Promoting Interactions Between Humans and Robots Using Robotic Emotional Behavior.

PubMed

Ficocelli, Maurizio; Terao, Junichi; Nejat, Goldie

2016-12-01

The objective of a socially assistive robot is to create a close and effective interaction with a human user for the purpose of giving assistance. In particular, the social interaction, guidance, and support that a socially assistive robot can provide a person can be very beneficial to patient-centered care. However, there are a number of research issues that need to be addressed in order to design such robots. This paper focuses on developing effective emotion-based assistive behavior for a socially assistive robot intended for natural human-robot interaction (HRI) scenarios with explicit social and assistive task functionalities. In particular, in this paper, a unique emotional behavior module is presented and implemented in a learning-based control architecture for assistive HRI. The module is utilized to determine the appropriate emotions of the robot to display, as motivated by the well-being of the person, during assistive task-driven interactions in order to elicit suitable actions from users to accomplish a given person-centered assistive task. A novel online updating technique is used in order to allow the emotional model to adapt to new people and scenarios. Experiments presented show the effectiveness of utilizing robotic emotional assistive behavior during HRI scenarios.

Supersmart Robots: The Next Generation of Robots Has Evolutionary Capabilities

ERIC Educational Resources Information Center

Simkins, Michael

2008-01-01

Robots that can learn new behaviors. Robots that can reproduce themselves. Science fiction? Not anymore. Roboticists at Cornell's Computational Synthesis Lab have developed just such engineered creatures that offer interesting implications for education. The team, headed by Hod Lipson, was intrigued by the question, "How can you get robots to be…

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.

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.

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…

Human motion behavior while interacting with an industrial robot.

PubMed

Bortot, Dino; Ding, Hao; Antonopolous, Alexandros; Bengler, Klaus

2012-01-01

Human workers and industrial robots both have specific strengths within industrial production. Advantageously they complement each other perfectly, which leads to the development of human-robot interaction (HRI) applications. Bringing humans and robots together in the same workspace may lead to potential collisions. The avoidance of such is a central safety requirement. It can be realized with sundry sensor systems, all of them decelerating the robot when the distance to the human decreases alarmingly and applying the emergency stop, when the distance becomes too small. As a consequence, the efficiency of the overall systems suffers, because the robot has high idle times. Optimized path planning algorithms have to be developed to avoid that. The following study investigates human motion behavior in the proximity of an industrial robot. Three different kinds of encounters between the two entities under three robot speed levels are prompted. A motion tracking system is used to capture the motions. Results show, that humans keep an average distance of about 0,5m to the robot, when the encounter occurs. Approximation of the workbenches is influenced by the robot in ten of 15 cases. Furthermore, an increase of participants' walking velocity with higher robot velocities is observed.

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

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.

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.

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.

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

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.

Robot Behavior Acquisition Superposition and Composting of Behaviors Learned through Teleoperation

NASA Technical Reports Server (NTRS)

Peters, Richard Alan, II

2004-01-01

Superposition of a small set of behaviors, learned via teleoperation, can lead to robust completion of a simple articulated reach-and-grasp task. Results support the hypothesis that a set of learned behaviors can be combined to generate new behaviors of a similar type. This supports the hypothesis that a robot can learn to interact purposefully with its environment through a developmental acquisition of sensory-motor coordination. Teleoperation bootstraps the process by enabling the robot to observe its own sensory responses to actions that lead to specific outcomes. A reach-and-grasp task, learned by an articulated robot through a small number of teleoperated trials, can be performed autonomously with success in the face of significant variations in the environment and perturbations of the goal. Superpositioning was performed using the Verbs and Adverbs algorithm that was developed originally for the graphical animation of articulated characters. Work was performed on Robonaut at NASA-JSC.

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.

Robot computer problem solving system

NASA Technical Reports Server (NTRS)

Becker, J. D.

1972-01-01

Continuing research is reported in a program aimed at the development of a robot computer problem solving system. The motivation and results are described of a theoretical investigation concerning the general properties of behavioral systems. Some of the important issues which a general theory of behavioral organization should encompass are outlined and discussed.

Physiological and Behavioral Responses of Dairy Cattle to the Introduction of Robot Scrapers.

PubMed

Doerfler, Renate L; Lehermeier, Christina; Kliem, Heike; Möstl, Erich; Bernhardt, Heinz

2016-01-01

Autonomous mobile robot scrapers are increasingly used in order to clean the floors on dairy farms. Given the complexity of robot scraper operation, stress may occur in cows due to unpredictability of the situation. Experiencing stress can impair animal welfare and, in the long term, the health and milk production of the cows. Therefore, this study addressed potential stress responses of dairy cattle to the robot scraper after introducing the autonomous mobile machine. Thirty-six cows in total were studied on three different farms to explore possible modifications in cardiac function, behavior, and adrenocortical activity. The research protocol on each farm consisted of four experimental periods including one baseline measurement without robot scraper operation followed by three test measurements, in which cows interacted with the robotic cleaning system. Interbeat intervals were recorded in order to calculate the heart rate variability (HRV) parameter RMSSD; behavior was observed to determine time budgets; and fecal samples were collected for analysis of the cortisol metabolites concentration. A statistical analysis was carried out using linear mixed-effects models. HRV decline immediately after the introduction of the robot scraper and modified behavior in the subsequent experimental periods indicated a stress response. The cortisol metabolites concentration remained constant. It is hypothesized that after the initial phase of decrease, HRV stabilized through the behavioral adjustments of the cows in the second part of the study. Persistent alterations in behavior gave rise to the assumption that the animals' habituation process to the robot scraper was not yet completed. In summary, the present study illustrated that the cows showed minor signs of disturbance toward the robotic cleaning system. Thus, our findings suggest that dairy cattle can largely adjust their behavior to avoid aversive effects on animal welfare. Additional research can provide further insight into the development of the animal-machine interaction beyond the initial phase of robot scraper operation considered in this study.

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.

Robot, computer problem solving system

NASA Technical Reports Server (NTRS)

Becker, J. D.

1972-01-01

The development of a computer problem solving system is reported that considers physical problems faced by an artificial robot moving around in a complex environment. Fundamental interaction constraints with a real environment are simulated for the robot by visual scan and creation of an internal environmental model. The programming system used in constructing the problem solving system for the simulated robot and its simulated world environment is outlined together with the task that the system is capable of performing. A very general framework for understanding the relationship between an observed behavior and an adequate description of that behavior is included.

Robots for use in autism research.

PubMed

Scassellati, Brian; Admoni, Henny; Matarić, Maja

2012-01-01

Autism spectrum disorders are a group of lifelong disabilities that affect people's ability to communicate and to understand social cues. Research into applying robots as therapy tools has shown that robots seem to improve engagement and elicit novel social behaviors from people (particularly children and teenagers) with autism. Robot therapy for autism has been explored as one of the first application domains in the field of socially assistive robotics (SAR), which aims to develop robots that assist people with special needs through social interactions. In this review, we discuss the past decade's work in SAR systems designed for autism therapy by analyzing robot design decisions, human-robot interactions, and system evaluations. We conclude by discussing challenges and future trends for this young but rapidly developing research area.

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.

Anticipation as a Strategy: A Design Paradigm for Robotics

NASA Astrophysics Data System (ADS)

Williams, Mary-Anne; Gärdenfors, Peter; Johnston, Benjamin; Wightwick, Glenn

Anticipation plays a crucial role during any action, particularly in agents operating in open, complex and dynamic environments. In this paper we consider the role of anticipation as a strategy from a design perspective. Anticipation is a crucial skill in sporting games like soccer, tennis and cricket. We explore the role of anticipation in robot soccer matches in the context of reaching the RoboCup vision to develop a robot soccer team capable of defeating the FIFA World Champions in 2050. Anticipation in soccer can be planned or emergent but whether planned or emergent, anticipation can be designed. Two key obstacles stand in the way of developing more anticipatory robot systems; an impoverished understanding of the "anticipation" process/capability and a lack of know-how in the design of anticipatory systems. Several teams at RoboCup have developed remarkable preemptive behaviors. The CMU Dive and UTS Dodge are two compelling examples. In this paper we take steps towards designing robots that can adopt anticipatory behaviors by proposing an innovative model of anticipation as a strategy that specifies the key characteristics of anticipation behaviors to be developed. The model can drive the design of autonomous systems by providing a means to explore and to represent anticipation requirements. Our approach is to analyze anticipation as a strategy and then to use the insights obtained to design a reference model that can be used to specify a set of anticipatory requirements for guiding an autonomous robot soccer system.

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

Flowrate behavior and clustering of self-driven robots in a channel

NASA Astrophysics Data System (ADS)

Tian, Bo; Sun, Wang-Ping; Li, Ming; Jiang, Rui; Hu, Mao-Bin

2018-03-01

In this paper, the collective motion of self-driven robots is studied experimentally and theoretically. In the channel, the flowrate of robots increases with the density linearly, even if the density of the robots tends to 1.0. There is no abrupt drop in the flowrate, similar to the collective motion of ants. We find that the robots will adjust their velocities by a serial of tiny collisions. The speed-adjustment will affect both robots involved in the collision, and will help to maintain a nearly uniform velocity for the robots. As a result, the flowrate drop will disappear. In the motion, the robots neither gather together nor scatter completely. Instead, they form some clusters to move together. These clusters are not stable during the moving process, but their sizes follow a power-law-alike distribution. We propose a theoretical model to simulate this collective motion process, which can reproduce these behaviors well. Analytic results about the flowrate behavior are also consistent with experiments. Project supported by the Key Research and Development Program, China (Grant No. 2016YFC0802508) and the National Natural Science Foundation of China (Grant Nos. 11672289 and 11422221).

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.

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

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.

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.

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

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.

Behavioral Mapless Navigation Using Rings

NASA Technical Reports Server (NTRS)

Monroe, Randall P.; Miller, Samuel A.; Bradley, Arthur T.

2012-01-01

This paper presents work on the development and implementation of a novel approach to robotic navigation. In this system, map-building and localization for obstacle avoidance are discarded in favor of moment-by-moment behavioral processing of the sonar sensor data. To accomplish this, we developed a network of behaviors that communicate through the passing of rings, data structures that are similar in form to the sonar data itself and express the decisions of each behavior. Through the use of these rings, behaviors can moderate each other, conflicting impulses can be mediated, and designers can easily connect modules to create complex emergent navigational techniques. We discuss the development of a number of these modules and their successful use as a navigation system in the Trinity omnidirectional robot.

Development of hierarchical structures for actions and motor imagery: a constructivist view from synthetic neuro-robotics study.

PubMed

Nishimoto, Ryunosuke; Tani, Jun

2009-07-01

The current paper shows a neuro-robotics experiment on developmental learning of goal-directed actions. The robot was trained to predict visuo-proprioceptive flow of achieving a set of goal-directed behaviors through iterative tutor training processes. The learning was conducted by employing a dynamic neural network model which is characterized by their multiple time-scale dynamics. The experimental results showed that functional hierarchical structures emerge through stages of developments where behavior primitives are generated in earlier stages and their sequences of achieving goals appear in later stages. It was also observed that motor imagery is generated in earlier stages compared to actual behaviors. Our claim that manipulatable inner representation should emerge through the sensory-motor interactions is corresponded to Piaget's constructivist view.

What are the preferred characteristics of a service robot for the elderly? A multi-country focus group study with older adults and caregivers.

PubMed

Bedaf, Sandra; Marti, Patrizia; De Witte, Luc

2017-11-10

This multi-perspective study focuses on how a service robot for the elderly should behave when interacting with potential users. An existing service robot and a scenario were used as a concrete case, which was discussed and analyzed during focus group sessions with older adults (n = 38), informal caregivers (n = 24), and professional caregivers (n = 35) in the Netherlands, France, and the United Kingdom. A total of seven topics-privacy, task execution, environment, appearance, behavior, visitors, and communication-were explored. The results showed that some of the characteristics mentioned were unique to a user group, but several were cross-cutting. Overall, potential users expected the service robot to be customizable in order to match the users' needs and preferences. Also, high expectations concerning its functioning and behavior were expressed, which sometimes could even be compared to the qualities of a human being. This emphasizes the complexity of service robot development for older adults, and highlights the need for a personalized and flexible solution. One size does not fit all, and specific attention should be paid to the development of the robot's social behavior and skills beyond a mere functional support for the person.

Biologically inspired robots elicit a robust fear response in zebrafish

NASA Astrophysics Data System (ADS)

Ladu, Fabrizio; Bartolini, Tiziana; Panitz, Sarah G.; Butail, Sachit; Macrı, Simone; Porfiri, Maurizio

2015-03-01

We investigate the behavioral response of zebrafish to three fear-evoking stimuli. In a binary choice test, zebrafish are exposed to a live allopatric predator, a biologically-inspired robot, and a computer-animated image of the live predator. A target tracking algorithm is developed to score zebrafish behavior. Unlike computer-animated images, the robotic and live predator elicit a robust avoidance response. Importantly, the robotic stimulus elicits more consistent inter-individual responses than the live predator. Results from this effort are expected to aid in hypothesis-driven studies on zebrafish fear response, by offering a valuable approach to maximize data-throughput and minimize animal subjects.

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.

Design and development of biomimetic quadruped robot for behavior studies of rats and mice.

PubMed

Ishii, Hiroyuki; Masuda, Yuichi; Miyagishima, Syunsuke; Fumino, Shogo; Takanishi, Atsuo; Laschi, Cecilia; Mazzolai, Barbara; Mattoli, Virgilio; Dario, Paolo

2009-01-01

This paper presents the design and development of a novel biomimetic quadruped robot for behavior studies of rats and mice. Many studies have been performed using these animals for the purpose of understanding human mind in psychology, pharmacology and brain science. In these fields, several experiments on social interactions have been performed using rats as basic studies of mental disorders or social learning. However, some researchers mention that the experiments on social interactions using animals are poorly-reproducible. Therefore, we consider that reproducibility of these experiments can be improved by using a robotic agent that interacts with an animal subject. Thus, we developed a small quadruped robot WR-2 (Waseda Rat No. 2) that behaves like a real rat. Proportion and DOF arrangement of WR-2 are designed based on those of a mature rat. This robot has four 3-DOF legs, a 2-DOF waist and a 1-DOF neck. A microcontroller and a wireless communication module are implemented on it. A battery is also implemented. Thus, it can walk, rear by limbs and groom its body.

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.

Social robots as embedded reinforcers of social behavior in children with autism.

PubMed

Kim, Elizabeth S; Berkovits, Lauren D; Bernier, Emily P; Leyzberg, Dan; Shic, Frederick; Paul, Rhea; Scassellati, Brian

2013-05-01

In this study we examined the social behaviors of 4- to 12-year-old children with autism spectrum disorders (ASD; N = 24) during three tradic interactions with an adult confederate and an interaction partner, where the interaction partner varied randomly among (1) another adult human, (2) a touchscreen computer game, and (3) a social dinosaur robot. Children spoke more in general, and directed more speech to the adult confederate, when the interaction partner was a robot, as compared to a human or computer game interaction partner. Children spoke as much to the robot as to the adult interaction partner. This study provides the largest demonstration of social human-robot interaction in children with autism to date. Our findings suggest that social robots may be developed into useful tools for social skills and communication therapies, specifically by embedding social interaction into intrinsic reinforcers and motivators.

Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human-Robot Interaction.

PubMed

Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

2016-01-01

To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

Educational robotics as an Innovative teaching practice using technology: minimization of risks

NASA Astrophysics Data System (ADS)

Kvesko, S. B.; Kvesko, N. G.; Korniyenko, A. A.; Kabanova, N. N.

2018-05-01

This research is focused on studying educational robotics, specifically robots which provide functions of educational activity. We have considered the questions of intelligent agents’ behavior and have studied their educational opportunities. Educational robotics is a powerful tool of developing person’s skills and abilities in various fields of technical creativity and professional activity. The evolutionary development of robotics is connected with development of artificial intelligence, where emotions play a great role in operations. Nowadays the main thing is to form the ability and skills of optimum interaction with social environment when a person, based on gained knowledge, is capable to put goals of the activity in strict accordance with laws and society conditions and using current technology.

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

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

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.

Algorithms and Sensors for Small Robot Path Following

NASA Technical Reports Server (NTRS)

Hogg, Robert W.; Rankin, Arturo L.; Roumeliotis, Stergios I.; McHenry, Michael C.; Helmick, Daniel M.; Bergh, Charles F.; Matthies, Larry

2002-01-01

Tracked mobile robots in the 20 kg size class are under development for applications in urban reconnaissance. For efficient deployment, it is desirable for teams of robots to be able to automatically execute path following behaviors, with one or more followers tracking the path taken by a leader. The key challenges to enabling such a capability are (l) to develop sensor packages for such small robots that can accurately determine the path of the leader and (2) to develop path following algorithms for the subsequent robots. To date, we have integrated gyros, accelerometers, compass/inclinometers, odometry, and differential GPS into an effective sensing package. This paper describes the sensor package, sensor processing algorithm, and path tracking algorithm we have developed for the leader/follower problem in small robots and shows the result of performance characterization of the system. We also document pragmatic lessons learned about design, construction, and electromagnetic interference issues particular to the performance of state sensors on small robots.

Development and demonstration of autonomous behaviors for urban environment exploration

NASA Astrophysics Data System (ADS)

Ahuja, Gaurav; Fellars, Donald; Kogut, Gregory; Pacis Rius, Estrellina; Schoolov, Misha; Xydes, Alexander

2012-06-01

Under the Urban Environment Exploration project, the Space and Naval Warfare Systems Center Pacic (SSC- PAC) is maturing technologies and sensor payloads that enable man-portable robots to operate autonomously within the challenging conditions of urban environments. Previously, SSC-PAC has demonstrated robotic capabilities to navigate and localize without GPS and map the ground oors of various building sizes.1 SSC-PAC has since extended those capabilities to localize and map multiple multi-story buildings within a specied area. To facilitate these capabilities, SSC-PAC developed technologies that enable the robot to detect stairs/stairwells, maintain localization across multiple environments (e.g. in a 3D world, on stairs, with/without GPS), visualize data in 3D, plan paths between any two points within the specied area, and avoid 3D obstacles. These technologies have been developed as independent behaviors under the Autonomous Capabilities Suite, a behavior architecture, and demonstrated at a MOUT site at Camp Pendleton. This paper describes the perceptions and behaviors used to produce these capabilities, as well as an example demonstration scenario.

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.

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).

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.

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.

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

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

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.

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.

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

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.

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.

Real time explosive hazard information sensing, processing, and communication for autonomous operation

DOEpatents

Versteeg, Roelof J; Few, Douglas A; Kinoshita, Robert A; Johnson, Doug; Linda, Ondrej

2015-02-24

Methods, computer readable media, and apparatuses provide robotic explosive hazard detection. A robot intelligence kernel (RIK) includes a dynamic autonomy structure with two or more autonomy levels between operator intervention and robot initiative A mine sensor and processing module (ESPM) operating separately from the RIK perceives environmental variables indicative of a mine using subsurface perceptors. The ESPM processes mine information to determine a likelihood of a presence of a mine. A robot can autonomously modify behavior responsive to an indication of a detected mine. The behavior is modified between detection of mines, detailed scanning and characterization of the mine, developing mine indication parameters, and resuming detection. Real time messages are passed between the RIK and the ESPM. A combination of ESPM bound messages and RIK bound messages cause the robot platform to switch between modes including a calibration mode, the mine detection mode, and the mine characterization mode.

Real time explosive hazard information sensing, processing, and communication for autonomous operation

DOEpatents

Versteeg, Roelof J.; Few, Douglas A.; Kinoshita, Robert A.; Johnson, Douglas; Linda, Ondrej

2015-12-15

Methods, computer readable media, and apparatuses provide robotic explosive hazard detection. A robot intelligence kernel (RIK) includes a dynamic autonomy structure with two or more autonomy levels between operator intervention and robot initiative A mine sensor and processing module (ESPM) operating separately from the RIK perceives environmental variables indicative of a mine using subsurface perceptors. The ESPM processes mine information to determine a likelihood of a presence of a mine. A robot can autonomously modify behavior responsive to an indication of a detected mine. The behavior is modified between detection of mines, detailed scanning and characterization of the mine, developing mine indication parameters, and resuming detection. Real time messages are passed between the RIK and the ESPM. A combination of ESPM bound messages and RIK bound messages cause the robot platform to switch between modes including a calibration mode, the mine detection mode, and the mine characterization mode.

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.

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.

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.

Designing a social and assistive robot for seniors.

PubMed

Eftring, H; Frennert, S

2016-06-01

The development of social assistive robots is an approach with the intention of preventing and detecting falls among seniors. There is a need for a relatively low-cost mobile robot with an arm and a gripper which is small enough to navigate through private homes. User requirements of a social assistive robot were collected using workshops, a questionnaire and interviews. Two prototype versions of a robot were designed, developed and tested by senior citizens (n = 49) in laboratory trials for 2 h each and in the private homes of elderly persons (n = 18) for 3 weeks each. The user requirement analysis resulted in a specification of tasks the robot should be able to do to prevent and detect falls. It was a challenge but possible to design and develop a robot where both the senior and the robot arm could reach the necessary interaction points of the robot. The seniors experienced the robot as happy and friendly. They wanted the robot to be narrower so it could pass through narrow passages in the home and they also wanted it to be able to pass over thresholds without using ramps and to drive over carpets. User trials in seniors' homes are very important to acquire relevant knowledge for developing robots that can handle real life situations in the domestic environment. Very high reliability of a robot is needed to get feedback about how seniors experience the overall behavior of the robot and to find out if the robot could reduce falls and improve the feeling of security for seniors living alone.

Research and development of service robot platform based on artificial psychology

NASA Astrophysics Data System (ADS)

Zhang, Xueyuan; Wang, Zhiliang; Wang, Fenhua; Nagai, Masatake

2007-12-01

Some related works about the control architecture of robot system are briefly summarized. According to the discussions above, this paper proposes control architecture of service robot based on artificial psychology. In this control architecture, the robot can obtain the cognition of environment through sensors, and then be handled with intelligent model, affective model and learning model, and finally express the reaction to the outside stimulation through its behavior. For better understanding the architecture, hierarchical structure is also discussed. The control system of robot can be divided into five layers, namely physical layer, drives layer, information-processing and behavior-programming layer, application layer and system inspection and control layer. This paper shows how to achieve system integration from hardware modules, software interface and fault diagnosis. Embedded system GENE-8310 is selected as the PC platform of robot APROS-I, and its primary memory media is CF card. The arms and body of the robot are constituted by 13 motors and some connecting fittings. Besides, the robot has a robot head with emotional facial expression, and the head has 13 DOFs. The emotional and intelligent model is one of the most important parts in human-machine interaction. In order to better simulate human emotion, an emotional interaction model for robot is proposed according to the theory of need levels of Maslom and mood information of Siminov. This architecture has already been used in our intelligent service robot.

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

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.

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

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.

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

Characteristics of Behavior of Robots with Emotion Model

NASA Astrophysics Data System (ADS)

Sato, Shigehiko; Nozawa, Akio; Ide, Hideto

Cooperated multi robots system has much dominance in comparison with single robot system. It is able to adapt to various circumstances and has a flexibility for variation of tasks. However it has still problems to control each robot, though methods for control multi robots system have been studied. Recently, the robots have been coming into real scene. And emotion and sensitivity of the robots have been widely studied. In this study, human emotion model based on psychological interaction was adapt to multi robots system to achieve methods for organization of multi robots. The characteristics of behavior of multi robots system achieved through computer simulation were analyzed. As a result, very complexed and interesting behavior was emerged even though it has rather simple configuration. And it has flexiblity in various circumstances. Additional experiment with actual robots will be conducted based on the emotion model.

A Platform for Developing Autonomy Technologies for Small Military Robots

DTIC Science & Technology

2008-12-01

angular increments around the disk so described. A line scanner oriented so the plane of detected points is horizontal (e.g., the axis about which...behaviors can be implemented. Thus it will contain the custom scripts , executables, and data that compose the actual behavior of the robot. Currently, the...operating system was constructed to be relatively small and boot fast. Debian GNU/Linux, however, provides an installation script that downloads a

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.

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.

ARTIE: An Integrated Environment for the Development of Affective Robot Tutors

PubMed Central

Imbernón Cuadrado, Luis-Eduardo; Manjarrés Riesco, Ángeles; De La Paz López, Félix

2016-01-01

Over the last decade robotics has attracted a great deal of interest from teachers and researchers as a valuable educational tool from preschool to highschool levels. The implementation of social-support behaviors in robot tutors, in particular in the emotional dimension, can make a significant contribution to learning efficiency. With the aim of contributing to the rising field of affective robot tutors we have developed ARTIE (Affective Robot Tutor Integrated Environment). We offer an architectural pattern which integrates any given educational software for primary school children with a component whose function is to identify the emotional state of the students who are interacting with the software, and with the driver of a robot tutor which provides personalized emotional pedagogical support to the students. In order to support the development of affective robot tutors according to the proposed architecture, we also provide a methodology which incorporates a technique for eliciting pedagogical knowledge from teachers, and a generic development platform. This platform contains a component for identiying emotional states by analysing keyboard and mouse interaction data, and a generic affective pedagogical support component which specifies the affective educational interventions (including facial expressions, body language, tone of voice,…) in terms of BML (a Behavior Model Language for virtual agent specification) files which are translated into actions of a robot tutor. The platform and the methodology are both adapted to primary school students. Finally, we illustrate the use of this platform to build a prototype implementation of the architecture, in which the educational software is instantiated with Scratch and the robot tutor with NAO. We also report on a user experiment we carried out to orient the development of the platform and of the prototype. We conclude from our work that, in the case of primary school students, it is possible to identify, without using intrusive and expensive identification methods, the emotions which most affect the character of educational interventions. Our work also demonstrates the feasibility of a general-purpose architecture of decoupled components, in which a wide range of educational software and robot tutors can be integrated and then used according to different educational criteria. PMID:27536230

ARTIE: An Integrated Environment for the Development of Affective Robot Tutors.

PubMed

Imbernón Cuadrado, Luis-Eduardo; Manjarrés Riesco, Ángeles; De La Paz López, Félix

2016-01-01

Over the last decade robotics has attracted a great deal of interest from teachers and researchers as a valuable educational tool from preschool to highschool levels. The implementation of social-support behaviors in robot tutors, in particular in the emotional dimension, can make a significant contribution to learning efficiency. With the aim of contributing to the rising field of affective robot tutors we have developed ARTIE (Affective Robot Tutor Integrated Environment). We offer an architectural pattern which integrates any given educational software for primary school children with a component whose function is to identify the emotional state of the students who are interacting with the software, and with the driver of a robot tutor which provides personalized emotional pedagogical support to the students. In order to support the development of affective robot tutors according to the proposed architecture, we also provide a methodology which incorporates a technique for eliciting pedagogical knowledge from teachers, and a generic development platform. This platform contains a component for identiying emotional states by analysing keyboard and mouse interaction data, and a generic affective pedagogical support component which specifies the affective educational interventions (including facial expressions, body language, tone of voice,…) in terms of BML (a Behavior Model Language for virtual agent specification) files which are translated into actions of a robot tutor. The platform and the methodology are both adapted to primary school students. Finally, we illustrate the use of this platform to build a prototype implementation of the architecture, in which the educational software is instantiated with Scratch and the robot tutor with NAO. We also report on a user experiment we carried out to orient the development of the platform and of the prototype. We conclude from our work that, in the case of primary school students, it is possible to identify, without using intrusive and expensive identification methods, the emotions which most affect the character of educational interventions. Our work also demonstrates the feasibility of a general-purpose architecture of decoupled components, in which a wide range of educational software and robot tutors can be integrated and then used according to different educational criteria.

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.

Can Children Have a Relationship with a Robot?

NASA Astrophysics Data System (ADS)

Beran, Tanya N.; Ramirez-Serrano, Alejandro

As the development of autonomous robots has moved towards creating social robots, children's interactions with robots will soon need to be investigated. This paper examines how children think about and attribute features of friendship to a robot. A total of 184 children between ages 5 to 16 years visiting a science centre were randomly selected to participate in an experiment with an approximate even number of boys and girls. Children were interviewed after observing a traditional small 5 degree of freedom robot arm, perform a block stacking task. A set of experiments was conducted to measure children's perceptions of affiliation with the robot. Content analysis revealed that a large majority would consider a relationship with the robot, and participate in friendship-type behaviors with it. Significant sex differences in how children ascribe characteristics of friendship to a robot were also found.

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.

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.

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)

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.

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.

Toward understanding social cues and signals in human-robot interaction: effects of robot gaze and proxemic behavior.

PubMed

Fiore, Stephen M; Wiltshire, Travis J; Lobato, Emilio J C; Jentsch, Florian G; Huang, Wesley H; Axelrod, Benjamin

2013-01-01

As robots are increasingly deployed in settings requiring social interaction, research is needed to examine the social signals perceived by humans when robots display certain social cues. In this paper, we report a study designed to examine how humans interpret social cues exhibited by robots. We first provide a brief overview of perspectives from social cognition in humans and how these processes are applicable to human-robot interaction (HRI). We then discuss the need to examine the relationship between social cues and signals as a function of the degree to which a robot is perceived as a socially present agent. We describe an experiment in which social cues were manipulated on an iRobot Ava(TM) mobile robotics platform in a hallway navigation scenario. Cues associated with the robot's proxemic behavior were found to significantly affect participant perceptions of the robot's social presence and emotional state while cues associated with the robot's gaze behavior were not found to be significant. Further, regardless of the proxemic behavior, participants attributed more social presence and emotional states to the robot over repeated interactions than when they first interacted with it. Generally, these results indicate the importance for HRI research to consider how social cues expressed by a robot can differentially affect perceptions of the robot's mental states and intentions. The discussion focuses on implications for the design of robotic systems and future directions for research on the relationship between social cues and signals.

Fish-inspired robots: design, sensing, actuation, and autonomy--a review of research.

PubMed

Raj, Aditi; Thakur, Atul

2016-04-13

Underwater robot designs inspired by the behavior, physiology, and anatomy of fishes can provide enhanced maneuverability, stealth, and energy efficiency. Over the last two decades, robotics researchers have developed and reported a large variety of fish-inspired robot designs. The purpose of this review is to report different types of fish-inspired robot designs based upon their intended locomotion patterns. We present a detailed comparison of various design features like sensing, actuation, autonomy, waterproofing, and morphological structure of fish-inspired robots reported in the past decade. We believe that by studying the existing robots, future designers will be able to create new designs by adopting features from the successful robots. The review also summarizes the open research issues that need to be taken up for the further advancement of the field and also for the deployment of fish-inspired robots in practice.

Experiences of a Motivational Interview Delivered by a Robot: Qualitative Study

PubMed Central

Galvão Gomes da Silva, Joana; Kavanagh, David J; Belpaeme, Tony; Taylor, Lloyd; Beeson, Konna

2018-01-01

Background Motivational interviewing is an effective intervention for supporting behavior change but traditionally depends on face-to-face dialogue with a human counselor. This study addressed a key challenge for the goal of developing social robotic motivational interviewers: creating an interview protocol, within the constraints of current artificial intelligence, which participants will find engaging and helpful. Objective The aim of this study was to explore participants’ qualitative experiences of a motivational interview delivered by a social robot, including their evaluation of usability of the robot during the interaction and its impact on their motivation. Methods NAO robots are humanoid, child-sized social robots. We programmed a NAO robot with Choregraphe software to deliver a scripted motivational interview focused on increasing physical activity. The interview was designed to be comprehensible even without an empathetic response from the robot. Robot breathing and face-tracking functions were used to give an impression of attentiveness. A total of 20 participants took part in the robot-delivered motivational interview and evaluated it after 1 week by responding to a series of written open-ended questions. Each participant was left alone to speak aloud with the robot, advancing through a series of questions by tapping the robot’s head sensor. Evaluations were content-analyzed utilizing Boyatzis’ steps: (1) sampling and design, (2) developing themes and codes, and (3) validating and applying the codes. Results Themes focused on interaction with the robot, motivation, change in physical activity, and overall evaluation of the intervention. Participants found the instructions clear and the navigation easy to use. Most enjoyed the interaction but also found it was restricted by the lack of individualized response from the robot. Many positively appraised the nonjudgmental aspect of the interview and how it gave space to articulate their motivation for change. Some participants felt that the intervention increased their physical activity levels. Conclusions Social robots can achieve a fundamental objective of motivational interviewing, encouraging participants to articulate their goals and dilemmas aloud. Because they are perceived as nonjudgmental, robots may have advantages over more humanoid avatars for delivering virtual support for behavioral change. PMID:29724701

A conceptual cognitive architecture for robots to learn behaviors from demonstrations in robotic aid area.

