fish pectoral fins with 5 fin rays that allow detailed study of fin motion, forces, and fluid dynamics associated with fin-based locomotion. We find that by tuning fin ray stiffness and the imposed motion program we can produce thrust both on the fin outstroke and instroke. Second, we are using a robotic flapping foil system to study the self-propulsion of flexible plastic foils of varying stiffness, length, and trailing edge shape as a means of investigating the fluid dynamic effect of simple changes in the properties of undulating bodies moving through water. We find unexpected non-linear stiffness-dependent effects of changing foil length on self-propelled speed, and as well as significant effects of trailing edge shape on foil swimming speed.

Managing and capturing the physics of robotic systems

NASA Astrophysics Data System (ADS)

Werfel, Justin

Algorithmic and other theoretical analyses of robotic systems often use a discretized or otherwise idealized framework, while the real world is continuous-valued and noisy. This disconnect can make theoretical work sometimes problematic to apply successfully to real-world systems. One approach to bridging the separation can be to design hardware to take advantage of simple physical effects mechanically, in order to guide elements into a desired set of discrete attracting states. As a result, the system behavior can effectively approximate a discretized formalism, so that proofs based on an idealization remain directly relevant, while control can be made simpler. It is important to note, conversely, that such an approach does not make a physical instantiation unnecessary nor a purely theoretical treatment sufficient. Experiments with hardware in practice always reveal physical effects not originally accounted for in simulation or analytic modeling, which lead to unanticipated results and require nontrivial modifications to control algorithms in order to achieve desired outcomes. I will discuss these points in the context of swarm robotic systems recently developed at the Self-Organizing Systems Research Group at Harvard.

Path Planning for Robot based on Chaotic Artificial Potential Field Method

NASA Astrophysics Data System (ADS)

Zhang, Cheng

2018-03-01

Robot path planning in unknown environments is one of the hot research topics in the field of robot control. Aiming at the shortcomings of traditional artificial potential field methods, we propose a new path planning for Robot based on chaotic artificial potential field method. The path planning adopts the potential function as the objective function and introduces the robot direction of movement as the control variables, which combines the improved artificial potential field method with chaotic optimization algorithm. Simulations have been carried out and the results demonstrate that the superior practicality and high efficiency of the proposed method.

Practical robotic self-awareness and self-knowledge

NASA Astrophysics Data System (ADS)

Gage, Douglas W.

2011-05-01

The functional software components of an autonomous robotic system express behavior via commands to its actuators, based on processed inputs from its sensors; we propose an additional set of "cognitive" capabilities for robotic systems of all types, based on the comprehensive logging of all available data, including sensor inputs, behavioral states, and outputs sent to actuators. A robot should maintain a "sense" of its own (piecewise) continuous existence through time and space; it should in some sense "get a life," providing a level of self-awareness and self-knowledge. Self-awareness includes the ability to survive and work through unexpected power glitches while executing a task or mission. Selfknowledge includes an extensive world model including a model of self and the purpose context in which it is operating (deontics). Our system must support proactive self-test, monitoring, and calibration, and maintain a "personal" health/repair history, supporting system test and evaluation by continuously measuring performance throughout the entire product lifecycle. It will include episodic memory, and a system "lifelog," and will also participate in multiple modes of Human Robotic interaction (HRI).

Controlling robots in the home: Factors that affect the performance of novice robot operators.

PubMed

McGinn, Conor; Sena, Aran; Kelly, Kevin

2017-11-01

For robots to successfully integrate into everyday life, it is important that they can be effectively controlled by laypeople. However, the task of manually controlling mobile robots can be challenging due to demanding cognitive and sensorimotor requirements. This research explores the effect that the built environment has on the manual control of domestic service robots. In this study, a virtual reality simulation of a domestic robot control scenario was developed. The performance of fifty novice users was evaluated, and their subjective experiences recorded through questionnaires. Through quantitative and qualitative analysis, it was found that untrained operators frequently perform poorly at navigation-based robot control tasks. The study found that passing through doorways accounted for the largest number of collisions, and was consistently identified as a very difficult operation to perform. These findings suggest that homes and other human-orientated settings present significant challenges to robot control. Copyright © 2017 Elsevier Ltd. All rights reserved.

TRICCS: A proposed teleoperator/robot integrated command and control system for space applications

NASA Technical Reports Server (NTRS)

Will, R. W.

1985-01-01

Robotic systems will play an increasingly important role in space operations. An integrated command and control system based on the requirements of space-related applications and incorporating features necessary for the evolution of advanced goal-directed robotic systems is described. These features include: interaction with a world model or domain knowledge base, sensor feedback, multiple-arm capability and concurrent operations. The system makes maximum use of manual interaction at all levels for debug, monitoring, and operational reliability. It is shown that the robotic command and control system may most advantageously be implemented as packages and tasks in Ada.

Stiffening Sheaths for Continuum Robots.

PubMed

Langer, Marlene; Amanov, Ernar; Burgner-Kahrs, Jessica

2018-06-01

Added to their high dexterity and ability to conform to complex shapes, continuum robots can be further improved to provide safer interaction with their environment. Indeed, controlling their stiffness is one of the most challenging yet promising research topics. We propose a tubular stiffening sheath as a replaceable cover for small-diameter continuum robots to temporarily increase the stiffness in a certain configuration. In this article, we assess and compare performances of two different stiffening modalities: granular and layer jamming, provide arguments for material selection and experimental results for stiffness with respect to lateral and axial applied forces. Furthermore, we detected empirically additional effects relating sheath stiffness to material parameters and added to recent investigations in the state of the art, which are based exclusively on material roughness. Finally, we integrated the selected layer jamming material in a miniaturized sheath (13 mm outer diameter, 2.5 mm wall thickness) and covered a tendon-actuated continuum robot with it. Experimental characterization of the behavior with respect to applied external forces was performed via stiffness measurements and proved that the initial tendon-actuated continuum robot stiffness can be improved by a factor up to 24.

A switching formation strategy for obstacle avoidance of a multi-robot system based on robot priority model.

PubMed

Dai, Yanyan; Kim, YoonGu; Wee, SungGil; Lee, DongHa; Lee, SukGyu

2015-05-01

This paper describes a switching formation strategy for multi-robots with velocity constraints to avoid and cross obstacles. In the strategy, a leader robot plans a safe path using the geometric obstacle avoidance control method (GOACM). By calculating new desired distances and bearing angles with the leader robot, the follower robots switch into a safe formation. With considering collision avoidance, a novel robot priority model, based on the desired distance and bearing angle between the leader and follower robots, is designed during the obstacle avoidance process. The adaptive tracking control algorithm guarantees that the trajectory and velocity tracking errors converge to zero. To demonstrate the validity of the proposed methods, simulation and experiment results present that multi-robots effectively form and switch formation avoiding obstacles without collisions. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

The real-time control of planetary rovers through behavior modification

NASA Technical Reports Server (NTRS)

Miller, David P.

1991-01-01

It is not yet clear of what type, and how much, intelligence is needed for a planetary rover to function semi-autonomously on a planetary surface. Current designs assume an advanced AI system that maintains a detailed map of its journeys and the surroundings, and that carefully calculates and tests every move in advance. To achieve these abilities, and because of the limitations of space-qualified electronics, the supporting rover is quite sizable, massing a large fraction of a ton, and requiring technology advances in everything from power to ground operations. An alternative approach is to use a behavior driven control scheme. Recent research has shown that many complex tasks may be achieved by programming a robot with a set of behaviors and activation or deactivating a subset of those behaviors as required by the specific situation in which the robot finds itself. Behavior control requires much less computation than is required by tradition AI planning techniques. The reduced computation requirements allows the entire rover to be scaled down as appropriate (only down-link communications and payload do not scale under these circumstances). The missions that can be handled by the real-time control and operation of a set of small, semi-autonomous, interacting, behavior-controlled planetary rovers are discussed.

The Co-simulation of Humanoid Robot Based on Solidworks, ADAMS and Simulink

NASA Astrophysics Data System (ADS)

Song, Dalei; Zheng, Lidan; Wang, Li; Qi, Weiwei; Li, Yanli

A simulation method of adaptive controller is proposed for the humanoid robot system based on co-simulation of Solidworks, ADAMS and Simulink. A complex mathematical modeling process is avoided by this method, and the real time dynamic simulating function of Simulink would be exerted adequately. This method could be generalized to other complicated control system. This method is adopted to build and analyse the model of humanoid robot. The trajectory tracking and adaptive controller design also proceed based on it. The effect of trajectory tracking is evaluated by fitting-curve theory of least squares method. The anti-interference capability of the robot is improved a lot through comparative analysis.

A focused bibliography on robotics

NASA Astrophysics Data System (ADS)

Mergler, H. W.

1983-08-01

The present bibliography focuses on eight robotics-related topics believed by the author to be of special interest to researchers in the field of industrial electronics: robots, sensors, kinematics, dynamics, control systems, actuators, vision, economics, and robot applications. This literature search was conducted through the 1970-present COMPENDEX data base, which provides world-wide coverage of nearly 3500 journals, conference proceedings and reports, and the 1969-1981 INSPEC data base, which is the largest for the English language in the fields of physics, electrotechnology, computers, and control.

Dynamics and control of robot for capturing objects in space

NASA Astrophysics Data System (ADS)

Huang, Panfeng

Space robots are expected to perform intricate tasks in future space services, such as satellite maintenance, refueling, and replacing the orbital replacement unit (ORU). To realize these missions, the capturing operation may not be avoided. Such operations will encounter some challenges because space robots have some unique characteristics unfound on ground-based robots, such as, dynamic singularities, dynamic coupling between manipulator and space base, limited energy supply and working without a fixed base, and so on. In addition, since contacts and impacts may not be avoided during capturing operation. Therefore, dynamics and control problems of space robot for capturing objects are significant research topics if the robots are to be deployed for the space services. A typical servicing operation mainly includes three phases: capturing the object, berthing and docking the object, then repairing the target. Therefore, this thesis will focus on resolving some challenging problems during capturing the object, berthing and docking, and so on. In this thesis, I study and analyze the dynamics and control problems of space robot for capturing objects. This work has potential impact in space robotic applications. I first study the contact and impact dynamics of space robot and objects. I specifically focus on analyzing the impact dynamics and mapping the relationship of influence and speed. Then, I develop the fundamental theory for planning the minimum-collision based trajectory of space robot and designing the configuration of space robot at the moment of capture. To compensate for the attitude of the space base during the capturing approach operation, a new balance control concept which can effectively balance the attitude of the space base using the dynamic couplings is developed. The developed balance control concept helps to understand of the nature of space dynamic coupling, and can be readily applied to compensate or minimize the disturbance to the space base. After capturing the object, the space robot must complete the following two tasks: one is to berth the object, and the other is to re-orientate the attitude of the whole robot system for communication and power supply. Therefore, I propose a method to accomplish these two tasks simultaneously using manipulator motion only. The ultimate goal of space services is to realize the capture and manipulation autonomously. Therefore, I propose an affective approach based on learning human skill to track and capture the objects automatically in space. With human-teaching demonstration, the space robot is able to learn and abstract human tracking and capturing skill using an efficient neural-network learning architecture that combines flexible Cascade Neural Networks with Node Decoupled Extended Kalman Filtering (CNN-NDEKF). The simulation results attest that this approach is useful and feasible in tracking trajectory planning and capturing of space robot. Finally I propose a novel approach based on Genetic Algorithms (GAs) to optimize the approach trajectory of space robots in order to realize effective and stable operations. I complete the minimum-torque path planning in order to save the limited energy in space, and design the minimum jerk trajectory for the stabilization of the space manipulator and its space base. These optimal algorithms are very important and useful for the application of space robot.

Robots show us how to teach them: feedback from robots shapes tutoring behavior during action learning.

PubMed

Vollmer, Anna-Lisa; Mühlig, Manuel; Steil, Jochen J; Pitsch, Karola; Fritsch, Jannik; Rohlfing, Katharina J; Wrede, Britta

2014-01-01

Robot learning by imitation requires the detection of a tutor's action demonstration and its relevant parts. Current approaches implicitly assume a unidirectional transfer of knowledge from tutor to learner. The presented work challenges this predominant assumption based on an extensive user study with an autonomously interacting robot. We show that by providing feedback, a robot learner influences the human tutor's movement demonstrations in the process of action learning. We argue that the robot's feedback strongly shapes how tutors signal what is relevant to an action and thus advocate a paradigm shift in robot action learning research toward truly interactive systems learning in and benefiting from interaction.