PubMed

Tan, Huan; Liang, Chen

2011-01-01

This paper proposes a conceptual hybrid cognitive architecture for cognitive robots to learn behaviors from demonstrations in robotic aid situations. Unlike the current cognitive architectures, this architecture puts concentration on the requirements of the safety, the interaction, and the non-centralized processing in robotic aid situations. Imitation learning technologies for cognitive robots have been integrated into this architecture for rapidly transferring the knowledge and skills between human teachers and robots.

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

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.

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.

Babybot: a biologically inspired developing robotic agent

NASA Astrophysics Data System (ADS)

Metta, Giorgio; Panerai, Francesco M.; Sandini, Giulio

2000-10-01

The study of development, either artificial or biological, can highlight the mechanisms underlying learning and adaptive behavior. We shall argue whether developmental studies might provide a different and potentially interesting perspective either on how to build an artificial adaptive agent, or on understanding how the brain solves sensory, motor, and cognitive tasks. It is our opinion that the acquisition of the proper behavior might indeed be facilitated because within an ecological context, the agent, its adaptive structure and the environment dynamically interact thus constraining the otherwise difficult learning problem. In very general terms we shall describe the proposed approach and supporting biological related facts. In order to further analyze these aspects from the modeling point of view, we shall demonstrate how a twelve degrees of freedom baby humanoid robot acquires orienting and reaching behaviors, and what advantages the proposed framework might offer. In particular, the experimental setup consists of five degrees-of-freedom (dof) robot head, and an off-the-shelf six dof robot manipulator, both mounted on a rotating base: i.e. the torso. From the sensory point of view, the robot is equipped with two space-variant cameras, an inertial sensor simulating the vestibular system, and proprioceptive information through motor encoders. The biological parallel is exploited at many implementation levels. It is worth mentioning, for example, the space- variant eyes, exploiting foveal and peripheral vision in a single arrangement, the inertial sensor providing efficient image stabilization (vestibulo-ocular reflex).

Survey of Methods and Algorithms of Robot Swarm Aggregation

NASA Astrophysics Data System (ADS)

E Shlyakhov, N.; Vatamaniuk, I. V.; Ronzhin, A. L.

2017-01-01

The paper considers the problem of swarm aggregation of autonomous robots with the use of three methods based on the analogy of the behavior of biological objects. The algorithms substantiating the requirements for hardware realization of sensor, computer and network resources and propulsion devices are presented. Techniques for efficiency estimation of swarm aggregation via space-time characteristics are described. The developed model of the robot swarm reconfiguration into a predetermined three-dimensional shape is presented.

Building entity models through observation and learning

NASA Astrophysics Data System (ADS)

Garcia, Richard; Kania, Robert; Fields, MaryAnne; Barnes, Laura

2011-05-01

To support the missions and tasks of mixed robotic/human teams, future robotic systems will need to adapt to the dynamic behavior of both teammates and opponents. One of the basic elements of this adaptation is the ability to exploit both long and short-term temporal data. This adaptation allows robotic systems to predict/anticipate, as well as influence, future behavior for both opponents and teammates and will afford the system the ability to adjust its own behavior in order to optimize its ability to achieve the mission goals. This work is a preliminary step in the effort to develop online entity behavior models through a combination of learning techniques and observations. As knowledge is extracted from the system through sensor and temporal feedback, agents within the multi-agent system attempt to develop and exploit a basic movement model of an opponent. For the purpose of this work, extraction and exploitation is performed through the use of a discretized two-dimensional game. The game consists of a predetermined number of sentries attempting to keep an unknown intruder agent from penetrating their territory. The sentries utilize temporal data coupled with past opponent observations to hypothesize the probable locations of the opponent and thus optimize their guarding locations.

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.

Robot calibration with a photogrammetric on-line system using reseau scanning cameras

NASA Astrophysics Data System (ADS)

Diewald, Bernd; Godding, Robert; Henrich, Andreas

1994-03-01

The possibility for testing and calibration of industrial robots becomes more and more important for manufacturers and users of such systems. Exacting applications in connection with the off-line programming techniques or the use of robots as measuring machines are impossible without a preceding robot calibration. At the LPA an efficient calibration technique has been developed. Instead of modeling the kinematic behavior of a robot, the new method describes the pose deviations within a user-defined section of the robot's working space. High- precision determination of 3D coordinates of defined path positions is necessary for calibration and can be done by digital photogrammetric systems. For the calibration of a robot at the LPA a digital photogrammetric system with three Rollei Reseau Scanning Cameras was used. This system allows an automatic measurement of a large number of robot poses with high accuracy.

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.

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.

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

Architecture for robot intelligence

NASA Technical Reports Server (NTRS)

Peters, II, Richard Alan (Inventor)

2004-01-01

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Realtime motion planning for a mobile robot in an unknown environment using a neurofuzzy based approach

NASA Astrophysics Data System (ADS)

Zheng, Taixiong

2005-12-01

A neuro-fuzzy network based approach for robot motion in an unknown environment was proposed. In order to control the robot motion in an unknown environment, the behavior of the robot was classified into moving to the goal and avoiding obstacles. Then, according to the dynamics of the robot and the behavior character of the robot in an unknown environment, fuzzy control rules were introduced to control the robot motion. At last, a 6-layer neuro-fuzzy network was designed to merge from what the robot sensed to robot motion control. After being trained, the network may be used for robot motion control. Simulation results show that the proposed approach is effective for robot motion control in unknown environment.

Robotic assistants in personal care: A scoping review.

PubMed

Bilyea, A; Seth, N; Nesathurai, S; Abdullah, H A

2017-11-01

The aim of this study is to present an overview of the technological advances in the field of robotics developed for assistance with activities of daily living (ADL), and to present areas where further research is required. Four databases were searched for articles presenting either a novel design of one of these personal care robotic system or trial results relating to these systems. Articles presenting nine different robotic personal care systems were examined, six of which had been developed after 2005. These six also all have publications relating to their trials. In the majority of trials, patient independence was improved with operation of the robotic device for a specific subset of ADL. A map of the current state of the field of personal care robotics is presented in this study. Areas requiring further research include improving feedback and awareness, as well as refining control methods and pre-programmed behaviors. Developing an affordable, easy to use system would help fill the current gap in the commercial market. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Behavior generation strategy of artificial behavioral system by self-learning paradigm for autonomous robot tasks

NASA Astrophysics Data System (ADS)

Dağlarli, Evren; Temeltaş, Hakan

2008-04-01

In this study, behavior generation and self-learning paradigms are investigated for the real-time applications of multi-goal mobile robot tasks. The method is capable to generate new behaviors and it combines them in order to achieve multi goal tasks. The proposed method is composed from three layers: Behavior Generating Module, Coordination Level and Emotion -Motivation Level. Last two levels use Hidden Markov models to manage dynamical structure of behaviors. The kinematics and dynamic model of the mobile robot with non-holonomic constraints are considered in the behavior based control architecture. The proposed method is tested on a four-wheel driven and four-wheel steered mobile robot with constraints in simulation environment and results are obtained successfully.

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.

Robots in the service of animal behavior.

PubMed

Klein, Barrett A; Stein, Joey; Taylor, Ryan C

2012-09-01

As reading fiction can challenge us to better understand fact, using fake animals can sometimes serve as our best solution to understanding the behavior of real animals. The use of dummies, doppelgangers, fakes, and physical models have served to elicit behaviors in animal experiments since the early history of behavior studies, and, more recently, robotic animals have been employed by researchers to further coax behaviors from their study subjects. Here, we review the use of robots in the service of animal behavior, and describe in detail the production and use of one type of robot - "faux" frogs - to test female responses to multisensory courtship signals. The túngara frog (Physalaemus pustulosus) has been a study subject for investigating multimodal signaling, and we discuss the benefits and drawbacks of using the faux frogs we have designed, with the larger aim of inspiring other scientists to consider the appropriate application of physical models and robots in their research.

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

Experiences of a Motivational Interview Delivered by a Robot: Qualitative Study.

PubMed

Galvão Gomes da Silva, Joana; Kavanagh, David J; Belpaeme, Tony; Taylor, Lloyd; Beeson, Konna; Andrade, Jackie

2018-05-03

Motivational interviewing is an effective intervention for supporting behavior change but traditionally depends on face-to-face dialogue with a human counselor. This study addressed a key challenge for the goal of developing social robotic motivational interviewers: creating an interview protocol, within the constraints of current artificial intelligence, which participants will find engaging and helpful. The aim of this study was to explore participants' qualitative experiences of a motivational interview delivered by a social robot, including their evaluation of usability of the robot during the interaction and its impact on their motivation. NAO robots are humanoid, child-sized social robots. We programmed a NAO robot with Choregraphe software to deliver a scripted motivational interview focused on increasing physical activity. The interview was designed to be comprehensible even without an empathetic response from the robot. Robot breathing and face-tracking functions were used to give an impression of attentiveness. A total of 20 participants took part in the robot-delivered motivational interview and evaluated it after 1 week by responding to a series of written open-ended questions. Each participant was left alone to speak aloud with the robot, advancing through a series of questions by tapping the robot's head sensor. Evaluations were content-analyzed utilizing Boyatzis' steps: (1) sampling and design, (2) developing themes and codes, and (3) validating and applying the codes. Themes focused on interaction with the robot, motivation, change in physical activity, and overall evaluation of the intervention. Participants found the instructions clear and the navigation easy to use. Most enjoyed the interaction but also found it was restricted by the lack of individualized response from the robot. Many positively appraised the nonjudgmental aspect of the interview and how it gave space to articulate their motivation for change. Some participants felt that the intervention increased their physical activity levels. Social robots can achieve a fundamental objective of motivational interviewing, encouraging participants to articulate their goals and dilemmas aloud. Because they are perceived as nonjudgmental, robots may have advantages over more humanoid avatars for delivering virtual support for behavioral change. ©Joana Galvão Gomes da Silva, David J Kavanagh, Tony Belpaeme, Lloyd Taylor, Konna Beeson, Jackie Andrade. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 03.05.2018.

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.

Multi-Robot Search for a Moving Target: Integrating World Modeling, Task Assignment and Context

DTIC Science & Technology

2016-12-01

Case Study Our approach to coordination was initially motivated and developed in RoboCup soccer games. In fact, it has been first deployed on a team of...features a rather accurate model of the behavior and capabilities of the humanoid robot in the field. In the soccer case study , our goal is to...on experiments carried out with a team of humanoid robots in a soccer scenario and a team of mobile bases in an office environment. I. INTRODUCTION

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

Proactive learning for artificial cognitive systems

NASA Astrophysics Data System (ADS)

Lee, Soo-Young

2010-04-01

The Artificial Cognitive Systems (ACS) will be developed for human-like functions such as vision, auditory, inference, and behavior. Especially, computational models and artificial HW/SW systems will be devised for Proactive Learning (PL) and Self-Identity (SI). The PL model provides bilateral interactions between robot and unknown environment (people, other robots, cyberspace). For the situation awareness in unknown environment it is required to receive audiovisual signals and to accumulate knowledge. If the knowledge is not enough, the PL should improve by itself though internet and others. For human-oriented decision making it is also required for the robot to have self-identify and emotion. Finally, the developed models and system will be mounted on a robot for the human-robot co-existing society. The developed ACS will be tested against the new Turing Test for the situation awareness. The Test problems will consist of several video clips, and the performance of the ACSs will be compared against those of human with several levels of cognitive ability.

Arousal regulation and affective adaptation to human responsiveness by a robot that explores and learns a novel environment

PubMed Central

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. PMID:24860492

Inventing Japan's 'robotics culture': the repeated assembly of science, technology, and culture in social robotics.

PubMed

Sabanović, Selma

2014-06-01

Using interviews, participant observation, and published documents, this article analyzes the co-construction of robotics and culture in Japan through the technical discourse and practices of robotics researchers. Three cases from current robotics research--the seal-like robot PARO, the Humanoid Robotics Project HRP-2 humanoid, and 'kansei robotics' - show the different ways in which scientists invoke culture to provide epistemological grounding and possibilities for social acceptance of their work. These examples show how the production and consumption of social robotic technologies are associated with traditional crafts and values, how roboticists negotiate among social, technical, and cultural constraints while designing robots, and how humans and robots are constructed as cultural subjects in social robotics discourse. The conceptual focus is on the repeated assembly of cultural models of social behavior, organization, cognition, and technology through roboticists' narratives about the development of advanced robotic technologies. This article provides a picture of robotics as the dynamic construction of technology and culture and concludes with a discussion of the limits and possibilities of this vision in promoting a culturally situated understanding of technology and a multicultural view of science.

Fish and Robots Swimming Together in a Water Tunnel: Robot Color and Tail-Beat Frequency Influence Fish Behavior

PubMed Central

Polverino, Giovanni; Phamduy, Paul; Porfiri, Maurizio

2013-01-01

The possibility of integrating bioinspired robots in groups of live social animals may constitute a valuable tool to study the basis of social behavior and uncover the fundamental determinants of animal functions and dysfunctions. In this study, we investigate the interactions between individual golden shiners (Notemigonus crysoleucas) and robotic fish swimming together in a water tunnel at constant flow velocity. The robotic fish is designed to mimic its live counterpart in the aspect ratio, body shape, dimension, and locomotory pattern. Fish positional preference with respect to the robot is experimentally analyzed as the robot's color pattern and tail-beat frequency are varied. Behavioral observations are corroborated by particle image velocimetry studies aimed at investigating the flow structure behind the robotic fish. Experimental results show that the time spent by golden shiners in the vicinity of the bioinspired robotic fish is the highest when the robot mimics their natural color pattern and beats its tail at the same frequency. In these conditions, fish tend to swim at the same depth of the robotic fish, where the wake from the robotic fish is stronger and hydrodynamic return is most likely to be effective. PMID:24204882

Fish and robots swimming together in a water tunnel: robot color and tail-beat frequency influence fish behavior.

PubMed

Polverino, Giovanni; Phamduy, Paul; Porfiri, Maurizio

2013-01-01

The possibility of integrating bioinspired robots in groups of live social animals may constitute a valuable tool to study the basis of social behavior and uncover the fundamental determinants of animal functions and dysfunctions. In this study, we investigate the interactions between individual golden shiners (Notemigonus crysoleucas) and robotic fish swimming together in a water tunnel at constant flow velocity. The robotic fish is designed to mimic its live counterpart in the aspect ratio, body shape, dimension, and locomotory pattern. Fish positional preference with respect to the robot is experimentally analyzed as the robot's color pattern and tail-beat frequency are varied. Behavioral observations are corroborated by particle image velocimetry studies aimed at investigating the flow structure behind the robotic fish. Experimental results show that the time spent by golden shiners in the vicinity of the bioinspired robotic fish is the highest when the robot mimics their natural color pattern and beats its tail at the same frequency. In these conditions, fish tend to swim at the same depth of the robotic fish, where the wake from the robotic fish is stronger and hydrodynamic return is most likely to be effective.

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.

Apparatus for multiprocessor-based control of a multiagent robot

NASA Technical Reports Server (NTRS)

Peters, II, Richard Alan (Inventor)

2009-01-01

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Architecture for Multiple Interacting Robot Intelligences

NASA Technical Reports Server (NTRS)

Peters, Richard Alan, II (Inventor)

2008-01-01

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a database associative memory (DBAM) that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Toward understanding social cues and signals in human–robot interaction: effects of robot gaze and proxemic behavior

PubMed Central

Fiore, Stephen M.; Wiltshire, Travis J.; Lobato, Emilio J. C.; Jentsch, Florian G.; Huang, Wesley H.; Axelrod, Benjamin

2013-01-01

As robots are increasingly deployed in settings requiring social interaction, research is needed to examine the social signals perceived by humans when robots display certain social cues. In this paper, we report a study designed to examine how humans interpret social cues exhibited by robots. We first provide a brief overview of perspectives from social cognition in humans and how these processes are applicable to human–robot interaction (HRI). We then discuss the need to examine the relationship between social cues and signals as a function of the degree to which a robot is perceived as a socially present agent. We describe an experiment in which social cues were manipulated on an iRobot AvaTM mobile robotics platform in a hallway navigation scenario. Cues associated with the robot’s proxemic behavior were found to significantly affect participant perceptions of the robot’s social presence and emotional state while cues associated with the robot’s gaze behavior were not found to be significant. Further, regardless of the proxemic behavior, participants attributed more social presence and emotional states to the robot over repeated interactions than when they first interacted with it. Generally, these results indicate the importance for HRI research to consider how social cues expressed by a robot can differentially affect perceptions of the robot’s mental states and intentions. The discussion focuses on implications for the design of robotic systems and future directions for research on the relationship between social cues and signals. PMID:24348434

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.

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

Measurement of Contact Behavior Including Slippage of Cuff When Using Wearable Physical Assistant Robot.

PubMed

Akiyama, Yasuhiro; Okamoto, Shogo; Yamada, Yoji; Ishiguro, Kenji

2016-07-01

Continuous use of wearable robots can cause skin injuries beneath the cuffs of robots. To prevent such injuries, understanding the contact behavior of the cuff is important. Thus far, this contact behavior has not been studied because of the difficulty involved in measuring the slippage under the cuff. In this study, for the first time, the relative displacement, slippage, and interaction force and moment at the thigh cuff of a robot during sit-to-stand motion were measured using an instrumented cuff, which was developed for this purpose. The results indicated that the slippage and relative displacement under the cuff was uneven because of the rotation of the cuff, which suggests that the risk of skin injuries is different at different positions. Especially, the skin closer to the hip showed larger dynamism, with a maximum slippage of approximately 10 mm and a displacement of 20 mm during motion. Another important phenomenon was the individual difference among subjects. During motion, the interaction force, moment, and slippage of some subjects suddenly increased. Such behavior results in stress concentration, which increases the risk of skin injuries. These analyses are intended to understand how skin injuries are caused and to design measures to prevent such injuries.

Google glass-based remote control of a mobile robot

NASA Astrophysics Data System (ADS)

Yu, Song; Wen, Xi; Li, Wei; Chen, Genshe

2016-05-01

In this paper, we present an approach to remote control of a mobile robot via a Google Glass with the multi-function and compact size. This wearable device provides a new human-machine interface (HMI) to control a robot without need for a regular computer monitor because the Google Glass micro projector is able to display live videos around robot environments. In doing it, we first develop a protocol to establish WI-FI connection between Google Glass and a robot and then implement five types of robot behaviors: Moving Forward, Turning Left, Turning Right, Taking Pause, and Moving Backward, which are controlled by sliding and clicking the touchpad located on the right side of the temple. In order to demonstrate the effectiveness of the proposed Google Glass-based remote control system, we navigate a virtual Surveyor robot to pass a maze. Experimental results demonstrate that the proposed control system achieves the desired performance.

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.

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.

A low-cost, computer-controlled robotic flower system for behavioral experiments.

PubMed

Kuusela, Erno; Lämsä, Juho

2016-04-01

Human observations during behavioral studies are expensive, time-consuming, and error prone. For this reason, automatization of experiments is highly desirable, as it reduces the risk of human errors and workload. The robotic system we developed is simple and cheap to build and handles feeding and data collection automatically. The system was built using mostly off-the-shelf components and has a novel feeding mechanism that uses servos to perform refill operations. We used the robotic system in two separate behavioral studies with bumblebees (Bombus terrestris): The system was used both for training of the bees and for the experimental data collection. The robotic system was reliable, with no flight in our studies failing due to a technical malfunction. The data recorded were easy to apply for further analysis. The software and the hardware design are open source. The development of cheap open-source prototyping platforms during the recent years has opened up many possibilities in designing of experiments. Automatization not only reduces workload, but also potentially allows experimental designs never done before, such as dynamic experiments, where the system responds to, for example, learning of the animal. We present a complete system with hardware and software, and it can be used as such in various experiments requiring feeders and collection of visitation data. Use of the system is not limited to any particular experimental setup or even species.

Developing a telepresence robot for interpersonal communication with the elderly in a home environment.

PubMed

Tsai, Tzung-Cheng; Hsu, Yeh-Liang; Ma, An-I; King, Trevor; Wu, Chang-Huei

2007-08-01

"Telepresence" is an interesting field that includes virtual reality implementations with human-system interfaces, communication technologies, and robotics. This paper describes the development of a telepresence robot called Telepresence Robot for Interpersonal Communication (TRIC) for the purpose of interpersonal communication with the elderly in a home environment. The main aim behind TRIC's development is to allow elderly populations to remain in their home environments, while loved ones and caregivers are able to maintain a higher level of communication and monitoring than via traditional methods. TRIC aims to be a low-cost, lightweight robot, which can be easily implemented in the home environment. Under this goal, decisions on the design elements included are discussed. In particular, the implementation of key autonomous behaviors in TRIC to increase the user's capability of projection of self and operation of the telepresence robot, in addition to increasing the interactive capability of the participant as a dialogist are emphasized. The technical development and integration of the modules in TRIC, as well as human factors considerations are then described. Preliminary functional tests show that new users were able to effectively navigate TRIC and easily locate visual targets. Finally the future developments of TRIC, especially the possibility of using TRIC for home tele-health monitoring and tele-homecare visits are discussed.

Variety Wins: Soccer-Playing Robots and Infant Walking.

PubMed

Ossmy, Ori; Hoch, Justine E; MacAlpine, Patrick; Hasan, Shohan; Stone, Peter; Adolph, Karen E

2018-01-01

Although both infancy and artificial intelligence (AI) researchers are interested in developing systems that produce adaptive, functional behavior, the two disciplines rarely capitalize on their complementary expertise. Here, we used soccer-playing robots to test a central question about the development of infant walking. During natural activity, infants' locomotor paths are immensely varied. They walk along curved, multi-directional paths with frequent starts and stops. Is the variability observed in spontaneous infant walking a "feature" or a "bug?" In other words, is variability beneficial for functional walking performance? To address this question, we trained soccer-playing robots on walking paths generated by infants during free play and tested them in simulated games of "RoboCup." In Tournament 1, we compared the functional performance of a simulated robot soccer team trained on infants' natural paths with teams trained on less varied, geometric paths-straight lines, circles, and squares. Across 1,000 head-to-head simulated soccer matches, the infant-trained team consistently beat all teams trained with less varied walking paths. In Tournament 2, we compared teams trained on different clusters of infant walking paths. The team trained with the most varied combination of path shape, step direction, number of steps, and number of starts and stops outperformed teams trained with less varied paths. This evidence indicates that variety is a crucial feature supporting functional walking performance. More generally, we propose that robotics provides a fruitful avenue for testing hypotheses about infant development; reciprocally, observations of infant behavior may inform research on artificial intelligence.

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.

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.

[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.

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.

On the Evolution of Behaviors through Embodied Imitation.

PubMed

Erbas, Mehmet D; Bull, Larry; Winfield, Alan F T

2015-01-01

This article describes research in which embodied imitation and behavioral adaptation are investigated in collective robotics. We model social learning in artificial agents with real robots. The robots are able to observe and learn each others' movement patterns using their on-board sensors only, so that imitation is embodied. We show that the variations that arise from embodiment allow certain behaviors that are better adapted to the process of imitation to emerge and evolve during multiple cycles of imitation. As these behaviors are more robust to uncertainties in the real robots' sensors and actuators, they can be learned by other members of the collective with higher fidelity. Three different types of learned-behavior memory have been experimentally tested to investigate the effect of memory capacity on the evolution of movement patterns, and results show that as the movement patterns evolve through multiple cycles of imitation, selection, and variation, the robots are able to, in a sense, agree on the structure of the behaviors that are imitated.

Robots in the service of animal behavior

PubMed Central

Klein, Barrett A.; Stein, Joey; Taylor, Ryan C.

2012-01-01

As reading fiction can challenge us to better understand fact, using fake animals can sometimes serve as our best solution to understanding the behavior of real animals. The use of dummies, doppelgangers, fakes, and physical models have served to elicit behaviors in animal experiments since the early history of behavior studies, and, more recently, robotic animals have been employed by researchers to further coax behaviors from their study subjects. Here, we review the use of robots in the service of animal behavior, and describe in detail the production and use of one type of robot – “faux” frogs – to test female responses to multisensory courtship signals. The túngara frog (Physalaemus pustulosus) has been a study subject for investigating multimodal signaling, and we discuss the benefits and drawbacks of using the faux frogs we have designed, with the larger aim of inspiring other scientists to consider the appropriate application of physical models and robots in their research. PMID:23181162

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

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.

Influences of a Socially Interactive Robot on the Affective Behavior of Young Children with Disabilities. Social Robots Research Reports, Number 3

ERIC Educational Resources Information Center

Dunst, Carl J.; Prior, Jeremy; Hamby, Deborah W.; Trivette, Carol M.

2013-01-01

Findings from two studies of 11 young children with autism, Down syndrome, or attention deficit disorders investigating the effects of Popchilla, a socially interactive robot, on the children's affective behavior are reported. The children were observed under two conditions, child-toy interactions and child-robot interactions, and ratings of child…

Modeling, validation and analysis of a Whegs robot in the USARSim environment

NASA Astrophysics Data System (ADS)

Taylor, Brian K.; Balakirsky, Stephen; Messina, Elena; Quinn, Roger D.

2008-04-01

Simulation of robots in a virtual domain has multiple benefits. End users can use the simulation as a training tool to increase their skill with the vehicle without risking damage to the robot or surrounding environment. Simulation allows researchers and developers to benchmark robot performance in a range of scenarios without having the physical robot or environment present. The simulation can also help guide and generate new design concepts. USARSim (Unified System for Automation and Robot Simulation) is a tool that is being used to accomplish these goals, particularly within the realm of search and rescue. It is based on the Unreal Tournament 2004 gaming engine, which approximates the physics of how a robot interacts with its environment. A family of vehicles that can benefit from simulation in USARSim are Whegs TM robots. Developed in the Biorobotics Laboratory at Case Western Reserve University, Whegs TM robots are highly mobile ground vehicles that use abstracted biological principles to achieve a robust level of locomotion, including passive gait adaptation and enhanced climbing abilities. This paper describes a Whegs TM robot model that was constructed in USARSim. The model was configured with the same kinds of behavioral characteristics found in real Whegs TM vehicles. Once these traits were implemented, a validation study was performed using identical performance metrics measured on both the virtual and real vehicles to quantify vehicle performance and to ensure that the virtual robot's performance matched that of the real robot.

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.

An Integrated Framework for Human-Robot Collaborative Manipulation.

PubMed

Sheng, Weihua; Thobbi, Anand; Gu, Ye

2015-10-01

This paper presents an integrated learning framework that enables humanoid robots to perform human-robot collaborative manipulation tasks. Specifically, a table-lifting task performed jointly by a human and a humanoid robot is chosen for validation purpose. The proposed framework is split into two phases: 1) phase I-learning to grasp the table and 2) phase II-learning to perform the manipulation task. An imitation learning approach is proposed for phase I. In phase II, the behavior of the robot is controlled by a combination of two types of controllers: 1) reactive and 2) proactive. The reactive controller lets the robot take a reactive control action to make the table horizontal. The proactive controller lets the robot take proactive actions based on human motion prediction. A measure of confidence of the prediction is also generated by the motion predictor. This confidence measure determines the leader/follower behavior of the robot. Hence, the robot can autonomously switch between the behaviors during the task. Finally, the performance of the human-robot team carrying out the collaborative manipulation task is experimentally evaluated on a platform consisting of a Nao humanoid robot and a Vicon motion capture system. Results show that the proposed framework can enable the robot to carry out the collaborative manipulation task successfully.

Robot Acquisition of Active Maps Through Teleoperation and Vector Space Analysis

NASA Technical Reports Server (NTRS)

Peters, Richard Alan, II

2003-01-01

The work performed under this contract was in the area of intelligent robotics. The problem being studied was the acquisition of intelligent behaviors by a robot. The method was to acquire action maps that describe tasks as sequences of reflexive behaviors. Action maps (a.k.a. topological maps) are graphs whose nodes represent sensorimotor states and whose edges represent the motor actions that cause the robot to proceed from one state to the next. The maps were acquired by the robot after being teleoperated or otherwise guided by a person through a task several times. During a guided task, the robot records all its sensorimotor signals. The signals from several task trials are partitioned into episodes of static behavior. The corresponding episodes from each trial are averaged to produce a task description as a sequence of characteristic episodes. The sensorimotor states that indicate episode boundaries become the nodes, and the static behaviors, the edges. It was demonstrated that if compound maps are constructed from a set of tasks then the robot can perform new tasks in which it was never explicitly trained.

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

Serendipitous Offline Learning in a Neuromorphic Robot.

PubMed

Stewart, Terrence C; Kleinhans, Ashley; Mundy, Andrew; Conradt, Jörg

2016-01-01

We demonstrate a hybrid neuromorphic learning paradigm that learns complex sensorimotor mappings based on a small set of hard-coded reflex behaviors. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviors. All sensor data is provided via a spike-based silicon retina camera (eDVS), and all control is implemented via spiking neurons simulated on neuromorphic hardware (SpiNNaker). Given this control system, the robot is capable of simple obstacle avoidance and random exploration. To train the robot to perform more complex tasks, we observe the robot and find instances where the robot accidentally performs the desired action. Data recorded from the robot during these times is then used to update the neural control system, increasing the likelihood of the robot performing that task in the future, given a similar sensor state. As an example application of this general-purpose method of training, we demonstrate the robot learning to respond to novel sensory stimuli (a mirror) by turning right if it is present at an intersection, and otherwise turning left. In general, this system can learn arbitrary relations between sensory input and motor behavior.

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

Evaluating the human likeness of an android by comparing gaze behaviors elicited by the android and a person

PubMed Central

MINATO, TAKASHI; SHIMADA, MICHIHIRO; ITAKURA, SHOJI; LEE, KANG; ISHIGURO, HIROSHI

2008-01-01

Our research goal is to discover the principles underlying natural communication among individuals and to establish a methodology for the development of expressive humanoid robots. For this purpose we have developed androids that closely resemble human beings. The androids enable us to investigate a number of phenomena related to human interaction that could not otherwise be investigated with mechanical-looking robots. This is because more human-like devices are in a better position to elicit the kinds of responses that people direct toward each other. Moreover, we cannot ignore the role of appearance in giving us a subjective impression of human presence or intelligence. However, this impression is influenced by behavior and the complex relationship between appearance and behavior. This paper proposes a hypothesis about how appearance and behavior are related, and maps out a plan for android research to investigate this hypothesis. We then examine a study that evaluates the human likeness of androids according to the gaze behavior they elicit. Studies such as these, which integrate the development of androids with the investigation of human behavior, constitute a new research area that fuses engineering and science. PMID:18985174

Robotics in scansorial environments

NASA Astrophysics Data System (ADS)

Autumn, Kellar; Buehler, Martin; Cutkosky, Mark; Fearing, Ronald; Full, Robert J.; Goldman, Daniel; Groff, Richard; Provancher, William; Rizzi, Alfred A.; Saranli, Uluc; Saunders, Aaron; Koditschek, Daniel E.

2005-05-01

We review a large multidisciplinary effort to develop a family of autonomous robots capable of rapid, agile maneuvers in and around natural and artificial vertical terrains such as walls, cliffs, caves, trees and rubble. Our robot designs are inspired by (but not direct copies of) biological climbers such as cockroaches, geckos, and squirrels. We are incorporating advanced materials (e.g., synthetic gecko hairs) into these designs and fabricating them using state of the art rapid prototyping techniques (e.g., shape deposition manufacturing) that permit multiple iterations of design and testing with an effective integration path for the novel materials and components. We are developing novel motion control techniques to support dexterous climbing behaviors that are inspired by neuroethological studies of animals and descended from earlier frameworks that have proven analytically tractable and empirically sound. Our near term behavioral targets call for vertical climbing on soft (e.g., bark) or rough surfaces and for ascents on smooth, hard steep inclines (e.g., 60 degree slopes on metal or glass sheets) at one body length per second.

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.