Robots Show Us How to Teach Them: Feedback from Robots Shapes Tutoring Behavior during Action Learning

PubMed Central

Vollmer, Anna-Lisa; Mühlig, Manuel; Steil, Jochen J.; Pitsch, Karola; Fritsch, Jannik; Rohlfing, Katharina J.; Wrede, Britta

2014-01-01

Robot learning by imitation requires the detection of a tutor's action demonstration and its relevant parts. Current approaches implicitly assume a unidirectional transfer of knowledge from tutor to learner. The presented work challenges this predominant assumption based on an extensive user study with an autonomously interacting robot. We show that by providing feedback, a robot learner influences the human tutor's movement demonstrations in the process of action learning. We argue that the robot's feedback strongly shapes how tutors signal what is relevant to an action and thus advocate a paradigm shift in robot action learning research toward truly interactive systems learning in and benefiting from interaction. PMID:24646510

The magic glove: a gesture-based remote controller for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Luo, Chaomin; Chen, Yue; Krishnan, Mohan; Paulik, Mark

2012-01-01

This paper describes the design of a gesture-based Human Robot Interface (HRI) for an autonomous mobile robot entered in the 2010 Intelligent Ground Vehicle Competition (IGVC). While the robot is meant to operate autonomously in the various Challenges of the competition, an HRI is useful in moving the robot to the starting position and after run termination. In this paper, a user-friendly gesture-based embedded system called the Magic Glove is developed for remote control of a robot. The system consists of a microcontroller and sensors that is worn by the operator as a glove and is capable of recognizing hand signals. These are then transmitted through wireless communication to the robot. The design of the Magic Glove included contributions on two fronts: hardware configuration and algorithm development. A triple axis accelerometer used to detect hand orientation passes the information to a microcontroller, which interprets the corresponding vehicle control command. A Bluetooth device interfaced to the microcontroller then transmits the information to the vehicle, which acts accordingly. The user-friendly Magic Glove was successfully demonstrated first in a Player/Stage simulation environment. The gesture-based functionality was then also successfully verified on an actual robot and demonstrated to judges at the 2010 IGVC.

Gait Planning and Stability Control of a Quadruped Robot

PubMed Central

Li, Junmin; Wang, Jinge; Yang, Simon X.; Zhou, Kedong; Tang, Huijuan

2016-01-01

In order to realize smooth gait planning and stability control of a quadruped robot, a new controller algorithm based on CPG-ZMP (central pattern generator-zero moment point) is put forward in this paper. To generate smooth gait and shorten the adjusting time of the model oscillation system, a new CPG model controller and its gait switching strategy based on Wilson-Cowan model are presented in the paper. The control signals of knee-hip joints are obtained by the improved multi-DOF reduced order control theory. To realize stability control, the adaptive speed adjustment and gait switch are completed by the real-time computing of ZMP. Experiment results show that the quadruped robot's gaits are efficiently generated and the gait switch is smooth in the CPG control algorithm. Meanwhile, the stability of robot's movement is improved greatly with the CPG-ZMP algorithm. The algorithm in this paper has good practicability, which lays a foundation for the production of the robot prototype. PMID:27143959

Gait Planning and Stability Control of a Quadruped Robot.

PubMed

Li, Junmin; Wang, Jinge; Yang, Simon X; Zhou, Kedong; Tang, Huijuan

2016-01-01

In order to realize smooth gait planning and stability control of a quadruped robot, a new controller algorithm based on CPG-ZMP (central pattern generator-zero moment point) is put forward in this paper. To generate smooth gait and shorten the adjusting time of the model oscillation system, a new CPG model controller and its gait switching strategy based on Wilson-Cowan model are presented in the paper. The control signals of knee-hip joints are obtained by the improved multi-DOF reduced order control theory. To realize stability control, the adaptive speed adjustment and gait switch are completed by the real-time computing of ZMP. Experiment results show that the quadruped robot's gaits are efficiently generated and the gait switch is smooth in the CPG control algorithm. Meanwhile, the stability of robot's movement is improved greatly with the CPG-ZMP algorithm. The algorithm in this paper has good practicability, which lays a foundation for the production of the robot prototype.

Model-based Robotic Dynamic Motion Control for the Robonaut 2 Humanoid Robot

NASA Technical Reports Server (NTRS)

Badger, Julia M.; Hulse, Aaron M.; Taylor, Ross C.; Curtis, Andrew W.; Gooding, Dustin R.; Thackston, Allison

2013-01-01

Robonaut 2 (R2), an upper-body dexterous humanoid robot, has been undergoing experimental trials on board the International Space Station (ISS) for more than a year. R2 will soon be upgraded with two climbing appendages, or legs, as well as a new integrated model-based control system. This control system satisfies two important requirements; first, that the robot can allow humans to enter its workspace during operation and second, that the robot can move its large inertia with enough precision to attach to handrails and seat track while climbing around the ISS. This is achieved by a novel control architecture that features an embedded impedance control law on the motor drivers called Multi-Loop control which is tightly interfaced with a kinematic and dynamic coordinated control system nicknamed RoboDyn that resides on centralized processors. This paper presents the integrated control algorithm as well as several test results that illustrate R2's safety features and performance.

Two Formal Gas Models For Multi-Agent Sweeping and Obstacle Avoidance

NASA Technical Reports Server (NTRS)

Kerr, Wesley; Spears, Diana; Spears, William; Thayer, David

2004-01-01

The task addressed here is a dynamic search through a bounded region, while avoiding multiple large obstacles, such as buildings. In the case of limited sensors and communication, maintaining spatial coverage - especially after passing the obstacles - is a challenging problem. Here, we investigate two physics-based approaches to solving this task with multiple simulated mobile robots, one based on artificial forces and the other based on the kinetic theory of gases. The desired behavior is achieved with both methods, and a comparison is made between them. Because both approaches are physics-based, formal assurances about the multi-robot behavior are straightforward, and are included in the paper.

Biologically-inspired hexapod robot design and simulation

NASA Technical Reports Server (NTRS)

Espenschied, Kenneth S.; Quinn, Roger D.

1994-01-01

The design and construction of a biologically-inspired hexapod robot is presented. A previously developed simulation is modified to include models of the DC drive motors, the motor driver circuits and their transmissions. The application of this simulation to the design and development of the robot is discussed. The mechanisms thought to be responsible for the leg coordination of the walking stick insect were previously applied to control the straight-line locomotion of a robot. We generalized these rules for a robot walking on a plane. This biologically-inspired control strategy is used to control the robot in simulation. Numerical results show that the general body motion and performance of the simulated robot is similar to that of the robot based on our preliminary experimental results.

Soft Robotics: New Perspectives for Robot Bodyware and Control

PubMed Central

Laschi, Cecilia; Cianchetti, Matteo

2014-01-01

The remarkable advances of robotics in the last 50 years, which represent an incredible wealth of knowledge, are based on the fundamental assumption that robots are chains of rigid links. The use of soft materials in robotics, driven not only by new scientific paradigms (biomimetics, morphological computation, and others), but also by many applications (biomedical, service, rescue robots, and many more), is going to overcome these basic assumptions and makes the well-known theories and techniques poorly applicable, opening new perspectives for robot design and control. The current examples of soft robots represent a variety of solutions for actuation and control. Though very first steps, they have the potential for a radical technological change. Soft robotics is not just a new direction of technological development, but a novel approach to robotics, unhinging its fundamentals, with the potential to produce a new generation of robots, in the support of humans in our natural environments. PMID:25022259

Imparting protean behavior to mobile robots accomplishing patrolling tasks in the presence of adversaries.

PubMed

Curiac, Daniel-Ioan; Volosencu, Constantin

2015-10-08

Providing unpredictable trajectories for patrol robots is essential when coping with adversaries. In order to solve this problem we developed an effective approach based on the known protean behavior of individual prey animals-random zig-zag movement. The proposed bio-inspired method modifies the normal robot's path by incorporating sudden and irregular direction changes without jeopardizing the robot's mission. Such a tactic is aimed to confuse the enemy (e.g. a sniper), offering less time to acquire and retain sight alignment and sight picture. This idea is implemented by simulating a series of fictive-temporary obstacles that will randomly appear in the robot's field of view, deceiving the obstacle avoiding mechanism to react. The new general methodology is particularized by using the Arnold's cat map to obtain the timely random appearance and disappearance of the fictive obstacles. The viability of the proposed method is confirmed through an extensive simulation case study.

Experientally guided robots. [for planet exploration

NASA Technical Reports Server (NTRS)

Merriam, E. W.; Becker, J. D.

1974-01-01

This paper argues that an experientally guided robot is necessary to successfully explore far-away planets. Such a robot is characterized as having sense organs which receive sensory information from its environment and motor systems which allow it to interact with that environment. The sensori-motor information which it receives is organized into an experiential knowledge structure and this knowledge in turn is used to guide the robot's future actions. A summary is presented of a problem solving system which is being used as a test bed for developing such a robot. The robot currently engages in the behaviors of visual tracking, focusing down, and looking around in a simulated Martian landscape. Finally, some unsolved problems are outlined whose solutions are necessary before an experientally guided robot can be produced. These problems center around organizing the motivational and memory structure of the robot and understanding its high-level control mechanisms.

Tracking control of a closed-chain five-bar robot with two degrees of freedom by integration of an approximation-based approach and mechanical design.

PubMed

Cheng, Long; Hou, Zeng-Guang; Tan, Min; Zhang, W J

2012-10-01

The trajectory tracking problem of a closed-chain five-bar robot is studied in this paper. Based on an error transformation function and the backstepping technique, an approximation-based tracking algorithm is proposed, which can guarantee the control performance of the robotic system in both the stable and transient phases. In particular, the overshoot, settling time, and final tracking error of the robotic system can be all adjusted by properly setting the parameters in the error transformation function. The radial basis function neural network (RBFNN) is used to compensate the complicated nonlinear terms in the closed-loop dynamics of the robotic system. The approximation error of the RBFNN is only required to be bounded, which simplifies the initial "trail-and-error" configuration of the neural network. Illustrative examples are given to verify the theoretical analysis and illustrate the effectiveness of the proposed algorithm. Finally, it is also shown that the proposed approximation-based controller can be simplified by a smart mechanical design of the closed-chain robot, which demonstrates the promise of the integrated design and control philosophy.

A visual servo-based teleoperation robot system for closed diaphyseal fracture reduction.

PubMed

Li, Changsheng; Wang, Tianmiao; Hu, Lei; Zhang, Lihai; Du, Hailong; Zhao, Lu; Wang, Lifeng; Tang, Peifu

2015-09-01

Common fracture treatments include open reduction and intramedullary nailing technology. However, these methods have disadvantages such as intraoperative X-ray radiation, delayed union or nonunion and postoperative rotation. Robots provide a novel solution to the aforementioned problems while posing new challenges. Against this scientific background, we develop a visual servo-based teleoperation robot system. In this article, we present a robot system, analyze the visual servo-based control system in detail and develop path planning for fracture reduction, inverse kinematics, and output forces of the reduction mechanism. A series of experimental tests is conducted on a bone model and an animal bone. The experimental results demonstrate the feasibility of the robot system. The robot system uses preoperative computed tomography data to realize high precision and perform minimally invasive teleoperation for fracture reduction via the visual servo-based control system while protecting surgeons from radiation. © IMechE 2015.

An overview on real-time control schemes for wheeled mobile robot

NASA Astrophysics Data System (ADS)

Radzak, M. S. A.; Ali, M. A. H.; Sha’amri, S.; Azwan, A. R.

2018-04-01

The purpose of this paper is to review real-time control motion algorithms for wheeled mobile robot (WMR) when navigating in environment such as road. Its need a good controller to avoid collision with any disturbance and maintain a track error at zero level. The controllers are used with other aiding sensors to measure the WMR’s velocities, posture, and interference to estimate the required torque to be applied on the wheels of mobile robot. Four main categories for wheeled mobile robot control systems have been found in literature which are namely: Kinematic based controller, Dynamic based controllers, artificial intelligence based control system, and Active Force control. A MATLAB/Simulink software is the main software to simulate and implement the control system. The real-time toolbox in MATLAB/SIMULINK are used to receive/send data from sensors/to actuator with presence of disturbances, however others software such C, C++ and visual basic are rare to be used.