Model-Based Experimental Development of Passive Compliant Robot Legs from Fiberglass Composites

PubMed Central

Lin, Shang-Chang; Hu, Chia-Jui; Lin, Pei-Chun

2015-01-01

We report on the methodology of developing compliant, half-circular, and composite robot legs with designable stiffness. First, force-displacement experiments on flat cantilever composites made by one or multifiberglass cloths are executed. By mapping the cantilever mechanics to the virtual spring model, the equivalent elastic moduli of the composites can be derived. Next, by using the model that links the curved beam mechanics back to the virtual spring, the resultant stiffness of the composite in a half-circular shape can be estimated without going through intensive experimental tryouts. The overall methodology has been experimentally validated, and the fabricated composites were used on a hexapod robot to perform walking and leaping behaviors. PMID:27065748

Autism and social robotics: A systematic review.

PubMed

Pennisi, Paola; Tonacci, Alessandro; Tartarisco, Gennaro; Billeci, Lucia; Ruta, Liliana; Gangemi, Sebastiano; Pioggia, Giovanni

2016-02-01

Social robotics could be a promising method for Autism Spectrum Disorders (ASD) treatment. The aim of this article is to carry out a systematic literature review of the studies on this topic that were published in the last 10 years. We tried to address the following questions: can social robots be a useful tool in autism therapy? We followed the PRISMA guidelines, and the protocol was registered within PROSPERO database (CRD42015016158). We found many positive implications in the use of social robots in therapy as for example: ASD subjects often performed better with a robot partner rather than a human partner; sometimes, ASD patients had, toward robots, behaviors that TD patients had toward human agents; ASDs had a lot of social behaviors toward robots; during robotic sessions, ASDs showed reduced repetitive and stereotyped behaviors and, social robots manage to improve spontaneous language during therapy sessions. Therefore, robots provide therapists and researchers a means to connect with autistic subjects in an easier way, but studies in this area are still insufficient. It is necessary to clarify whether sex, intelligence quotient, and age of participants affect the outcome of therapy and whether any beneficial effects only occur during the robotic session or if they are still observable outside the clinical/experimental context. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

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

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.

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.

Investigating Models of Social Development Using a Humanoid Robot

DTIC Science & Technology

1998-01-01

robot interaction and cooper- and neural models of spinal motor neurons (Williamson ation (Takanishi, Hirano & Sato 1998, Morita, Shibuya 1996...etiology and behavioral manifestations of pervasive de- Individuals with autism tend to have normal sensory velopmental disorders such as autism and...grasp the implications of this information. Wlile interested in joint attention both as an explanation the deficits of autism certainly cover many other

An affordable compact humanoid robot for Autism Spectrum Disorder interventions in children.

PubMed

Dickstein-Fischer, Laurie; Alexander, Elizabeth; Yan, Xiaoan; Su, Hao; Harrington, Kevin; Fischer, Gregory S

2011-01-01

Autism Spectrum Disorder impacts an ever-increasing number of children. The disorder is marked by social functioning that is characterized by impairment in the use of nonverbal behaviors, failure to develop appropriate peer relationships and lack of social and emotional exchanges. Providing early intervention through the modality of play therapy has been effective in improving behavioral and social outcomes for children with autism. Interacting with humanoid robots that provide simple emotional response and interaction has been shown to improve the communication skills of autistic children. In particular, early intervention and continuous care provide significantly better outcomes. Currently, there are no robots capable of meeting these requirements that are both low-cost and available to families of autistic children for in-home use. This paper proposes the piloting the use of robotics as an improved diagnostic and early intervention tool for autistic children that is affordable, non-threatening, durable, and capable of interacting with an autistic child. This robot has the ability to track the child with its 3 degree of freedom (DOF) eyes and 3-DOF head, open and close its 1-DOF beak and 1-DOF each eyelids, raise its 1-DOF each wings, play sound, and record sound. These attributes will give it the ability to be used for the diagnosis and treatment of autism. As part of this project, the robot and the electronic and control software have been developed, and integrating semi-autonomous interaction, teleoperation from a remote healthcare provider and initiating trials with children in a local clinic are in progress.

Plume-tracking robots: a new application of chemical sensors.

PubMed

Ishid, H; Nakamoto, T; Moriizumi, T; Kikas, T; Janata, J

2001-04-01

Many animals have the ability to search for odor sources by tracking their plumes. Some of the key features of this search behavior have been successfully transferred to robot platforms, although the capabilities of animals are still beyond the current level of sensor technologies. The examples described in this paper are (1) incorporating into a wheeled robot the upwind surges and casting used by moths in tracking pheromone plumes, (2) extracting useful information from the response patterns of a chemical sensor array patterned after the spatially distributed chemoreceptors of some animals, and (3) mimicking the fanning behavior of silkworm moths to enhance the reception of chemical signals by drawing molecules from one direction. The achievements so far and current efforts are reviewed to illustrate the steps to be taken toward future development of this technology.

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.

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.

Variety Wins: Soccer-Playing Robots and Infant Walking

PubMed Central

Ossmy, Ori; Hoch, Justine E.; MacAlpine, Patrick; Hasan, Shohan; Stone, Peter; Adolph, Karen E.

2018-01-01

Although both infancy and artificial intelligence (AI) researchers are interested in developing systems that produce adaptive, functional behavior, the two disciplines rarely capitalize on their complementary expertise. Here, we used soccer-playing robots to test a central question about the development of infant walking. During natural activity, infants' locomotor paths are immensely varied. They walk along curved, multi-directional paths with frequent starts and stops. Is the variability observed in spontaneous infant walking a “feature” or a “bug?” In other words, is variability beneficial for functional walking performance? To address this question, we trained soccer-playing robots on walking paths generated by infants during free play and tested them in simulated games of “RoboCup.” In Tournament 1, we compared the functional performance of a simulated robot soccer team trained on infants' natural paths with teams trained on less varied, geometric paths—straight lines, circles, and squares. Across 1,000 head-to-head simulated soccer matches, the infant-trained team consistently beat all teams trained with less varied walking paths. In Tournament 2, we compared teams trained on different clusters of infant walking paths. The team trained with the most varied combination of path shape, step direction, number of steps, and number of starts and stops outperformed teams trained with less varied paths. This evidence indicates that variety is a crucial feature supporting functional walking performance. More generally, we propose that robotics provides a fruitful avenue for testing hypotheses about infant development; reciprocally, observations of infant behavior may inform research on artificial intelligence. PMID:29867427

Novel locomotion via biological inspiration

NASA Astrophysics Data System (ADS)

Quinn, Roger D.; Boxerbaum, Alexander; Palmer, Luther; Chiel, Hillel; Diller, Eric; Hunt, Alexander; Bachmann, Richard

2011-05-01

Animal behavioral, physiological and neurobiological studies are providing a wealth of inspirational data for robot design and control. Several very different biologically inspired mobile robots will be reviewed. A robot called DIGbot is being developed that moves independent of the direction of gravity using Distributed Inward Gripping (DIG) as a rapid and robust attachment mechanism observed in climbing animals. DIGbot is an 18 degree of freedom hexapod with onboard power and control systems. Passive compliance in its feet, which is inspired by the flexible tarsus of the cockroach, increases the robustness of the adhesion strategy and enables DIGbot to execute large steps and stationary turns while walking on mesh screens. A Whegs™ robot, inspired by insect locomotion principles, is being developed that can be rapidly reconfigured between tracks and wheel-legs and carry GeoSystems Zipper Mast. The mechanisms that cause it to passively change its gait on irregular terrain have been integrated into its hubs for a compact and modular design. The robot is designed to move smoothly on moderately rugged terrain using its tracks and run on irregular terrain and stairs using its wheel-legs. We are also developing soft bodied robots that use peristalsis, the same method of locomotion earthworms use. We present a technique of using a braided mesh exterior to produce fluid waves of motion along the body of the robot that increase the robot's speed relative to previous designs. The concept is highly scalable, for endoscopes to water, oil or gas line inspection.

Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior

DTIC Science & Technology

2006-09-28

navigate in an unstructured environment to a specific target or location. 15. SUBJECT TERMS autonomous vehicles , fuzzy logic, learning behavior...ANSI-Std Z39-18 Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior FINAL REPORT 9/28/2006 Dean B. Edwards Department...the future, as greater numbers of autonomous vehicles are employed, it is hoped that lower LONG-TERM GOALS Use LAGR (Learning Applied to Ground Robots

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.

Towards Autonomous Operation of Robonaut 2

NASA Technical Reports Server (NTRS)

Badger, Julia M.; Hart, Stephen W.; Yamokoski, J. D.

2011-01-01

The Robonaut 2 (R2) platform, as shown in Figure 1, was designed through a collaboration between NASA and General Motors to be a capable robotic assistant with the dexterity similar to a suited astronaut [1]. An R2 robot was sent to the International Space Station (ISS) in February 2011 and, in doing so, became the first humanoid robot in space. Its capabilities are presently being tested and expanded to increase its usefulness to the crew. Current work on R2 includes the addition of a mobility platform to allow the robot to complete tasks (such as cleaning, maintenance, or simple construction activities) both inside and outside of the ISS. To support these new activities, R2's software architecture is being developed to provide efficient ways of programming robust and autonomous behavior. In particular, a multi-tiered software architecture is proposed that combines principles of low-level feedback control with higher-level planners that accomplish behavioral goals at the task level given the run-time context, user constraints, the health of the system, and so on. The proposed architecture is shown in Figure 2. At the lowest-level, the resource level, there exists the various sensory and motor signals available to the system. The sensory signals for a robot such as R2 include multiple channels of force/torque data, joint or Cartesian positions calculated through the robot's proprioception, and signals derived from objects observable by its cameras.

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.

Multi-source micro-friction identification for a class of cable-driven robots with passive backbone

NASA Astrophysics Data System (ADS)

Tjahjowidodo, Tegoeh; Zhu, Ke; Dailey, Wayne; Burdet, Etienne; Campolo, Domenico

2016-12-01

This paper analyses the dynamics of cable-driven robots with a passive backbone and develops techniques for their dynamic identification, which are tested on the H-Man, a planar cabled differential transmission robot for haptic interaction. The mechanism is optimized for human-robot interaction by accounting for the cost-benefit-ratio of the system, specifically by eliminating the necessity of an external force sensor to reduce the overall cost. As a consequence, this requires an effective dynamic model for accurate force feedback applications which include friction behavior in the system. We first consider the significance of friction in both the actuator and backbone spaces. Subsequently, we study the required complexity of the stiction model for the application. Different models representing different levels of complexity are investigated, ranging from the conventional approach of Coulomb to an advanced model which includes hysteresis. The results demonstrate each model's ability to capture the dynamic behavior of the system. In general, it is concluded that there is a trade-off between model accuracy and the model cost.

A robotic system for researching social integration in honeybees.

PubMed

Griparić, Karlo; Haus, Tomislav; Miklić, Damjan; Polić, Marsela; Bogdan, Stjepan

2017-01-01

In this paper, we present a novel robotic system developed for researching collective social mechanisms in a biohybrid society of robots and honeybees. The potential for distributed coordination, as observed in nature in many different animal species, has caused an increased interest in collective behaviour research in recent years because of its applicability to a broad spectrum of technical systems requiring robust multi-agent control. One of the main problems is understanding the mechanisms driving the emergence of collective behaviour of social animals. With the aim of deepening the knowledge in this field, we have designed a multi-robot system capable of interacting with honeybees within an experimental arena. The final product, stationary autonomous robot units, designed by specificaly considering the physical, sensorimotor and behavioral characteristics of the honeybees (lat. Apis mallifera), are equipped with sensing, actuating, computation, and communication capabilities that enable the measurement of relevant environmental states, such as honeybee presence, and adequate response to the measurements by generating heat, vibration and airflow. The coordination among robots in the developed system is established using distributed controllers. The cooperation between the two different types of collective systems is realized by means of a consensus algorithm, enabling the honeybees and the robots to achieve a common objective. Presented results, obtained within ASSISIbf project, show successful cooperation indicating its potential for future applications.

ARV robotic technologies (ART): a risk reduction effort for future unmanned systems

NASA Astrophysics Data System (ADS)

Jaster, Jeffrey F.

2006-05-01

The Army's ARV (Armed Robotic Vehicle) Robotic Technologies (ART) program is working on the development of various technological thrusts for use in the robotic forces of the future. The ART program will develop, integrate and demonstrate the technology required to advance the maneuver technologies (i.e., perception, mobility, tactical behaviors) and increase the survivability of unmanned platforms for the future force while focusing on reducing the soldiers' burden by providing an increase in vehicle autonomy coinciding with a decrease in the total number user interventions required to control the unmanned assets. This program will advance the state of the art in perception technologies to provide the unmanned platform an increasingly accurate view of the terrain that surrounds it; while developing tactical/mission behavior technologies to provide the Unmanned Ground Vehicle (UGV) the capability to maneuver tactically, in conjunction with the manned systems in an autonomous mode. The ART testbed will be integrated with the advanced technology software and associated hardware developed under this effort, and incorporate appropriate mission modules (e.g. RSTA sensors, MILES, etc.) to support Warfighter experiments and evaluations (virtual and field) in a military significant environment (open/rolling and complex/urban terrain). The outcome of these experiments as well as other lessons learned through out the program life cycle will be used to reduce the current risks that are identified for the future UGV systems that will be developed under the Future Combat Systems (FCS) program, including the early integration of an FCS-like autonomous navigation system onto a tracked skid steer platform.

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

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.

Model-based safety analysis of human-robot interactions: the MIRAS walking assistance robot.

PubMed

Guiochet, Jérémie; Hoang, Quynh Anh Do; Kaaniche, Mohamed; Powell, David

2013-06-01

Robotic systems have to cope with various execution environments while guaranteeing safety, and in particular when they interact with humans during rehabilitation tasks. These systems are often critical since their failure can lead to human injury or even death. However, such systems are difficult to validate due to their high complexity and the fact that they operate within complex, variable and uncertain environments (including users), in which it is difficult to foresee all possible system behaviors. Because of the complexity of human-robot interactions, rigorous and systematic approaches are needed to assist the developers in the identification of significant threats and the implementation of efficient protection mechanisms, and in the elaboration of a sound argumentation to justify the level of safety that can be achieved by the system. For threat identification, we propose a method called HAZOP-UML based on a risk analysis technique adapted to system description models, focusing on human-robot interaction models. The output of this step is then injected in a structured safety argumentation using the GSN graphical notation. Those approaches have been successfully applied to the development of a walking assistant robot which is now in clinical validation.

Electrically Driven Microengineered Bioinspired Soft Robots.

PubMed

Shin, Su Ryon; Migliori, Bianca; Miccoli, Beatrice; Li, Yi-Chen; Mostafalu, Pooria; Seo, Jungmok; Mandla, Serena; Enrico, Alessandro; Antona, Silvia; Sabarish, Ram; Zheng, Ting; Pirrami, Lorenzo; Zhang, Kaizhen; Zhang, Yu Shrike; Wan, Kai-Tak; Demarchi, Danilo; Dokmeci, Mehmet R; Khademhosseini, Ali

2018-03-01

To create life-like movements, living muscle actuator technologies have borrowed inspiration from biomimetic concepts in developing bioinspired robots. Here, the development of a bioinspired soft robotics system, with integrated self-actuating cardiac muscles on a hierarchically structured scaffold with flexible gold microelectrodes is reported. Inspired by the movement of living organisms, a batoid-fish-shaped substrate is designed and reported, which is composed of two micropatterned hydrogel layers. The first layer is a poly(ethylene glycol) hydrogel substrate, which provides a mechanically stable structure for the robot, followed by a layer of gelatin methacryloyl embedded with carbon nanotubes, which serves as a cell culture substrate, to create the actuation component for the soft body robot. In addition, flexible Au microelectrodes are embedded into the biomimetic scaffold, which not only enhance the mechanical integrity of the device, but also increase its electrical conductivity. After culturing and maturation of cardiomyocytes on the biomimetic scaffold, they show excellent myofiber organization and provide self-actuating motions aligned with the direction of the contractile force of the cells. The Au microelectrodes placed below the cell layer further provide localized electrical stimulation and control of the beating behavior of the bioinspired soft robot. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Query Processing for Probabilistic State Diagrams Describing Multiple Robot Navigation in an Indoor Environment

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

Czejdo, Bogdan; Bhattacharya, Sambit; Ferragut, Erik M

2012-01-01

This paper describes the syntax and semantics of multi-level state diagrams to support probabilistic behavior of cooperating robots. The techniques are presented to analyze these diagrams by querying combined robots behaviors. It is shown how to use state abstraction and transition abstraction to create, verify and process large probabilistic state diagrams.

Adaptive model-based assistive control for pneumatic direct driven soft rehabilitation robots.

PubMed

Wilkening, Andre; Ivlev, Oleg

2013-06-01

Assistive behavior and inherent compliance are assumed to be the essential properties for effective robot-assisted therapy in neurological as well as in orthopedic rehabilitation. This paper presents two adaptive model-based assistive controllers for pneumatic direct driven soft rehabilitation robots that are based on separated models of the soft-robot and the patient's extremity, in order to take into account the individual patient's behavior, effort and ability during control, what is assumed to be essential to relearn lost motor functions in neurological and facilitate muscle reconstruction in orthopedic rehabilitation. The high inherent compliance of soft-actuators allows for a general human-robot interaction and provides the base for effective and dependable assistive control. An inverse model of the soft-robot with estimated parameters is used to achieve robot transparency during treatment and inverse adaptive models of the individual patient's extremity allow the controllers to learn on-line the individual patient's behavior and effort and react in a way that assist the patient only as much as needed. The effectiveness of the controllers is evaluated with unimpaired subjects using a first prototype of a soft-robot for elbow training. Advantages and disadvantages of both controllers are analyzed and discussed.

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.

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.

Evolving a Behavioral Repertoire for a Walking Robot.

PubMed

Cully, A; Mouret, J-B

2016-01-01

Numerous algorithms have been proposed to allow legged robots to learn to walk. However, most of these algorithms are devised to learn walking in a straight line, which is not sufficient to accomplish any real-world mission. Here we introduce the Transferability-based Behavioral Repertoire Evolution algorithm (TBR-Evolution), a novel evolutionary algorithm that simultaneously discovers several hundreds of simple walking controllers, one for each possible direction. By taking advantage of solutions that are usually discarded by evolutionary processes, TBR-Evolution is substantially faster than independently evolving each controller. Our technique relies on two methods: (1) novelty search with local competition, which searches for both high-performing and diverse solutions, and (2) the transferability approach, which combines simulations and real tests to evolve controllers for a physical robot. We evaluate this new technique on a hexapod robot. Results show that with only a few dozen short experiments performed on the robot, the algorithm learns a repertoire of controllers that allows the robot to reach every point in its reachable space. Overall, TBR-Evolution introduced a new kind of learning algorithm that simultaneously optimizes all the achievable behaviors of a robot.

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.

Put Your Robot In, Put Your Robot Out: Sequencing through Programming Robots in Early Childhood

ERIC Educational Resources Information Center

Kazakoff, Elizabeth R.; Bers, Marina Umaschi

2014-01-01

This article examines the impact of programming robots on sequencing ability in early childhood. Thirty-four children (ages 4.5-6.5 years) participated in computer programming activities with a developmentally appropriate tool, CHERP, specifically designed to program a robot's behaviors. The children learned to build and program robots over three…

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).

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.

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.

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.

Nasa's Ant-Inspired Swarmie Robots

NASA Technical Reports Server (NTRS)

Leucht, Kurt W.

2016-01-01

As humans push further beyond the grasp of earth, robotic missions in advance of human missions will play an increasingly important role. These robotic systems will find and retrieve valuable resources as part of an in-situ resource utilization (ISRU) strategy. They will need to be highly autonomous while maintaining high task performance levels. NASA Kennedy Space Center has teamed up with the Biological Computation Lab at the University of New Mexico to create a swarm of small, low-cost, autonomous robots to be used as a ground-based research platform for ISRU missions. The behavior of the robot swarm mimics the central-place foraging strategy of ants to find and collect resources in a previously unmapped environment and return those resources to a central site. This talk will guide the audience through the Swarmie robot project from its conception by students in a New Mexico research lab to its robot trials in an outdoor parking lot at NASA. The software technologies and techniques used on the project will be discussed, as well as various challenges and solutions that were encountered by the development team along the way.

Team Oriented Robotic Exploration Task on Scorpion and K9 Platforms

NASA Technical Reports Server (NTRS)

Kirchner, Frank

2003-01-01

This final report describes the achievements that have been made in the project over the complete period of performance. The technical progress highlights the different areas of work in terms of Progress in Mechatronics, Sensor integration, Software Development. User Interfaces, Behavior Development and Experimental Results and System Testing. The different areas are: Mechatronics, Sensor integration, Software development, Experimental results and Basic System Testing, Behaviors Development and Advanced System Testing, User Interface and Wireless Communication.

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development

PubMed Central

Honig, Shanee; Oron-Gilad, Tal

2018-01-01

While substantial effort has been invested in making robots more reliable, experience demonstrates that robots operating in unstructured environments are often challenged by frequent failures. Despite this, robots have not yet reached a level of design that allows effective management of faulty or unexpected behavior by untrained users. To understand why this may be the case, an in-depth literature review was done to explore when people perceive and resolve robot failures, how robots communicate failure, how failures influence people's perceptions and feelings toward robots, and how these effects can be mitigated. Fifty-two studies were identified relating to communicating failures and their causes, the influence of failures on human-robot interaction (HRI), and mitigating failures. Since little research has been done on these topics within the HRI community, insights from the fields of human computer interaction (HCI), human factors engineering, cognitive engineering and experimental psychology are presented and discussed. Based on the literature, we developed a model of information processing for robotic failures (Robot Failure Human Information Processing, RF-HIP), that guides the discussion of our findings. The model describes the way people perceive, process, and act on failures in human robot interaction. The model includes three main parts: (1) communicating failures, (2) perception and comprehension of failures, and (3) solving failures. Each part contains several stages, all influenced by contextual considerations and mitigation strategies. Several gaps in the literature have become evident as a result of this evaluation. More focus has been given to technical failures than interaction failures. Few studies focused on human errors, on communicating failures, or the cognitive, psychological, and social determinants that impact the design of mitigation strategies. By providing the stages of human information processing, RF-HIP can be used as a tool to promote the development of user-centered failure-handling strategies for HRIs.

Artificial intelligence exploration of unstable protocells leads to predictable properties and discovery of collective behavior.

PubMed

Points, Laurie J; Taylor, James Ward; Grizou, Jonathan; Donkers, Kevin; Cronin, Leroy

2018-01-30

Protocell models are used to investigate how cells might have first assembled on Earth. Some, like oil-in-water droplets, can be seemingly simple models, while able to exhibit complex and unpredictable behaviors. How such simple oil-in-water systems can come together to yield complex and life-like behaviors remains a key question. Herein, we illustrate how the combination of automated experimentation and image processing, physicochemical analysis, and machine learning allows significant advances to be made in understanding the driving forces behind oil-in-water droplet behaviors. Utilizing >7,000 experiments collected using an autonomous robotic platform, we illustrate how smart automation cannot only help with exploration, optimization, and discovery of new behaviors, but can also be core to developing fundamental understanding of such systems. Using this process, we were able to relate droplet formulation to behavior via predicted physical properties, and to identify and predict more occurrences of a rare collective droplet behavior, droplet swarming. Proton NMR spectroscopic and qualitative pH methods enabled us to better understand oil dissolution, chemical change, phase transitions, and droplet and aqueous phase flows, illustrating the utility of the combination of smart-automation and traditional analytical chemistry techniques. We further extended our study for the simultaneous exploration of both the oil and aqueous phases using a robotic platform. Overall, this work shows that the combination of chemistry, robotics, and artificial intelligence enables discovery, prediction, and mechanistic understanding in ways that no one approach could achieve alone.

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.

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.

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.

Coordinated Dynamic Behaviors for Multirobot Systems With Collision Avoidance.

PubMed

Sabattini, Lorenzo; Secchi, Cristian; Fantuzzi, Cesare

2017-12-01

In this paper, we propose a novel methodology for achieving complex dynamic behaviors in multirobot systems. In particular, we consider a multirobot system partitioned into two subgroups: 1) dependent and 2) independent robots. Independent robots are utilized as a control input, and their motion is controlled in such a way that the dependent robots solve a tracking problem, that is following arbitrarily defined setpoint trajectories, in a coordinated manner. The control strategy proposed in this paper explicitly addresses the collision avoidance problem, utilizing a null space-based behavioral approach: this leads to combining, in a non conflicting manner, the tracking control law with a collision avoidance strategy. The combination of these control actions allows the robots to execute their task in a safe way. Avoidance of collisions is formally proven in this paper, and the proposed methodology is validated by means of simulations and experiments on real robots.

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.

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.

Ethorobotics: A New Approach to Human-Robot Relationship

PubMed Central

Miklósi, Ádám; Korondi, Péter; Matellán, Vicente; Gácsi, Márta

2017-01-01

Here we aim to lay the theoretical foundations of human-robot relationship drawing upon insights from disciplines that govern relevant human behaviors: ecology and ethology. We show how the paradox of the so called “uncanny valley hypothesis” can be solved by applying the “niche” concept to social robots, and relying on the natural behavior of humans. Instead of striving to build human-like social robots, engineers should construct robots that are able to maximize their performance in their niche (being optimal for some specific functions), and if they are endowed with appropriate form of social competence then humans will eventually interact with them independent of their embodiment. This new discipline, which we call ethorobotics, could change social robotics, giving a boost to new technical approaches and applications. PMID:28649213

Co-development of manner and path concepts in language, action, and eye-gaze behavior.

PubMed

Lohan, Katrin S; Griffiths, Sascha S; Sciutti, Alessandra; Partmann, Tim C; Rohlfing, Katharina J

2014-07-01

In order for artificial intelligent systems to interact naturally with human users, they need to be able to learn from human instructions when actions should be imitated. Human tutoring will typically consist of action demonstrations accompanied by speech. In the following, the characteristics of human tutoring during action demonstration will be examined. A special focus will be put on the distinction between two kinds of motion events: path-oriented actions and manner-oriented actions. Such a distinction is inspired by the literature pertaining to cognitive linguistics, which indicates that the human conceptual system can distinguish these two distinct types of motion. These two kinds of actions are described in language by more path-oriented or more manner-oriented utterances. In path-oriented utterances, the source, trajectory, or goal is emphasized, whereas in manner-oriented utterances the medium, velocity, or means of motion are highlighted. We examined a video corpus of adult-child interactions comprised of three age groups of children-pre-lexical, early lexical, and lexical-and two different tasks, one emphasizing manner more strongly and one emphasizing path more strongly. We analyzed the language and motion of the caregiver and the gazing behavior of the child to highlight the differences between the tutoring and the acquisition of the manner and path concepts. The results suggest that age is an important factor in the development of these action categories. The analysis of this corpus has also been exploited to develop an intelligent robotic behavior-the tutoring spotter system-able to emulate children's behaviors in a tutoring situation, with the aim of evoking in human subjects a natural and effective behavior in teaching to a robot. The findings related to the development of manner and path concepts have been used to implement new effective feedback strategies in the tutoring spotter system, which should provide improvements in human-robot interaction. Copyright © 2014 Cognitive Science Society, Inc.

We perceive a mind in a robot when we help it

PubMed Central

Hashimoto, Takaaki; Karasawa, Kaori

2017-01-01

People sometimes perceive a mind in inorganic entities like robots. Psychological research has shown that mind perception correlates with moral judgments and that immoral behaviors (i.e., intentional harm) facilitate mind perception toward otherwise mindless victims. We conducted a vignette experiment (N = 129; Mage = 21.8 ± 6.0 years) concerning human-robot interactions and extended previous research’s results in two ways. First, mind perception toward the robot was facilitated when it received a benevolent behavior, although only when participants took the perspective of an actor. Second, imagining a benevolent interaction led to more positive attitudes toward the robot, and this effect was mediated by mind perception. These results help predict what people’s reactions in future human-robot interactions would be like, and have implications for how to design future social rules about the treatment of robots. PMID:28727735

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

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.

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.

Analyzing Cyber-Physical Threats on Robotic Platforms.

PubMed

Ahmad Yousef, Khalil M; AlMajali, Anas; Ghalyon, Salah Abu; Dweik, Waleed; Mohd, Bassam J

2018-05-21

Robots are increasingly involved in our daily lives. Fundamental to robots are the communication link (or stream) and the applications that connect the robots to their clients or users. Such communication link and applications are usually supported through client/server network connection. This networking system is amenable of being attacked and vulnerable to the security threats. Ensuring security and privacy for robotic platforms is thus critical, as failures and attacks could have devastating consequences. In this paper, we examine several cyber-physical security threats that are unique to the robotic platforms; specifically the communication link and the applications. Threats target integrity, availability and confidential security requirements of the robotic platforms, which use MobileEyes/arnlServer client/server applications. A robot attack tool (RAT) was developed to perform specific security attacks. An impact-oriented approach was adopted to analyze the assessment results of the attacks. Tests and experiments of attacks were conducted in simulation environment and physically on the robot. The simulation environment was based on MobileSim; a software tool for simulating, debugging and experimenting on MobileRobots/ActivMedia platforms and their environments. The robot platform PeopleBot TM was used for physical experiments. The analysis and testing results show that certain attacks were successful at breaching the robot security. Integrity attacks modified commands and manipulated the robot behavior. Availability attacks were able to cause Denial-of-Service (DoS) and the robot was not responsive to MobileEyes commands. Integrity and availability attacks caused sensitive information on the robot to be hijacked. To mitigate security threats, we provide possible mitigation techniques and suggestions to raise awareness of threats on the robotic platforms, especially when the robots are involved in critical missions or applications.

Analyzing Cyber-Physical Threats on Robotic Platforms †

PubMed Central

2018-01-01

Robots are increasingly involved in our daily lives. Fundamental to robots are the communication link (or stream) and the applications that connect the robots to their clients or users. Such communication link and applications are usually supported through client/server network connection. This networking system is amenable of being attacked and vulnerable to the security threats. Ensuring security and privacy for robotic platforms is thus critical, as failures and attacks could have devastating consequences. In this paper, we examine several cyber-physical security threats that are unique to the robotic platforms; specifically the communication link and the applications. Threats target integrity, availability and confidential security requirements of the robotic platforms, which use MobileEyes/arnlServer client/server applications. A robot attack tool (RAT) was developed to perform specific security attacks. An impact-oriented approach was adopted to analyze the assessment results of the attacks. Tests and experiments of attacks were conducted in simulation environment and physically on the robot. The simulation environment was based on MobileSim; a software tool for simulating, debugging and experimenting on MobileRobots/ActivMedia platforms and their environments. The robot platform PeopleBotTM was used for physical experiments. The analysis and testing results show that certain attacks were successful at breaching the robot security. Integrity attacks modified commands and manipulated the robot behavior. Availability attacks were able to cause Denial-of-Service (DoS) and the robot was not responsive to MobileEyes commands. Integrity and availability attacks caused sensitive information on the robot to be hijacked. To mitigate security threats, we provide possible mitigation techniques and suggestions to raise awareness of threats on the robotic platforms, especially when the robots are involved in critical missions or applications. PMID:29883403

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.

Artificial humanoid for the elderly people.

PubMed

Simou, Panagiota; Alexiou, Athanasios; Tiligadis, Konstantinos

2015-01-01

While frailty and other multi-scale factors have to be correlated during a geriatric assessment, few prototype robots have already been developed in order to measure and provide real-time information, concerning elderly daily activities. Cognitive impairment and alterations on daily functions should be immediate recognized from caregivers, in order to be prevented and probably treated. In this chapter we recognize the necessity of artificial robots during the personal service of the elderly population, not only as a mobile laboratory-geriatrician, but mainly as a socialized digital humanoid able to develop social behavior and activate memories and emotions.

Making Sense by Building Sense: Kindergarten Children's Construction and Understanding of Adaptive Robot Behaviors

ERIC Educational Resources Information Center

Mioduser, David; Levy, Sharona T.

2010-01-01

This study explores young children's ability to construct and explain adaptive behaviors of a behaving artifact, an autonomous mobile robot with sensors. A central component of the behavior construction environment is the RoboGan software that supports children's construction of spatiotemporal events with an a-temporal rule structure. Six…

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.

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.

Inter-rater reliability of kinesthetic measurements with the KINARM robotic exoskeleton.