Crew/Robot Coordinated Planetary EVA Operations at a Lunar Base Analog Site

NASA Technical Reports Server (NTRS)

Diftler, M. A.; Ambrose, R. O.; Bluethmann, W. J.; Delgado, F. J.; Herrera, E.; Kosmo, J. J.; Janoiko, B. A.; Wilcox, B. H.; Townsend, J. A.; Matthews, J. B.;

Navigation strategies for multiple autonomous mobile robots moving in formation

NASA Technical Reports Server (NTRS)

Wang, P. K. C.

1991-01-01

The problem of deriving navigation strategies for a fleet of autonomous mobile robots moving in formation is considered. Here, each robot is represented by a particle with a spherical effective spatial domain and a specified cone of visibility. The global motion of each robot in the world space is described by the equations of motion of the robot's center of mass. First, methods for formation generation are discussed. Then, simple navigation strategies for robots moving in formation are derived. A sufficient condition for the stability of a desired formation pattern for a fleet of robots each equipped with the navigation strategy based on nearest neighbor tracking is developed. The dynamic behavior of robot fleets consisting of three or more robots moving in formation in a plane is studied by means of computer simulation.

A Hybrid Robotic Control System Using Neuroblastoma Cultures

NASA Astrophysics Data System (ADS)

Ferrández, J. M.; Lorente, V.; Cuadra, J. M.; Delapaz, F.; Álvarez-Sánchez, José Ramón; Fernández, E.

The main objective of this work is to analyze the computing capabilities of human neuroblastoma cultured cells and to define connection schemes for controlling a robot behavior. Multielectrode Array (MEA) setups have been designed for direct culturing neural cells over silicon or glass substrates, providing the capability to stimulate and record simultaneously populations of neural cells. This paper describes the process of growing human neuroblastoma cells over MEA substrates and tries to modulate the natural physiologic responses of these cells by tetanic stimulation of the culture. We show that the large neuroblastoma networks developed in cultured MEAs are capable of learning: establishing numerous and dynamic connections, with modifiability induced by external stimuli and we propose an hybrid system for controlling a robot to avoid obstacles.

Memetic Engineering as a Basis for Learning in Robotic Communities

NASA Technical Reports Server (NTRS)

Truszkowski, Walter F.; Rouff, Christopher; Akhavannik, Mohammad H.

2014-01-01

This paper represents a new contribution to the growing literature on memes. While most memetic thought has been focused on its implications on humans, this paper speculates on the role that memetics can have on robotic communities. Though speculative, the concepts are based on proven advanced multi agent technology work done at NASA - Goddard Space Flight Center and Lockheed Martin. The paper is composed of the following sections : 1) An introductory section which gently leads the reader into the realm of memes. 2) A section on memetic engineering which addresses some of the central issues with robotic learning via memes. 3) A section on related work which very concisely identifies three other areas of memetic applications, i.e., news, psychology, and the study of human behaviors. 4) A section which discusses the proposed approach for realizing memetic behaviors in robots and robotic communities. 5) A section which presents an exploration scenario for a community of robots working on Mars. 6) A final section which discusses future research which will be required to realize a comprehensive science of robotic memetics.

Electroencephalography (EEG) Based Control in Assistive Mobile Robots: A Review

NASA Astrophysics Data System (ADS)

Krishnan, N. Murali; Mariappan, Muralindran; Muthukaruppan, Karthigayan; Hijazi, Mohd Hanafi Ahmad; Kitt, Wong Wei

2016-03-01

Recently, EEG based control in assistive robot usage has been gradually increasing in the area of biomedical field for giving quality and stress free life for disabled and elderly people. This study reviews the deployment of EGG based control in assistive robots, especially for those who in need and neurologically disabled. The main objective of this paper is to describe the methods used for (i) EEG data acquisition and signal preprocessing, (ii) feature extraction and (iii) signal classification methods. Besides that, this study presents the specific research challenges in the designing of these control systems and future research directions.

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots.

PubMed

Zhao, Jing; Li, Wei; Mao, Xiaoqian; Li, Mengfan

2015-11-24

Brain-Robot Interaction (BRI), which provides an innovative communication pathway between human and a robotic device via brain signals, is prospective in helping the disabled in their daily lives. The overall goal of our method is to establish an SSVEP-based experimental procedure by integrating multiple software programs, such as OpenViBE, Choregraph, and Central software as well as user developed programs written in C++ and MATLAB, to enable the study of brain-robot interaction with humanoid robots. This is achieved by first placing EEG electrodes on a human subject to measure the brain responses through an EEG data acquisition system. A user interface is used to elicit SSVEP responses and to display video feedback in the closed-loop control experiments. The second step is to record the EEG signals of first-time subjects, to analyze their SSVEP features offline, and to train the classifier for each subject. Next, the Online Signal Processor and the Robot Controller are configured for the online control of a humanoid robot. As the final step, the subject completes three specific closed-loop control experiments within different environments to evaluate the brain-robot interaction performance. The advantage of this approach is its reliability and flexibility because it is developed by integrating multiple software programs. The results show that using this approach, the subject is capable of interacting with the humanoid robot via brain signals. This allows the mind-controlled humanoid robot to perform typical tasks that are popular in robotic research and are helpful in assisting the disabled.

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

PubMed Central

Zhao, Jing; Li, Wei; Mao, Xiaoqian; Li, Mengfan

2015-01-01

Brain-Robot Interaction (BRI), which provides an innovative communication pathway between human and a robotic device via brain signals, is prospective in helping the disabled in their daily lives. The overall goal of our method is to establish an SSVEP-based experimental procedure by integrating multiple software programs, such as OpenViBE, Choregraph, and Central software as well as user developed programs written in C++ and MATLAB, to enable the study of brain-robot interaction with humanoid robots. This is achieved by first placing EEG electrodes on a human subject to measure the brain responses through an EEG data acquisition system. A user interface is used to elicit SSVEP responses and to display video feedback in the closed-loop control experiments. The second step is to record the EEG signals of first-time subjects, to analyze their SSVEP features offline, and to train the classifier for each subject. Next, the Online Signal Processor and the Robot Controller are configured for the online control of a humanoid robot. As the final step, the subject completes three specific closed-loop control experiments within different environments to evaluate the brain-robot interaction performance. The advantage of this approach is its reliability and flexibility because it is developed by integrating multiple software programs. The results show that using this approach, the subject is capable of interacting with the humanoid robot via brain signals. This allows the mind-controlled humanoid robot to perform typical tasks that are popular in robotic research and are helpful in assisting the disabled. PMID:26650051

Telerobot control system

NASA Technical Reports Server (NTRS)

Backes, Paul G. (Inventor); Tso, Kam S. (Inventor)

1993-01-01

This invention relates to an operator interface for controlling a telerobot to perform tasks in a poorly modeled environment and/or within unplanned scenarios. The telerobot control system includes a remote robot manipulator linked to an operator interface. The operator interface includes a setup terminal, simulation terminal, and execution terminal for the control of the graphics simulator and local robot actuator as well as the remote robot actuator. These terminals may be combined in a single terminal. Complex tasks are developed from sequential combinations of parameterized task primitives and recorded teleoperations, and are tested by execution on a graphics simulator and/or local robot actuator, together with adjustable time delays. The novel features of this invention include the shared and supervisory control of the remote robot manipulator via operator interface by pretested complex tasks sequences based on sequences of parameterized task primitives combined with further teleoperation and run-time binding of parameters based on task context.

High degree-of-freedom dynamic manipulation

NASA Astrophysics Data System (ADS)

Murphy, Michael P.; Stephens, Benjamin; Abe, Yeuhi; Rizzi, Alfred A.

2012-06-01

The creation of high degree of freedom dynamic mobile manipulation techniques and behaviors will allow robots to accomplish difficult tasks in the field. We are investigating the use of the body and legs of legged robots to improve the strength, velocity, and workspace of an integrated manipulator to accomplish dynamic manipulation. This is an especially challenging task, as all of the degrees of freedom are active at all times, the dynamic forces generated are high, and the legged system must maintain robust balance throughout the duration of the tasks. To accomplish this goal, we are utilizing trajectory optimization techniques to generate feasible open-loop behaviors for our 28 dof quadruped robot (BigDog) by planning the trajectories in a 13 dimensional space. Covariance Matrix Adaptation techniques are utilized to optimize for several criteria such as payload capability and task completion speed while also obeying constraints such as torque and velocity limits, kinematic limits, and center of pressure location. These open-loop behaviors are then used to generate feed-forward terms, which are subsequently used online to improve tracking and maintain low controller gains. Some initial results on one of our existing balancing quadruped robots with an additional human-arm-like manipulator are demonstrated on robot hardware, including dynamic lifting and throwing of heavy objects 16.5kg cinder blocks, using motions that resemble a human athlete more than typical robotic motions. Increased payload capacity is accomplished through coordinated body motion.

Trajectory tracking control for a nonholonomic mobile robot under ROS

NASA Astrophysics Data System (ADS)

Lakhdar Besseghieur, Khadir; Trębiński, Radosław; Kaczmarek, Wojciech; Panasiuk, Jarosław

2018-05-01

In this paper, the implementation of the trajectory tracking control strategy on a ROS-based mobile robot is considered. Our test-bench is the nonholonomic mobile robot ‘TURTLEBOT’. ROS facilitates considerably setting-up a suitable environment to test the designed controller. Our aim is to develop a framework using ROS concepts so that a trajectory tracking controller can be implemented on any ROS-enabled mobile robot. Practical experiments with ‘TURTLEBOT’ are conducted to assess the framework reliability.

A simple highly efficient non invasive EMG-based HMI.

PubMed

Vitiello, N; Olcese, U; Oddo, C M; Carpaneto, J; Micera, S; Carrozza, M C; Dario, P

2006-01-01

Muscle activity recorded non-invasively is sufficient to control a mobile robot if it is used in combination with an algorithm for its asynchronous analysis. In this paper, we show that several subjects successfully can control the movements of a robot in a structured environment made up of six rooms by contracting two different muscles using a simple algorithm. After a small training period, subjects were able to control the robot with performances comparable to those achieved manually controlling the robot.

Distributed and Modular CAN-Based Architecture for Hardware Control and Sensor Data Integration

PubMed Central

Losada, Diego P.; Fernández, Joaquín L.; Paz, Enrique; Sanz, Rafael

2017-01-01

In this article, we present a CAN-based (Controller Area Network) distributed system to integrate sensors, actuators and hardware controllers in a mobile robot platform. With this work, we provide a robust, simple, flexible and open system to make hardware elements or subsystems communicate, that can be applied to different robots or mobile platforms. Hardware modules can be connected to or disconnected from the CAN bus while the system is working. It has been tested in our mobile robot Rato, based on a RWI (Real World Interface) mobile platform, to replace the old sensor and motor controllers. It has also been used in the design of two new robots: BellBot and WatchBot. Currently, our hardware integration architecture supports different sensors, actuators and control subsystems, such as motor controllers and inertial measurement units. The integration architecture was tested and compared with other solutions through a performance analysis of relevant parameters such as transmission efficiency and bandwidth usage. The results conclude that the proposed solution implements a lightweight communication protocol for mobile robot applications that avoids transmission delays and overhead. PMID:28467381

Distributed and Modular CAN-Based Architecture for Hardware Control and Sensor Data Integration.

PubMed

Losada, Diego P; Fernández, Joaquín L; Paz, Enrique; Sanz, Rafael

2017-05-03

In this article, we present a CAN-based (Controller Area Network) distributed system to integrate sensors, actuators and hardware controllers in a mobile robot platform. With this work, we provide a robust, simple, flexible and open system to make hardware elements or subsystems communicate, that can be applied to different robots or mobile platforms. Hardware modules can be connected to or disconnected from the CAN bus while the system is working. It has been tested in our mobile robot Rato, based on a RWI (Real World Interface) mobile platform, to replace the old sensor and motor controllers. It has also been used in the design of two new robots: BellBot and WatchBot. Currently, our hardware integration architecture supports different sensors, actuators and control subsystems, such as motor controllers and inertial measurement units. The integration architecture was tested and compared with other solutions through a performance analysis of relevant parameters such as transmission efficiency and bandwidth usage. The results conclude that the proposed solution implements a lightweight communication protocol for mobile robot applications that avoids transmission delays and overhead.

Interactions With Robots: The Truths We Reveal About Ourselves.

PubMed

Broadbent, Elizabeth

2017-01-03

In movies, robots are often extremely humanlike. Although these robots are not yet reality, robots are currently being used in healthcare, education, and business. Robots provide benefits such as relieving loneliness and enabling communication. Engineers are trying to build robots that look and behave like humans and thus need comprehensive knowledge not only of technology but also of human cognition, emotion, and behavior. This need is driving engineers to study human behavior toward other humans and toward robots, leading to greater understanding of how humans think, feel, and behave in these contexts, including our tendencies for mindless social behaviors, anthropomorphism, uncanny feelings toward robots, and the formation of emotional attachments. However, in considering the increased use of robots, many people have concerns about deception, privacy, job loss, safety, and the loss of human relationships. Human-robot interaction is a fascinating field and one in which psychologists have much to contribute, both to the development of robots and to the study of human behavior.

Some aspects of robotics calibration, design and control

NASA Technical Reports Server (NTRS)

Tawfik, Hazem

1990-01-01

The main objective is to introduce techniques in the areas of testing and calibration, design, and control of robotic systems. A statistical technique is described that analyzes a robot's performance and provides quantitative three-dimensional evaluation of its repeatability, accuracy, and linearity. Based on this analysis, a corrective action should be taken to compensate for any existing errors and enhance the robot's overall accuracy and performance. A comparison between robotics simulation software packages that were commercially available (SILMA, IGRIP) and that of Kennedy Space Center (ROBSIM) is also included. These computer codes simulate the kinematics and dynamics patterns of various robot arm geometries to help the design engineer in sizing and building the robot manipulator and control system. A brief discussion on an adaptive control algorithm is provided.

State-of-the-art robotic devices for ankle rehabilitation: Mechanism and control review.

PubMed

Hussain, Shahid; Jamwal, Prashant K; Ghayesh, Mergen H

2017-12-01

There is an increasing research interest in exploring use of robotic devices for the physical therapy of patients suffering from stroke and spinal cord injuries. Rehabilitation of patients suffering from ankle joint dysfunctions such as drop foot is vital and therefore has called for the development of newer robotic devices. Several robotic orthoses and parallel ankle robots have been developed during the last two decades to augment the conventional ankle physical therapy of patients. A comprehensive review of these robotic ankle rehabilitation devices is presented in this article. Recent developments in the mechanism design, actuation and control are discussed. The study encompasses robotic devices for treadmill and over-ground training as well as platform-based parallel ankle robots. Control strategies for these robotic devices are deliberated in detail with an emphasis on the assist-as-needed training strategies. Experimental evaluations of the mechanism designs and various control strategies of these robotic ankle rehabilitation devices are also presented.

Nonlinear disturbance observer based sliding mode control of a cable-driven rehabilitation robot.

PubMed

Niu, Jie; Yang, Qianqian; Chen, Guangtao; Song, Rong

2017-07-01

This paper introduces a cable-driven robot for upper-limb rehabilitation. Kinematic and dynamic of this rehabilitation robot is analyzed. A sliding mode controller combined with a nonlinear disturbance observer is proposed to control this robot in the presence of disturbances. Simulation is carried out to prove the effectiveness of the proposed control scheme, and the results of the proposed controller is compared with a PID controller and a traditional sliding mode controller. Results show that the proposed controller can effectively improve the tracking performance as compared with the other two controllers and cause lower chattering as compared with a traditional sliding mode controller.

Piezoelectrically Actuated Robotic System for MRI-Guided Prostate Percutaneous Therapy

PubMed Central

Su, Hao; Shang, Weijian; Cole, Gregory; Li, Gang; Harrington, Kevin; Camilo, Alexander; Tokuda, Junichi; Tempany, Clare M.; Hata, Nobuhiko; Fischer, Gregory S.

2014-01-01

This paper presents a fully-actuated robotic system for percutaneous prostate therapy under continuously acquired live magnetic resonance imaging (MRI) guidance. The system is composed of modular hardware and software to support the surgical workflow of intra-operative MRI-guided surgical procedures. We present the development of a 6-degree-of-freedom (DOF) needle placement robot for transperineal prostate interventions. The robot consists of a 3-DOF needle driver module and a 3-DOF Cartesian motion module. The needle driver provides needle cannula translation and rotation (2-DOF) and stylet translation (1-DOF). A custom robot controller consisting of multiple piezoelectric motor drivers provides precision closed-loop control of piezoelectric motors and enables simultaneous robot motion and MR imaging. The developed modular robot control interface software performs image-based registration, kinematics calculation, and exchanges robot commands and coordinates between the navigation software and the robot controller with a new implementation of the open network communication protocol OpenIGTLink. Comprehensive compatibility of the robot is evaluated inside a 3-Tesla MRI scanner using standard imaging sequences and the signal-to-noise ratio (SNR) loss is limited to 15%. The image deterioration due to the present and motion of robot demonstrates unobservable image interference. Twenty-five targeted needle placements inside gelatin phantoms utilizing an 18-gauge ceramic needle demonstrated 0.87 mm root mean square (RMS) error in 3D Euclidean distance based on MRI volume segmentation of the image-guided robotic needle placement procedure. PMID:26412962

Extracting motor synergies from random movements for low-dimensional task-space control of musculoskeletal robots.

PubMed

Fu, Kin Chung Denny; Dalla Libera, Fabio; Ishiguro, Hiroshi

2015-10-08

In the field of human motor control, the motor synergy hypothesis explains how humans simplify body control dimensionality by coordinating groups of muscles, called motor synergies, instead of controlling muscles independently. In most applications of motor synergies to low-dimensional control in robotics, motor synergies are extracted from given optimal control signals. In this paper, we address the problems of how to extract motor synergies without optimal data given, and how to apply motor synergies to achieve low-dimensional task-space tracking control of a human-like robotic arm actuated by redundant muscles, without prior knowledge of the robot. We propose to extract motor synergies from a subset of randomly generated reaching-like movement data. The essence is to first approximate the corresponding optimal control signals, using estimations of the robot's forward dynamics, and to extract the motor synergies subsequently. In order to avoid modeling difficulties, a learning-based control approach is adopted such that control is accomplished via estimations of the robot's inverse dynamics. We present a kernel-based regression formulation to estimate the forward and the inverse dynamics, and a sliding controller in order to cope with estimation error. Numerical evaluations show that the proposed method enables extraction of motor synergies for low-dimensional task-space control.

A PIC microcontroller-based system for real-life interfacing of external peripherals with a mobile robot

NASA Astrophysics Data System (ADS)

Singh, N. Nirmal; Chatterjee, Amitava; Rakshit, Anjan

2010-02-01

The present article describes the development of a peripheral interface controller (PIC) microcontroller-based system for interfacing external add-on peripherals with a real mobile robot, for real life applications. This system serves as an important building block of a complete integrated vision-based mobile robot system, integrated indigenously in our laboratory. The system is composed of the KOALA mobile robot in conjunction with a personal computer (PC) and a two-camera-based vision system where the PIC microcontroller is used to drive servo motors, in interrupt-driven mode, to control additional degrees of freedom of the vision system. The performance of the developed system is tested by checking it under the control of several user-specified commands, issued from the PC end.

Effectiveness of Social Behaviors for Autonomous Wheelchair Robot to Support Elderly People in Japan

PubMed Central

Shiomi, Masahiro; Iio, Takamasa; Kamei, Koji; Sharma, Chandraprakash; Hagita, Norihiro

2015-01-01

We developed a wheelchair robot to support the movement of elderly people and specifically implemented two functions to enhance their intention to use it: speaking behavior to convey place/location related information and speed adjustment based on individual preferences. Our study examines how the evaluations of our wheelchair robot differ when compared with human caregivers and a conventional autonomous wheelchair without the two proposed functions in a moving support context. 28 senior citizens participated in the experiment to evaluate three different conditions. Our measurements consisted of questionnaire items and the coding of free-style interview results. Our experimental results revealed that elderly people evaluated our wheelchair robot higher than the wheelchair without the two functions and the human caregivers for some items. PMID:25993038

Classifying a Person's Degree of Accessibility From Natural Body Language During Social Human-Robot Interactions.

PubMed

McColl, Derek; Jiang, Chuan; Nejat, Goldie

2017-02-01

For social robots to be successfully integrated and accepted within society, they need to be able to interpret human social cues that are displayed through natural modes of communication. In particular, a key challenge in the design of social robots is developing the robot's ability to recognize a person's affective states (emotions, moods, and attitudes) in order to respond appropriately during social human-robot interactions (HRIs). In this paper, we present and discuss social HRI experiments we have conducted to investigate the development of an accessibility-aware social robot able to autonomously determine a person's degree of accessibility (rapport, openness) toward the robot based on the person's natural static body language. In particular, we present two one-on-one HRI experiments to: 1) determine the performance of our automated system in being able to recognize and classify a person's accessibility levels and 2) investigate how people interact with an accessibility-aware robot which determines its own behaviors based on a person's speech and accessibility levels.

Emergent of Burden Sharing of Robots with Emotion Model

NASA Astrophysics Data System (ADS)

Kusano, Takuya; Nozawa, Akio; Ide, Hideto

Cooperated multi robots system has much dominance in comparison with single robot system. Multi robots system is able to adapt to various circumstances and has a flexibility for variation of tasks. Robots are necessary that build a cooperative relations and acts as an organization to attain a purpose in multi robots system. Then, group behavior of insects which doesn't have advanced ability is observed. For example, ants called a sociality insect emerge systematic activities by the interaction with using a very simple way. Though ants make a communication with chemical matter, a human plans a communication by words and gestures. In this paper, we paid attention to the interaction based on psychological viewpoint. And a human's emotion model was used for the parameter which became a base of the motion planning of robots. These robots were made to do both-way action in test field with obstacle. As a result, a burden sharing like guide or carrier was seen even though those had a simple setup.

Human-Robot Interaction in High Vulnerability Domains

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2016-01-01

Future NASA missions will require successful integration of the human with highly complex systems. Highly complex systems are likely to involve humans, automation, and some level of robotic assistance. The complex environments will require successful integration of the human with automation, with robots, and with human-automation-robot teams to accomplish mission critical goals. Many challenges exist for the human performing in these types of operational environments with these kinds of systems. Systems must be designed to optimally integrate various levels of inputs and outputs based on the roles and responsibilities of the human, the automation, and the robots; from direct manual control, shared human-robotic control, or no active human control (i.e. human supervisory control). It is assumed that the human will remain involved at some level. Technologies that vary based on contextual demands and on operator characteristics (workload, situation awareness) will be needed when the human integrates into these systems. Predictive models that estimate the impact of the technologies on the system performance and the on the human operator are also needed to meet the challenges associated with such future complex human-automation-robot systems in extreme environments.

Acquiring neural signals for developing a perception and cognition model

NASA Astrophysics Data System (ADS)

Li, Wei; Li, Yunyi; Chen, Genshe; Shen, Dan; Blasch, Erik; Pham, Khanh; Lynch, Robert

2012-06-01

The understanding of how humans process information, determine salience, and combine seemingly unrelated information is essential to automated processing of large amounts of information that is partially relevant, or of unknown relevance. Recent neurological science research in human perception, and in information science regarding contextbased modeling, provides us with a theoretical basis for using a bottom-up approach for automating the management of large amounts of information in ways directly useful for human operators. However, integration of human intelligence into a game theoretic framework for dynamic and adaptive decision support needs a perception and cognition model. For the purpose of cognitive modeling, we present a brain-computer-interface (BCI) based humanoid robot system to acquire brainwaves during human mental activities of imagining a humanoid robot-walking behavior. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model. The BCI system consists of a data acquisition unit with an electroencephalograph (EEG), a humanoid robot, and a charge couple CCD camera. An EEG electrode cup acquires brainwaves from the skin surface on scalp. The humanoid robot has 20 degrees of freedom (DOFs); 12 DOFs located on hips, knees, and ankles for humanoid robot walking, 6 DOFs on shoulders and arms for arms motion, and 2 DOFs for head yaw and pitch motion. The CCD camera takes video clips of the human subject's hand postures to identify mental activities that are correlated to the robot-walking behaviors. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model.

Combining psychological and engineering approaches to utilizing social robots with children with autism.