PubMed

Semrau, Jennifer A; Herter, Troy M; Scott, Stephen H; Dukelow, Sean P

2017-05-22

Kinesthesia (sense of limb movement) has been extremely difficult to measure objectively, especially in individuals who have survived a stroke. The development of valid and reliable measurements for proprioception is important to developing a better understanding of proprioceptive impairments after stroke and their impact on the ability to perform daily activities. We recently developed a robotic task to evaluate kinesthetic deficits after stroke and found that the majority (~60%) of stroke survivors exhibit significant deficits in kinesthesia within the first 10 days post-stroke. Here we aim to determine the inter-rater reliability of this robotic kinesthetic matching task. Twenty-five neurologically intact control subjects and 15 individuals with first-time stroke were evaluated on a robotic kinesthetic matching task (KIN). Subjects sat in a robotic exoskeleton with their arms supported against gravity. In the KIN task, the robot moved the subjects' stroke-affected arm at a preset speed, direction and distance. As soon as subjects felt the robot begin to move their affected arm, they matched the robot movement with the unaffected arm. Subjects were tested in two sessions on the KIN task: initial session and then a second session (within an average of 18.2 ± 13.8 h of the initial session for stroke subjects), which were supervised by different technicians. The task was performed both with and without the use of vision in both sessions. We evaluated intra-class correlations of spatial and temporal parameters derived from the KIN task to determine the reliability of the robotic task. We evaluated 8 spatial and temporal parameters that quantify kinesthetic behavior. We found that the parameters exhibited moderate to high intra-class correlations between the initial and retest conditions (Range, r-value = [0.53-0.97]). The robotic KIN task exhibited good inter-rater reliability. This validates the KIN task as a reliable, objective method for quantifying kinesthesia after stroke.

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.

Developing Autonomy for Unmanned Surface Vehicles by Using Virtual Environments

DTIC Science & Technology

2010-10-11

successfully evolved for a wide variety of behaviors as obstacle avoidance (Barate and Manzanera 2007; Nehmzow 2002), wall-following ( Dain 1998...Advances in unmanned marine vehicles pp 311-328 Dain R (1998) Developing mobile robot wall-following algorithms using ge- netic programming. Applied

Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot.

PubMed

Bengochea-Guevara, José M; Conesa-Muñoz, Jesus; Andújar, Dionisio; Ribeiro, Angela

2016-02-24

The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal cost. In this study, a small autonomous field inspection vehicle was developed to minimise the impact of the scouting on the crop and soil compaction. The proposed approach integrates a camera with a GPS receiver to obtain a set of basic behaviours required of an autonomous mobile robot to inspect a crop field with full coverage. A path planner considered the field contour and the crop type to determine the best inspection route. An image-processing method capable of extracting the central crop row under uncontrolled lighting conditions in real time from images acquired with a reflex camera positioned on the front of the robot was developed. Two fuzzy controllers were also designed and developed to achieve vision-guided navigation. A method for detecting the end of a crop row using camera-acquired images was developed. In addition, manoeuvres necessary for the robot to change rows were established. These manoeuvres enabled the robot to autonomously cover the entire crop by following a previously established plan and without stepping on the crop row, which is an essential behaviour for covering crops such as maize without damaging them.

Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot

PubMed Central

Bengochea-Guevara, José M.; Conesa-Muñoz, Jesus; Andújar, Dionisio; Ribeiro, Angela

2016-01-01

The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal cost. In this study, a small autonomous field inspection vehicle was developed to minimise the impact of the scouting on the crop and soil compaction. The proposed approach integrates a camera with a GPS receiver to obtain a set of basic behaviours required of an autonomous mobile robot to inspect a crop field with full coverage. A path planner considered the field contour and the crop type to determine the best inspection route. An image-processing method capable of extracting the central crop row under uncontrolled lighting conditions in real time from images acquired with a reflex camera positioned on the front of the robot was developed. Two fuzzy controllers were also designed and developed to achieve vision-guided navigation. A method for detecting the end of a crop row using camera-acquired images was developed. In addition, manoeuvres necessary for the robot to change rows were established. These manoeuvres enabled the robot to autonomously cover the entire crop by following a previously established plan and without stepping on the crop row, which is an essential behaviour for covering crops such as maize without damaging them. PMID:26927102

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.

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.

Visual exploration and analysis of human-robot interaction rules

NASA Astrophysics Data System (ADS)

Zhang, Hui; Boyles, Michael J.

2013-01-01

We present a novel interaction paradigm for the visual exploration, manipulation and analysis of human-robot interaction (HRI) rules; our development is implemented using a visual programming interface and exploits key techniques drawn from both information visualization and visual data mining to facilitate the interaction design and knowledge discovery process. HRI is often concerned with manipulations of multi-modal signals, events, and commands that form various kinds of interaction rules. Depicting, manipulating and sharing such design-level information is a compelling challenge. Furthermore, the closed loop between HRI programming and knowledge discovery from empirical data is a relatively long cycle. This, in turn, makes design-level verification nearly impossible to perform in an earlier phase. In our work, we exploit a drag-and-drop user interface and visual languages to support depicting responsive behaviors from social participants when they interact with their partners. For our principal test case of gaze-contingent HRI interfaces, this permits us to program and debug the robots' responsive behaviors through a graphical data-flow chart editor. We exploit additional program manipulation interfaces to provide still further improvement to our programming experience: by simulating the interaction dynamics between a human and a robot behavior model, we allow the researchers to generate, trace and study the perception-action dynamics with a social interaction simulation to verify and refine their designs. Finally, we extend our visual manipulation environment with a visual data-mining tool that allows the user to investigate interesting phenomena such as joint attention and sequential behavioral patterns from multiple multi-modal data streams. We have created instances of HRI interfaces to evaluate and refine our development paradigm. As far as we are aware, this paper reports the first program manipulation paradigm that integrates visual programming interfaces, information visualization, and visual data mining methods to facilitate designing, comprehending, and evaluating HRI interfaces.

MEART: The Semi-Living Artist

PubMed Central

Bakkum, Douglas J.; Gamblen, Philip M.; Ben-Ary, Guy; Chao, Zenas C.; Potter, Steve M.

2007-01-01

Here, we and others describe an unusual neurorobotic project, a merging of art and science called MEART, the semi-living artist. We built a pneumatically actuated robotic arm to create drawings, as controlled by a living network of neurons from rat cortex grown on a multi-electrode array (MEA). Such embodied cultured networks formed a real-time closed-loop system which could now behave and receive electrical stimulation as feedback on its behavior. We used MEART and simulated embodiments, or animats, to study the network mechanisms that produce adaptive, goal-directed behavior. This approach to neural interfacing will help instruct the design of other hybrid neural-robotic systems we call hybrots. The interfacing technologies and algorithms developed have potential applications in responsive deep brain stimulation systems and for motor prosthetics using sensory components. In a broader context, MEART educates the public about neuroscience, neural interfaces, and robotics. It has paved the way for critical discussions on the future of bio-art and of biotechnology. PMID:18958276

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.

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.

Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots.

PubMed

Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne

2016-01-01

Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.

Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots

PubMed Central

Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne

2016-01-01

Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers. PMID:26999614

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,…

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…

Robotic Follow Algorithm

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

2005-03-30

The Robotic Follow Algorithm enables allows any robotic vehicle to follow a moving target while reactively choosing a route around nearby obstacles. The robotic follow behavior can be used with different camera systems and can be used with thermal or visual tracking as well as other tracking methods such as radio frequency tags.

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.

Electro-Statically Stricted Polymers (ESSP)

NASA Technical Reports Server (NTRS)

Liu, C.; Bar-Cohen, Y.; Leary, S.

1999-01-01

Miniature, lightweight, miser actuators that operate similar to biological muscles can be used to develop robotic devices with unmatched capabilities and impact many technology areas. Electroactive polymers (EAP) offer the potential to producing such actuators and their main attractive feature is their ability to induce relatively large bending or longitudinal strain. EAP actuators can change the paradigm about the complexity of robots, where robotic components such as motors, gears, bearings, and others can be eliminated with simple drive mechanisms. Generally, these materials produce a relatively low force and the applications that can be considered at the current state of the art are relatively limited. While improved material are being developed there is a need for methods to develop longitudinal actuators that can contract similar to muscles. In this study, the authors began investigating the electromechanical behavior of polymers in reaction to a complex configuration of electric fields. A computer model was used to simulate the electromechanical response. Efforts were made to develop both the material basis as well as the electromechanical modeling of the actuator.

Mobile robot navigation modulated by artificial emotions.

PubMed

Lee-Johnson, C P; Carnegie, D A

2010-04-01

For artificial intelligence research to progress beyond the highly specialized task-dependent implementations achievable today, researchers may need to incorporate aspects of biological behavior that have not traditionally been associated with intelligence. Affective processes such as emotions may be crucial to the generalized intelligence possessed by humans and animals. A number of robots and autonomous agents have been created that can emulate human emotions, but the majority of this research focuses on the social domain. In contrast, we have developed a hybrid reactive/deliberative architecture that incorporates artificial emotions to improve the general adaptive performance of a mobile robot for a navigation task. Emotions are active on multiple architectural levels, modulating the robot's decisions and actions to suit the context of its situation. Reactive emotions interact with the robot's control system, altering its parameters in response to appraisals from short-term sensor data. Deliberative emotions are learned associations that bias path planning in response to eliciting objects or events. Quantitative results are presented that demonstrate situations in which each artificial emotion can be beneficial to performance.

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.

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

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.

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.

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

Applied estimation for hybrid dynamical systems using perceptional information

NASA Astrophysics Data System (ADS)

Plotnik, Aaron M.

This dissertation uses the motivating example of robotic tracking of mobile deep ocean animals to present innovations in robotic perception and estimation for hybrid dynamical systems. An approach to estimation for hybrid systems is presented that utilizes uncertain perceptional information about the system's mode to improve tracking of its mode and continuous states. This results in significant improvements in situations where previously reported methods of estimation for hybrid systems perform poorly due to poor distinguishability of the modes. The specific application that motivates this research is an automatic underwater robotic observation system that follows and films individual deep ocean animals. A first version of such a system has been developed jointly by the Stanford Aerospace Robotics Laboratory and Monterey Bay Aquarium Research Institute (MBARI). This robotic observation system is successfully fielded on MBARI's ROVs, but agile specimens often evade the system. When a human ROV pilot performs this task, one advantage that he has over the robotic observation system in these situations is the ability to use visual perceptional information about the target, immediately recognizing any changes in the specimen's behavior mode. With the approach of the human pilot in mind, a new version of the robotic observation system is proposed which is extended to (a) derive perceptional information (visual cues) about the behavior mode of the tracked specimen, and (b) merge this dissimilar, discrete and uncertain information with more traditional continuous noisy sensor data by extending existing algorithms for hybrid estimation. These performance enhancements are enabled by integrating techniques in hybrid estimation, computer vision and machine learning. First, real-time computer vision and classification algorithms extract a visual observation of the target's behavior mode. Existing hybrid estimation algorithms are extended to admit this uncertain but discrete observation, complementing the information available from more traditional sensors. State tracking is achieved using a new form of Rao-Blackwellized particle filter called the mode-observed Gaussian Particle Filter. Performance is demonstrated using data from simulation and data collected on actual specimens in the ocean. The framework for estimation using both traditional and perceptional information is easily extensible to other stochastic hybrid systems with mode-related perceptional observations available.

A simple running model with rolling contact and its role as a template for dynamic locomotion on a hexapod robot.

PubMed

Huang, Ke-Jung; Huang, Chun-Kai; Lin, Pei-Chun

2014-10-07

We report on the development of a robot's dynamic locomotion based on a template which fits the robot's natural dynamics. The developed template is a low degree-of-freedom planar model for running with rolling contact, which we call rolling spring loaded inverted pendulum (R-SLIP). Originating from a reduced-order model of the RHex-style robot with compliant circular legs, the R-SLIP model also acts as the template for general dynamic running. The model has a torsional spring and a large circular arc as the distributed foot, so during locomotion it rolls on the ground with varied equivalent linear stiffness. This differs from the well-known spring loaded inverted pendulum (SLIP) model with fixed stiffness and ground contact points. Through dimensionless steps-to-fall and return map analysis, within a wide range of parameter spaces, the R-SLIP model is revealed to have self-stable gaits and a larger stability region than that of the SLIP model. The R-SLIP model is then embedded as the reduced-order 'template' in a more complex 'anchor', the RHex-style robot, via various mapping definitions between the template and the anchor. Experimental validation confirms that by merely deploying the stable running gaits of the R-SLIP model on the empirical robot with simple open-loop control strategy, the robot can easily initiate its dynamic running behaviors with a flight phase and can move with similar body state profiles to those of the model, in all five testing speeds. The robot, embedded with the SLIP model but performing walking locomotion, further confirms the importance of finding an adequate template of the robot for dynamic locomotion.

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology.

PubMed

Rubenstein, Michael; Sai, Ying; Chuong, Cheng-Ming; Shen, Wei-Min

2009-01-01

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. Self here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering.

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology

PubMed Central

RUBENSTEIN, MICHAEL; SAI, YING; CHUONG, CHENG-MING; SHEN, WEI-MIN

2010-01-01

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. “Self” here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering. PMID:19557691

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

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.

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.

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.

Portraits of self-organization in fish schools interacting with robots

NASA Astrophysics Data System (ADS)

Aureli, M.; Fiorilli, F.; Porfiri, M.

2012-05-01

In this paper, we propose an enabling computational and theoretical framework for the analysis of experimental instances of collective behavior in response to external stimuli. In particular, this work addresses the characterization of aggregation and interaction phenomena in robot-animal groups through the exemplary analysis of fish schooling in the vicinity of a biomimetic robot. We adapt global observables from statistical mechanics to capture the main features of the shoal collective motion and its response to the robot from experimental observations. We investigate the shoal behavior by using a diffusion mapping analysis performed on these global observables that also informs the definition of relevant portraits of self-organization.

Information-driven self-organization: the dynamical system approach to autonomous robot behavior.

PubMed

Ay, Nihat; Bernigau, Holger; Der, Ralf; Prokopenko, Mikhail

2012-09-01

In recent years, information theory has come into the focus of researchers interested in the sensorimotor dynamics of both robots and living beings. One root for these approaches is the idea that living beings are information processing systems and that the optimization of these processes should be an evolutionary advantage. Apart from these more fundamental questions, there is much interest recently in the question how a robot can be equipped with an internal drive for innovation or curiosity that may serve as a drive for an open-ended, self-determined development of the robot. The success of these approaches depends essentially on the choice of a convenient measure for the information. This article studies in some detail the use of the predictive information (PI), also called excess entropy or effective measure complexity, of the sensorimotor process. The PI of a process quantifies the total information of past experience that can be used for predicting future events. However, the application of information theoretic measures in robotics mostly is restricted to the case of a finite, discrete state-action space. This article aims at applying the PI in the dynamical systems approach to robot control. We study linear systems as a first step and derive exact results for the PI together with explicit learning rules for the parameters of the controller. Interestingly, these learning rules are of Hebbian nature and local in the sense that the synaptic update is given by the product of activities available directly at the pertinent synaptic ports. The general findings are exemplified by a number of case studies. In particular, in a two-dimensional system, designed at mimicking embodied systems with latent oscillatory locomotion patterns, it is shown that maximizing the PI means to recognize and amplify the latent modes of the robotic system. This and many other examples show that the learning rules derived from the maximum PI principle are a versatile tool for the self-organization of behavior in complex robotic systems.

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.

Origami mechanologic.

PubMed

Treml, Benjamin; Gillman, Andrew; Buskohl, Philip; Vaia, Richard

2018-06-18

Robots autonomously interact with their environment through a continual sense-decide-respond control loop. Most commonly, the decide step occurs in a central processing unit; however, the stiffness mismatch between rigid electronics and the compliant bodies of soft robots can impede integration of these systems. We develop a framework for programmable mechanical computation embedded into the structure of soft robots that can augment conventional digital electronic control schemes. Using an origami waterbomb as an experimental platform, we demonstrate a 1-bit mechanical storage device that writes, erases, and rewrites itself in response to a time-varying environmental signal. Further, we show that mechanical coupling between connected origami units can be used to program the behavior of a mechanical bit, produce logic gates such as AND, OR, and three input majority gates, and transmit signals between mechanologic gates. Embedded mechanologic provides a route to add autonomy and intelligence in soft robots and machines. Copyright © 2018 the Author(s). Published by PNAS.

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.

Long-Term Simultaneous Localization and Mapping in Dynamic Environments

DTIC Science & Technology

2015-01-01

core competencies required for autonomous mobile robotics is the ability to use sensors to perceive the environment. From this noisy sensor data, the...and mapping (SLAM), is a prerequisite for almost all higher-level autonomous behavior in mobile robotics. By associating the robot???s sensory...distributed stochastic neighbor embedding x ABSTRACT One of the core competencies required for autonomous mobile robotics is the ability to use sensors

Integration of Fiber-Optic Sensor Arrays into a Multi-Modal Tactile Sensor Processing System for Robotic End-Effectors

PubMed Central

Kampmann, Peter; Kirchner, Frank

2014-01-01

With the increasing complexity of robotic missions and the development towards long-term autonomous systems, the need for multi-modal sensing of the environment increases. Until now, the use of tactile sensor systems has been mostly based on sensing one modality of forces in the robotic end-effector. The use of a multi-modal tactile sensory system is motivated, which combines static and dynamic force sensor arrays together with an absolute force measurement system. This publication is focused on the development of a compact sensor interface for a fiber-optic sensor array, as optic measurement principles tend to have a bulky interface. Mechanical, electrical and software approaches are combined to realize an integrated structure that provides decentralized data pre-processing of the tactile measurements. Local behaviors are implemented using this setup to show the effectiveness of this approach. PMID:24743158

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.

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.

How Evolution May Work Through Curiosity-Driven Developmental Process.

PubMed

Oudeyer, Pierre-Yves; Smith, Linda B

2016-04-01

Infants' own activities create and actively select their learning experiences. Here we review recent models of embodied information seeking and curiosity-driven learning and show that these mechanisms have deep implications for development and evolution. We discuss how these mechanisms yield self-organized epigenesis with emergent ordered behavioral and cognitive developmental stages. We describe a robotic experiment that explored the hypothesis that progress in learning, in and for itself, generates intrinsic rewards: The robot learners probabilistically selected experiences according to their potential for reducing uncertainty. In these experiments, curiosity-driven learning led the robot learner to successively discover object affordances and vocal interaction with its peers. We explain how a learning curriculum adapted to the current constraints of the learning system automatically formed, constraining learning and shaping the developmental trajectory. The observed trajectories in the robot experiment share many properties with those in infant development, including a mixture of regularities and diversities in the developmental patterns. Finally, we argue that such emergent developmental structures can guide and constrain evolution, in particular with regard to the origins of language. Copyright © 2016 Cognitive Science Society, Inc.

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…

Redundant arm control in a supervisory and shared control system

NASA Technical Reports Server (NTRS)

Backes, Paul G.; Long, Mark K.

1992-01-01

The Extended Task Space Control approach to robotic operations based on manipulator behaviors derived from task requirements is described. No differentiation between redundant and non-redundant robots is made at the task level. The manipulation task behaviors are combined into a single set of motion commands. The manipulator kinematics are used subsequently in mapping motion commands into actuator commands. Extended Task Space Control is applied to a Robotics Research K-1207 seven degree-of-freedom manipulator in a supervisory telerobot system as an example.

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.

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.

Artificial pheromone for path selection by a foraging swarm of robots.

PubMed

Campo, Alexandre; Gutiérrez, Alvaro; Nouyan, Shervin; Pinciroli, Carlo; Longchamp, Valentin; Garnier, Simon; Dorigo, Marco

2010-11-01

Foraging robots involved in a search and retrieval task may create paths to navigate faster in their environment. In this context, a swarm of robots that has found several resources and created different paths may benefit strongly from path selection. Path selection enhances the foraging behavior by allowing the swarm to focus on the most profitable resource with the possibility for unused robots to stop participating in the path maintenance and to switch to another task. In order to achieve path selection, we implement virtual ants that lay artificial pheromone inside a network of robots. Virtual ants are local messages transmitted by robots; they travel along chains of robots and deposit artificial pheromone on the robots that are literally forming the chain and indicating the path. The concentration of artificial pheromone on the robots allows them to decide whether they are part of a selected path. We parameterize the mechanism with a mathematical model and provide an experimental validation using a swarm of 20 real robots. We show that our mechanism favors the selection of the closest resource is able to select a new path if a selected resource becomes unavailable and selects a newly detected and better resource when possible. As robots use very simple messages and behaviors, the system would be particularly well suited for swarms of microrobots with minimal abilities.

Improving therapeutic outcomes in autism spectrum disorders: Enhancing social communication and sensory processing through the use of interactive robots.

PubMed

Sartorato, Felippe; Przybylowski, Leon; Sarko, Diana K

2017-07-01

For children with autism spectrum disorders (ASDs), social robots are increasingly utilized as therapeutic tools in order to enhance social skills and communication. Robots have been shown to generate a number of social and behavioral benefits in children with ASD including heightened engagement, increased attention, and decreased social anxiety. Although social robots appear to be effective social reinforcement tools in assistive therapies, the perceptual mechanism underlying these benefits remains unknown. To date, social robot studies have primarily relied on expertise in fields such as engineering and clinical psychology, with measures of social robot efficacy principally limited to qualitative observational assessments of children's interactions with robots. In this review, we examine a range of socially interactive robots that currently have the most widespread use as well as the utility of these robots and their therapeutic effects. In addition, given that social interactions rely on audiovisual communication, we discuss how enhanced sensory processing and integration of robotic social cues may underlie the perceptual and behavioral benefits that social robots confer. Although overall multisensory processing (including audiovisual integration) is impaired in individuals with ASD, social robot interactions may provide therapeutic benefits by allowing audiovisual social cues to be experienced through a simplified version of a human interaction. By applying systems neuroscience tools to identify, analyze, and extend the multisensory perceptual substrates that may underlie the therapeutic benefits of social robots, future studies have the potential to strengthen the clinical utility of social robots for individuals with ASD. Copyright © 2017 Elsevier Ltd. All rights reserved.

Embodied neurofeedback with an anthropomorphic robotic hand

PubMed Central

Braun, Niclas; Emkes, Reiner; Thorne, Jeremy D.; Debener, Stefan

2016-01-01

Neurofeedback-guided motor imagery training (NF-MIT) has been suggested as a promising therapy for stroke-induced motor impairment. Whereas much NF-MIT research has aimed at signal processing optimization, the type of sensory feedback given to the participant has received less attention. Often the feedback signal is highly abstract and not inherently coupled to the mental act performed. In this study, we asked whether an embodied feedback signal is more efficient for neurofeedback operation than a non-embodiable feedback signal. Inspired by the rubber hand illusion, demonstrating that an artificial hand can be incorporated into one’s own body scheme, we used an anthropomorphic robotic hand to visually guide the participants’ motor imagery act and to deliver neurofeedback. Using two experimental manipulations, we investigated how a participant’s neurofeedback performance and subjective experience were influenced by the embodiability of the robotic hand, and by the neurofeedback signal’s validity. As pertains to embodiment, we found a promoting effect of robotic-hand embodiment in subjective, behavioral, electrophysiological and electrodermal measures. Regarding neurofeedback signal validity, we found some differences between real and sham neurofeedback in terms of subjective and electrodermal measures, but not in terms of behavioral and electrophysiological measures. This study motivates the further development of embodied feedback signals for NF-MIT. PMID:27869190

Execution monitoring for a mobile robot system

NASA Technical Reports Server (NTRS)

Miller, David P.

1990-01-01

Due to sensor errors, uncertainty, incomplete knowledge, and a dynamic world, robot plans will not always be executed exactly as planned. This paper describes an implemented robot planning system that enhances the traditional sense-think-act cycle in ways that allow the robot system monitor its behavior and react in emergencies in real-time. A proposal on how robot systems can completely break away from the traditional three-step cycle is also made.

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.

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.

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.

Accessibility to surgical robot technology and prostate-cancer patient behavior for prostatectomy.

PubMed

Sugihara, Toru; Yasunaga, Hideo; Matsui, Hiroki; Nagao, Go; Ishikawa, Akira; Fujimura, Tetsuya; Fukuhara, Hiroshi; Fushimi, Kiyohide; Ohori, Makoto; Homma, Yukio

2017-07-01

To examine how surgical robot emergence affects prostate-cancer patient behavior in seeking radical prostatectomy focusing on geographical accessibility. In Japan, robotic surgery was approved in April 2012. Based on data in the Japanese Diagnosis Procedure Combination database between April 2012 and March 2014, distance to nearest surgical robot and interval days to radical prostatectomy (divided by mean interval in 2011: % interval days to radical prostatectomy) were calculated for individual radical prostatectomy cases at non-robotic hospitals. Caseload changes regarding distance to nearest surgical robot and robot introduction were investigated. Change in % interval days to radical prostatectomy was evaluated by multivariate analysis including distance to nearest surgical robot, age, comorbidity, hospital volume, operation type, hospital academic status, bed volume and temporal progress. % Interval days to radical prostatectomy became wider for distance to nearest surgical robot <30 km. When a surgical robot emerged within 30 and 10 km, the prostatectomy caseload in non-robot hospitals reduced by 13 and 18% within 6 months, respectively, while the robot hospitals gained +101% caseload (P < 0.01 for all) Multivariate analyses including 9759 open and 5052 non-robotic minimally invasive radical prostatectomies in 483 non-robot hospitals revealed a significant inverse association between distance to nearest surgical robot and % interval days to radical prostatectomy (B = -17.3% for distance to nearest surgical robot ≥30 km and -11.7% for 10-30 km versus distance to nearest surgical robot <10 km), while younger age, high-volume hospital, open-prostatectomy provider and temporal progress were other significant factors related to % interval days to radical prostatectomy widening (P < 0.05 for all). Robotic surgery accessibility within 30 km would make patients less likely select conventional surgery. The nearer a robot was, the faster the caseload reduction was. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Supervisory Control of a Humanoid Robot in Microgravity for Manipulation Tasks

NASA Technical Reports Server (NTRS)

Farrell, Logan C.; Strawser, Phil; Hambuchen, Kimberly; Baker, Will; Badger, Julia

2017-01-01

Teleoperation is the dominant form of dexterous robotic tasks in the field. However, there are many use cases in which direct teleoperation is not feasible such as disaster areas with poor communication as posed in the DARPA Robotics Challenge, or robot operations on spacecraft a large distance from Earth with long communication delays. Presented is a solution that combines the Affordance Template Framework for object interaction with TaskForce for supervisory control in order to accomplish high level task objectives with basic autonomous behavior from the robot. TaskForce, is a new commanding infrastructure that allows for optimal development of task execution, clear feedback to the user to aid in off-nominal situations, and the capability to add autonomous verification and corrective actions. This framework has allowed the robot to take corrective actions before requesting assistance from the user. This framework is demonstrated with Robonaut 2 removing a Cargo Transfer Bag from a simulated logistics resupply vehicle for spaceflight using a single operator command. This was executed with 80% success with no human involvement, and 95% success with limited human interaction. This technology sets the stage to do any number of high level tasks using a similar framework, allowing the robot to accomplish tasks with minimal to no human interaction.

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

Robotic Nudges: The Ethics of Engineering a More Socially Just Human Being.

PubMed

Borenstein, Jason; Arkin, Ron

2016-02-01

Robots are becoming an increasingly pervasive feature of our personal lives. As a result, there is growing importance placed on examining what constitutes appropriate behavior when they interact with human beings. In this paper, we discuss whether companion robots should be permitted to "nudge" their human users in the direction of being "more ethical". More specifically, we use Rawlsian principles of justice to illustrate how robots might nurture "socially just" tendencies in their human counterparts. Designing technological artifacts in such a way to influence human behavior is already well-established but merely because the practice is commonplace does not necessarily resolve the ethical issues associated with its implementation.

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.

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…

Orientation Behavior Using Registered Topographic Maps

DTIC Science & Technology

2006-01-01

integrated with the ability to reach for visual targets ( Marjanovic , Scassel- lati, & Williamson 1996). The same is true for social skills where the robot...behavior with reaching and manipula- tion tasks currently under parallel development by other members of the group ( Marjanovic et al. 1996). 8 Conclusions...in alphabet- ical order): Mike Binnard, Rod Brooks, Robert Irie, Eleni Kapogannis, Matt Marjanovic , Yoky Matsuoka, Brian Scasselatti, Nick Shectman

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.

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.

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.

A Compact Magnetic Field-Based Obstacle Detection and Avoidance System for Miniature Spherical Robots.

PubMed

Wu, Fang; Vibhute, Akash; Soh, Gim Song; Wood, Kristin L; Foong, Shaohui

2017-05-28

Due to their efficient locomotion and natural tolerance to hazardous environments, spherical robots have wide applications in security surveillance, exploration of unknown territory and emergency response. Numerous studies have been conducted on the driving mechanism, motion planning and trajectory tracking methods of spherical robots, yet very limited studies have been conducted regarding the obstacle avoidance capability of spherical robots. Most of the existing spherical robots rely on the "hit and run" technique, which has been argued to be a reasonable strategy because spherical robots have an inherent ability to recover from collisions. Without protruding components, they will not become stuck and can simply roll back after running into bstacles. However, for small scale spherical robots that contain sensitive surveillance sensors and cannot afford to utilize heavy protective shells, the absence of obstacle avoidance solutions would leave the robot at the mercy of potentially dangerous obstacles. In this paper, a compact magnetic field-based obstacle detection and avoidance system has been developed for miniature spherical robots. It utilizes a passive magnetic field so that the system is both compact and power efficient. The proposed system can detect not only the presence, but also the approaching direction of a ferromagnetic obstacle, therefore, an intelligent avoidance behavior can be generated by adapting the trajectory tracking method with the detection information. Design optimization is conducted to enhance the obstacle detection performance and detailed avoidance strategies are devised. Experimental results are also presented for validation purposes.

Controlling Herds of Cooperative Robots

NASA Technical Reports Server (NTRS)

Quadrelli, Marco B.

2006-01-01

A document poses, and suggests a program of research for answering, questions of how to achieve autonomous operation of herds of cooperative robots to be used in exploration and/or colonization of remote planets. In a typical scenario, a flock of mobile sensory robots would be deployed in a previously unexplored region, one of the robots would be designated the leader, and the leader would issue commands to move the robots to different locations or aim sensors at different targets to maximize scientific return. It would be necessary to provide for this hierarchical, cooperative behavior even in the face of such unpredictable factors as terrain obstacles. A potential-fields approach is proposed as a theoretical basis for developing methods of autonomous command and guidance of a herd. A survival-of-the-fittest approach is suggested as a theoretical basis for selection, mutation, and adaptation of a description of (1) the body, joints, sensors, actuators, and control computer of each robot, and (2) the connectivity of each robot with the rest of the herd, such that the herd could be regarded as consisting of a set of artificial creatures that evolve to adapt to a previously unknown environment. A distributed simulation environment has been developed to test the proposed approaches in the Titan environment. One blimp guides three surface sondes via a potential field approach. The results of the simulation demonstrate that the method used for control is feasible, even if significant uncertainty exists in the dynamics and environmental models, and that the control architecture provides the autonomy needed to enable surface science data collection.

A robotic home telehealth platform system for treatment adherence, social assistance and companionship - an overview.

PubMed

Oddsson, Lars I E; Radomski, Mary V; White, Matthew; Nilsson, Daniel

2009-01-01

Well-known difficulties of making patients adhere to assigned treatments have made engineers and clinicians look towards technology for possible solutions. Recent studies have found that cell phone-based text messaging can help drive positive changes in patients' disease management and preventive health behavior. Furthermore, work in the area of assistive robotics indicates benefits for patients although robotic solutions tend to become expensive. However, continued improvement in sensor, computer and wireless technologies combined with decreases in cost is paving the way for development of affordable robotic systems that can help improve patient care and potentially add value to the healthcare system. This paper provides a high-level design overview of SKOTEE, the Sister Kenny hOme ThErapy systEm, an inexpensive robotic platform system designed to provide adherence support for home exercise programs, taking medication, appointment reminders and clinician communication. SKOTEE will also offer companionship as well as entertainment and social networking opportunities to the patient in their home. A video of the system is presented at the conference.

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.

Peripersonal Space and Margin of Safety around the Body: Learning Visuo-Tactile Associations in a Humanoid Robot with Artificial Skin.