PubMed

Dickstein-Fischer, Laurie; Fischer, Gregory S

2014-01-01

It is estimated that Autism Spectrum Disorder (ASD) affects 1 in 68 children. Early identification of an ASD is exceedingly important to the introduction of an intervention. We are developing a robot-assisted approach that will serve as an improved diagnostic and early intervention tool for children with autism. The robot, named PABI® (Penguin for Autism Behavioral Interventions), is a compact humanoid robot taking on an expressive cartoon-like embodiment. The robot is affordable, durable, and portable so that it can be used in various settings including schools, clinics, and the home. Thus enabling significantly enhanced and more readily available diagnosis and continuation of care. Through facial expressions, body motion, verbal cues, stereo vision-based tracking, and a tablet computer, the robot is capable of interacting meaningfully with an autistic child. Initial implementations of the robot, as part of a comprehensive treatment model (CTM), include Applied Behavioral Analysis (ABA) therapy where the child interacts with a tablet computer wirelessly interfaced with the robot. At the same time, the robot makes meaningful expressions and utterances and uses stereo cameras in eyes to track the child, maintain eye contact, and collect data such as affect and gaze direction for charting of progress. In this paper we present the clinical justification, anticipated usage with corresponding requirements, prototype development of the robotic system, and demonstration of a sample application for robot-assisted ABA therapy.

TROTER's (Tiny Robotic Operation Team Experiment): A new concept of space robots

NASA Technical Reports Server (NTRS)

Su, Renjeng

1990-01-01

In view of the future need of automation and robotics in space and the existing approaches to the problem, we proposed a new concept of robots for space construction. The new concept is based on the basic idea of decentralization. Decentralization occurs, on the one hand, in using teams of many cooperative robots for construction tasks. Redundancy and modular design are explored to achieve high reliability for team robotic operations. Reliability requirement on individual robots is greatly reduced. Another area of decentralization is manifested by the proposed control hierarchy which eventually includes humans in the loop. The control strategy is constrained by various time delays and calls for different levels of abstraction of the task dynamics. Such technology is needed for remote control of robots in an uncertain environment. Thus, concerns of human safety around robots are relaxed. This presentation also introduces the required technologies behind the new robotic concept.

Obstacle negotiation control for a mobile robot suspended on overhead ground wires by optoelectronic sensors

NASA Astrophysics Data System (ADS)

Zheng, Li; Yi, Ruan

2009-11-01

Power line inspection and maintenance already benefit from developments in mobile robotics. This paper presents mobile robots capable of crossing obstacles on overhead ground wires. A teleoperated robot realizes inspection and maintenance tasks on power transmission line equipment. The inspection robot is driven by 11 motor with two arms, two wheels and two claws. The inspection robot is designed to realize the function of observation, grasp, walk, rolling, turn, rise, and decline. This paper is oriented toward 100% reliable obstacle detection and identification, and sensor fusion to increase the autonomy level. An embedded computer based on PC/104 bus is chosen as the core of control system. Visible light camera and thermal infrared Camera are both installed in a programmable pan-and-tilt camera (PPTC) unit. High-quality visual feedback rapidly becomes crucial for human-in-the-loop control and effective teleoperation. The communication system between the robot and the ground station is based on Mesh wireless networks by 700 MHz bands. An expert system programmed with Visual C++ is developed to implement the automatic control. Optoelectronic laser sensors and laser range scanner were installed in robot for obstacle-navigation control to grasp the overhead ground wires. A novel prototype with careful considerations on mobility was designed to inspect the 500KV power transmission lines. Results of experiments demonstrate that the robot can be applied to execute the navigation and inspection tasks.

On-Line Method and Apparatus for Coordinated Mobility and Manipulation of Mobile Robots

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1996-01-01

A simple and computationally efficient approach is disclosed for on-line coordinated control of mobile robots consisting of a manipulator arm mounted on a mobile base. The effect of base mobility on the end-effector manipulability index is discussed. The base mobility and arm manipulation degrees-of-freedom are treated equally as the joints of a kinematically redundant composite robot. The redundancy introduced by the mobile base is exploited to satisfy a set of user-defined additional tasks during the end-effector motion. A simple on-line control scheme is proposed which allows the user to assign weighting factors to individual degrees-of-mobility and degrees-of-manipulation, as well as to each task specification. The computational efficiency of the control algorithm makes it particularly suitable for real-time implementations. Four case studies are discussed in detail to demonstrate the application of the coordinated control scheme to various mobile robots.

Design and control of an embedded vision guided robotic fish with multiple control surfaces.

PubMed

Yu, Junzhi; Wang, Kai; Tan, Min; Zhang, Jianwei

2014-01-01

This paper focuses on the development and control issues of a self-propelled robotic fish with multiple artificial control surfaces and an embedded vision system. By virtue of the hybrid propulsion capability in the body plus the caudal fin and the complementary maneuverability in accessory fins, a synthesized propulsion scheme including a caudal fin, a pair of pectoral fins, and a pelvic fin is proposed. To achieve flexible yet stable motions in aquatic environments, a central pattern generator- (CPG-) based control method is employed. Meanwhile, a monocular underwater vision serves as sensory feedback that modifies the control parameters. The integration of the CPG-based motion control and the visual processing in an embedded microcontroller allows the robotic fish to navigate online. Aquatic tests demonstrate the efficacy of the proposed mechatronic design and swimming control methods. Particularly, a pelvic fin actuated sideward swimming gait was first implemented. It is also found that the speeds and maneuverability of the robotic fish with coordinated control surfaces were largely superior to that of the swimming robot propelled by a single control surface.

Design and Control of an Embedded Vision Guided Robotic Fish with Multiple Control Surfaces

PubMed Central

Wang, Kai; Tan, Min; Zhang, Jianwei

2014-01-01

This paper focuses on the development and control issues of a self-propelled robotic fish with multiple artificial control surfaces and an embedded vision system. By virtue of the hybrid propulsion capability in the body plus the caudal fin and the complementary maneuverability in accessory fins, a synthesized propulsion scheme including a caudal fin, a pair of pectoral fins, and a pelvic fin is proposed. To achieve flexible yet stable motions in aquatic environments, a central pattern generator- (CPG-) based control method is employed. Meanwhile, a monocular underwater vision serves as sensory feedback that modifies the control parameters. The integration of the CPG-based motion control and the visual processing in an embedded microcontroller allows the robotic fish to navigate online. Aquatic tests demonstrate the efficacy of the proposed mechatronic design and swimming control methods. Particularly, a pelvic fin actuated sideward swimming gait was first implemented. It is also found that the speeds and maneuverability of the robotic fish with coordinated control surfaces were largely superior to that of the swimming robot propelled by a single control surface. PMID:24688413

Tegotae-based decentralised control scheme for autonomous gait transition of snake-like robots.

PubMed

Kano, Takeshi; Yoshizawa, Ryo; Ishiguro, Akio

2017-08-04

Snakes change their locomotion patterns in response to the environment. This ability is a motivation for developing snake-like robots with highly adaptive functionality. In this study, a decentralised control scheme of snake-like robots that exhibited autonomous gait transition (i.e. the transition between concertina locomotion in narrow aisles and scaffold-based locomotion on unstructured terrains) was developed. Additionally, the control scheme was validated via simulations. A key insight revealed is that these locomotion patterns were not preprogrammed but emerged by exploiting Tegotae, a concept that describes the extent to which a perceived reaction matches a generated action. Unlike local reflexive mechanisms proposed previously, the Tegotae-based feedback mechanism enabled the robot to 'selectively' exploit environments beneficial for propulsion, and generated reasonable locomotion patterns. It is expected that the results of this study can form the basis to design robots that can work under unpredictable and unstructured environments.

i-SAIRAS '90; Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space, Kobe, Japan, Nov. 18-20, 1990

NASA Technical Reports Server (NTRS)

1990-01-01

The present conference on artificial intelligence (AI), robotics, and automation in space encompasses robot systems, lunar and planetary robots, advanced processing, expert systems, knowledge bases, issues of operation and management, manipulator control, and on-orbit service. Specific issues addressed include fundamental research in AI at NASA, the FTS dexterous telerobot, a target-capture experiment by a free-flying robot, the NASA Planetary Rover Program, the Katydid system for compiling KEE applications to Ada, and speech recognition for robots. Also addressed are a knowledge base for real-time diagnosis, a pilot-in-the-loop simulation of an orbital docking maneuver, intelligent perturbation algorithms for space scheduling optimization, a fuzzy control method for a space manipulator system, hyperredundant manipulator applications, robotic servicing of EOS instruments, and a summary of astronaut inputs on automation and robotics for the Space Station Freedom.

Rhythm Patterns Interaction - Synchronization Behavior for Human-Robot Joint Action

PubMed Central

Mörtl, Alexander; Lorenz, Tamara; Hirche, Sandra

2014-01-01

Interactive behavior among humans is governed by the dynamics of movement synchronization in a variety of repetitive tasks. This requires the interaction partners to perform for example rhythmic limb swinging or even goal-directed arm movements. Inspired by that essential feature of human interaction, we present a novel concept and design methodology to synthesize goal-directed synchronization behavior for robotic agents in repetitive joint action tasks. The agents’ tasks are described by closed movement trajectories and interpreted as limit cycles, for which instantaneous phase variables are derived based on oscillator theory. Events segmenting the trajectories into multiple primitives are introduced as anchoring points for enhanced synchronization modes. Utilizing both continuous phases and discrete events in a unifying view, we design a continuous dynamical process synchronizing the derived modes. Inverse to the derivation of phases, we also address the generation of goal-directed movements from the behavioral dynamics. The developed concept is implemented to an anthropomorphic robot. For evaluation of the concept an experiment is designed and conducted in which the robot performs a prototypical pick-and-place task jointly with human partners. The effectiveness of the designed behavior is successfully evidenced by objective measures of phase and event synchronization. Feedback gathered from the participants of our exploratory study suggests a subjectively pleasant sense of interaction created by the interactive behavior. The results highlight potential applications of the synchronization concept both in motor coordination among robotic agents and in enhanced social interaction between humanoid agents and humans. PMID:24752212

A comparison of force control algorithms for robots in contact with flexible environments

NASA Technical Reports Server (NTRS)

Wilfinger, Lee S.

1992-01-01

In order to perform useful tasks, the robot end-effector must come into contact with its environment. For such tasks, force feedback is frequently used to control the interaction forces. Control of these forces is complicated by the fact that the flexibility of the environment affects the stability of the force control algorithm. Because of the wide variety of different materials present in everyday environments, it is necessary to gain an understanding of how environmental flexibility affects the stability of force control algorithms. This report presents the theory and experimental results of two force control algorithms: Position Accommodation Control and Direct Force Servoing. The implementation of each of these algorithms on a two-arm robotic test bed located in the Center for Intelligent Robotic Systems for Space Exploration (CIRSSE) is discussed in detail. The behavior of each algorithm when contacting materials of different flexibility is experimentally determined. In addition, several robustness improvements to the Direct Force Servoing algorithm are suggested and experimentally verified. Finally, a qualitative comparison of the force control algorithms is provided, along with a description of a general tuning process for each control method.

Building adaptive connectionist-based controllers: review of experiments in human-robot interaction, collective robotics, and computational neuroscience

NASA Astrophysics Data System (ADS)

Billard, Aude

2000-10-01

This paper summarizes a number of experiments in biologically inspired robotics. The common feature to all experiments is the use of artificial neural networks as the building blocks for the controllers. The experiments speak in favor of using a connectionist approach for designing adaptive and flexible robot controllers, and for modeling neurological processes. I present 1) DRAMA, a novel connectionist architecture, which has general property for learning time series and extracting spatio-temporal regularities in multi-modal and highly noisy data; 2) Robota, a doll-shaped robot, which imitates and learns a proto-language; 3) an experiment in collective robotics, where a group of 4 to 15 Khepera robots learn dynamically the topography of an environment whose features change frequently; 4) an abstract, computational model of primate ability to learn by imitation; 5) a model for the control of locomotor gaits in a quadruped legged robot.

Tracking Control of Mobile Robots Localized via Chained Fusion of Discrete and Continuous Epipolar Geometry, IMU and Odometry.

PubMed

Tick, David; Satici, Aykut C; Shen, Jinglin; Gans, Nicholas

2013-08-01

This paper presents a novel navigation and control system for autonomous mobile robots that includes path planning, localization, and control. A unique vision-based pose and velocity estimation scheme utilizing both the continuous and discrete forms of the Euclidean homography matrix is fused with inertial and optical encoder measurements to estimate the pose, orientation, and velocity of the robot and ensure accurate localization and control signals. A depth estimation system is integrated in order to overcome the loss of scale inherent in vision-based estimation. A path following control system is introduced that is capable of guiding the robot along a designated curve. Stability analysis is provided for the control system and experimental results are presented that prove the combined localization and control system performs with high accuracy.