PubMed

Roncone, Alessandro; Hoffmann, Matej; Pattacini, Ugo; Fadiga, Luciano; Metta, Giorgio

2016-01-01

This paper investigates a biologically motivated model of peripersonal space through its implementation on a humanoid robot. Guided by the present understanding of the neurophysiology of the fronto-parietal system, we developed a computational model inspired by the receptive fields of polymodal neurons identified, for example, in brain areas F4 and VIP. The experiments on the iCub humanoid robot show that the peripersonal space representation i) can be learned efficiently and in real-time via a simple interaction with the robot, ii) can lead to the generation of behaviors like avoidance and reaching, and iii) can contribute to the understanding the biological principle of motor equivalence. More specifically, with respect to i) the present model contributes to hypothesizing a learning mechanisms for peripersonal space. In relation to point ii) we show how a relatively simple controller can exploit the learned receptive fields to generate either avoidance or reaching of an incoming stimulus and for iii) we show how the robot can select arbitrary body parts as the controlled end-point of an avoidance or reaching movement.

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.

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.

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.

Evolving self-assembly in autonomous homogeneous robots: experiments with two physical robots.

PubMed

Ampatzis, Christos; Tuci, Elio; Trianni, Vito; Christensen, Anders Lyhne; Dorigo, Marco

2009-01-01

This research work illustrates an approach to the design of controllers for self-assembling robots in which the self-assembly is initiated and regulated by perceptual cues that are brought forth by the physical robots through their dynamical interactions. More specifically, we present a homogeneous control system that can achieve assembly between two modules (two fully autonomous robots) of a mobile self-reconfigurable system without a priori introduced behavioral or morphological heterogeneities. The controllers are dynamic neural networks evolved in simulation that directly control all the actuators of the two robots. The neurocontrollers cause the dynamic specialization of the robots by allocating roles between them based solely on their interaction. We show that the best evolved controller proves to be successful when tested on a real hardware platform, the swarm-bot. The performance achieved is similar to the one achieved by existing modular or behavior-based approaches, also due to the effect of an emergent recovery mechanism that was neither explicitly rewarded by the fitness function, nor observed during the evolutionary simulation. Our results suggest that direct access to the orientations or intentions of the other agents is not a necessary condition for robot coordination: Our robots coordinate without direct or explicit communication, contrary to what is assumed by most research works in collective robotics. This work also contributes to strengthening the evidence that evolutionary robotics is a design methodology that can tackle real-world tasks demanding fine sensory-motor coordination.

Children's Behavior toward and Understanding of Robotic and Living Dogs

ERIC Educational Resources Information Center

Melson, Gail F.; Kahn, Peter H., Jr.; Beck, Alan; Friedman, Batya; Roberts, Trace; Garrett, Erik; Gill, Brian T.

2009-01-01

This study investigated children's reasoning about and behavioral interactions with a computationally sophisticated robotic dog (Sony's AIBO) compared to a live dog (an Australian Shepherd). Seventy-two children from three age groups (7-9 years, 10-12 years, and 13-15 years) participated in this study. Results showed that more children…

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.

A cognitive robotic system based on the Soar cognitive architecture for mobile robot navigation, search, and mapping missions

NASA Astrophysics Data System (ADS)

Hanford, Scott D.

Most unmanned vehicles used for civilian and military applications are remotely operated or are designed for specific applications. As these vehicles are used to perform more difficult missions or a larger number of missions in remote environments, there will be a great need for these vehicles to behave intelligently and autonomously. Cognitive architectures, computer programs that define mechanisms that are important for modeling and generating domain-independent intelligent behavior, have the potential for generating intelligent and autonomous behavior in unmanned vehicles. The research described in this presentation explored the use of the Soar cognitive architecture for cognitive robotics. The Cognitive Robotic System (CRS) has been developed to integrate software systems for motor control and sensor processing with Soar for unmanned vehicle control. The CRS has been tested using two mobile robot missions: outdoor navigation and search in an indoor environment. The use of the CRS for the outdoor navigation mission demonstrated that a Soar agent could autonomously navigate to a specified location while avoiding obstacles, including cul-de-sacs, with only a minimal amount of knowledge about the environment. While most systems use information from maps or long-range perceptual capabilities to avoid cul-de-sacs, a Soar agent in the CRS was able to recognize when a simple approach to avoiding obstacles was unsuccessful and switch to a different strategy for avoiding complex obstacles. During the indoor search mission, the CRS autonomously and intelligently searches a building for an object of interest and common intersection types. While searching the building, the Soar agent builds a topological map of the environment using information about the intersections the CRS detects. The agent uses this topological model (along with Soar's reasoning, planning, and learning mechanisms) to make intelligent decisions about how to effectively search the building. Once the object of interest has been detected, the Soar agent uses the topological map to make decisions about how to efficiently return to the location where the mission began. Additionally, the CRS can send an email containing step-by-step directions using the intersections in the environment as landmarks that describe a direct path from the mission's start location to the object of interest. The CRS has displayed several characteristics of intelligent behavior, including reasoning, planning, learning, and communication of learned knowledge, while autonomously performing two missions. The CRS has also demonstrated how Soar can be integrated with common robotic motor and perceptual systems that complement the strengths of Soar for unmanned vehicles and is one of the few systems that use perceptual systems such as occupancy grid, computer vision, and fuzzy logic algorithms with cognitive architectures for robotics. The use of these perceptual systems to generate symbolic information about the environment during the indoor search mission allowed the CRS to use Soar's planning and learning mechanisms, which have rarely been used by agents to control mobile robots in real environments. Additionally, the system developed for the indoor search mission represents the first known use of a topological map with a cognitive architecture on a mobile robot. The ability to learn both a topological map and production rules allowed the Soar agent used during the indoor search mission to make intelligent decisions and behave more efficiently as it learned about its environment. While the CRS has been applied to two different missions, it has been developed with the intention that it be extended in the future so it can be used as a general system for mobile robot control. The CRS can be expanded through the addition of new sensors and sensor processing algorithms, development of Soar agents with more production rules, and the use of new architectural mechanisms in Soar.

Flexible Virtual Structure Consideration in Dynamic Modeling of Mobile Robots Formation

NASA Astrophysics Data System (ADS)

El Kamel, A. Essghaier; Beji, L.; Lerbet, J.; Abichou, A.

2009-03-01

In cooperative mobile robotics, we look for formation keeping and maintenance of a geometric configuration during movement. As a solution to these problems, the concept of a virtual structure is considered. Based on this idea, we have developed an efficient flexible virtual structure, describing the dynamic model of n vehicles in formation and where the whole formation is kept dependant. Notes that, for 2D and 3D space navigation, only a rigid virtual structure was proposed in the literature. Further, the problem was limited to a kinematic behavior of the structure. Hence, the flexible virtual structure in dynamic modeling of mobile robots formation presented in this paper, gives more capabilities to the formation to avoid obstacles in hostile environment while keeping formation and avoiding inter-agent collision.

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.

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.

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

The Dominant Robot: Threatening Robots Cause Psychological Reactance, Especially When They Have Incongruent Goals

NASA Astrophysics Data System (ADS)

Roubroeks, M. A. J.; Ham, J. R. C.; Midden, C. J. H.

Persuasive technology can take the form of a social agent that persuades people to change behavior or attitudes. However, like any persuasive technology, persuasive social agents might trigger psychological reactance, which can lead to restoration behavior. The current study investigated whether interacting with a persuasive robot can cause psychological reactance. Additionally, we investigated whether goal congruency plays a role in psychological reactance. Participants programmed a washing machine while a robot gave threatening advice. Confirming expectations, participants experienced more psychological reactance when receiving high-threatening advice compared to low-threatening advice. Moreover, when the robot gave high-threatening advice and expressed an incongruent goal, participants reported the highest level of psychological reactance (on an anger measure). Finally, high-threatening advice led to more restoration, and this relationship was partially mediated by psychological reactance. Overall, results imply that under certain circumstances persuasive technology can trigger opposite effects, especially when people have incongruent goal intentions.

Achieving "organic compositionality" through self-organization: reviews on brain-inspired robotics experiments.

PubMed

Tani, Jun; Nishimoto, Ryunosuke; Paine, Rainer W

2008-05-01

The current paper examines how compositional structures can self-organize in given neuro-dynamical systems when robot agents are forced to learn multiple goal-directed behaviors simultaneously. Firstly, we propose a basic model accounting for the roles of parietal-premotor interactions for representing skills for goal-directed behaviors. The basic model had been implemented in a set of robotics experiments employing different neural network architectures. The comparative reviews among those experimental results address the issues of local vs distributed representations in representing behavior and the effectiveness of level structures associated with different sensory-motor articulation mechanisms. It is concluded that the compositional structures can be acquired "organically" by achieving generalization in learning and by capturing the contextual nature of skilled behaviors under specific conditions. Furthermore, the paper discusses possible feedback for empirical neuroscience studies in the future.

Robotic Intelligence Kernel: Driver

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

The INL Robotic Intelligence Kernel-Driver is built on top of the RIK-A and implements a dynamic autonomy structure. The RIK-D is used to orchestrate hardware for sensing and action as well as software components for perception, communication, behavior and world modeling into a single cognitive behavior kernel that provides intrinsic intelligence for a wide variety of unmanned ground vehicle systems.

A neural framework for organization and flexible utilization of episodic memory in cumulatively learning baby humanoids.

PubMed

Mohan, Vishwanathan; Sandini, Giulio; Morasso, Pietro

2014-12-01

Cumulatively developing robots offer a unique opportunity to reenact the constant interplay between neural mechanisms related to learning, memory, prospection, and abstraction from the perspective of an integrated system that acts, learns, remembers, reasons, and makes mistakes. Situated within such interplay lie some of the computationally elusive and fundamental aspects of cognitive behavior: the ability to recall and flexibly exploit diverse experiences of one's past in the context of the present to realize goals, simulate the future, and keep learning further. This article is an adventurous exploration in this direction using a simple engaging scenario of how the humanoid iCub learns to construct the tallest possible stack given an arbitrary set of objects to play with. The learning takes place cumulatively, with the robot interacting with different objects (some previously experienced, some novel) in an open-ended fashion. Since the solution itself depends on what objects are available in the "now," multiple episodes of past experiences have to be remembered and creatively integrated in the context of the present to be successful. Starting from zero, where the robot knows nothing, we explore the computational basis of organization episodic memory in a cumulatively learning humanoid and address (1) how relevant past experiences can be reconstructed based on the present context, (2) how multiple stored episodic memories compete to survive in the neural space and not be forgotten, (3) how remembered past experiences can be combined with explorative actions to learn something new, and (4) how multiple remembered experiences can be recombined to generate novel behaviors (without exploration). Through the resulting behaviors of the robot as it builds, breaks, learns, and remembers, we emphasize that mechanisms of episodic memory are fundamental design features necessary to enable the survival of autonomous robots in a real world where neither everything can be known nor can everything be experienced.

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.

What can robots tell us about brains? A synthetic approach towards the study of learning and problem solving.

PubMed

Voegtlin, T; Verschure, P F

1999-01-01

This paper argues for the development of synthetic approaches towards the study of brain and behavior as a complement to the more traditional empirical mode of research. As an example we present our own work on learning and problem solving which relates to the behavioral paradigms of classical and operant conditioning. We define the concept of learning in the context of behavior and lay out the basic methodological requirements a model needs to satisfy, which includes evaluations using robots. In addition, we define a number of design principles neuronal models should obey to be considered relevant. We present in detail the construction of a neural model of short- and long-term memory which can be applied to an artificial behaving system. The presented model (DAC4) provides a novel self-consistent implementation of these processes, which satisfies our principles. This model will be interpreted towards the present understanding of the neuronal substrate of memory.

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

Cooperative Exploration of Rough Martian Terrains with the "Scorpion" Legged Robot as an Adjunct to a Rover.

NASA Technical Reports Server (NTRS)

Colombano, Silvano P.; Kirchner, Frank; Spenneberg, Dirk; Starman, Jared; Hanratty, James; Kovsmeyer, David (Technical Monitor)

2003-01-01

NASA needs autonomous robotic exploration of difficult (rough and/or steep) scientifically interesting Martian terrains. Concepts involving distributed autonomy for cooperative robotic exploration are key to enabling new scientific objectives in robotic missions. We propose to utilize a legged robot as an adjunct scout to a rover for access to difficult - scientifically interesting - terrains (rocky areas, slopes, cliffs). Our final mission scenario involves the Ames rover platform "K9" and Scorpion acting together to explore a steep cliff, with the Scorpion robot rappelling down using the K9 as an anchor as well as mission planner and executive. Cooperation concepts, including wheeled rappelling robots have been proposed before. Now we propose to test the combined advantages of a wheeled vehicle with a legged scout as well as the advantages of merging of high level planning and execution with biologically inspired, behavior based robotics. We propose to use the 8-legged, multifunctional autonomous robot platform Scorpion that is currently capable of: Walking on different terrains (rocks, sand, grass, ...). Perceiving its environment and modifying its behavioral pattern accordingly. These capabilities would be extended to enable the Scorpion to: communicate and cooperate with a partner robot; climb over rocks, rubble piles, and objects with structural features. This will be done in the context of exploration of rough terrains in the neighborhood of the rover, but inaccessible to it, culminating in the added capability of rappelling down a steep cliff for both vertical and horizontal terrain observation.

Unsolved problems in observational astronomy. II. Focus on rapid response - mining the sky with ``thinking" telescopes

NASA Astrophysics Data System (ADS)

Vestrand, W. T.; Theiler, J.; Woznia, P. R.

2004-10-01

The existence of rapidly slewing robotic telescopes and fast alert distribution via the Internet is revolutionizing our capability to study the physics of fast astrophysical transients. But the salient challenge that optical time domain surveys must conquer is mining the torrent of data to recognize important transients in a scene full of normal variations. Humans simply do not have the attention span, memory, or reaction time required to recognize fast transients and rapidly respond. Autonomous robotic instrumentation with the ability to extract pertinent information from the data stream in real time will therefore be essential for recognizing transients and commanding rapid follow-up observations while the ephemeral behavior is still present. Here we discuss how the development and integration of three technologies: (1) robotic telescope networks; (2) machine learning; and (3) advanced database technology, can enable the construction of smart robotic telescopes, which we loosely call ``thinking'' telescopes, capable of mining the sky in real time.

Twitching in Sensorimotor Development from Sleeping Rats to Robots

PubMed Central

Marques, Hugo Gravato; Iida, Fumiya

2013-01-01

It is still not known how the “rudimentary” movements of fetuses and infants are transformed into the coordinated, flexible, and adaptive movements of adults. In addressing this important issue, we consider a behavior that has been perennially viewed as a functionless by-product of a dreaming brain: the jerky limb movements called myoclonic twitches. Recent work has identified the neural mechanisms that produce twitching as well as those that convey sensory feedback from twitching limbs to the spinal cord and brain. In turn, these mechanistic insights have helped inspire new ideas about the functional roles that twitching might play in the self-organization of spinal and supraspinal sensorimotor circuits. Striking support for these ideas is coming from the field of developmental robotics: When twitches are mimicked in robot models of the musculoskeletal system, basic neural circuitry self-organizes. Mutually inspired biological and synthetic approaches promise not only to produce better robots, but also to solve fundamental problems concerning the developmental origins of sensorimotor maps in the spinal cord and brain. PMID:23787051

Free-standing leaping experiments with a power-autonomous elastic-spined quadruped

NASA Astrophysics Data System (ADS)

Pusey, Jason L.; Duperret, Jeffrey M.; Haynes, G. Clark; Knopf, Ryan; Koditschek, Daniel E.

2013-05-01

We document initial experiments with Canid, a freestanding, power-autonomous quadrupedal robot equipped with a parallel actuated elastic spine. Research into robotic bounding and galloping platforms holds scientific and engineering interest because it can both probe biological hypotheses regarding bounding and galloping mammals and also provide the engineering community with a new class of agile, efficient and rapidly-locomoting legged robots. We detail the design features of Canid that promote our goals of agile operation in a relatively cheap, conventionally prototyped, commercial off-the-shelf actuated platform. We introduce new measurement methodology aimed at capturing our robot's "body energy" during real time operation as a means of quantifying its potential for agile behavior. Finally, we present joint motor, inertial and motion capture data taken from Canid's initial leaps into highly energetic regimes exhibiting large accelerations that illustrate the use of this measure and suggest its future potential as a platform for developing efficient, stable, hence useful bounding gaits.

Facilitators and Barriers to Adopting Robotic-Assisted Surgery: Contextualizing the Unified Theory of Acceptance and Use of Technology

PubMed Central

BenMessaoud, Christine; Kharrazi, Hadi; MacDorman, Karl F.

2011-01-01

Robotic-assisted surgical techniques are not yet well established among surgeon practice groups beyond a few surgical subspecialties. To help identify the facilitators and barriers to their adoption, this belief-elicitation study contextualized and supplemented constructs of the unified theory of acceptance and use of technology (UTAUT) in robotic-assisted surgery. Semi-structured individual interviews were conducted with 21 surgeons comprising two groups: users and nonusers. The main facilitators to adoption were Perceived Usefulness and Facilitating Conditions among both users and nonusers, followed by Attitude Toward Using Technology among users and Extrinsic Motivation among nonusers. The three main barriers to adoption for both users and nonusers were Perceived Ease of Use and Complexity, Perceived Usefulness, and Perceived Behavioral Control. This study's findings can assist surgeons, hospital and medical school administrators, and other policy makers on the proper adoption of robotic-assisted surgery and can guide future research on the development of theories and framing of hypotheses. PMID:21283719

The Tactile Ethics of Soft Robotics: Designing Wisely for Human-Robot Interaction.

PubMed

Arnold, Thomas; Scheutz, Matthias

2017-06-01

Soft robots promise an exciting design trajectory in the field of robotics and human-robot interaction (HRI), promising more adaptive, resilient movement within environments as well as a safer, more sensitive interface for the objects or agents the robot encounters. In particular, tactile HRI is a critical dimension for designers to consider, especially given the onrush of assistive and companion robots into our society. In this article, we propose to surface an important set of ethical challenges for the field of soft robotics to meet. Tactile HRI strongly suggests that soft-bodied robots balance tactile engagement against emotional manipulation, model intimacy on the bonding with a tool not with a person, and deflect users from personally and socially destructive behavior the soft bodies and surfaces could normally entice.

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.

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

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.

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.

Dragons, Ladybugs, and Softballs: Girls' STEM Engagement with Human-Centered Robotics

NASA Astrophysics Data System (ADS)

Gomoll, Andrea; Hmelo-Silver, Cindy E.; Šabanović, Selma; Francisco, Matthew

2016-12-01

Early experiences in science, technology, engineering, and math (STEM) are important for getting youth interested in STEM fields, particularly for girls. Here, we explore how an after-school robotics club can provide informal STEM experiences that inspire students to engage with STEM in the future. Human-centered robotics, with its emphasis on the social aspects of science and technology, may be especially important for bringing girls into the STEM pipeline. Using a problem-based approach, we designed two robotics challenges. We focus here on the more extended second challenge, in which participants were asked to imagine and build a telepresence robot that would allow others to explore their space from a distance. This research follows four girls as they engage with human-centered telepresence robotics design. We constructed case studies of these target participants to explore their different forms of engagement and phases of interest development—considering facets of behavioral, social, cognitive, and conceptual-to-consequential engagement as well as stages of interest ranging from triggered interest to well-developed individual interest. The results demonstrated that opportunities to personalize their robots and feedback from peers and facilitators were important motivators. We found both explicit and vicarious engagement and varied interest phases in our group of four focus participants. This first iteration of our project demonstrated that human-centered robotics is a promising approach to getting girls interested and engaged in STEM practices. As we design future iterations of our robotics club environment, we must consider how to harness multiple forms of leadership and engagement without marginalizing students with different working preferences.

Robots As Intentional Agents: Using Neuroscientific Methods to Make Robots Appear More Social

PubMed Central

Wiese, Eva; Metta, Giorgio; Wykowska, Agnieszka

2017-01-01

Robots are increasingly envisaged as our future cohabitants. However, while considerable progress has been made in recent years in terms of their technological realization, the ability of robots to interact with humans in an intuitive and social way is still quite limited. An important challenge for social robotics is to determine how to design robots that can perceive the user’s needs, feelings, and intentions, and adapt to users over a broad range of cognitive abilities. It is conceivable that if robots were able to adequately demonstrate these skills, humans would eventually accept them as social companions. We argue that the best way to achieve this is using a systematic experimental approach based on behavioral and physiological neuroscience methods such as motion/eye-tracking, electroencephalography, or functional near-infrared spectroscopy embedded in interactive human–robot paradigms. This approach requires understanding how humans interact with each other, how they perform tasks together and how they develop feelings of social connection over time, and using these insights to formulate design principles that make social robots attuned to the workings of the human brain. In this review, we put forward the argument that the likelihood of artificial agents being perceived as social companions can be increased by designing them in a way that they are perceived as intentional agents that activate areas in the human brain involved in social-cognitive processing. We first review literature related to social-cognitive processes and mechanisms involved in human–human interactions, and highlight the importance of perceiving others as intentional agents to activate these social brain areas. We then discuss how attribution of intentionality can positively affect human–robot interaction by (a) fostering feelings of social connection, empathy and prosociality, and by (b) enhancing performance on joint human–robot tasks. Lastly, we describe circumstances under which attribution of intentionality to robot agents might be disadvantageous, and discuss challenges associated with designing social robots that are inspired by neuroscientific principles. PMID:29046651

Robots As Intentional Agents: Using Neuroscientific Methods to Make Robots Appear More Social.

PubMed

Wiese, Eva; Metta, Giorgio; Wykowska, Agnieszka

2017-01-01

Robots are increasingly envisaged as our future cohabitants. However, while considerable progress has been made in recent years in terms of their technological realization, the ability of robots to interact with humans in an intuitive and social way is still quite limited. An important challenge for social robotics is to determine how to design robots that can perceive the user's needs, feelings, and intentions, and adapt to users over a broad range of cognitive abilities. It is conceivable that if robots were able to adequately demonstrate these skills, humans would eventually accept them as social companions. We argue that the best way to achieve this is using a systematic experimental approach based on behavioral and physiological neuroscience methods such as motion/eye-tracking, electroencephalography, or functional near-infrared spectroscopy embedded in interactive human-robot paradigms. This approach requires understanding how humans interact with each other, how they perform tasks together and how they develop feelings of social connection over time, and using these insights to formulate design principles that make social robots attuned to the workings of the human brain. In this review, we put forward the argument that the likelihood of artificial agents being perceived as social companions can be increased by designing them in a way that they are perceived as intentional agents that activate areas in the human brain involved in social-cognitive processing. We first review literature related to social-cognitive processes and mechanisms involved in human-human interactions, and highlight the importance of perceiving others as intentional agents to activate these social brain areas. We then discuss how attribution of intentionality can positively affect human-robot interaction by (a) fostering feelings of social connection, empathy and prosociality, and by (b) enhancing performance on joint human-robot tasks. Lastly, we describe circumstances under which attribution of intentionality to robot agents might be disadvantageous, and discuss challenges associated with designing social robots that are inspired by neuroscientific principles.

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.

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

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.

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.

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.

Increasing Safety of a Robotic System for Inner Ear Surgery Using Probabilistic Error Modeling Near Vital Anatomy

PubMed Central

Dillon, Neal P.; Siebold, Michael A.; Mitchell, Jason E.; Blachon, Gregoire S.; Balachandran, Ramya; Fitzpatrick, J. Michael; Webster, Robert J.

2017-01-01

Safe and effective planning for robotic surgery that involves cutting or ablation of tissue must consider all potential sources of error when determining how close the tool may come to vital anatomy. A pre-operative plan that does not adequately consider potential deviations from ideal system behavior may lead to patient injury. Conversely, a plan that is overly conservative may result in ineffective or incomplete performance of the task. Thus, enforcing simple, uniform-thickness safety margins around vital anatomy is insufficient in the presence of spatially varying, anisotropic error. Prior work has used registration error to determine a variable-thickness safety margin around vital structures that must be approached during mastoidectomy but ultimately preserved. In this paper, these methods are extended to incorporate image distortion and physical robot errors, including kinematic errors and deflections of the robot. These additional sources of error are discussed and stochastic models for a bone-attached robot for otologic surgery are developed. An algorithm for generating appropriate safety margins based on a desired probability of preserving the underlying anatomical structure is presented. Simulations are performed on a CT scan of a cadaver head and safety margins are calculated around several critical structures for planning of a robotic mastoidectomy. PMID:29200595

Biologically inspired intelligent robots

NASA Astrophysics Data System (ADS)

Bar-Cohen, Yoseph; Breazeal, Cynthia

2003-07-01

Humans throughout history have always sought to mimic the appearance, mobility, functionality, intelligent operation, and thinking process of biological creatures. This field of biologically inspired technology, having the moniker biomimetics, has evolved from making static copies of human and animals in the form of statues to the emergence of robots that operate with realistic behavior. Imagine a person walking towards you where suddenly you notice something weird about him--he is not real but rather he is a robot. Your reaction would probably be "I can't believe it but this robot looks very real" just as you would react to an artificial flower that is a good imitation. You may even proceed and touch the robot to check if your assessment is correct but, as oppose to the flower case, the robot may be programmed to respond physical and verbally. This science fiction scenario could become a reality as the current trend continues in developing biologically inspired technologies. Technology evolution led to such fields as artificial muscles, artificial intelligence, and artificial vision as well as biomimetic capabilities in materials science, mechanics, electronics, computing science, information technology and many others. This paper will review the state of the art and challenges to biologically-inspired technologies and the role that EAP is expected to play as the technology evolves.

Increasing safety of a robotic system for inner ear surgery using probabilistic error modeling near vital anatomy

NASA Astrophysics Data System (ADS)

Dillon, Neal P.; Siebold, Michael A.; Mitchell, Jason E.; Blachon, Gregoire S.; Balachandran, Ramya; Fitzpatrick, J. Michael; Webster, Robert J.

2016-03-01

Safe and effective planning for robotic surgery that involves cutting or ablation of tissue must consider all potential sources of error when determining how close the tool may come to vital anatomy. A pre-operative plan that does not adequately consider potential deviations from ideal system behavior may lead to patient injury. Conversely, a plan that is overly conservative may result in ineffective or incomplete performance of the task. Thus, enforcing simple, uniform-thickness safety margins around vital anatomy is insufficient in the presence of spatially varying, anisotropic error. Prior work has used registration error to determine a variable-thickness safety margin around vital structures that must be approached during mastoidectomy but ultimately preserved. In this paper, these methods are extended to incorporate image distortion and physical robot errors, including kinematic errors and deflections of the robot. These additional sources of error are discussed and stochastic models for a bone-attached robot for otologic surgery are developed. An algorithm for generating appropriate safety margins based on a desired probability of preserving the underlying anatomical structure is presented. Simulations are performed on a CT scan of a cadaver head and safety margins are calculated around several critical structures for planning of a robotic mastoidectomy.

Behavior coordination of mobile robotics using supervisory control of fuzzy discrete event systems.

PubMed

Jayasiri, Awantha; Mann, George K I; Gosine, Raymond G

2011-10-01

In order to incorporate the uncertainty and impreciseness present in real-world event-driven asynchronous systems, fuzzy discrete event systems (DESs) (FDESs) have been proposed as an extension to crisp DESs. In this paper, first, we propose an extension to the supervisory control theory of FDES by redefining fuzzy controllable and uncontrollable events. The proposed supervisor is capable of enabling feasible uncontrollable and controllable events with different possibilities. Then, the extended supervisory control framework of FDES is employed to model and control several navigational tasks of a mobile robot using the behavior-based approach. The robot has limited sensory capabilities, and the navigations have been performed in several unmodeled environments. The reactive and deliberative behaviors of the mobile robotic system are weighted through fuzzy uncontrollable and controllable events, respectively. By employing the proposed supervisory controller, a command-fusion-type behavior coordination is achieved. The observability of fuzzy events is incorporated to represent the sensory imprecision. As a systematic analysis of the system, a fuzzy-state-based controllability measure is introduced. The approach is implemented in both simulation and real time. A performance evaluation is performed to quantitatively estimate the validity of the proposed approach over its counterparts.

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.

Critiquing the Reasons for Making Artificial Moral Agents.

PubMed

van Wynsberghe, Aimee; Robbins, Scott

2018-02-19

Many industry leaders and academics from the field of machine ethics would have us believe that the inevitability of robots coming to have a larger role in our lives demands that robots be endowed with moral reasoning capabilities. Robots endowed in this way may be referred to as artificial moral agents (AMA). Reasons often given for developing AMAs are: the prevention of harm, the necessity for public trust, the prevention of immoral use, such machines are better moral reasoners than humans, and building these machines would lead to a better understanding of human morality. Although some scholars have challenged the very initiative to develop AMAs, what is currently missing from the debate is a closer examination of the reasons offered by machine ethicists to justify the development of AMAs. This closer examination is especially needed because of the amount of funding currently being allocated to the development of AMAs (from funders like Elon Musk) coupled with the amount of attention researchers and industry leaders receive in the media for their efforts in this direction. The stakes in this debate are high because moral robots would make demands on society; answers to a host of pending questions about what counts as an AMA and whether they are morally responsible for their behavior or not. This paper shifts the burden of proof back to the machine ethicists demanding that they give good reasons to build AMAs. The paper argues that until this is done, the development of commercially available AMAs should not proceed further.

5-7 Year Old Children's Conceptions of Behaving Artifacts and the Influence of Constructing Their Behavior on the Development of Theory of Mind (ToM) and Theory of Artificial Mind (ToAM)

ERIC Educational Resources Information Center

Spektor-Precel, Karen; Mioduser, David

2015-01-01

Nowadays, we are surrounded by artifacts that are capable of adaptive behavior, such as electric pots, boiler timers, automatic doors, and robots. The literature concerning human beings' conceptions of "traditional" artifacts is vast, however, little is known about our conceptions of behaving artifacts, nor of the influence of the…

Types of verbal interaction with instructable robots

NASA Technical Reports Server (NTRS)

Crangle, C.; Suppes, P.; Michalowski, S.

1987-01-01

An instructable robot is one that accepts instruction in some natural language such as English and uses that instruction to extend its basic repertoire of actions. Such robots are quite different in conception from autonomously intelligent robots, which provide the impetus for much of the research on inference and planning in artificial intelligence. Examined here are the significant problem areas in the design of robots that learn from vebal instruction. Examples are drawn primarily from our earlier work on instructable robots and recent work on the Robotic Aid for the physically disabled. Natural-language understanding by machines is discussed as well as in the possibilities and limits of verbal instruction. The core problem of verbal instruction, namely, how to achieve specific concrete action in the robot in response to commands that express general intentions, is considered, as are two major challenges to instructability: achieving appropriate real-time behavior in the robot, and extending the robot's language capabilities.

Improving precise positioning of surgical robotic instruments by a three-side-view presentation system on telesurgery.

PubMed

Hori, Kenta; Kuroda, Tomohiro; Oyama, Hiroshi; Ozaki, Yasuhiko; Nakamura, Takehiko; Takahashi, Takashi

2005-12-01

For faultless collaboration among the surgeon, surgical staffs, and surgical robots in telesurgery, communication must include environmental information of the remote operating room, such as behavior of robots and staffs, vital information of a patient, named supporting information, in addition to view of surgical field. "Surgical Cockpit System, " which is a telesurgery support system that has been developed by the authors, is mainly focused on supporting information exchange between remote sites. Live video presentation is important technology for Surgical Cockpit System. Visualization method to give precise location/posture of surgical instruments is indispensable for accurate control and faultless operation. In this paper, the authors propose three-side-view presentation method for precise location/posture control of surgical instruments in telesurgery. The experimental results show that the proposed method improved accurate positioning of a telemanipulator.

The Role of Reciprocity in Verbally Persuasive Robots.

PubMed

Lee, Seungcheol Austin; Liang, Yuhua Jake

2016-08-01

The current research examines the persuasive effects of reciprocity in the context of human-robot interaction. This is an important theoretical and practical extension of persuasive robotics by testing (1) if robots can utilize verbal requests and (2) if robots can utilize persuasive mechanisms (e.g., reciprocity) to gain human compliance. Participants played a trivia game with a robot teammate. The ostensibly autonomous robot helped (or failed to help) the participants by providing the correct (vs. incorrect) trivia answers. Then, the robot directly asked participants to complete a 15-minute task for pattern recognition. Compared to no help, results showed that a robot's prior helping behavior significantly increased the likelihood of compliance (60 percent vs. 33 percent). Interestingly, participants' evaluations toward the robot (i.e., competence, warmth, and trustworthiness) did not predict compliance. These results also provided an insightful comparison showing that participants complied at similar rates with the robot and with computer agents. This result documents a clear empirically powerful potential for the role of verbal messages in persuasive robotics.