Dynamical network interactions in distributed control of robots

NASA Astrophysics Data System (ADS)

Buscarino, Arturo; Fortuna, Luigi; Frasca, Mattia; Rizzo, Alessandro

2006-03-01

In this paper the dynamical network model of the interactions within a group of mobile robots is investigated and proposed as a possible strategy for controlling the robots without central coordination. Motivated by the results of the analysis of our simple model, we show that the system performance in the presence of noise can be improved by including long-range connections between the robots. Finally, a suitable strategy based on this model to control exploration and transport is introduced.

A new approach for modular robot system behavioral modeling: Base on Petri net and category theory

NASA Astrophysics Data System (ADS)

Zhang, Yun; Wei, Hongxing; Yang, Bo

2018-04-01

To design modular robot system, Petri nets and category theory are combined and the ability of simulation of Petri net is discussed. According to category theory, the method of describing the category of components in the dynamic characteristics of the system is deduced. Moreover, a modular robot system is analyzed, which provides a verifiable description of the dynamic characteristics of the system.

Multi-layer robot skin with embedded sensors and muscles

NASA Astrophysics Data System (ADS)

Tomar, Ankit; Tadesse, Yonas

2016-04-01

Soft artificial skin with embedded sensors and actuators is proposed for a crosscutting study of cognitive science on a facial expressive humanoid platform. This paper focuses on artificial muscles suitable for humanoid robots and prosthetic devices for safe human-robot interactions. Novel composite artificial skin consisting of sensors and twisted polymer actuators is proposed. The artificial skin is conformable to intricate geometries and includes protective layers, sensor layers, and actuation layers. Fluidic channels are included in the elastomeric skin to inject fluids in order to control actuator response time. The skin can be used to develop facially expressive humanoid robots or other soft robots. The humanoid robot can be used by computer scientists and other behavioral science personnel to test various algorithms, and to understand and develop more perfect humanoid robots with facial expression capability. The small-scale humanoid robots can also assist ongoing therapeutic treatment research with autistic children. The multilayer skin can be used for many soft robots enabling them to detect both temperature and pressure, while actuating the entire structure.

Experimental robot gripper control for handling of soft objects

NASA Astrophysics Data System (ADS)

Friedrich, Werner E.; Ziegler, T. H.; Lim, P.

1996-10-01

The challenging task of automated handling of variable objects necessitates a combination of innovative engineering and advanced information technology. This paper describes the application of a recently developed control strategy applied to overcome some limitations of robot handling, particularly when dealing with variable objects. The paper focuses on a novel approach to accommodate the need for sensing and actuation in controlling the pickup procedure. An experimental robot-based system for the handling of soft parts, ranging from artificial components to natural objects such as fruit and meat pieces was developed. The configuration comprises a modular gripper subsystem, and an industrial robot as part of a distributed control system. The gripper subsystem features manually configurable fingers with integrated sensing capabilities. The control architecture is based on a concept of decentralized control differentiating between positioning and gripping procedures. In this way, the robot and gripper systems are treated as individual handling operations. THis concept allows very short set-up times for future changes involving one or more sub-systems.

A sub-target approach to the kinodynamic motion control of a wheeled mobile robot

NASA Astrophysics Data System (ADS)

Motonaka, Kimiko; Watanabe, Keigo; Maeyama, Shoichi

2018-02-01

A mobile robot with two independently driven wheels is popular, but it is difficult to stabilize it by a continuous controller with a constant gain, due to its nonholonomic property. It is guaranteed that a nonholonomic controlled object can always be converged to an arbitrary point using a switching control method or a quasi-continuous control method based on an invariant manifold in a chained form. From this, the authors already proposed a kinodynamic controller to converge the states of such a two-wheeled mobile robot to the arbitrary target position while avoiding obstacles, by combining the control based on the invariant manifold and the harmonic potential field (HPF). On the other hand, it was confirmed in the previous research that there is a case that the robot cannot avoid the obstacle because there is no enough space to converge the current state to the target state. In this paper, we propose a method that divides the final target position into some sub-target positions and moves the robot step by step, and it is confirmed by the simulation that the robot can converge to the target position while avoiding obstacles using the proposed method.

Fuzzy variable impedance control based on stiffness identification for human-robot cooperation

NASA Astrophysics Data System (ADS)

Mao, Dachao; Yang, Wenlong; Du, Zhijiang

2017-06-01

This paper presents a dynamic fuzzy variable impedance control algorithm for human-robot cooperation. In order to estimate the intention of human for co-manipulation, a fuzzy inference system is set up to adjust the impedance parameter. Aiming at regulating the output fuzzy universe based on the human arm’s stiffness, an online stiffness identification method is developed. A drag interaction task is conducted on a 5-DOF robot with variable impedance control. Experimental results demonstrate that the proposed algorithm is superior.

Control of free-flying space robot manipulator systems

NASA Technical Reports Server (NTRS)

Cannon, Robert H., Jr.

1988-01-01

The focus of the work is to develop and perform a set of research projects using laboratory models of satellite robots. These devices use air cushion technology to simulate in two dimensions the drag-free, zero-g conditions of space. Five research areas are examined: cooperative manipulation on a fixed base; cooperative manipulation on a free-floating base; global navigation and control of a free-floating robot; an alternative transport mode call Locomotion Enhancement via Arm Push-Off (LEAP), and adaptive control of LEAP.

A motion sensing-based framework for robotic manipulation.

PubMed

Deng, Hao; Xia, Zeyang; Weng, Shaokui; Gan, Yangzhou; Fang, Peng; Xiong, Jing

2016-01-01

To data, outside of the controlled environments, robots normally perform manipulation tasks operating with human. This pattern requires the robot operators with high technical skills training for varied teach-pendant operating system. Motion sensing technology, which enables human-machine interaction in a novel and natural interface using gestures, has crucially inspired us to adopt this user-friendly and straightforward operation mode on robotic manipulation. Thus, in this paper, we presented a motion sensing-based framework for robotic manipulation, which recognizes gesture commands captured from motion sensing input device and drives the action of robots. For compatibility, a general hardware interface layer was also developed in the framework. Simulation and physical experiments have been conducted for preliminary validation. The results have shown that the proposed framework is an effective approach for general robotic manipulation with motion sensing control.

High level language-based robotic control system

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Inventor); Kruetz, Kenneth K. (Inventor); Jain, Abhinandan (Inventor)

1994-01-01

This invention is a robot control system based on a high level language implementing a spatial operator algebra. There are two high level languages included within the system. At the highest level, applications programs can be written in a robot-oriented applications language including broad operators such as MOVE and GRASP. The robot-oriented applications language statements are translated into statements in the spatial operator algebra language. Programming can also take place using the spatial operator algebra language. The statements in the spatial operator algebra language from either source are then translated into machine language statements for execution by a digital control computer. The system also includes the capability of executing the control code sequences in a simulation mode before actual execution to assure proper action at execution time. The robot's environment is checked as part of the process and dynamic reconfiguration is also possible. The languages and system allow the programming and control of multiple arms and the use of inward/outward spatial recursions in which every computational step can be related to a transformation from one point in the mechanical robot to another point to name two major advantages.

High level language-based robotic control system

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Inventor); Kreutz, Kenneth K. (Inventor); Jain, Abhinandan (Inventor)

1996-01-01

This invention is a robot control system based on a high level language implementing a spatial operator algebra. There are two high level languages included within the system. At the highest level, applications programs can be written in a robot-oriented applications language including broad operators such as MOVE and GRASP. The robot-oriented applications language statements are translated into statements in the spatial operator algebra language. Programming can also take place using the spatial operator algebra language. The statements in the spatial operator algebra language from either source are then translated into machine language statements for execution by a digital control computer. The system also includes the capability of executing the control code sequences in a simulation mode before actual execution to assure proper action at execution time. The robot's environment is checked as part of the process and dynamic reconfiguration is also possible. The languages and system allow the programming and control of multiple arms and the use of inward/outward spatial recursions in which every computational step can be related to a transformation from one point in the mechanical robot to another point to name two major advantages.

A task control architecture for autonomous robots

NASA Technical Reports Server (NTRS)

Simmons, Reid; Mitchell, Tom

1990-01-01

An architecture is presented for controlling robots that have multiple tasks, operate in dynamic domains, and require a fair degree of autonomy. The architecture is built on several layers of functionality, including a distributed communication layer, a behavior layer for querying sensors, expanding goals, and executing commands, and a task level for managing the temporal aspects of planning and achieving goals, coordinating tasks, allocating resources, monitoring, and recovering from errors. Application to a legged planetary rover and an indoor mobile manipulator is described.

Robot-Arm Dynamic Control by Computer

NASA Technical Reports Server (NTRS)

Bejczy, Antal K.; Tarn, Tzyh J.; Chen, Yilong J.

1987-01-01

Feedforward and feedback schemes linearize responses to control inputs. Method for control of robot arm based on computed nonlinear feedback and state tranformations to linearize system and decouple robot end-effector motions along each of cartesian axes augmented with optimal scheme for correction of errors in workspace. Major new feature of control method is: optimal error-correction loop directly operates on task level and not on joint-servocontrol level.

Extending human proprioception to cyber-physical systems

NASA Astrophysics Data System (ADS)

Keller, Kevin; Robinson, Ethan; Dickstein, Leah; Hahn, Heidi A.; Cattaneo, Alessandro; Mascareñas, David

2016-04-01

Despite advances in computational cognition, there are many cyber-physical systems where human supervision and control is desirable. One pertinent example is the control of a robot arm, which can be found in both humanoid and commercial ground robots. Current control mechanisms require the user to look at several screens of varying perspective on the robot, then give commands through a joystick-like mechanism. This control paradigm fails to provide the human operator with an intuitive state feedback, resulting in awkward and slow behavior and underutilization of the robot's physical capabilities. To overcome this bottleneck, we introduce a new human-machine interface that extends the operator's proprioception by exploiting sensory substitution. Humans have a proprioceptive sense that provides us information on how our bodies are configured in space without having to directly observe our appendages. We constructed a wearable device with vibrating actuators on the forearm, where frequency of vibration corresponds to the spatial configuration of a robotic arm. The goal of this interface is to provide a means to communicate proprioceptive information to the teleoperator. Ultimately we will measure the change in performance (time taken to complete the task) achieved by the use of this interface.

Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning

PubMed Central

Baykal, Cenk; Torres, Luis G.; Alterovitz, Ron

2015-01-01

Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot’s behavior and reachable workspace. Optimizing a robot’s design by appropriately selecting tube parameters can improve the robot’s effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot’s configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy. PMID:26951790

Neural Network-Based Landmark Recognition and Navigation with IAMRs. Understanding the Principles of Thought and Behavior.

ERIC Educational Resources Information Center

Doty, Keith L.

1999-01-01

Research on neural networks and hippocampal function demonstrating how mammals construct mental maps and develop navigation strategies is being used to create Intelligent Autonomous Mobile Robots (IAMRs). Such robots are able to recognize landmarks and navigate without "vision." (SK)

Watching from a distance: A robotically controlled laser and real-time subject tracking software for the study of conditioned predator/prey-like interactions.

PubMed

Wilson, James C; Kesler, Mitch; Pelegrin, Sara-Lynn E; Kalvi, LeAnna; Gruber, Aaron; Steenland, Hendrik W

2015-09-30

The physical distance between predator and prey is a primary determinant of behavior, yet few paradigms exist to study this reliably in rodents. The utility of a robotically controlled laser for use in a predator-prey-like (PPL) paradigm was explored for use in rats. This involved the construction of a robotic two-dimensional gimbal to dynamically position a laser beam in a behavioral test chamber. Custom software was used to control the trajectory and final laser position in response to user input on a console. The software also detected the location of the laser beam and the rodent continuously so that the dynamics of the distance between them could be analyzed. When the animal or laser beam came within a fixed distance the animal would either be rewarded with electrical brain stimulation or shocked subcutaneously. Animals that received rewarding electrical brain stimulation could learn to chase the laser beam, while animals that received aversive subcutaneous shock learned to actively avoid the laser beam in the PPL paradigm. Mathematical computations are presented which describe the dynamic interaction of the laser and rodent. The robotic laser offers a neutral stimulus to train rodents in an open field and is the first device to be versatile enough to assess distance between predator and prey in real time. With ongoing behavioral testing this tool will permit the neurobiological investigation of predator/prey-like relationships in rodents, and may have future implications for prosthetic limb development through brain-machine interfaces. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of a soft untethered robot using artificial muscle actuators

NASA Astrophysics Data System (ADS)

Cao, Jiawei; Qin, Lei; Lee, Heow Pueh; Zhu, Jian

2017-04-01

Soft robots have attracted much interest recently, due to their potential capability to work effectively in unstructured environment. Soft actuators are key components in soft robots. Dielectric elastomer actuators are one class of soft actuators, which can deform in response to voltage. Dielectric elastomer actuators exhibit interesting attributes including large voltage-induced deformation and high energy density. These attributes make dielectric elastomer actuators capable of functioning as artificial muscles for soft robots. It is significant to develop untethered robots, since connecting the cables to external power sources greatly limits the robots' functionalities, especially autonomous movements. In this paper we develop a soft untethered robot based on dielectric elastomer actuators. This robot mainly consists of a deformable robotic body and two paper-based feet. The robotic body is essentially a dielectric elastomer actuator, which can expand or shrink at voltage on or off. In addition, the two feet can achieve adhesion or detachment based on the mechanism of electroadhesion. In general, the entire robotic system can be controlled by electricity or voltage. By optimizing the mechanical design of the robot (the size and weight of electric circuits), we put all these components (such as batteries, voltage amplifiers, control circuits, etc.) onto the robotic feet, and the robot is capable of realizing autonomous movements. Experiments are conducted to study the robot's locomotion. Finite element method is employed to interpret the deformation of dielectric elastomer actuators, and the simulations are qualitatively consistent with the experimental observations.

Cooperative path following control of multiple nonholonomic mobile robots.

PubMed

Cao, Ke-Cai; Jiang, Bin; Yue, Dong

2017-11-01

Cooperative path following control problem of multiple nonholonomic mobile robots has been considered in this paper. Based on the framework of decomposition, the cooperative path following problem has been transformed into path following problem and cooperative control problem; Then cascaded theory of non-autonomous system has been employed in the design of controllers without resorting to feedback linearization. One time-varying coordinate transformation based on dilation has been introduced to solve the uncontrollable problem of nonholonomic robots when the whole group's reference converges to stationary point. Cooperative path following controllers for nonholonomic robots have been proposed under persistent reference or reference target that converges to stationary point respectively. Simulation results using Matlab have illustrated the effectiveness of the obtained theoretical results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

3D force control for robotic-assisted beating heart surgery based on viscoelastic tissue model.

PubMed

Liu, Chao; Moreira, Pedro; Zemiti, Nabil; Poignet, Philippe

2011-01-01

Current cardiac surgery faces the challenging problem of heart beating motion even with the help of mechanical stabilizer which makes delicate operation on the heart surface difficult. Motion compensation methods for robotic-assisted beating heart surgery have been proposed recently in literature, but research on force control for such kind of surgery has hardly been reported. Moreover, the viscoelasticity property of the interaction between organ tissue and robotic instrument further complicates the force control design which is much easier in other applications by assuming the interaction model to be elastic (industry, stiff object manipulation, etc.). In this work, we present a three-dimensional force control method for robotic-assisted beating heart surgery taking into consideration of the viscoelastic interaction property. Performance studies based on our D2M2 robot and 3D heart beating motion information obtained through Da Vinci™ system are provided.

Automatic behavior sensing for a bomb-detecting dog

NASA Astrophysics Data System (ADS)

Nguyen, Hoa G.; Nans, Adam; Talke, Kurt; Candela, Paul; Everett, H. R.

2015-05-01

Bomb-detecting dogs are trained to detect explosives through their sense of smell and often perform a specific behavior to indicate a possible bomb detection. This behavior is noticed by the dog handler, who confirms the probable explosives, determines the location, and forwards the information to an explosive ordnance disposal (EOD) team. To improve the speed and accuracy of this process and better integrate it with the EOD team's robotic explosive disposal operation, SPAWAR Systems Center Pacific has designed and prototyped an electronic dog collar that automatically tracks the dog's location and attitude, detects the indicative behavior, and records the data. To account for the differences between dogs, a 5-minute training routine can be executed before the mission to establish initial values for the k-mean clustering algorithm that classifies a specific dog's behavior. The recorded data include GPS location of the suspected bomb, the path the dog took to approach this location, and a video clip covering the detection event. The dog handler reviews and confirms the data before it is packaged up and forwarded on to the EOD team. The EOD team uses the video clip to better identify the type of bomb and for awareness of the surrounding environment before they arrive at the scene. Before the robotic neutralization operation commences at the site, the location and path data (which are supplied in a format understandable by the next-generation EOD robots—the Advanced EOD Robotic System) can be loaded into the robotic controller to automatically guide the robot to the bomb site. This paper describes the project with emphasis on the dog-collar hardware, behavior-classification software, and feasibility testing.

Toward anthropomimetic robotics: development, simulation, and control of a musculoskeletal torso.

PubMed

Wittmeier, Steffen; Alessandro, Cristiano; Bascarevic, Nenad; Dalamagkidis, Konstantinos; Devereux, David; Diamond, Alan; Jäntsch, Michael; Jovanovic, Kosta; Knight, Rob; Marques, Hugo Gravato; Milosavljevic, Predrag; Mitra, Bhargav; Svetozarevic, Bratislav; Potkonjak, Veljko; Pfeifer, Rolf; Knoll, Alois; Holland, Owen

2013-01-01

Anthropomimetic robotics differs from conventional approaches by capitalizing on the replication of the inner structures of the human body, such as muscles, tendons, bones, and joints. Here we present our results of more than three years of research in constructing, simulating, and, most importantly, controlling anthropomimetic robots. We manufactured four physical torsos, each more complex than its predecessor, and developed the tools required to simulate their behavior. Furthermore, six different control approaches, inspired by classical control theory, machine learning, and neuroscience, were developed and evaluated via these simulations or in small-scale setups. While the obtained results are encouraging, we are aware that we have barely exploited the potential of the anthropomimetic design so far. But, with the tools developed, we are confident that this novel approach will contribute to our understanding of morphological computation and human motor control in the future.

Toward autonomous spacecraft

NASA Technical Reports Server (NTRS)

Fogel, L. J.; Calabrese, P. G.; Walsh, M. J.; Owens, A. J.

1982-01-01

Ways in which autonomous behavior of spacecraft can be extended to treat situations wherein a closed loop control by a human may not be appropriate or even possible are explored. Predictive models that minimize mean least squared error and arbitrary cost functions are discussed. A methodology for extracting cyclic components for an arbitrary environment with respect to usual and arbitrary criteria is developed. An approach to prediction and control based on evolutionary programming is outlined. A computer program capable of predicting time series is presented. A design of a control system for a robotic dense with partially unknown physical properties is presented.

Integration of advanced teleoperation technologies for control of space robots

NASA Technical Reports Server (NTRS)

Stagnaro, Michael J.

1993-01-01

Teleoperated robots require one or more humans to control actuators, mechanisms, and other robot equipment given feedback from onboard sensors. To accomplish this task, the human or humans require some form of control station. Desirable features of such a control station include operation by a single human, comfort, and natural human interfaces (visual, audio, motion, tactile, etc.). These interfaces should work to maximize performance of the human/robot system by streamlining the link between human brain and robot equipment. This paper describes development of a control station testbed with the characteristics described above. Initially, this testbed will be used to control two teleoperated robots. Features of the robots include anthropomorphic mechanisms, slaving to the testbed, and delivery of sensory feedback to the testbed. The testbed will make use of technologies such as helmet mounted displays, voice recognition, and exoskeleton masters. It will allow tor integration and testing of emerging telepresence technologies along with techniques for coping with control link time delays. Systems developed from this testbed could be applied to ground control of space based robots. During man-tended operations, the Space Station Freedom may benefit from ground control of IVA or EVA robots with science or maintenance tasks. Planetary exploration may also find advanced teleoperation systems to be very useful.

A graphical, rule based robotic interface system

NASA Technical Reports Server (NTRS)

Mckee, James W.; Wolfsberger, John

1988-01-01

The ability of a human to take control of a robotic system is essential in any use of robots in space in order to handle unforeseen changes in the robot's work environment or scheduled tasks. But in cases in which the work environment is known, a human controlling a robot's every move by remote control is both time consuming and frustrating. A system is needed in which the user can give the robotic system commands to perform tasks but need not tell the system how. To be useful, this system should be able to plan and perform the tasks faster than a telerobotic system. The interface between the user and the robot system must be natural and meaningful to the user. A high level user interface program under development at the University of Alabama, Huntsville, is described. A graphical interface is proposed in which the user selects objects to be manipulated by selecting representations of the object on projections of a 3-D model of the work environment. The user may move in the work environment by changing the viewpoint of the projections. The interface uses a rule based program to transform user selection of items on a graphics display of the robot's work environment into commands for the robot. The program first determines if the desired task is possible given the abilities of the robot and any constraints on the object. If the task is possible, the program determines what movements the robot needs to make to perform the task. The movements are transformed into commands for the robot. The information defining the robot, the work environment, and how objects may be moved is stored in a set of data bases accessible to the program and displayable to the user.

Perspectives of construction robots

NASA Astrophysics Data System (ADS)

Stepanov, M. A.; Gridchin, A. M.

2018-03-01

This article is an overview of construction robots features, based on formulating the list of requirements for different types of construction robots in relation to different types of construction works.. It describes a variety of construction works and ways to construct new or to adapt existing robot designs for a construction process. Also, it shows the prospects of AI-controlled machines, implementation of automated control systems and networks on construction sites. In the end, different ways to develop and improve, including ecological aspect, the construction process through the wide robotization, creating of data communication networks and, in perspective, establishing of fully AI-controlled construction complex are formulated.

Robustness of a distributed neural network controller for locomotion in a hexapod robot

NASA Technical Reports Server (NTRS)

Chiel, Hillel J.; Beer, Randall D.; Quinn, Roger D.; Espenschied, Kenneth S.

1992-01-01

A distributed neural-network controller for locomotion, based on insect neurobiology, has been used to control a hexapod robot. How robust is this controller? Disabling any single sensor, effector, or central component did not prevent the robot from walking. Furthermore, statically stable gaits could be established using either sensor input or central connections. Thus, a complex interplay between central neural elements and sensor inputs is responsible for the robustness of the controller and its ability to generate a continuous range of gaits. These results suggest that biologically inspired neural-network controllers may be a robust method for robotic control.

Survey of Visual and Force/Tactile Control of Robots for Physical Interaction in Spain

PubMed Central

Garcia, Gabriel J.; Corrales, Juan A.; Pomares, Jorge; Torres, Fernando

2009-01-01

Sensors provide robotic systems with the information required to perceive the changes that happen in unstructured environments and modify their actions accordingly. The robotic controllers which process and analyze this sensory information are usually based on three types of sensors (visual, force/torque and tactile) which identify the most widespread robotic control strategies: visual servoing control, force control and tactile control. This paper presents a detailed review on the sensor architectures, algorithmic techniques and applications which have been developed by Spanish researchers in order to implement these mono-sensor and multi-sensor controllers which combine several sensors. PMID:22303146

Sustainable Cooperative Robotic Technologies for Human and Robotic Outpost Infrastructure Construction and Maintenance

NASA Technical Reports Server (NTRS)

Stroupe, Ashley W.; Okon, Avi; Robinson, Matthew; Huntsberger, Terry; Aghazarian, Hrand; Baumgartner, Eric

2004-01-01

Robotic Construction Crew (RCC) is a heterogeneous multi-robot system for autonomous acquisition, transport, and precision mating of components in construction tasks. RCC minimizes resources constrained in a space environment such as computation, power, communication and, sensing. A behavior-based architecture provides adaptability and robustness despite low computational requirements. RCC successfully performs several construction related tasks in an emulated outdoor environment despite high levels of uncertainty in motions and sensing. Quantitative results are provided for formation keeping in component transport, precision instrument placement, and construction tasks.

Stiffness Control of Surgical Continuum Manipulators

PubMed Central

Mahvash, Mohsen; Dupont, Pierre E.

2013-01-01

This paper introduces the first stiffness controller for continuum robots. The control law is based on an accurate approximation of a continuum robot’s coupled kinematic and static force model. To implement a desired tip stiffness, the controller drives the actuators to positions corresponding to a deflected robot configuration that produces the required tip force for the measured tip position. This approach provides several important advantages. First, it enables the use of robot deflection sensing as a means to both sense and control tip forces. Second, it enables stiffness control to be implemented by modification of existing continuum robot position controllers. The proposed controller is demonstrated experimentally in the context of a concentric tube robot. Results show that the stiffness controller achieves the desired stiffness in steady state, provides good dynamic performance, and exhibits stability during contact transitions. PMID:24273466

Development of the first force-controlled robot for otoneurosurgery.