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

Intelligent systems for urban search and rescue: challenges and lessons learned

NASA Astrophysics Data System (ADS)

Jacoff, Adam; Messina, Elena; Weiss, Brian A.

2003-09-01

Urban search and rescue (USAR) is one of the most dangerous and time-critical non-wartime activities. Researchers have been developing hardware and software to enable robots to perform some search and rescue functions so as to minimize the exposure of human rescue personnel to danger and maximize the survival of victims. Significant progress has been achieved, but much work remains. USAR demands a blending of numerous specialized technologies. An effective USAR robot must be endowed with key competencies, such as being able to negotiate collapsed structures, find victims and assess their condition, identify potential hazards, generate maps of the structure and victim locations, and communicate with rescue personnel. These competencies bring to bear work in numerous sub-disciplines of intelligent systems (or artificial intelligence) such as sensory processing, world modeling, behavior generation, path planning, and human-robot interaction, in addition to work in communications, mechanism design and advanced sensors. In an attempt to stimulate progress in the field, reference USAR challenges are being developed and propagated worldwide. In order to make efficient use of finite research resources, the robotic USAR community must share a common understanding of what is required, technologically, to attain each competency, and have a rigorous measure of the current level of effectiveness of various technologies. NIST is working with partner organizations to measure the performance of robotic USAR competencies and technologies. In this paper, we describe the reference test arenas for USAR robots, assess the current challenges within the field, and discuss experiences thus far in the testing effort.

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.

Peripersonal Space and Margin of Safety around the Body: Learning Visuo-Tactile Associations in a Humanoid Robot with Artificial Skin

PubMed Central

Roncone, Alessandro; Fadiga, Luciano; Metta, Giorgio

2016-01-01

This paper investigates a biologically motivated model of peripersonal space through its implementation on a humanoid robot. Guided by the present understanding of the neurophysiology of the fronto-parietal system, we developed a computational model inspired by the receptive fields of polymodal neurons identified, for example, in brain areas F4 and VIP. The experiments on the iCub humanoid robot show that the peripersonal space representation i) can be learned efficiently and in real-time via a simple interaction with the robot, ii) can lead to the generation of behaviors like avoidance and reaching, and iii) can contribute to the understanding the biological principle of motor equivalence. More specifically, with respect to i) the present model contributes to hypothesizing a learning mechanisms for peripersonal space. In relation to point ii) we show how a relatively simple controller can exploit the learned receptive fields to generate either avoidance or reaching of an incoming stimulus and for iii) we show how the robot can select arbitrary body parts as the controlled end-point of an avoidance or reaching movement. PMID:27711136

Developmental Approach for Behavior Learning Using Primitive Motion Skills.

PubMed

Dawood, Farhan; Loo, Chu Kiong

2018-05-01

Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet the discussion on the origin of primitive imitative abilities is often neglected, referring instead to the possibility of its innateness. This paper presents a developmental model of imitation learning based on the hypothesis that humanoid robot acquires imitative abilities as induced by sensorimotor associative learning through self-exploration. In designing such learning system, several key issues will be addressed: automatic segmentation of the observed actions into motion primitives using raw images acquired from the camera without requiring any kinematic model; incremental learning of spatio-temporal motion sequences to dynamically generates a topological structure in a self-stabilizing manner; organization of the learned data for easy and efficient retrieval using a dynamic associative memory; and utilizing segmented motion primitives to generate complex behavior by the combining these motion primitives. In our experiment, the self-posture is acquired through observing the image of its own body posture while performing the action in front of a mirror through body babbling. The complete architecture was evaluated by simulation and real robot experiments performed on DARwIn-OP humanoid robot.

Building Robota, a Mini-Humanoid Robot for the Rehabilitation of Children with Autism

ERIC Educational Resources Information Center

Billard, Aude; Robins, Ben; Nadel, Jacqueline; Dautenhahn, Kerstin

2007-01-01

The Robota project constructs a series of multiple-degrees-of-freedom, doll-shaped humanoid robots, whose physical features resemble those of a human baby. The Robota robots have been applied as assistive technologies in behavioral studies with low-functioning children with autism. These studies investigate the potential of using an imitator robot…

The Potential of Peer Robots to Assist Human Creativity in Finding Problems and Problem Solving

ERIC Educational Resources Information Center

Okita, Sandra

2015-01-01

Many technological artifacts (e.g., humanoid robots, computer agents) consist of biologically inspired features of human-like appearance and behaviors that elicit a social response. The strong social components of technology permit people to share information and ideas with these artifacts. As robots cross the boundaries between humans and…

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.

Molecular Robots Obeying Asimov's Three Laws of Robotics.

PubMed

Kaminka, Gal A; Spokoini-Stern, Rachel; Amir, Yaniv; Agmon, Noa; Bachelet, Ido

2017-01-01

Asimov's three laws of robotics, which were shaped in the literary work of Isaac Asimov (1920-1992) and others, define a crucial code of behavior that fictional autonomous robots must obey as a condition for their integration into human society. While, general implementation of these laws in robots is widely considered impractical, limited-scope versions have been demonstrated and have proven useful in spurring scientific debate on aspects of safety and autonomy in robots and intelligent systems. In this work, we use Asimov's laws to examine these notions in molecular robots fabricated from DNA origami. We successfully programmed these robots to obey, by means of interactions between individual robots in a large population, an appropriately scoped variant of Asimov's laws, and even emulate the key scenario from Asimov's story "Runaround," in which a fictional robot gets into trouble despite adhering to the laws. Our findings show that abstract, complex notions can be encoded and implemented at the molecular scale, when we understand robots on this scale on the basis of their interactions.

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

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.

Robot Lies in Health Care: When Is Deception Morally Permissible?

PubMed

Matthias, Andreas

2015-06-01

Autonomous robots are increasingly interacting with users who have limited knowledge of robotics and are likely to have an erroneous mental model of the robot's workings, capabilities, and internal structure. The robot's real capabilities may diverge from this mental model to the extent that one might accuse the robot's manufacturer of deceiving the user, especially in cases where the user naturally tends to ascribe exaggerated capabilities to the machine (e.g. conversational systems in elder-care contexts, or toy robots in child care). This poses the question, whether misleading or even actively deceiving the user of an autonomous artifact about the capabilities of the machine is morally bad and why. By analyzing trust, autonomy, and the erosion of trust in communicative acts as consequences of deceptive robot behavior, we formulate four criteria that must be fulfilled in order for robot deception to be morally permissible, and in some cases even morally indicated.

A crawling robot driven by multi-stable origami

NASA Astrophysics Data System (ADS)

Pagano, Alexander; Yan, Tongxi; Chien, Brian; Wissa, A.; Tawfick, S.

2017-09-01

Using origami folding to construct and actuate mechanisms and machines offers attractive opportunities from small, scalable, and cheap robots to deployable adaptive structures. This paper presents the design of a bio-inspired origami crawling robot constructed by folding sheets of paper. The origami building block structure is based on the Kresling crease pattern (CP), a chiral tower with a polygonal base, which expands and contracts through coupled longitudinal and rotational motion similar to a screw. We design the origami to have multi-stable structural equilibria which can be tuned by changing the folding CP. Kinematic analysis of these structures based on rigid-plates and hinges at fold lines precludes the shape transformation associated with the bistability of the physical models. To capture the kinematics of the bi-stable origami, the panels’ deformation behavior is modeled utilizing principles of virtual folds. Virtual folds approximate material bending by hinged, rigid panels, which facilitates the development of a kinematic solution via rigid-plate rotation analysis. As such, the kinetics and stability of folded structures are investigated by assigning suitable torsional spring constants to the fold lines. The results presented demonstrate the effect of fold-pattern geometries on the snapping behavior of the bi-stable origami structure based on the Kresling pattern. The crawling robot is presented as a case study for the use of this origami structure to mimic crawling locomotion. The robot is comprised of two origami towers nested inside a paper bellow, and connected by 3D printed end plates. DC motors are used to actuate the expansion and contraction of the internal origami structures to achieve forward locomotion and steering. Beyond locomotion, this simple design can find applications in manipulators, booms, and active structures.

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.

Robot-assisted procedures in pediatric neurosurgery.

PubMed

De Benedictis, Alessandro; Trezza, Andrea; Carai, Andrea; Genovese, Elisabetta; Procaccini, Emidio; Messina, Raffaella; Randi, Franco; Cossu, Silvia; Esposito, Giacomo; Palma, Paolo; Amante, Paolina; Rizzi, Michele; Marras, Carlo Efisio

2017-05-01

OBJECTIVE During the last 3 decades, robotic technology has rapidly spread across several surgical fields due to the continuous evolution of its versatility, stability, dexterity, and haptic properties. Neurosurgery pioneered the development of robotics, with the aim of improving the quality of several procedures requiring a high degree of accuracy and safety. Moreover, robot-guided approaches are of special interest in pediatric patients, who often have altered anatomy and challenging relationships between the diseased and eloquent structures. Nevertheless, the use of robots has been rarely reported in children. In this work, the authors describe their experience using the ROSA device (Robotized Stereotactic Assistant) in the neurosurgical management of a pediatric population. METHODS Between 2011 and 2016, 116 children underwent ROSA-assisted procedures for a variety of diseases (epilepsy, brain tumors, intra- or extraventricular and tumor cysts, obstructive hydrocephalus, and movement and behavioral disorders). Each patient received accurate preoperative planning of optimal trajectories, intraoperative frameless registration, surgical treatment using specific instruments held by the robotic arm, and postoperative CT or MR imaging. RESULTS The authors performed 128 consecutive surgeries, including implantation of 386 electrodes for stereo-electroencephalography (36 procedures), neuroendoscopy (42 procedures), stereotactic biopsy (26 procedures), pallidotomy (12 procedures), shunt placement (6 procedures), deep brain stimulation procedures (3 procedures), and stereotactic cyst aspiration (3 procedures). For each procedure, the authors analyzed and discussed accuracy, timing, and complications. CONCLUSIONS To the best their knowledge, the authors present the largest reported series of pediatric neurosurgical cases assisted by robotic support. The ROSA system provided improved safety and feasibility of minimally invasive approaches, thus optimizing the surgical result, while minimizing postoperative morbidity.

Toward Self-Growing Soft Robots Inspired by Plant Roots and Based on Additive Manufacturing Technologies.

PubMed

Sadeghi, Ali; Mondini, Alessio; Mazzolai, Barbara

2017-09-01

In this article, we present a novel class of robots that are able to move by growing and building their own structure. In particular, taking inspiration by the growing abilities of plant roots, we designed and developed a plant root-like robot that creates its body through an additive manufacturing process. Each robotic root includes a tubular body, a growing head, and a sensorized tip that commands the robot behaviors. The growing head is a customized three-dimensional (3D) printer-like system that builds the tubular body of the root in the format of circular layers by fusing and depositing a thermoplastic material (i.e., polylactic acid [PLA] filament) at the tip level, thus obtaining movement by growing. A differential deposition of the material can create an asymmetry that results in curvature of the built structure, providing the possibility of root bending to follow or escape from a stimulus or to reach a desired point in space. Taking advantage of these characteristics, the robotic roots are able to move inside a medium by growing their body. In this article, we describe the design of the growing robot together with the modeling of the deposition process and the description of the implemented growing movement strategy. Experiments were performed in air and in an artificial medium to verify the functionalities and to evaluate the robot performance. The results showed that the robotic root, with a diameter of 50 mm, grows with a speed of up to 4 mm/min, overcoming medium pressure of up to 37 kPa (i.e., it is able to lift up to 6 kg) and bending with a minimum radius of 100 mm.

Toward Self-Growing Soft Robots Inspired by Plant Roots and Based on Additive Manufacturing Technologies

PubMed Central

Mondini, Alessio

2017-01-01

Abstract In this article, we present a novel class of robots that are able to move by growing and building their own structure. In particular, taking inspiration by the growing abilities of plant roots, we designed and developed a plant root-like robot that creates its body through an additive manufacturing process. Each robotic root includes a tubular body, a growing head, and a sensorized tip that commands the robot behaviors. The growing head is a customized three-dimensional (3D) printer-like system that builds the tubular body of the root in the format of circular layers by fusing and depositing a thermoplastic material (i.e., polylactic acid [PLA] filament) at the tip level, thus obtaining movement by growing. A differential deposition of the material can create an asymmetry that results in curvature of the built structure, providing the possibility of root bending to follow or escape from a stimulus or to reach a desired point in space. Taking advantage of these characteristics, the robotic roots are able to move inside a medium by growing their body. In this article, we describe the design of the growing robot together with the modeling of the deposition process and the description of the implemented growing movement strategy. Experiments were performed in air and in an artificial medium to verify the functionalities and to evaluate the robot performance. The results showed that the robotic root, with a diameter of 50 mm, grows with a speed of up to 4 mm/min, overcoming medium pressure of up to 37 kPa (i.e., it is able to lift up to 6 kg) and bending with a minimum radius of 100 mm. PMID:29062628

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.

Dynamic Behavior Sequencing in a Hybrid Robot Architecture

DTIC Science & Technology

2008-03-01

107 Appendix A. Implemented Behavior Representations . . . . . . . . . . 109 Appendix B . Example Behavior...114 A.12 Implemented Behavior wander . . . . . . . . . . . . . . . . . . . . 115 B .1 Example Behavior avoid-obstacle...116 B .2 Example Behavior deliver-object . . . . . . . . . . . . . . . . . 117 B .3 Example Behavior get-object

Socialization between toddlers and robots at an early childhood education center

PubMed Central

Tanaka, Fumihide; Cicourel, Aaron; Movellan, Javier R.

2007-01-01

A state-of-the-art social robot was immersed in a classroom of toddlers for >5 months. The quality of the interaction between children and robots improved steadily for 27 sessions, quickly deteriorated for 15 sessions when the robot was reprogrammed to behave in a predictable manner, and improved in the last three sessions when the robot displayed again its full behavioral repertoire. Initially, the children treated the robot very differently than the way they treated each other. By the last sessions, 5 months later, they treated the robot as a peer rather than as a toy. Results indicate that current robot technology is surprisingly close to achieving autonomous bonding and socialization with human toddlers for sustained periods of time and that it could have great potential in educational settings assisting teachers and enriching the classroom environment. PMID:17984068

Modelling robot construction systems

NASA Technical Reports Server (NTRS)

Grasso, Chris

1990-01-01

TROTER's are small, inexpensive robots that can work together to accomplish sophisticated construction tasks. To understand the issues involved in designing and operating a team of TROTER's, the robots and their components are being modeled. A TROTER system that features standardized component behavior is introduced. An object-oriented model implemented in the Smalltalk programming language is described and the advantages of the object-oriented approach for simulating robot and component interactions are discussed. The presentation includes preliminary results and a discussion of outstanding issues.

3D Printer Instrumentation to Create Varied Geometries of Robotic Limbs and Heterogeneous Granular Media

DTIC Science & Technology

2015-05-20

Transfer Robo Ant The 3D printer was used to rapidly prototype a robot ant . The robot ant was used to model the behavior of the fire ant and to model...computer models and 3D printed ant robots are shown below. Snake Bot We used the 3D printed to rapidly design a modular, easily-modified snake...living organism (modern mudskippers, a terrestrial fish) and extinct early tetrapods (e.g. Ichthyostega, Acanthostega) while allowing us to explore

Does It "Want" or "Was It Programmed to..."? Kindergarten Children's Explanations of an Autonomous Robot's Adaptive Functioning

ERIC Educational Resources Information Center

Levy, Sharona T.; Mioduser, David

2008-01-01

This study investigates young children's perspectives in explaining a self-regulating mobile robot, as they learn to program its behaviors from rules. We explore their descriptions of a robot in action to determine the nature of their explanatory frameworks: psychological or technological. We have also studied the role of an adult's intervention…

Robots as Imagined in the Television Series Humans.

PubMed

Wicclair, Mark R

2018-07-01

Humans is a science fiction television series set in what appears to be present-day London. What makes it science fiction is that in London and worldwide, there are robots that look like humans and can mimic human behavior. The series raises several important ethical and philosophical questions about artificial intelligence and robotics, which should be of interest to bioethicists.

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

Autonomous Legged Hill and Stairwell Ascent

DTIC Science & Technology

2011-11-01

environments with little burden to a human operator. Keywords: autonomous robot , hill climbing , stair climbing , sequential composition, hexapod, self...X-RHex robot on a set of stairs with laser scanner, IMU, wireless repeater, and handle payloads. making them useful for both climbing hills and...reconciliation into that more powerful (but restrictive) framework. 1) The Stair Climbing Behavior: RHex robots have been climbing single-flight stairs

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.

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.

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.

Swimming Performance of Toy Robotic Fish

NASA Astrophysics Data System (ADS)

Petelina, Nina; Mendelson, Leah; Techet, Alexandra

2015-11-01

HEXBUG AquaBotsTM are a commercially available small robot fish that come in a variety of ``species''. These models have varying caudal fin shapes and randomly-varied modes of swimming including forward locomotion, diving, and turning. In this study, we assess the repeatability and performance of the HEXBUG swimming behaviors and discuss the use of these toys to develop experimental techniques and analysis methods to study live fish swimming. In order to determine whether these simple, affordable model fish can be a valid representation for live fish movement, two models, an angelfish and a shark, were studied using 2D Particle Image Velocimetry (PIV) and 3D Synthetic Aperture PIV. In a series of experiments, the robotic fish were either allowed to swim freely or towed in one direction at a constant speed. The resultant measurements of the caudal fin wake are compared to data from previous studies of a real fish and simplified flapping propulsors.

Effectiveness of a social robot, "Paro," in a VA long-term care setting.

PubMed

Lane, Geoffrey W; Noronha, Delilah; Rivera, Alexandra; Craig, Kathy; Yee, Christina; Mills, Brent; Villanueva, Eimee

2016-08-01

Interest in animal assisted interventions (AAI) has grown over the years, but acceptance of AAI by the clinical and research community has been hampered by safety, hygiene, and logistical concerns. Advances in the field of social robotics have provided a promising route to deliver AAI while avoiding these aforementioned obstacles. Although there has been promising initial research on social robotics in older adults, to date there has been no such research conducted with a veteran population. The present pilot study followed 23 veteran residents of a Veterans Affairs (VA) geropsychiatric long-term care facility over the span of approximately a year and a half. It was found that use of Paro, a social robot, resulted in increased observed positive affective and behavioral indicators, with concomitant decreases observed in negative affective and behavioral indicators. The authors concluded that Paro is likely an effective nonpharmacological approach for managing dementia-related mood and behavior problems with veterans in VA long term care facilities. They additionally observed that Paro is best presented to residents who are relatively calm and approachable, as opposed to actively exhibiting behavior or mood problems. Future research directions are discussed in light of both the positive results noted and the inherent limitations of our pilot study. (PsycINFO Database Record (c) 2016 APA, 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.

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.

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.

Vision servo of industrial robot: A review

NASA Astrophysics Data System (ADS)

Zhang, Yujin

2018-04-01

Robot technology has been implemented to various areas of production and life. With the continuous development of robot applications, requirements of the robot are also getting higher and higher. In order to get better perception of the robots, vision sensors have been widely used in industrial robots. In this paper, application directions of industrial robots are reviewed. The development, classification and application of robot vision servo technology are discussed, and the development prospect of industrial robot vision servo technology is proposed.

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.

Information-theoretic decomposition of embodied and situated systems.

PubMed

Da Rold, Federico

2018-07-01

The embodied and situated view of cognition stresses the importance of real-time and nonlinear bodily interaction with the environment for developing concepts and structuring knowledge. In this article, populations of robots controlled by an artificial neural network learn a wall-following task through artificial evolution. At the end of the evolutionary process, time series are recorded from perceptual and motor neurons of selected robots. Information-theoretic measures are estimated on pairings of variables to unveil nonlinear interactions that structure the agent-environment system. Specifically, the mutual information is utilized to quantify the degree of dependence and the transfer entropy to detect the direction of the information flow. Furthermore, the system is analyzed with the local form of such measures, thus capturing the underlying dynamics of information. Results show that different measures are interdependent and complementary in uncovering aspects of the robots' interaction with the environment, as well as characteristics of the functional neural structure. Therefore, the set of information-theoretic measures provides a decomposition of the system, capturing the intricacy of nonlinear relationships that characterize robots' behavior and neural dynamics. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Robot-assisted surgery: an emerging platform for human neuroscience research

PubMed Central

Jarc, Anthony M.; Nisky, Ilana

2015-01-01

Classic studies in human sensorimotor control use simplified tasks to uncover fundamental control strategies employed by the nervous system. Such simple tasks are critical for isolating specific features of motor, sensory, or cognitive processes, and for inferring causality between these features and observed behavioral changes. However, it remains unclear how these theories translate to complex sensorimotor tasks or to natural behaviors. Part of the difficulty in performing such experiments has been the lack of appropriate tools for measuring complex motor skills in real-world contexts. Robot-assisted surgery (RAS) provides an opportunity to overcome these challenges by enabling unobtrusive measurements of user behavior. In addition, a continuum of tasks with varying complexity—from simple tasks such as those in classic studies to highly complex tasks such as a surgical procedure—can be studied using RAS platforms. Finally, RAS includes a diverse participant population of inexperienced users all the way to expert surgeons. In this perspective, we illustrate how the characteristics of RAS systems make them compelling platforms to extend many theories in human neuroscience, as well as, to develop new theories altogether. PMID:26089785

Quantitative Laughter Detection, Measurement, and Classification-A Critical Survey.

PubMed

Cosentino, Sarah; Sessa, Salvatore; Takanishi, Atsuo

2016-01-01

The study of human nonverbal social behaviors has taken a more quantitative and computational approach in recent years due to the development of smart interfaces and virtual agents or robots able to interact socially. One of the most interesting nonverbal social behaviors, producing a characteristic vocal signal, is laughing. Laughter is produced in several different situations: in response to external physical, cognitive, or emotional stimuli; to negotiate social interactions; and also, pathologically, as a consequence of neural damage. For this reason, laughter has attracted researchers from many disciplines. A consequence of this multidisciplinarity is the absence of a holistic vision of this complex behavior: the methods of analysis and classification of laughter, as well as the terminology used, are heterogeneous; the findings sometimes contradictory and poorly documented. This survey aims at collecting and presenting objective measurement methods and results from a variety of different studies in different fields, to contribute to build a unified model and taxonomy of laughter. This could be successfully used for advances in several fields, from artificial intelligence and human-robot interaction to medicine and psychiatry.

A Self-Organizing Interaction and Synchronization Method between a Wearable Device and Mobile Robot.

PubMed

Kim, Min Su; Lee, Jae Geun; Kang, Soon Ju

2016-06-08

In the near future, we can expect to see robots naturally following or going ahead of humans, similar to pet behavior. We call this type of robots "Pet-Bot". To implement this function in a robot, in this paper we introduce a self-organizing interaction and synchronization method between wearable devices and Pet-Bots. First, the Pet-Bot opportunistically identifies its owner without any human intervention, which means that the robot self-identifies the owner's approach on its own. Second, Pet-Bot's activity is synchronized with the owner's behavior. Lastly, the robot frequently encounters uncertain situations (e.g., when the robot goes ahead of the owner but meets a situation where it cannot make a decision, or the owner wants to stop the Pet-Bot synchronization mode to relax). In this case, we have adopted a gesture recognition function that uses a 3-D accelerometer in the wearable device. In order to achieve the interaction and synchronization in real-time, we use two wireless communication protocols: 125 kHz low-frequency (LF) and 2.4 GHz Bluetooth low energy (BLE). We conducted experiments using a prototype Pet-Bot and wearable devices to verify their motion recognition of and synchronization with humans in real-time. The results showed a guaranteed level of accuracy of at least 94%. A trajectory test was also performed to demonstrate the robot's control performance when following or leading a human in real-time.

Brief biomechanical analysis on the walking of spinal cord injury patients with a lower limb exoskeleton robot.

PubMed

Jung, Jun-Young; Park, Hyunsub; Yang, Hyun-Dae; Chae, Mingi

2013-06-01

This paper presents a brief biomechanical analysis on the walking behavior of spinal cord injury (SCI) patients. It is known that SCI patients who have serious injuries to their spines cannot walk, and hence, several walking assistance lower limb exoskeleton robots have been proposed whose assistance abilities are shown to be well customized. However, these robots are not yet fully helpful to all SCI patients for several reasons. To overcome these problems, an exact analysis and evaluation of the restored walking function while the exoskeleton is worn is important. In this work, walking behavior of SCI patients wearing the rehabilitation of brain injuries (ROBIN) lower-limb walking assistant exoskeleton was analyzed in comparison to that of normal unassisted walking. The analysis method and results presented herein can be used by other researchers to improve their robots.

Autonomous Evolution of Dynamic Gaits with Two Quadruped Robots

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.; Takamura, Seichi; Yamamoto, Takashi; Fujita, Masahiro

2004-01-01

A challenging task that must be accomplished for every legged robot is creating the walking and running behaviors needed for it to move. In this paper we describe our system for autonomously evolving dynamic gaits on two of Sony's quadruped robots. Our evolutionary algorithm runs on board the robot and uses the robot's sensors to compute the quality of a gait without assistance from the experimenter. First we show the evolution of a pace and trot gait on the OPEN-R prototype robot. With the fastest gait, the robot moves at over 10/min/min., which is more than forty body-lengths/min. While these first gaits are somewhat sensitive to the robot and environment in which they are evolved, we then show the evolution of robust dynamic gaits, one of which is used on the ERS-110, the first consumer version of AIBO.

RoboJockey: Designing an Entertainment Experience with Robots.

PubMed

Yoshida, Shigeo; Shirokura, Takumi; Sugiura, Yuta; Sakamoto, Daisuke; Ono, Tetsuo; Inami, Masahiko; Igarashi, Takeo

2016-01-01

The RoboJockey entertainment system consists of a multitouch tabletop interface for multiuser collaboration. RoboJockey enables a user to choreograph a mobile robot or a humanoid robot by using a simple visual language. With RoboJockey, a user can coordinate the mobile robot's actions with a combination of back, forward, and rotating movements and coordinate the humanoid robot's actions with a combination of arm and leg movements. Every action is automatically performed to background music. RoboJockey was demonstrated to the public during two pilot studies, and the authors observed users' behavior. Here, they report the results of their observations and discuss the RoboJockey entertainment experience.

Using virtual robot-mediated play activities to assess cognitive skills.

PubMed

Encarnação, Pedro; Alvarez, Liliana; Rios, Adriana; Maya, Catarina; Adams, Kim; Cook, Al

2014-05-01

To evaluate the feasibility of using virtual robot-mediated play activities to assess cognitive skills. Children with and without disabilities utilized both a physical robot and a matching virtual robot to perform the same play activities. The activities were designed such that successfully performing them is an indication of understanding of the underlying cognitive skills. Participants' performance with both robots was similar when evaluated by the success rates in each of the activities. Session video analysis encompassing participants' behavioral, interaction and communication aspects revealed differences in sustained attention, visuospatial and temporal perception, and self-regulation, favoring the virtual robot. The study shows that virtual robots are a viable alternative to the use of physical robots for assessing children's cognitive skills, with the potential of overcoming limitations of physical robots such as cost, reliability and the need for on-site technical support. Virtual robots can provide a vehicle for children to demonstrate cognitive understanding. Virtual and physical robots can be used as augmentative manipulation tools allowing children with disabilities to actively participate in play, educational and therapeutic activities. Virtual robots have the potential of overcoming limitations of physical robots such as cost, reliability and the need for on-site technical support.

Learning Semantics of Gestural Instructions for Human-Robot Collaboration

PubMed Central

Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

2018-01-01

Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions. PMID:29615888

Learning Semantics of Gestural Instructions for Human-Robot Collaboration.

PubMed

Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

2018-01-01

Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions.

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).

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

A fluid-filled soft robot that exhibits spontaneous switching among versatile spatiotemporal oscillatory patterns inspired by the true slime mold.

PubMed

Umedachi, Takuya; Idei, Ryo; Ito, Kentaro; Ishiguro, Akio

2013-01-01

Behavioral diversity is an essential feature of living systems, enabling them to exhibit adaptive behavior in hostile and dynamically changing environments. However, traditional engineering approaches strive to avoid, or suppress, the behavioral diversity in artificial systems to achieve high performance in specific environments for given tasks. The goals of this research include understanding how living systems exhibit behavioral diversity and using these findings to build lifelike robots that exhibit truly adaptive behaviors. To this end, we have focused on one of the most primitive forms of intelligence concerning behavioral diversity, namely, a plasmodium of true slime mold. The plasmodium is a large amoeba-like unicellular organism that does not possess any nervous system or specialized organs. However, it exhibits versatile spatiotemporal oscillatory patterns and switches spontaneously between these. Inspired by the plasmodium, we built a mathematical model that exhibits versatile oscillatory patterns and spontaneously transitions between these patterns. This model demonstrates that, in contrast to coupled nonlinear oscillators with a well-designed complex diffusion network, physically interacting mechanosensory oscillators are capable of generating versatile oscillatory patterns without changing any parameters. Thus, the results are expected to shed new light on the design scheme for lifelike robots that exhibit amazingly versatile and adaptive behaviors.

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

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.

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.

Physiological and subjective evaluation of a human-robot object hand-over task.

PubMed

Dehais, Frédéric; Sisbot, Emrah Akin; Alami, Rachid; Causse, Mickaël

2011-11-01

In the context of task sharing between a robot companion and its human partners, the notions of safe and compliant hardware are not enough. It is necessary to guarantee ergonomic robot motions. Therefore, we have developed Human Aware Manipulation Planner (Sisbot et al., 2010), a motion planner specifically designed for human-robot object transfer by explicitly taking into account the legibility, the safety and the physical comfort of robot motions. The main objective of this research was to define precise subjective metrics to assess our planner when a human interacts with a robot in an object hand-over task. A second objective was to obtain quantitative data to evaluate the effect of this interaction. Given the short duration, the "relative ease" of the object hand-over task and its qualitative component, classical behavioral measures based on accuracy or reaction time were unsuitable to compare our gestures. In this perspective, we selected three measurements based on the galvanic skin conductance response, the deltoid muscle activity and the ocular activity. To test our assumptions and validate our planner, an experimental set-up involving Jido, a mobile manipulator robot, and a seated human was proposed. For the purpose of the experiment, we have defined three motions that combine different levels of legibility, safety and physical comfort values. After each robot gesture the participants were asked to rate them on a three dimensional subjective scale. It has appeared that the subjective data were in favor of our reference motion. Eventually the three motions elicited different physiological and ocular responses that could be used to partially discriminate them. Copyright © 2011 Elsevier Ltd and the Ergonomics Society. All rights reserved.

Regulation and Entrainment in Human-Robot Interaction

DTIC Science & Technology

2000-01-01

applications for domestic, health care related, or entertainment based robots motivate the development of robots that can socially interact with, learn...picture shows WE-3RII, an expressive face robot developed at Waseda University. The middle right picture shows Robita, an upper-torso robot also... developed at Waseda University to track speaking turns. The far right picture shows our expressive robot, Kismet, developed at MIT. The two leftmost photos

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.

Why Are There Developmental Stages in Language Learning? A Developmental Robotics Model of Language Development.

PubMed

Morse, Anthony F; Cangelosi, Angelo

2017-02-01

Most theories of learning would predict a gradual acquisition and refinement of skills as learning progresses, and while some highlight exponential growth, this fails to explain why natural cognitive development typically progresses in stages. Models that do span multiple developmental stages typically have parameters to "switch" between stages. We argue that by taking an embodied view, the interaction between learning mechanisms, the resulting behavior of the agent, and the opportunities for learning that the environment provides can account for the stage-wise development of cognitive abilities. We summarize work relevant to this hypothesis and suggest two simple mechanisms that account for some developmental transitions: neural readiness focuses on changes in the neural substrate resulting from ongoing learning, and perceptual readiness focuses on the perceptual requirements for learning new tasks. Previous work has demonstrated these mechanisms in replications of a wide variety of infant language experiments, spanning multiple developmental stages. Here we piece this work together as a single model of ongoing learning with no parameter changes at all. The model, an instance of the Epigenetic Robotics Architecture (Morse et al 2010) embodied on the iCub humanoid robot, exhibits ongoing multi-stage development while learning pre-linguistic and then basic language skills. Copyright © 2016 Cognitive Science Society, Inc.

Understanding Engagement in Dementia Through Behavior. The Ethographic and Laban-Inspired Coding System of Engagement (ELICSE) and the Evidence-Based Model of Engagement-Related Behavior (EMODEB)

PubMed Central

Perugia, Giulia; van Berkel, Roos; Díaz-Boladeras, Marta; Català-Mallofré, Andreu; Rauterberg, Matthias; Barakova, Emilia

2018-01-01

Engagement in activities is of crucial importance for people with dementia. State of the art assessment techniques rely exclusively on behavior observation to measure engagement in dementia. These techniques are either too general to grasp how engagement is naturally expressed through behavior or too complex to be traced back to an overall engagement state. We carried out a longitudinal study to develop a coding system of engagement-related behavior that could tackle these issues and to create an evidence-based model of engagement to make meaning of such a coding system. Fourteen elderlies with mild to moderate dementia took part in the study. They were involved in two activities: a game-based cognitive stimulation and a robot-based free play. The coding system was developed with a mixed approach: ethographic and Laban-inspired. First, we developed two ethograms to describe the behavior of participants in the two activities in detail. Then, we used Laban Movement Analysis (LMA) to identify a common structure to the behaviors in the two ethograms and unify them in a unique coding system. The inter-rater reliability (IRR) of the coding system proved to be excellent for cognitive games (kappa = 0.78) and very good for robot play (kappa = 0.74). From the scoring of the videos, we developed an evidence-based model of engagement. This was based on the most frequent patterns of body part organization (i.e., the way body parts are connected in movement) observed during activities. Each pattern was given a meaning in terms of engagement by making reference to the literature. The model was tested using structural equation modeling (SEM). It achieved an excellent goodness of fit and all the hypothesized relations between variables were significant. We called the coding system that we developed the Ethographic and Laban-Inspired Coding System of Engagement (ELICSE) and the model the Evidence-based Model of Engagement-related Behavior (EMODEB). To the best of our knowledge, the ELICSE and the EMODEB constitute the first formalization of engagement-related behavior for dementia that describes how behavior unfolds over time and what it means in terms of engagement. PMID:29881360

Understanding Engagement in Dementia Through Behavior. The Ethographic and Laban-Inspired Coding System of Engagement (ELICSE) and the Evidence-Based Model of Engagement-Related Behavior (EMODEB).

PubMed

Perugia, Giulia; van Berkel, Roos; Díaz-Boladeras, Marta; Català-Mallofré, Andreu; Rauterberg, Matthias; Barakova, Emilia

2018-01-01

Engagement in activities is of crucial importance for people with dementia. State of the art assessment techniques rely exclusively on behavior observation to measure engagement in dementia. These techniques are either too general to grasp how engagement is naturally expressed through behavior or too complex to be traced back to an overall engagement state. We carried out a longitudinal study to develop a coding system of engagement-related behavior that could tackle these issues and to create an evidence-based model of engagement to make meaning of such a coding system. Fourteen elderlies with mild to moderate dementia took part in the study. They were involved in two activities: a game-based cognitive stimulation and a robot-based free play. The coding system was developed with a mixed approach: ethographic and Laban-inspired. First, we developed two ethograms to describe the behavior of participants in the two activities in detail. Then, we used Laban Movement Analysis (LMA) to identify a common structure to the behaviors in the two ethograms and unify them in a unique coding system. The inter-rater reliability (IRR) of the coding system proved to be excellent for cognitive games (kappa = 0.78) and very good for robot play (kappa = 0.74). From the scoring of the videos, we developed an evidence-based model of engagement. This was based on the most frequent patterns of body part organization (i.e., the way body parts are connected in movement) observed during activities. Each pattern was given a meaning in terms of engagement by making reference to the literature. The model was tested using structural equation modeling (SEM). It achieved an excellent goodness of fit and all the hypothesized relations between variables were significant. We called the coding system that we developed the Ethographic and Laban-Inspired Coding System of Engagement (ELICSE) and the model the Evidence-based Model of Engagement-related Behavior (EMODEB). To the best of our knowledge, the ELICSE and the EMODEB constitute the first formalization of engagement-related behavior for dementia that describes how behavior unfolds over time and what it means in terms of engagement.

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.

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.

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.

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.

Concentric Tube Robots as Steerable Needles: Achieving Follow-the-Leader Deployment

PubMed Central

Gilbert, Hunter B.; Neimat, Joseph; Webster, Robert J.

2015-01-01

Concentric tube robots can enable new clinical interventions if they are able to pass through soft tissue, deploy along desired paths through open cavities, or travel along winding lumens. These behaviors require the robot to deploy in such a way that the curved shape of its shaft remains unchanged as the tip progresses forward (i.e., “follow-the-leader” deployment). Follow-the-leader deployment is challenging for concentric tube robots due to elastic (and particularly torsional) coupling between the tubes that form the robot. However, as we show in this paper, follow-the-leader deployment is possible, provided that tube precurvatures and deployment sequences are appropriately selected. We begin by defining follow-the-leader deployment and providing conditions that must be satisfied for a concentric tube robot to achieve it. We then examine several useful special cases of follow-the-leader deployment, showing that both circular and helical precurvatures can be employed, and provide an experimental illustration of the helical case. We also explore approximate follow-the-leader behavior and provide a metric for the similarity of a general deployment to a follow-the-leader deployment. Finally, we consider access to the hippocampus in the brain to treat epilepsy, as a motivating clinical example for follow-the-leader deployment. PMID:26622208

Concentric Tube Robots as Steerable Needles: Achieving Follow-the-Leader Deployment.

PubMed

Gilbert, Hunter B; Neimat, Joseph; Webster, Robert J

2015-04-01

Concentric tube robots can enable new clinical interventions if they are able to pass through soft tissue, deploy along desired paths through open cavities, or travel along winding lumens. These behaviors require the robot to deploy in such a way that the curved shape of its shaft remains unchanged as the tip progresses forward (i.e., "follow-the-leader" deployment). Follow-the-leader deployment is challenging for concentric tube robots due to elastic (and particularly torsional) coupling between the tubes that form the robot. However, as we show in this paper, follow-the-leader deployment is possible, provided that tube precurvatures and deployment sequences are appropriately selected. We begin by defining follow-the-leader deployment and providing conditions that must be satisfied for a concentric tube robot to achieve it. We then examine several useful special cases of follow-the-leader deployment, showing that both circular and helical precurvatures can be employed, and provide an experimental illustration of the helical case. We also explore approximate follow-the-leader behavior and provide a metric for the similarity of a general deployment to a follow-the-leader deployment. Finally, we consider access to the hippocampus in the brain to treat epilepsy, as a motivating clinical example for follow-the-leader deployment.

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.

Cognitive Offloading Does Not Prevent but Rather Promotes Cognitive Development

PubMed Central

Nolfi, Stefano

2016-01-01

We investigate the relation between the development of reactive and cognitive capabilities. In particular we investigate whether the development of reactive capabilities prevents or promotes the development of cognitive capabilities in a population of evolving robots that have to solve a time-delay navigation task in a double T-Maze environment. Analysis of the experiments reveals that the evolving robots always select reactive strategies that rely on cognitive offloading, i.e., the possibility of acting so as to encode onto the relation between the agent and the environment the states that can be used later to regulate the agent’s behavior. The discovery of these strategies does not prevent, but rather facilitates, the development of cognitive strategies that also rely on the extraction and use of internal states. Detailed analysis of the results obtained in the different experimental conditions provides evidence that helps clarify why, contrary to expectations, reactive and cognitive strategies tend to have synergetic relationships. PMID:27505162

Prototyping and Simulation of Robot Group Intelligence using Kohonen Networks.

PubMed

Wang, Zhijun; Mirdamadi, Reza; Wang, Qing

2016-01-01

Intelligent agents such as robots can form ad hoc networks and replace human being in many dangerous scenarios such as a complicated disaster relief site. This project prototypes and builds a computer simulator to simulate robot kinetics, unsupervised learning using Kohonen networks, as well as group intelligence when an ad hoc network is formed. Each robot is modeled using an object with a simple set of attributes and methods that define its internal states and possible actions it may take under certain circumstances. As the result, simple, reliable, and affordable robots can be deployed to form the network. The simulator simulates a group of robots as an unsupervised learning unit and tests the learning results under scenarios with different complexities. The simulation results show that a group of robots could demonstrate highly collaborative behavior on a complex terrain. This study could potentially provide a software simulation platform for testing individual and group capability of robots before the design process and manufacturing of robots. Therefore, results of the project have the potential to reduce the cost and improve the efficiency of robot design and building.

Prototyping and Simulation of Robot Group Intelligence using Kohonen Networks

PubMed Central

Wang, Zhijun; Mirdamadi, Reza; Wang, Qing

2016-01-01

Intelligent agents such as robots can form ad hoc networks and replace human being in many dangerous scenarios such as a complicated disaster relief site. This project prototypes and builds a computer simulator to simulate robot kinetics, unsupervised learning using Kohonen networks, as well as group intelligence when an ad hoc network is formed. Each robot is modeled using an object with a simple set of attributes and methods that define its internal states and possible actions it may take under certain circumstances. As the result, simple, reliable, and affordable robots can be deployed to form the network. The simulator simulates a group of robots as an unsupervised learning unit and tests the learning results under scenarios with different complexities. The simulation results show that a group of robots could demonstrate highly collaborative behavior on a complex terrain. This study could potentially provide a software simulation platform for testing individual and group capability of robots before the design process and manufacturing of robots. Therefore, results of the project have the potential to reduce the cost and improve the efficiency of robot design and building. PMID:28540284

Towards a sustainable modular robot system for planetary exploration

NASA Astrophysics Data System (ADS)

Hossain, S. G. M.

This thesis investigates multiple perspectives of developing an unmanned robotic system suited for planetary terrains. In this case, the unmanned system consists of unit-modular robots. This type of robot has potential to be developed and maintained as a sustainable multi-robot system while located far from direct human intervention. Some characteristics that make this possible are: the cooperation, communication and connectivity among the robot modules, flexibility of individual robot modules, capability of self-healing in the case of a failed module and the ability to generate multiple gaits by means of reconfiguration. To demonstrate the effects of high flexibility of an individual robot module, multiple modules of a four-degree-of-freedom unit-modular robot were developed. The robot was equipped with a novel connector mechanism that made self-healing possible. Also, design strategies included the use of series elastic actuators for better robot-terrain interaction. In addition, various locomotion gaits were generated and explored using the robot modules, which is essential for a modular robot system to achieve robustness and thus successfully navigate and function in a planetary environment. To investigate multi-robot task completion, a biomimetic cooperative load transportation algorithm was developed and simulated. Also, a liquid motion-inspired theory was developed consisting of a large number of robot modules. This can be used to traverse obstacles that inevitably occur in maneuvering over rough terrains such as in a planetary exploration. Keywords: Modular robot, cooperative robots, biomimetics, planetary exploration, sustainability.

Eyeblink Synchrony in Multimodal Human-Android Interaction.

PubMed

Tatsukawa, Kyohei; Nakano, Tamami; Ishiguro, Hiroshi; Yoshikawa, Yuichiro

2016-12-23

As the result of recent progress in technology of communication robot, robots are becoming an important social partner for humans. Behavioral synchrony is understood as an important factor in establishing good human-robot relationships. In this study, we hypothesized that biasing a human's attitude toward a robot changes the degree of synchrony between human and robot. We first examined whether eyeblinks were synchronized between a human and an android in face-to-face interaction and found that human listeners' eyeblinks were entrained to android speakers' eyeblinks. This eyeblink synchrony disappeared when the android speaker spoke while looking away from the human listeners but was enhanced when the human participants listened to the speaking android while touching the android's hand. These results suggest that eyeblink synchrony reflects a qualitative state in human-robot interactions.

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.

Interactive autonomy and robotic skills

NASA Technical Reports Server (NTRS)

Kellner, A.; Maediger, B.

1994-01-01

Current concepts of robot-supported operations for space laboratories (payload servicing, inspection, repair, and ORU exchange) are mainly based on the concept of 'interactive autonomy' which implies autonomous behavior of the robot according to predefined timelines, predefined sequences of elementary robot operations and within predefined world models supplying geometrical and other information for parameter instantiation on the one hand, and the ability to override and change the predefined course of activities by human intervention on the other hand. Although in principle a very powerful and useful concept, in practice the confinement of the robot to the abstract world models and predefined activities appears to reduce the robot's stability within real world uncertainties and its applicability to non-predefined parts of the world, calling for frequent corrective interaction by the operator, which in itself may be tedious and time-consuming. Methods are presented to improve this situation by incorporating 'robotic skills' into the concept of interactive autonomy.

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.

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.

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.

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.

A Self-Organizing Interaction and Synchronization Method between a Wearable Device and Mobile Robot

PubMed Central

Kim, Min Su; Lee, Jae Geun; Kang, Soon Ju

2016-01-01

In the near future, we can expect to see robots naturally following or going ahead of humans, similar to pet behavior. We call this type of robots “Pet-Bot”. To implement this function in a robot, in this paper we introduce a self-organizing interaction and synchronization method between wearable devices and Pet-Bots. First, the Pet-Bot opportunistically identifies its owner without any human intervention, which means that the robot self-identifies the owner’s approach on its own. Second, Pet-Bot’s activity is synchronized with the owner’s behavior. Lastly, the robot frequently encounters uncertain situations (e.g., when the robot goes ahead of the owner but meets a situation where it cannot make a decision, or the owner wants to stop the Pet-Bot synchronization mode to relax). In this case, we have adopted a gesture recognition function that uses a 3-D accelerometer in the wearable device. In order to achieve the interaction and synchronization in real-time, we use two wireless communication protocols: 125 kHz low-frequency (LF) and 2.4 GHz Bluetooth low energy (BLE). We conducted experiments using a prototype Pet-Bot and wearable devices to verify their motion recognition of and synchronization with humans in real-time. The results showed a guaranteed level of accuracy of at least 94%. A trajectory test was also performed to demonstrate the robot’s control performance when following or leading a human in real-time. PMID:27338384

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

Stability Study of Anthropomorphic Robot Antares under External Load Action

NASA Astrophysics Data System (ADS)

Kodyakov, A. S.; Pavlyuk, N. A.; Budkov, V. Yu; Prakapovich, R. A.

2017-01-01

The paper presents the study of the behavior of the major structural elements of the lower limbs of anthropomorphic robot Antares under the influence of different types of loads (torsion, fracture). We have determined the required values for actuators torques for motion of the robot in space. The maximum values of torques are 5 Nm and 5.2 Nm respectively, and are able to withstand the upper and lower leg structures.

Kinematic Optimization of Robot Trajectories for Thermal Spray Coating Application

NASA Astrophysics Data System (ADS)

Deng, Sihao; Liang, Hong; Cai, Zhenhua; Liao, Hanlin; Montavon, Ghislain

2014-12-01

Industrial robots are widely used in the field of thermal spray nowadays. Due to their characteristics of high-accuracy and programmable flexibility, spraying on complex geometrical workpieces can be realized in the equipped spray room. However, in some cases, the robots cannot guarantee the process parameters defined by the robot movement, such as the scanning trajectory, spray angle, relative speed between the torch and the substrate, etc., which have distinct influences on heat and mass transfer during the generation of any thermally sprayed coatings. In this study, an investigation on the robot kinematics was proposed to find the rules of motion in a common case. The results showed that the motion behavior of each axis of robot permits to identify the motion problems in the trajectory. This approach allows to optimize the robot trajectory generation in a limited working envelop. It also minimizes the influence of robot performance to achieve a more constant relative scanning speed which is represented as a key parameter in thermal spraying.

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.

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.

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.

Supervised Remote Robot with Guided Autonomy and Teleoperation (SURROGATE): A Framework for Whole-Body Manipulation

NASA Technical Reports Server (NTRS)

Hebert, Paul; Ma, Jeremy; Borders, James; Aydemir, Alper; Bajracharya, Max; Hudson, Nicolas; Shankar, Krishna; Karumanchi, Sisir; Douillard, Bertrand; Burdick, Joel

2015-01-01

The use of the cognitive capabilties of humans to help guide the autonomy of robotics platforms in what is typically called "supervised-autonomy" is becoming more commonplace in robotics research. The work discussed in this paper presents an approach to a human-in-the-loop mode of robot operation that integrates high level human cognition and commanding with the intelligence and processing power of autonomous systems. Our framework for a "Supervised Remote Robot with Guided Autonomy and Teleoperation" (SURROGATE) is demonstrated on a robotic platform consisting of a pan-tilt perception head, two 7-DOF arms connected by a single 7-DOF torso, mounted on a tracked-wheel base. We present an architecture that allows high-level supervisory commands and intents to be specified by a user that are then interpreted by the robotic system to perform whole body manipulation tasks autonomously. We use a concept of "behaviors" to chain together sequences of "actions" for the robot to perform which is then executed real time.

Do infants perceive the social robot Keepon as a communicative partner?

PubMed

Peca, Andreea; Simut, Ramona; Cao, Hoang-Long; Vanderborght, Bram

2016-02-01

This study investigates if infants perceive an unfamiliar agent, such as the robot Keepon, as a social agent after observing an interaction between the robot and a human adult. 23 infants, aged 9-17 month, were exposed, in a first phase, to either a contingent interaction between the active robot and an active human adult, or to an interaction between an active human adult and the non-active robot, followed by a second phase, in which infants were offered the opportunity to initiate a turn-taking interaction with Keepon. The measured variables were: (1) the number of social initiations the infant directed toward the robot, and (2) the number of anticipatory orientations of attention to the agent that follows in the conversation. The results indicate a significant higher level of initiations in the interactive robot condition compared to the non-active robot condition, while the difference between the frequencies of anticipations of turn-taking behaviors was not significant. Copyright © 2015 Elsevier Inc. All rights reserved.

Development of inspection robots for bridge cables.

PubMed

Yun, Hae-Bum; Kim, Se-Hoon; Wu, Liuliu; Lee, Jong-Jae

2013-01-01

This paper presents the bridge cable inspection robot developed in Korea. Two types of the cable inspection robots were developed for cable-suspension bridges and cable-stayed bridge. The design of the robot system and performance of the NDT techniques associated with the cable inspection robot are discussed. A review on recent advances in emerging robot-based inspection technologies for bridge cables and current bridge cable inspection methods is also presented.

Robotics in urologic surgery: an evolving new technology.

PubMed

Atug, Fatih; Castle, Erik P; Woods, Michael; Davis, Rodney; Thomas, Raju

2006-07-01

Rapid technological developments in the past two decades have produced new inventions such as robots and incorporated them into our daily lives. Today, robots perform vital functions in homes, outer space, hospitals and on military instillations. The development of robotic surgery has given hospitals and health care providers a valuable tool that is making a profound impact on highly technical surgical procedures. The field of urology is one area of medicine that has adopted and incorporated robotic surgery into its armamentarium. Innovative robotic urologic surgical applications and techniques are being developed and reported everyday. Increased utilization and development will ultimately fuel the discovery of newer applications of robotic systems in urologic surgery. Herein we provide an overview of the history, development, and applications of robotics in surgery with a focus on urologic surgery.

Dynamic whole-body robotic manipulation

NASA Astrophysics Data System (ADS)

Abe, Yeuhi; Stephens, Benjamin; Murphy, Michael P.; Rizzi, Alfred A.

2013-05-01

The creation of dynamic manipulation behaviors for high degree of freedom, mobile robots will allow them to accomplish increasingly difficult tasks in the field. We are investigating how the coordinated use of the body, legs, and integrated manipulator, on a mobile robot, can improve the strength, velocity, and workspace when handling heavy objects. We envision that such a capability would aid in a search and rescue scenario when clearing obstacles from a path or searching a rubble pile quickly. Manipulating heavy objects is especially challenging because the dynamic forces are high and a legged system must coordinate all its degrees of freedom to accomplish tasks while maintaining balance. To accomplish these types of manipulation tasks, we use trajectory optimization techniques to generate feasible open-loop behaviors for our 28 dof quadruped robot (BigDog) by planning trajectories in a 13 dimensional space. We apply the Covariance Matrix Adaptation (CMA) algorithm to solve for trajectories that optimize task performance while also obeying important constraints such as torque and velocity limits, kinematic limits, and center of pressure location. These open-loop behaviors are then used to generate desired feed-forward body forces and foot step locations, which enable tracking on the robot. Some hardware results for cinderblock throwing are demonstrated on the BigDog quadruped platform augmented with a human-arm-like manipulator. The results are analogous to how a human athlete maximizes distance in the discus event by performing a precise sequence of choreographed steps.

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.

Spectrally queued feature selection for robotic visual odometery

NASA Astrophysics Data System (ADS)

Pirozzo, David M.; Frederick, Philip A.; Hunt, Shawn; Theisen, Bernard; Del Rose, Mike

2011-01-01

Over the last two decades, research in Unmanned Vehicles (UV) has rapidly progressed and become more influenced by the field of biological sciences. Researchers have been investigating mechanical aspects of varying species to improve UV air and ground intrinsic mobility, they have been exploring the computational aspects of the brain for the development of pattern recognition and decision algorithms and they have been exploring perception capabilities of numerous animals and insects. This paper describes a 3 month exploratory applied research effort performed at the US ARMY Research, Development and Engineering Command's (RDECOM) Tank Automotive Research, Development and Engineering Center (TARDEC) in the area of biologically inspired spectrally augmented feature selection for robotic visual odometry. The motivation for this applied research was to develop a feasibility analysis on multi-spectrally queued feature selection, with improved temporal stability, for the purposes of visual odometry. The intended application is future semi-autonomous Unmanned Ground Vehicle (UGV) control as the richness of data sets required to enable human like behavior in these systems has yet to be defined.

Development of Inspection Robots for Bridge Cables

PubMed Central

Kim, Se-Hoon; Lee, Jong-Jae

2013-01-01

This paper presents the bridge cable inspection robot developed in Korea. Two types of the cable inspection robots were developed for cable-suspension bridges and cable-stayed bridge. The design of the robot system and performance of the NDT techniques associated with the cable inspection robot are discussed. A review on recent advances in emerging robot-based inspection technologies for bridge cables and current bridge cable inspection methods is also presented. PMID:24459453

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

Eyeblink Synchrony in Multimodal Human-Android Interaction

PubMed Central

Tatsukawa, Kyohei; Nakano, Tamami; Ishiguro, Hiroshi; Yoshikawa, Yuichiro

2016-01-01

As the result of recent progress in technology of communication robot, robots are becoming an important social partner for humans. Behavioral synchrony is understood as an important factor in establishing good human-robot relationships. In this study, we hypothesized that biasing a human’s attitude toward a robot changes the degree of synchrony between human and robot. We first examined whether eyeblinks were synchronized between a human and an android in face-to-face interaction and found that human listeners’ eyeblinks were entrained to android speakers’ eyeblinks. This eyeblink synchrony disappeared when the android speaker spoke while looking away from the human listeners but was enhanced when the human participants listened to the speaking android while touching the android’s hand. These results suggest that eyeblink synchrony reflects a qualitative state in human-robot interactions. PMID:28009014

Opportunistic Behavior in Motivated Learning Agents.

PubMed

Graham, James; Starzyk, Janusz A; Jachyra, Daniel

2015-08-01

This paper focuses on the novel motivated learning (ML) scheme and opportunistic behavior of an intelligent agent. It extends previously developed ML to opportunistic behavior in a multitask situation. Our paper describes the virtual world implementation of autonomous opportunistic agents learning in a dynamically changing environment, creating abstract goals, and taking advantage of arising opportunities to improve their performance. An opportunistic agent achieves better results than an agent based on ML only. It does so by minimizing the average value of all need signals rather than a dominating need. This paper applies to the design of autonomous embodied systems (robots) learning in real-time how to operate in a complex environment.

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 Role of Language and Gender in "The Transformers": An Analysis of Messages in Cartoons for Children.

ERIC Educational Resources Information Center

Aitken, Joan E.

New technologically-oriented cartoons have been developed in the 1980s, and they may influence the attitudes and behaviors of their viewing audiences, who are comprised primarily of male children. A study analyzed "The Transformers" television program (a new robotic cartoon consisting of a mixture of violence, technology, space travel,…

Bio-inspired flexible joints with passive feathering for robotic fish pectoral fins.

PubMed

Behbahani, Sanaz Bazaz; Tan, Xiaobo

2016-05-04

In this paper a novel flexible joint is proposed for robotic fish pectoral fins, which enables a swimming behavior emulating the fin motions of many aquatic animals. In particular, the pectoral fin operates primarily in the rowing mode, while undergoing passive feathering during the recovery stroke to reduce hydrodynamic drag on the fin. The latter enables effective locomotion even with symmetric base actuation during power and recovery strokes. A dynamic model is developed to facilitate the understanding and design of the joint, where blade element theory is used to calculate the hydrodynamic forces on the pectoral fins, and the joint is modeled as a paired torsion spring and damper. Experimental results on a robotic fish prototype are presented to illustrate the effectiveness of the joint mechanism, validate the proposed model, and indicate the utility of the proposed model for the optimal design of joint depth and stiffness in achieving the trade-off between swimming speed and mechanical efficiency.

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

Land, sea, and air unmanned systems research and development at SPAWAR Systems Center Pacific

NASA Astrophysics Data System (ADS)

Nguyen, Hoa G.; Laird, Robin; Kogut, Greg; Andrews, John; Fletcher, Barbara; Webber, Todd; Arrieta, Rich; Everett, H. R.

2009-05-01

The Space and Naval Warfare (SPAWAR) Systems Center Pacific (SSC Pacific) has a long and extensive history in unmanned systems research and development, starting with undersea applications in the 1960s and expanding into ground and air systems in the 1980s. In the ground domain, we are addressing force-protection scenarios using large unmanned ground vehicles (UGVs) and fixed sensors, and simultaneously pursuing tactical and explosive ordnance disposal (EOD) operations with small man-portable robots. Technology thrusts include improving robotic intelligence and functionality, autonomous navigation and world modeling in urban environments, extended operational range of small teleoperated UGVs, enhanced human-robot interaction, and incorporation of remotely operated weapon systems. On the sea surface, we are pushing the envelope on dynamic obstacle avoidance while conforming to established nautical rules-of-the-road. In the air, we are addressing cooperative behaviors between UGVs and small vertical-takeoff- and-landing unmanned air vehicles (UAVs). Underwater applications involve very shallow water mine countermeasures, ship hull inspection, oceanographic data collection, and deep ocean access. Specific technology thrusts include fiber-optic communications, adaptive mission controllers, advanced navigation techniques, and concepts of operations (CONOPs) development. This paper provides a review of recent accomplishments and current status of a number of projects in these areas.

Robotic Anesthesia – A Vision for the Future of Anesthesia

PubMed Central

Hemmerling, Thomas M; Taddei, Riccardo; Wehbe, Mohamad; Morse, Joshua; Cyr, Shantale; Zaouter, Cedrick

2011-01-01

Summary This narrative review describes a rationale for robotic anesthesia. It offers a first classification of robotic anesthesia by separating it into pharmacological robots and robots for aiding or replacing manual gestures. Developments in closed loop anesthesia are outlined. First attempts to perform manual tasks using robots are described. A critical analysis of the delayed development and introduction of robots in anesthesia is delivered. PMID:23905028

Stability control for high speed tracked unmanned vehicles

NASA Astrophysics Data System (ADS)

Pape, Olivier; Morillon, Joel G.; Houbloup, Philippe; Leveque, Stephane; Fialaire, Cecile; Gauthier, Thierry; Ropars, Patrice

2005-05-01

The French Military Robotic Study Program (introduced in Aerosense 2003), sponsored by the French Defense Procurement Agency and managed by Thales as the prime contractor, focuses on about 15 robotic themes which can provide an immediate "operational add-on value". The paper details the "automatic speed adjustment" behavior (named SYR4), developed by Giat Industries Company, which main goal is to secure the teleoperated mobility of high speed tracked vehicles on rough grounds; more precisely, the validated low level behavior continuously adjusts the vehicle speed taking into account the teleperator wish AND the maximum speed that the vehicle can manage safely according to the commanded radius of curvature. The algorithm is based on a realistic physical model of the ground-tracks relation, taking into account many vehicle and ground parameters (such as ground adherence and dynamic specificities of tracked vehicles). It also deals with the teleoperator-machine interface, providing a balanced strategy between both extreme behaviors: a) maximum speed reduction before initiating the commanded curve; b) executing the minimum possible radius without decreasing the commanded speed. The paper presents the results got from the military acceptance tests performed on tracked SYRANO vehicle (French Operational Demonstrator).

Cyber Moat: Adaptive Virtualized Network Framework for Deception and Disinformation

DTIC Science & Technology

2016-12-12

As one type of bots, web crawlers have been leveraged by search engines (e.g., Googlebot by Google) to popularize websites through website indexing...However, the number of malicious bots is increasing too. To regulate the behavior of crawlers, most websites include a file called "robots.txt" that...However, "robots.txt" only provides a guideline, and almost all malicious robots ignore it. Moreover, since this file is publicly available, malicious

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.

Service innovation through social robot engagement to improve dementia care quality.

PubMed

Chu, Mei-Tai; Khosla, Rajiv; Khaksar, Seyed Mohammad Sadegh; Nguyen, Khanh

2017-01-01

Assistive technologies, such as robots, have proven to be useful in a social context and to improve the quality of life for people with dementia (PwD). This study aims to show how the engagement between two social robots and PwD in Australian residential care facilities can improve care quality. An observational method is adopted in the research methodology to discover behavioural patterns during interactions between the robots and PwD. This observational study has undertaken to explore the improvement arising from: (1) approaching social baby-face robots (AR), (2) experiencing pleasure engaging with the robots (P), (3) interacting with the robots (IR), and (4) interacting with others (IO). The findings show that social robots can improve diversion therapy service value to PwD through sensory enrichment, positive social engagement, and entertainment. More than 11,635 behavioral reactions, such as facial expressions and gestures, from 139 PwD over 5 years were coded, in order to identify the engagement effectiveness between PwD and two social robots named Sophie and Jack. The results suggest that these innovative social robots can improve the quality of care for people suffering from dementia.

Artificial intelligence in medicine.

PubMed

Hamet, Pavel; Tremblay, Johanne

2017-04-01

Artificial Intelligence (AI) is a general term that implies the use of a computer to model intelligent behavior with minimal human intervention. AI is generally accepted as having started with the invention of robots. The term derives from the Czech word robota, meaning biosynthetic machines used as forced labor. In this field, Leonardo Da Vinci's lasting heritage is today's burgeoning use of robotic-assisted surgery, named after him, for complex urologic and gynecologic procedures. Da Vinci's sketchbooks of robots helped set the stage for this innovation. AI, described as the science and engineering of making intelligent machines, was officially born in 1956. The term is applicable to a broad range of items in medicine such as robotics, medical diagnosis, medical statistics, and human biology-up to and including today's "omics". AI in medicine, which is the focus of this review, has two main branches: virtual and physical. The virtual branch includes informatics approaches from deep learning information management to control of health management systems, including electronic health records, and active guidance of physicians in their treatment decisions. The physical branch is best represented by robots used to assist the elderly patient or the attending surgeon. Also embodied in this branch are targeted nanorobots, a unique new drug delivery system. The societal and ethical complexities of these applications require further reflection, proof of their medical utility, economic value, and development of interdisciplinary strategies for their wider application. Copyright © 2017. Published by Elsevier Inc.

Overview and Categorization of Robots Supporting Independent Living of Elderly People: What Activities Do They Support and How Far Have They Developed.

PubMed

Bedaf, Sandra; Gelderblom, Gert Jan; De Witte, Luc

2015-01-01

Over the past decades, many robots for the elderly have been developed, supporting different activities of elderly people. A systematic review in four scientific literature databases and a search in article references and European projects was performed in order to create an overview of robots supporting independent living of elderly people. The robots found were categorized based on their development stage, the activity domains they claim to support, and the type of support provided (i.e., physical, non-physical, and/or non-specified). In total, 107 robots for the elderly were identified. Six robots were still in a concept phase, 95 in a development phase, and six of these robots were commercially available. These robots claimed to provide support related to four activity domains: mobility, self-care, interpersonal interaction & relationships, and other activities. Of the many robots developed, only a small percentage is commercially available. Technical ambitions seem to be guiding robot development. To prolong independent living, the step towards physical support is inevitable and needs to be taken. However, it will be a long time before a robot will be capable of supporting multiple activities in a physical manner in the home of an elderly person in order to enhance their independent living.