PubMed

Federspil, Philipp A; Geisthoff, Urban W; Henrich, Dominik; Plinkert, Peter K

2003-03-01

In some surgical specialties (eg, orthopedics), robots are already used in the operating room for bony milling work. Otological surgery and otoneurosurgery may also greatly benefit from the enhanced precision of robotics. Experimental study on robotic milling of oak wood and human temporal bone specimen. A standard industrial robot with a six-degrees-of-freedom serial kinematics was used, with force feedback to proportionally control the robot speed. Different milling modes and characteristic path parameters were evaluated to generate milling paths based on computer-aided design (CAD) geometry data of a cochlear implant and an implantable hearing system. The best-suited strategy proved to be the spiral horizontal milling mode with the burr held perpendicular to the temporal bone surface. To reduce groove height, the distance between paths should equal half the radius of the cutting burr head. Because of the vibration of the robot's own motors, a high oscillation of the SD of forces was encountered. This oscillation dropped drastically to nearly 0 Newton (N) when the burr head made contact with the dura mater, because of its damping characteristics. The cutting burr could be kept in contact with the dura mater for an extended period without damaging it, because of the burr's blunt head form. The robot moved the burr smoothly according to the encountered resistances. The study reports the first development of a functional robotic milling procedure for otoneurosurgery with force-based speed control. Future plans include implementation of ultrasound-based local navigation and performance of robotic mastoidectomy.

Real-time cartesian force feedback control of a teleoperated robot

NASA Technical Reports Server (NTRS)

Campbell, Perry

1989-01-01

Active cartesian force control of a teleoperated robot is investigated. An economical microcomputer based control method was tested. Limitations are discussed and methods of performance improvement suggested. To demonstrate the performance of this technique, a preliminary test was performed with success. A general purpose bilateral force reflecting hand controller is currently being constructed based on this control method.

You Look Human, But Act Like a Machine: Agent Appearance and Behavior Modulate Different Aspects of Human-Robot Interaction.

PubMed

Abubshait, Abdulaziz; Wiese, Eva

2017-01-01

Gaze following occurs automatically in social interactions, but the degree to which gaze is followed depends on whether an agent is perceived to have a mind, making its behavior socially more relevant for the interaction. Mind perception also modulates the attitudes we have toward others, and determines the degree of empathy, prosociality, and morality invested in social interactions. Seeing mind in others is not exclusive to human agents, but mind can also be ascribed to non-human agents like robots, as long as their appearance and/or behavior allows them to be perceived as intentional beings. Previous studies have shown that human appearance and reliable behavior induce mind perception to robot agents, and positively affect attitudes and performance in human-robot interaction. What has not been investigated so far is whether different triggers of mind perception have an independent or interactive effect on attitudes and performance in human-robot interaction. We examine this question by manipulating agent appearance (human vs. robot) and behavior (reliable vs. random) within the same paradigm and examine how congruent (human/reliable vs. robot/random) versus incongruent (human/random vs. robot/reliable) combinations of these triggers affect performance (i.e., gaze following) and attitudes (i.e., agent ratings) in human-robot interaction. The results show that both appearance and behavior affect human-robot interaction but that the two triggers seem to operate in isolation, with appearance more strongly impacting attitudes, and behavior more strongly affecting performance. The implications of these findings for human-robot interaction are discussed.

Adaptive Proactive Inhibitory Control for Embedded Real-Time Applications

PubMed Central

Yang, Shufan; McGinnity, T. Martin; Wong-Lin, KongFatt

2012-01-01

Psychologists have studied the inhibitory control of voluntary movement for many years. In particular, the countermanding of an impending action has been extensively studied. In this work, we propose a neural mechanism for adaptive inhibitory control in a firing-rate type model based on current findings in animal electrophysiological and human psychophysical experiments. We then implement this model on a field-programmable gate array (FPGA) prototyping system, using dedicated real-time hardware circuitry. Our results show that the FPGA-based implementation can run in real-time while achieving behavioral performance qualitatively suggestive of the animal experiments. Implementing such biological inhibitory control in an embedded device can lead to the development of control systems that may be used in more realistic cognitive robotics or in neural prosthetic systems aiding human movement control. PMID:22701420

Brain-machine interfacing control of whole-body humanoid motion

PubMed Central

Bouyarmane, Karim; Vaillant, Joris; Sugimoto, Norikazu; Keith, François; Furukawa, Jun-ichiro; Morimoto, Jun

2014-01-01

We propose to tackle in this paper the problem of controlling whole-body humanoid robot behavior through non-invasive brain-machine interfacing (BMI), motivated by the perspective of mapping human motor control strategies to human-like mechanical avatar. Our solution is based on the adequate reduction of the controllable dimensionality of a high-DOF humanoid motion in line with the state-of-the-art possibilities of non-invasive BMI technologies, leaving the complement subspace part of the motion to be planned and executed by an autonomous humanoid whole-body motion planning and control framework. The results are shown in full physics-based simulation of a 36-degree-of-freedom humanoid motion controlled by a user through EEG-extracted brain signals generated with motor imagery task. PMID:25140134

Two modular neuro-fuzzy system for mobile robot navigation

NASA Astrophysics Data System (ADS)

Bobyr, M. V.; Titov, V. S.; Kulabukhov, S. A.; Syryamkin, V. I.

2018-05-01

The article considers the fuzzy model for navigation of a mobile robot operating in two modes. In the first mode the mobile robot moves along a line. In the second mode, the mobile robot looks for an target in unknown space. Structural and schematic circuit of four-wheels mobile robot are presented in the article. The article describes the movement of a mobile robot based on two modular neuro-fuzzy system. The algorithm of neuro-fuzzy inference used in two modular control system for movement of a mobile robot is given in the article. The experimental model of the mobile robot and the simulation of the neuro-fuzzy algorithm used for its control are presented in the article.

Workspace Safe Operation of a Force- or Impedance-Controlled Robot

NASA Technical Reports Server (NTRS)

Abdallah, Muhammad E. (Inventor); Hargrave, Brian (Inventor); Strawser, Philip A. (Inventor); Yamokoski, John D. (Inventor)

2013-01-01

A method of controlling a robotic manipulator of a force- or impedance-controlled robot within an unstructured workspace includes imposing a saturation limit on a static force applied by the manipulator to its surrounding environment, and may include determining a contact force between the manipulator and an object in the unstructured workspace, and executing a dynamic reflex when the contact force exceeds a threshold to thereby alleviate an inertial impulse not addressed by the saturation limited static force. The method may include calculating a required reflex torque to be imparted by a joint actuator to a robotic joint. A robotic system includes a robotic manipulator having an unstructured workspace and a controller that is electrically connected to the manipulator, and which controls the manipulator using force- or impedance-based commands. The controller, which is also disclosed herein, automatically imposes the saturation limit and may execute the dynamic reflex noted above.

New robotics: design principles for intelligent systems.

PubMed

Pfeifer, Rolf; Iida, Fumiya; Bongard, Josh

2005-01-01

New robotics is an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e. g., from control theory), designing agents in the new robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics, or design principles, that on the one hand capture theoretical insights about intelligent (adaptive) behavior, and on the other provide guidance in actually designing and building systems. In this article we provide an overview of all the principles but focus on the principles of ecological balance, which concerns the relation between environment, morphology, materials, and control, and sensory-motor coordination, which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we argue, artificial evolution together with morphogenesis is not only "nice to have" but is in fact a necessary tool for designing embodied agents.

Framsticks

NASA Astrophysics Data System (ADS)

Komosinski, Maciej; Ulatowski, Szymon

Life is one of the most complex phenomena known in our world. Researchers construct various models of life that serve diverse purposes and are applied in a wide range of areas — from medicine to entertainment. A part of artificial life research focuses on designing three-dimensional (3D) models of life-forms, which are obviously appealing to observers because the world we live in is three dimensional. Thus, we can easily understand behaviors demonstrated by virtual individuals, study behavioral changes during simulated evolution, analyze dependencies between groups of creatures, and so forth. However, 3D models of life-forms are not only attractive because of their resemblance to the real-world organisms. Simulating 3D agents has practical implications: If the simulation is accurate enough, then real robots can be built based on the simulation, as in [22]. Agents can be designed, tested, and optimized in a virtual environment, and the best ones can be constructed as real robots with embedded control systems. This way artificial intelligence algorithms can be “embodied” in the 3D mechanical constructs.

Arousal regulation and affective adaptation to human responsiveness by a robot that explores and learns a novel environment.

PubMed

Hiolle, Antoine; Lewis, Matthew; Cañamero, Lola

2014-01-01

In the context of our work in developmental robotics regarding robot-human caregiver interactions, in this paper we investigate how a "baby" robot that explores and learns novel environments can adapt its affective regulatory behavior of soliciting help from a "caregiver" to the preferences shown by the caregiver in terms of varying responsiveness. We build on two strands of previous work that assessed independently (a) the differences between two "idealized" robot profiles-a "needy" and an "independent" robot-in terms of their use of a caregiver as a means to regulate the "stress" (arousal) produced by the exploration and learning of a novel environment, and (b) the effects on the robot behaviors of two caregiving profiles varying in their responsiveness-"responsive" and "non-responsive"-to the regulatory requests of the robot. Going beyond previous work, in this paper we (a) assess the effects that the varying regulatory behavior of the two robot profiles has on the exploratory and learning patterns of the robots; (b) bring together the two strands previously investigated in isolation and take a step further by endowing the robot with the capability to adapt its regulatory behavior along the "needy" and "independent" axis as a function of the varying responsiveness of the caregiver; and (c) analyze the effects that the varying regulatory behavior has on the exploratory and learning patterns of the adaptive robot.

Wireless intraoral tongue control of an assistive robotic arm for individuals with tetraplegia.

PubMed

Andreasen Struijk, Lotte N S; Egsgaard, Line Lindhardt; Lontis, Romulus; Gaihede, Michael; Bentsen, Bo

2017-11-06

For an individual with tetraplegia assistive robotic arms provide a potentially invaluable opportunity for rehabilitation. However, there is a lack of available control methods to allow these individuals to fully control the assistive arms. Here we show that it is possible for an individual with tetraplegia to use the tongue to fully control all 14 movements of an assistive robotic arm in a three dimensional space using a wireless intraoral control system, thus allowing for numerous activities of daily living. We developed a tongue-based robotic control method incorporating a multi-sensor inductive tongue interface. One abled-bodied individual and one individual with tetraplegia performed a proof of concept study by controlling the robot with their tongue using direct actuator control and endpoint control, respectively. After 30 min of training, the able-bodied experimental participant tongue controlled the assistive robot to pick up a roll of tape in 80% of the attempts. Further, the individual with tetraplegia succeeded in fully tongue controlling the assistive robot to reach for and touch a roll of tape in 100% of the attempts and to pick up the roll in 50% of the attempts. Furthermore, she controlled the robot to grasp a bottle of water and pour its contents into a cup; her first functional action in 19 years. To our knowledge, this is the first time that an individual with tetraplegia has been able to fully control an assistive robotic arm using a wireless intraoral tongue interface. The tongue interface used to control the robot is currently available for control of computers and of powered wheelchairs, and the robot employed in this study is also commercially available. Therefore, the presented results may translate into available solutions within reasonable time.

Energy-Saving Control of a Novel Hydraulic Drive System for Field Walking Robot

NASA Astrophysics Data System (ADS)

Fang, Delei; Shang, Jianzhong; Xue, Yong; Yang, Junhong; Wang, Zhuo

2018-01-01

To improve the efficiency of the hydraulic drive system in field walking robot, this paper proposed a novel hydraulic system based on two-stage pressure source. Based on the analysis of low efficiency of robot single-stage hydraulic system, the paper firstly introduces the concept and design of two-stage pressure source drive system. Then, the new hydraulic system energy-saving control is planned according to the characteristics of walking robot. The feasibility of the new hydraulic system is proved by the simulation of the walking robot squatting. Finally, the efficiencies of two types hydraulic system are calculated, indicating that the novel hydraulic system can increase the efficiency by 41.5%, which can contribute to enhance knowledge about hydraulic drive system for field walking robot.