New technologies in robotic surgery: the Korean experience.

PubMed

Tuliao, Patrick H; Kim, Sang W; Rha, Koon H

2014-01-01

The development of the robotic systems has made surgery an increasingly technology-driven field. Since the introduction of the first robotic platform in 2005, surgical practice in South Korea has also been caught up in the global robotic revolution. Consequently, a market focused on improving the robotic systems was created and Korea has emerged as one of its frontrunners. This article reviews the Korean experience in developing various robotic technologies and then Korea's most recent contributions to the development of new technologies in robotic surgery. The goal of new technologies in the field of robotic surgery has been to improve on the current platforms by eliminating their disadvantages. The pressing goal is to develop a platform that is less bulky, more ergonomic, and capable of providing force feedback to the surgeon. In Korea, the Lapabot and two new robotic systems for single-port laparoscopic surgery are the most recent advances that have been reported. Robotic surgery is rapidly evolving and Korea has stayed in the forefront of its development. These new advancements in technology will eventually produce better robotic platforms that will greatly improve the manner in which surgical care is delivered.

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.

ROBOSIM: An intelligent simulator for robotic systems

NASA Technical Reports Server (NTRS)

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

1993-01-01

The purpose of this paper is to present an update of an intelligent robotics simulator package, ROBOSIM, first introduced at Technology 2000 in 1990. ROBOSIM is used for three-dimensional geometrical modeling of robot manipulators and various objects in their workspace, and for the simulation of action sequences performed by the manipulators. Geometric modeling of robot manipulators has an expanding area of interest because it can aid the design and usage of robots in a number of ways, including: design and testing of manipulators, robot action planning, on-line control of robot manipulators, telerobotic user interface, and training and education. NASA developed ROBOSIM between 1985-88 to facilitate the development of robotics, and used the package to develop robotics for welding, coating, and space operations. ROBOSIM has been further developed for academic use by its co-developer Vanderbilt University, and has been in both classroom and laboratory environments for teaching complex robotic concepts. Plans are being formulated to make ROBOSIM available to all U.S. engineering/engineering technology schools (over three hundred total with an estimated 10,000+ users per year).

TARDEC's Intelligent Ground Systems overview

NASA Astrophysics Data System (ADS)

Jaster, Jeffrey F.

2009-05-01

The mission of the Intelligent Ground Systems (IGS) Area at the Tank Automotive Research, Development and Engineering Center (TARDEC) is to conduct technology maturation and integration to increase Soldier robot control/interface intuitiveness and robotic ground system robustness, functionality and overall system effectiveness for the Future Combat System Brigade Combat Team, Robotics Systems Joint Project Office and game changing capabilities to be fielded beyond the current force. This is accomplished through technology component development focused on increasing unmanned ground vehicle autonomy, optimizing crew interfaces and mission planners that capture commanders' intent, integrating payloads that provide 360 degree local situational awareness and expanding current UGV tactical behavior, learning and adaptation capabilities. The integration of these technology components into ground vehicle demonstrators permits engineering evaluation, User assessment and performance characterization in increasingly complex, dynamic and relevant environments to include high speed on road or cross country operations, all weather/visibility conditions and military operations in urban terrain (MOUT). Focused testing and experimentation is directed at reducing PM risk areas (safe operations, autonomous maneuver, manned-unmanned collaboration) and transitioning technology in the form of hardware, software algorithms, test and performance data, as well as User feedback and lessons learned.

Development of RT-components for the M-3 Strawberry Harvesting Robot

NASA Astrophysics Data System (ADS)

Yamashita, Tomoki; Tanaka, Motomasa; Yamamoto, Satoshi; Hayashi, Shigehiko; Saito, Sadafumi; Sugano, Shigeki

We are now developing the strawberry harvest robot called “M-3” prototype robot system under the 4th urgent project of MAFF. In order to develop the control software of the M-3 robot more efficiently, we innovated the RT-middleware “OpenRTM-aist” software platform. In this system, we developed 9 kind of RT-Components (RTC): Robot task sequence player RTC, Proxy RTC for image processing software, DC motor controller RTC, Arm kinematics RTC, and so on. In this paper, we discuss advantages of RT-middleware developing system and problems about operating the RTC-configured robotic system by end-users.

Environmental restoration and waste management: Robotics technology development program: Robotics 5-year program plan

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

Not Available

This plan covers robotics Research, Development, Demonstration, Testing and Evaluation activities in the Program for the next five years. These activities range from bench-scale R D to full-scale hot demonstrations at DOE sites. This plan outlines applications of existing technology to near-term needs, the development and application of enhanced technology for longer-term needs, and initiation of advanced technology development to meet those needs beyond the five-year plan. The objective of the Robotic Technology Development Program (RTDP) is to develop and apply robotics technologies that will enable Environmental Restoration and Waste Management (ER WM) operations at DOE sites to be safer,more » faster and cheaper. Five priority DOE sites were visited in March 1990 to identify needs for robotics technology in ER WM operations. This 5-Year Program Plan for the RTDP detailed annual plans for robotics technology development based on identified needs. In July 1990 a forum was held announcing the robotics program. Over 60 organizations (industrial, university, and federal laboratory) made presentations on their robotics capabilities. To stimulate early interactions with the ER WM activities at DOE sites, as well as with the robotics community, the RTDP sponsored four technology demonstrations related to ER WM needs. These demonstrations integrated commercial technology with robotics technology developed by DOE in support of areas such as nuclear reactor maintenance and the civilian reactor waste program. 2 figs.« less

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

A Mini-Curriculum for Robotics Education.

ERIC Educational Resources Information Center

Jones, Preston K.

This practicum report documents the development of a four-lesson multimedia program for robotics instruction for fourth and seventh grade students. The commercial film "Robot Revolution" and the videocassette tape "Robotics" were used, along with two author-developed slide/audiotape presentations and 14 overhead transparency foils. Two robots,…

Characterization and Application of Four-Layer Semiconductor Structures in Pulse Mode Operation

DTIC Science & Technology

2006-09-01

the cutting edge adaptive AI of the Marathon videogame [14] and can be directly applied to Information Operations in Military Operations Other Than...walk behavior is lost because the DC motor does not develop sufficient power to turn the wheels. This was overcome by converting the spikes into...motivation for creating a micro-robotic swarm is to demonstrate the capability of a simple logic circuit in developing a distributed processing system. The

Robot flow, clogging and jamming in confined spaces

NASA Astrophysics Data System (ADS)

Monaenkova, Daria; Linevich, Vadim; Goodisman, Michael A. D.; Goldman, Daniel I.

We hypothesized that when a collection of robots operate in confined space, maximization of individual effort could negatively affect the collective performance by impeding the mobility of the individuals. To test our hypothesis, we built and programmed groups of 1-4 autonomous robotic diggers to construct a tunnel in a model cohesive soil. The robots' mobility, defined in terms of the residence time (T) required for a robot to move one body-length within the tunnel, was compared between groups of maximally active robots (mode 1), groups with different levels of activity between individuals (mode 2), and maximally active robots with a ``giving up'' behavior (mode 3), in which the robot ceased the attempt to excavate in a crowded tunnel. In small groups of two robots, T was ~3 sec and did not depend on the mode of operation. However, an increase in the number of robots caused an increase in T which depended upon mode. The residence time in groups of four robots in mode 1 (~9 sec) significantly exceeded the residence time in mode 2 and 3 (~4 sec), indicating that crowding was causing slower movement of individuals, particularly under maximum effort (mode 1). We will use our robophysical studies to discover principles of collective construction in subterranean social animals.

Multiresolutional schemata for unsupervised learning of autonomous robots for 3D space operation

NASA Technical Reports Server (NTRS)

Lacaze, Alberto; Meystel, Michael; Meystel, Alex

1994-01-01

This paper describes a novel approach to the development of a learning control system for autonomous space robot (ASR) which presents the ASR as a 'baby' -- that is, a system with no a priori knowledge of the world in which it operates, but with behavior acquisition techniques that allows it to build this knowledge from the experiences of actions within a particular environment (we will call it an Astro-baby). The learning techniques are rooted in the recursive algorithm for inductive generation of nested schemata molded from processes of early cognitive development in humans. The algorithm extracts data from the environment and by means of correlation and abduction, it creates schemata that are used for control. This system is robust enough to deal with a constantly changing environment because such changes provoke the creation of new schemata by generalizing from experiences, while still maintaining minimal computational complexity, thanks to the system's multiresolutional nature.

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.

Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

PubMed

Cipresso, Pietro; Riva, Giuseppe

2015-01-01

There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

Experiences in Developing an Experimental Robotics Course Program for Undergraduate Education

ERIC Educational Resources Information Center

Jung, Seul

2013-01-01

An interdisciplinary undergraduate-level robotics course offers students the chance to integrate their engineering knowledge learned throughout their college years by building a robotic system. Robotics is thus a core course in system and control-related engineering education. This paper summarizes the experience of developing robotics courses…

Environmental restoration and waste management: Robotics technology development program: Robotics 5-year program plan. [Contains glossary

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

Not Available

This plan covers robotics Research, Development, Demonstration, Testing, activities in the Program for the next five years. These activities range from bench-scale R D to fullscale hot demonstrations at DOE sites. This plan outlines applications of existing technology to near-term needs, the development and application of enhanced technology for longer-term needs, and an initiation of advanced technology development to meet those needs beyond the five-year plan. The objective of the Robotic Technology Development (RTDP) is to develop and apply robotics technologies that will enable Environmental Restoration and Waste Management operations at DOE sites to be safer, faster and cheaper. Fivemore » priority DOE sites were visited in March 1990 to identify needs for robotics technology in ER WM operations. This 5-Year Program Plan for the RTDP detailed annual plans for robotics technology development based on identified needs. This 5-Year Program Plan discusses the overall approach to be adopted by the RTDP to aggressively develop robotics technology and contains discussions of the Program Management Plan, Site Visit and Needs Summary, Approach to Needs-Directed Technical Development, Application-Specific Technical Development, and Cross-Cutting and Advanced Technology. Integrating application-specific ER WM needs, the current state of robotics technology, and the potential benefits (in terms of faster, safer, and cheaper) of new technology, the Plan develops application-specific road maps for robotics RDDT E for the period FY 1991 through FY 1995. In addition, the Plan identifies areas where longer-term research in robotics will have a high payoff in the 5- to 20-year time frame. 12 figs.« less

Electroencephalographic markers of robot-aided therapy in stroke patients for the evaluation of upper limb rehabilitation.

PubMed

Sale, Patrizio; Infarinato, Francesco; Del Percio, Claudio; Lizio, Roberta; Babiloni, Claudio; Foti, Calogero; Franceschini, Marco

2015-12-01

Stroke is the leading cause of permanent disability in developed countries; its effects may include sensory, motor, and cognitive impairment as well as a reduced ability to perform self-care and participate in social and community activities. A number of studies have shown that the use of robotic systems in upper limb motor rehabilitation programs provides safe and intensive treatment to patients with motor impairments because of a neurological injury. Furthermore, robot-aided therapy was shown to be well accepted and tolerated by all patients; however, it is not known whether a specific robot-aided rehabilitation can induce beneficial cortical plasticity in stroke patients. Here, we present a procedure to study neural underpinning of robot-aided upper limb rehabilitation in stroke patients. Neurophysiological recordings use the following: (a) 10-20 system electroencephalographic (EEG) electrode montage; (b) bipolar vertical and horizontal electrooculographies; and (c) bipolar electromyography from the operating upper limb. Behavior monitoring includes the following: (a) clinical data and (b) kinematic and dynamic of the operant upper limb movements. Experimental conditions include the following: (a) resting state eyes closed and eyes open, and (b) robotic rehabilitation task (maximum 80 s each block to reach 4-min EEG data; interblock pause of 1 min). The data collection is performed before and after a program of 30 daily rehabilitation sessions. EEG markers include the following: (a) EEG power density in the eyes-closed condition; (b) reactivity of EEG power density to eyes opening; and (c) reactivity of EEG power density to robotic rehabilitation task. The above procedure was tested on a subacute patient (29 poststroke days) and on a chronic patient (21 poststroke months). After the rehabilitation program, we observed (a) improved clinical condition; (b) improved performance during the robotic task; (c) reduced delta rhythms (1-4 Hz) and increased alpha rhythms (8-12 Hz) during the resting state eyes-closed condition; (d) increased alpha desynchronization to eyes opening; and (e) decreased alpha desynchronization during the robotic rehabilitation task. We conclude that the present procedure is suitable for evaluation of the neural underpinning of robot-aided upper limb rehabilitation.

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.

Creepiness Creeps In: Uncanny Valley Feelings Are Acquired in Childhood.

PubMed

Brink, Kimberly A; Gray, Kurt; Wellman, Henry M

2017-12-13

The uncanny valley posits that very human-like robots are unsettling, a phenomenon amply demonstrated in adults but unexplored in children. Two hundred forty 3- to 18-year-olds viewed one of two robots (machine-like or very human-like) and rated their feelings toward (e.g., "Does the robot make you feel weird or happy?") and perceptions of the robot's capacities (e.g., "Does the robot think for itself?"). Like adults, children older than 9 judged the human-like robot as creepier than the machine-like robot-but younger children did not. Children's perceptions of robots' mental capacities predicted uncanny feelings: children judge robots to be creepy depending on whether they have human-like minds. The uncanny valley is therefore acquired over development and relates to changing conceptions about robot minds. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Autonomous Navigation, Dynamic Path and Work Flow Planning in Multi-Agent Robotic Swarms Project

NASA Technical Reports Server (NTRS)

Falker, John; Zeitlin, Nancy; Leucht, Kurt; Stolleis, Karl

2015-01-01

Kennedy Space Center has teamed up with the Biological Computation Lab at the University of New Mexico to create a swarm of small, low-cost, autonomous robots, called Swarmies, to be used as a ground-based research platform for in-situ resource utilization missions. The behavior of the robot swarm mimics the central-place foraging strategy of ants to find and collect resources in an unknown environment and return those resources to a central site.

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.

Using sensor habituation in mobile robots to reduce oscillatory movements in narrow corridors.

PubMed

Chang, Carolina

2005-11-01

Habituation is a form of nonassociative learning observed in a variety of species of animals. Arguably, it is the simplest form of learning. Nonetheless, the ability to habituate to certain stimuli implies plastic neural systems and adaptive behaviors. This paper describes how computational models of habituation can be applied to real robots. In particular, we discuss the problem of the oscillatory movements observed when a Khepera robot navigates through narrow hallways using a biologically inspired neurocontroller. Results show that habituation to the proximity of the walls can lead to smoother navigation. Habituation to sensory stimulation to the sides of the robot does not interfere with the robot's ability to turn at dead ends and to avoid obstacles outside the hallway. This paper shows that simple biological mechanisms of learning can be adapted to achieve better performance in real mobile robots.

Development of Pneumatic Robot Hand and Construction of Master-Slave System

NASA Astrophysics Data System (ADS)

Tsujiuchi, Nobutaka; Koizumi, Takayuki; Nishino, Shinya; Komatsubara, Hiroyuki; Kudawara, Tatsuwo; Hirano, Masanori

Recently, research and development has focused on robots that work in place of people. It is necessary for robots to perform the same flexible motions as people. Additionally, such robots need to incorporate high-level safety features in order not to injure people. For creation of such robots, we need to develop a robot hand that functions like a human hand. At the same time, this type of robot hand can be used as an artificial hand. Here, we present artificial muscle-type pneumatic actuators as the driving source of a robot hand that is both safe and flexible. Some development of robot hands using pneumatic actuators has already taken place. But, until now, when a pneumatic actuator is used, a big compressor is needed. So, the driving system also needs to be big; enlargement of the driving system is a major problem. Consequently, in this research, we develop a low-pressure, low-volume pneumatic actuator for driving a robot hand that works flexibly and safely on the assumption that it will be in contact with people. We develop a five-fingered robot hand with pneumatic actuators. And, we construct a master-slave system to enable the robot hand to perform the same operations as a human hand. We make a 1-link arm that has one degree of freedom using a pneumatic actuator, and construct a control system for the 1-link arm and verify its control performance.

Behavioral networks as a model for intelligent agents

NASA Technical Reports Server (NTRS)

Sliwa, Nancy E.

1990-01-01

On-going work at NASA Langley Research Center in the development and demonstration of a paradigm called behavioral networks as an architecture for intelligent agents is described. This work focuses on the need to identify a methodology for smoothly integrating the characteristics of low-level robotic behavior, including actuation and sensing, with intelligent activities such as planning, scheduling, and learning. This work assumes that all these needs can be met within a single methodology, and attempts to formalize this methodology in a connectionist architecture called behavioral networks. Behavioral networks are networks of task processes arranged in a task decomposition hierarchy. These processes are connected by both command/feedback data flow, and by the forward and reverse propagation of weights which measure the dynamic utility of actions and beliefs.

Upper-limb kinematic reconstruction during stroke robot-aided therapy.

PubMed

Papaleo, E; Zollo, L; Garcia-Aracil, N; Badesa, F J; Morales, R; Mazzoleni, S; Sterzi, S; Guglielmelli, E

2015-09-01

The paper proposes a novel method for an accurate and unobtrusive reconstruction of the upper-limb kinematics of stroke patients during robot-aided rehabilitation tasks with end-effector machines. The method is based on a robust analytic procedure for inverse kinematics that simply uses, in addition to hand pose data provided by the robot, upper arm acceleration measurements for computing a constraint on elbow position; it is exploited for task space augmentation. The proposed method can enable in-depth comprehension of planning strategy of stroke patients in the joint space and, consequently, allow developing therapies tailored for their residual motor capabilities. The experimental validation has a twofold purpose: (1) a comparative analysis with an optoelectronic motion capturing system is used to assess the method capability to reconstruct joint motion; (2) the application of the method to healthy and stroke subjects during circle-drawing tasks with InMotion2 robot is used to evaluate its efficacy in discriminating stroke from healthy behavior. The experimental results have shown that arm angles are reconstructed with a RMSE of 8.3 × 10(-3) rad. Moreover, the comparison between healthy and stroke subjects has revealed different features in the joint space in terms of mean values and standard deviations, which also allow assessing inter- and intra-subject variability. The findings of this study contribute to the investigation of motor performance in the joint space and Cartesian space of stroke patients undergoing robot-aided therapy, thus allowing: (1) evaluating the outcomes of the therapeutic approach, (2) re-planning the robotic treatment based on patient needs, and (3) understanding pathology-related motor strategies.

Ghost-in-the-Machine reveals human social signals for human-robot interaction.

PubMed

Loth, Sebastian; Jettka, Katharina; Giuliani, Manuel; de Ruiter, Jan P

2015-01-01

We used a new method called "Ghost-in-the-Machine" (GiM) to investigate social interactions with a robotic bartender taking orders for drinks and serving them. Using the GiM paradigm allowed us to identify how human participants recognize the intentions of customers on the basis of the output of the robotic recognizers. Specifically, we measured which recognizer modalities (e.g., speech, the distance to the bar) were relevant at different stages of the interaction. This provided insights into human social behavior necessary for the development of socially competent robots. When initiating the drink-order interaction, the most important recognizers were those based on computer vision. When drink orders were being placed, however, the most important information source was the speech recognition. Interestingly, the participants used only a subset of the available information, focussing only on a few relevant recognizers while ignoring others. This reduced the risk of acting on erroneous sensor data and enabled them to complete service interactions more swiftly than a robot using all available sensor data. We also investigated socially appropriate response strategies. In their responses, the participants preferred to use the same modality as the customer's requests, e.g., they tended to respond verbally to verbal requests. Also, they added redundancy to their responses, for instance by using echo questions. We argue that incorporating the social strategies discovered with the GiM paradigm in multimodal grammars of human-robot interactions improves the robustness and the ease-of-use of these interactions, and therefore provides a smoother user experience.

Ghost-in-the-Machine reveals human social signals for human–robot interaction

PubMed Central

Loth, Sebastian; Jettka, Katharina; Giuliani, Manuel; de Ruiter, Jan P.

2015-01-01

We used a new method called “Ghost-in-the-Machine” (GiM) to investigate social interactions with a robotic bartender taking orders for drinks and serving them. Using the GiM paradigm allowed us to identify how human participants recognize the intentions of customers on the basis of the output of the robotic recognizers. Specifically, we measured which recognizer modalities (e.g., speech, the distance to the bar) were relevant at different stages of the interaction. This provided insights into human social behavior necessary for the development of socially competent robots. When initiating the drink-order interaction, the most important recognizers were those based on computer vision. When drink orders were being placed, however, the most important information source was the speech recognition. Interestingly, the participants used only a subset of the available information, focussing only on a few relevant recognizers while ignoring others. This reduced the risk of acting on erroneous sensor data and enabled them to complete service interactions more swiftly than a robot using all available sensor data. We also investigated socially appropriate response strategies. In their responses, the participants preferred to use the same modality as the customer’s requests, e.g., they tended to respond verbally to verbal requests. Also, they added redundancy to their responses, for instance by using echo questions. We argue that incorporating the social strategies discovered with the GiM paradigm in multimodal grammars of human–robot interactions improves the robustness and the ease-of-use of these interactions, and therefore provides a smoother user experience. PMID:26582998

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.

A development of intelligent entertainment robot for home life

NASA Astrophysics Data System (ADS)

Kim, Cheoltaek; Lee, Ju-Jang

2005-12-01

The purpose of this paper was to present the study and design idea for entertainment robot with educational purpose (IRFEE). The robot has been designed for home life considering dependability and interaction. The developed robot has three objectives - 1. Develop autonomous robot, 2. Design robot considering mobility and robustness, 3. Develop robot interface and software considering entertainment and education functionalities. The autonomous navigation was implemented by active vision based SLAM and modified EPF algorithm. The two differential wheels, the pan-tilt were designed mobility and robustness and the exterior was designed considering esthetic element and minimizing interference. The speech and tracking algorithm provided the good interface with human. The image transfer and Internet site connection is needed for service of remote connection and educational purpose.

Robotic Surgical Training in an Academic Institution

PubMed Central

Chitwood, W. Randolph; Nifong, L. Wiley; Chapman, William H. H.; Felger, Jason E.; Bailey, B. Marcus; Ballint, Tara; Mendleson, Kim G.; Kim, Victor B.; Young, James A.; Albrecht, Robert A.

2001-01-01

Objective To detail robotic procedure development and clinical applications for mitral valve, biliary, and gastric reflux operations, and to implement a multispecialty robotic surgery training curriculum for both surgeons and surgical teams. Summary Background Data Remote, accurate telemanipulation of intracavitary instruments by general and cardiac surgeons is now possible. Complex technologic advancements in surgical robotics require well-designed training programs. Moreover, efficient robotic surgical procedures must be developed methodically and safely implemented clinically. Methods Advanced training on robotic systems provides surgeon confidence when operating in tiny intracavitary spaces. Three-dimensional vision and articulated instrument control are essential. The authors’ two da Vinci robotic systems have been dedicated to procedure development, clinical surgery, and training of surgical specialists. Their center has been the first United States site to train surgeons formally in clinical robotics. Results Established surgeons and residents have been trained using a defined robotic surgical educational curriculum. Also, 30 multispecialty teams have been trained in robotic mechanics and electronics. Initially, robotic procedures were developed experimentally and are described. In the past year the authors have performed 52 robotic-assisted clinical operations: 18 mitral valve repairs, 20 cholecystectomies, and 14 Nissen fundoplications. These respective operations required 108, 28, and 73 minutes of robotic telemanipulation to complete. Procedure times for the last half of the abdominal operations decreased significantly, as did the knot-tying time in mitral operations. There have been no deaths and few complications. One mitral patient had postoperative bleeding. Conclusion Robotic surgery can be performed safely with excellent results. The authors have developed an effective curriculum for training teams in robotic surgery. After training, surgeons have applied these methods effectively and safely. PMID:11573041

Predictive Interfaces for Long-Distance Tele-Operations

NASA Technical Reports Server (NTRS)

Wheeler, Kevin R.; Martin, Rodney; Allan, Mark B.; Sunspiral, Vytas

2005-01-01

We address the development of predictive tele-operator interfaces for humanoid robots with respect to two basic challenges. Firstly, we address automating the transition from fully tele-operated systems towards degrees of autonomy. Secondly, we develop compensation for the time-delay that exists when sending telemetry data from a remote operation point to robots located at low earth orbit and beyond. Humanoid robots have a great advantage over other robotic platforms for use in space-based construction and maintenance because they can use the same tools as astronauts do. The major disadvantage is that they are difficult to control due to the large number of degrees of freedom, which makes it difficult to synthesize autonomous behaviors using conventional means. We are working with the NASA Johnson Space Center's Robonaut which is an anthropomorphic robot with fully articulated hands, arms, and neck. We have trained hidden Markov models that make use of the command data, sensory streams, and other relevant data sources to predict a tele-operator's intent. This allows us to achieve subgoal level commanding without the use of predefined command dictionaries, and to create sub-goal autonomy via sequence generation from generative models. Our method works as a means to incrementally transition from manual tele-operation to semi-autonomous, supervised operation. The multi-agent laboratory experiments conducted by Ambrose et. al. have shown that it is feasible to directly tele-operate multiple Robonauts with humans to perform complex tasks such as truss assembly. However, once a time-delay is introduced into the system, the rate of tele\\ioperation slows down to mimic a bump and wait type of activity. We would like to maintain the same interface to the operator despite time-delays. To this end, we are developing an interface which will allow for us to predict the intentions of the operator while interacting with a 3D virtual representation of the expected state of the robot. The predictive interface anticipates the intention of the operator, and then uses this prediction to initiate appropriate sub-goal autonomy tasks.

Development of soft robots using dielectric elastomer actuators

NASA Astrophysics Data System (ADS)

Godaba, Hareesh; Wang, Yuzhe; Cao, Jiawei; Zhu, Jian

2016-04-01

Soft robots are gaining in popularity due to their unique attributes such as low weight, compliance, flexibility and diverse range in motion types. This paper illustrates soft robots and actuators which are developed using dielectric elastomer. These developments include a jellyfish robot, a worm like robot and artificial muscle actuators for jaw movement in a robotic skull. The jellyfish robot which employs a bulged dielectric elastomer membrane has been demonstrated too generate thrust and buoyant forces and can move effectively in water. The artificial muscle for jaw movement employs a pure shear configuration and has been shown to closely mimic the jaw motion while chewing or singing a song. Thee inchworm robot, powered by dielectric elastomer actuator can demonstrate stable movement in one-direction.

In vivo robotics: the automation of neuroscience and other intact-system biological fields

PubMed Central

Kodandaramaiah, Suhasa B.; Boyden, Edward S.; Forest, Craig R.

2013-01-01

Robotic and automation technologies have played a huge role in in vitro biological science, having proved critical for scientific endeavors such as genome sequencing and high-throughput screening. Robotic and automation strategies are beginning to play a greater role in in vivo and in situ sciences, especially when it comes to the difficult in vivo experiments required for understanding the neural mechanisms of behavior and disease. In this perspective, we discuss the prospects for robotics and automation to impact neuroscientific and intact-system biology fields. We discuss how robotic innovations might be created to open up new frontiers in basic and applied neuroscience, and present a concrete example with our recent automation of in vivo whole cell patch clamp electrophysiology of neurons in the living mouse brain. PMID:23841584

Artificial organisms as tools for the development of psychological theory: Tolman's lesson.

PubMed

Miglino, Orazio; Gigliotta, Onofrio; Cardaci, Maurizio; Ponticorvo, Michela

2007-12-01

In the 1930s and 1940s, Edward Tolman developed a psychological theory of spatial orientation in rats and humans. He expressed his theory as an automaton (the "schematic sowbug") or what today we would call an "artificial organism." With the technology of the day, he could not implement his model. Nonetheless, he used it to develop empirical predictions which tested with animals in the laboratory. This way of proceeding was in line with scientific practice dating back to Galileo. The way psychologists use artificial organisms in their work today breaks with this tradition. Modern "artificial organisms" are constructed a posteriori, working from experimental or ethological observations. As a result, researchers can use them to confirm a theoretical model or to simulate its operation. But they make no contribution to the actual building of models. In this paper, we try to return to Tolman's original strategy: implementing his theory of "vicarious trial and error" in a simulated robot, forecasting the robot's behavior and conducting experiments that verify or falsify these predictions.

Close-range sensors for small unmanned bottom vehicles: update

NASA Astrophysics Data System (ADS)

Bernstein, Charles L.

2000-07-01

The Surf Zone Reconnaissance Project is developing sensors for small, autonomous, Underwater Bottom-crawling Vehicles. The objective is to enable small, crawling robots to autonomously detect and classify mines and obstacles on the ocean bottom in depths between 0 and 10 feet. We have identified a promising set of techniques that will exploit the electromagnetic, shape, texture, image, and vibratory- modal features of this images. During FY99 and FY00 we have worked toward refining these techniques. Signature data sets have been collected for a standard target set to facilitate the development of sensor fusion and target detection and classification algorithms. Specific behaviors, termed microbehaviors, are developed to utilize the robot's mobility to position and operate the sensors. A first generation, close-range sensor suite, composed of 5 sensors, will be completed and tested on a crawling platform in FY00, and will be further refined and demonstrated in FY01 as part of the Mine Countermeasures 6.3 core program sponsored by the Office of Naval Research.

Robotics and Automation Education: Developing the Versatile, Practical Lab.

ERIC Educational Resources Information Center

Stenerson, Jon

1986-01-01

Elements of the development of a robotics and automation laboratory are discussed. These include the benefits of upgrading current staff, ways to achieve this staff development, formation of a robotics factory automation committee, topics to be taught with a robot, elements of a laboratory, laboratory funding, and design safety. (CT)

Robot initiative in a team learning task increases the rhythm of interaction but not the perceived engagement.

PubMed

Ivaldi, Serena; Anzalone, Salvatore M; Rousseau, Woody; Sigaud, Olivier; Chetouani, Mohamed

2014-01-01

We hypothesize that the initiative of a robot during a collaborative task with a human can influence the pace of interaction, the human response to attention cues, and the perceived engagement. We propose an object learning experiment where the human interacts in a natural way with the humanoid iCub. Through a two-phases scenario, the human teaches the robot about the properties of some objects. We compare the effect of the initiator of the task in the teaching phase (human or robot) on the rhythm of the interaction in the verification phase. We measure the reaction time of the human gaze when responding to attention utterances of the robot. Our experiments show that when the robot is the initiator of the learning task, the pace of interaction is higher and the reaction to attention cues faster. Subjective evaluations suggest that the initiating role of the robot, however, does not affect the perceived engagement. Moreover, subjective and third-person evaluations of the interaction task suggest that the attentive mechanism we implemented in the humanoid robot iCub is able to arouse engagement and make the robot's behavior readable.

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.

Robot initiative in a team learning task increases the rhythm of interaction but not the perceived engagement

PubMed Central

Ivaldi, Serena; Anzalone, Salvatore M.; Rousseau, Woody; Sigaud, Olivier; Chetouani, Mohamed

2014-01-01

We hypothesize that the initiative of a robot during a collaborative task with a human can influence the pace of interaction, the human response to attention cues, and the perceived engagement. We propose an object learning experiment where the human interacts in a natural way with the humanoid iCub. Through a two-phases scenario, the human teaches the robot about the properties of some objects. We compare the effect of the initiator of the task in the teaching phase (human or robot) on the rhythm of the interaction in the verification phase. We measure the reaction time of the human gaze when responding to attention utterances of the robot. Our experiments show that when the robot is the initiator of the learning task, the pace of interaction is higher and the reaction to attention cues faster. Subjective evaluations suggest that the initiating role of the robot, however, does not affect the perceived engagement. Moreover, subjective and third-person evaluations of the interaction task suggest that the attentive mechanism we implemented in the humanoid robot iCub is able to arouse engagement and make the robot's behavior readable. PMID:24596554

Development of intelligent robots - Achievements and issues

NASA Astrophysics Data System (ADS)

Nitzan, D.

1985-03-01

A flexible, intelligent robot is regarded as a general purpose machine system that may include effectors, sensors, computers, and auxiliary equipment and, like a human, can perform a variety of tasks under unpredictable conditions. Development of intelligent robots is essential for increasing the growth rate of today's robot population in industry and elsewhere. Robotics research and development topics include manipulation, end effectors, mobility, sensing (noncontact and contact), adaptive control, robot programming languages, and manufacturing process planning. Past achievements and current issues related to each of these topics are described briefly.