Optimization of the computational load of a hypercube supercomputer onboard a mobile robot

NASA Technical Reports Server (NTRS)

Barhen, Jacob; Toomarian, N.; Protopopescu, V.

1987-01-01

A combinatorial optimization methodology is developed, which enables the efficient use of hypercube multiprocessors onboard mobile intelligent robots dedicated to time-critical missions. The methodology is implemented in terms of large-scale concurrent algorithms based either on fast simulated annealing, or on nonlinear asynchronous neural networks. In particular, analytic expressions are given for the effect of single-neuron perturbations on the systems' configuration energy. Compact neuromorphic data structures are used to model effects such as precedence constraints, processor idling times, and task-schedule overlaps. Results for a typical robot-dynamics benchmark are presented.

Soft robotics: a review and progress towards faster and higher torque actuators (presentation video)

NASA Astrophysics Data System (ADS)

Shepherd, Robert

2014-03-01

Last year, nearly 160,000 industrial robots were shipped worldwide—into a total market valued at 26 Bn (including hardware, software, and peripherals).[1] Service robots for professional (e.g., defense, medical, agriculture) and personal (e.g., household, handicap assistance, toys, and education) use accounted for 16,000 units, 3.4 Bn and 3,000,000 units, $1.2 Bn respectively.[1] The vast majority of these robotic systems use fully actuated, rigid components that take little advantage of passive dynamics. Soft robotics is a field that is taking advantage of compliant actuators and passive dynamics to achieve several goals: reduced design, manufacturing and control complexity, improved energy efficiency, more sophisticated motions, and safe human-machine interactions to name a few. The potential for societal impact is immense. In some instances, soft actuators have achieved commercial success; however, large scale adoption will require improved methods of controlling non-linear systems, greater reliability in their function, and increased utility from faster and more forceful actuation. In my talk, I will describe efforts from my work in the Whitesides group at Harvard to prove sophisticated motions in these machines using simple controls, as well capabilities unique to soft machines. I will also describe the potential for combinations of different classes of soft actuators (e.g., electrically and pneumatically actuated systems) to improve the utility of soft robots. 1. World Robotics - Industrial Robots 2013, 2013, International Federation of Robotics.

Controlling free flight of a robotic fly using an onboard vision sensor inspired by insect ocelli

PubMed Central

Fuller, Sawyer B.; Karpelson, Michael; Censi, Andrea; Ma, Kevin Y.; Wood, Robert J.

2014-01-01

Scaling a flying robot down to the size of a fly or bee requires advances in manufacturing, sensing and control, and will provide insights into mechanisms used by their biological counterparts. Controlled flight at this scale has previously required external cameras to provide the feedback to regulate the continuous corrective manoeuvres necessary to keep the unstable robot from tumbling. One stabilization mechanism used by flying insects may be to sense the horizon or Sun using the ocelli, a set of three light sensors distinct from the compound eyes. Here, we present an ocelli-inspired visual sensor and use it to stabilize a fly-sized robot. We propose a feedback controller that applies torque in proportion to the angular velocity of the source of light estimated by the ocelli. We demonstrate theoretically and empirically that this is sufficient to stabilize the robot's upright orientation. This constitutes the first known use of onboard sensors at this scale. Dipteran flies use halteres to provide gyroscopic velocity feedback, but it is unknown how other insects such as honeybees stabilize flight without these sensory organs. Our results, using a vehicle of similar size and dynamics to the honeybee, suggest how the ocelli could serve this role. PMID:24942846

Morphological communication: exploiting coupled dynamics in a complex mechanical structure to achieve locomotion

PubMed Central

Rieffel, John A.; Valero-Cuevas, Francisco J.; Lipson, Hod

2010-01-01

Traditional engineering approaches strive to avoid, or actively suppress, nonlinear dynamic coupling among components. Biological systems, in contrast, are often rife with these dynamics. Could there be, in some cases, a benefit to high degrees of dynamical coupling? Here we present a distributed robotic control scheme inspired by the biological phenomenon of tensegrity-based mechanotransduction. This emergence of morphology-as-information-conduit or ‘morphological communication’, enabled by time-sensitive spiking neural networks, presents a new paradigm for the decentralized control of large, coupled, modular systems. These results significantly bolster, both in magnitude and in form, the idea of morphological computation in robotic control. Furthermore, they lend further credence to ideas of embodied anatomical computation in biological systems, on scales ranging from cellular structures up to the tendinous networks of the human hand. PMID:19776146

Dynamic legged locomotion in robots and animals

NASA Astrophysics Data System (ADS)

Raibert, Marc; Playter, Robert; Ringrose, Robert; Bailey, Dave; Leeser, Karl

1995-01-01

This report documents our study of active legged systems that balance actively and move dynamically. The purpose of this research is to build a foundation of knowledge that can lead both to the construction of useful legged vehicles and to a better understanding of how animal locomotion works. In this report we provide an update on progress during the past year. Here are the topics covered in this report: (1) Is cockroach locomotion dynamic? To address this question we created three models of cockroaches, each abstracted at a different level. We provided each model with a control system and computer simulation. One set of results suggests that 'Groucho Running,' a type of dynamic walking, seems feasible at cockroach scale. (2) How do bipeds shift weight between the legs? We built a simple planar biped robot specifically to explore this question. It shifts its weight from one curved foot to the other, using a toe-off and toe-on strategy, in conjunction with dynamic tipping. (3) 3D biped gymnastics: The 3D biped robot has done front somersaults in the laboratory. The robot changes its leg length in flight to control rotation rate. This in turn provides a mechanism for controlling the landing attitude of the robot once airborne. (4) Passively stabilized layout somersault: We have found that the passive structure of a gymnast, the configuration of masses and compliances, can stabilize inherently unstable maneuvers. This means that body biomechanics could play a larger role in controlling behavior than is generally thought. We used a physical 'doll' model and computer simulation to illustrate the point. (5) Twisting: Some gymnastic maneuvers require twisting. We are studying how to couple the biomechanics of the system to its control to produce efficient, stable twisting maneuvers.

Hardware Design and Testing of SUPERball, A Modular Tensegrity Robot

NASA Technical Reports Server (NTRS)

Sabelhaus, Andrew P.; Bruce, Jonathan; Caluwaerts, Ken; Chen, Yangxin; Lu, Dizhou; Liu, Yuejia; Agogino, Adrian K.; SunSpiral, Vytas; Agogino, Alice M.

2014-01-01

We are developing a system of modular, autonomous "tensegrity end-caps" to enable the rapid exploration of untethered tensegrity robot morphologies and functions. By adopting a self-contained modular approach, different end-caps with various capabilities (such as peak torques, or motor speeds), can be easily combined into new tensegrity robots composed of rods, cables, and actuators of different scale (such as in length, mass, peak loads, etc). As a first step in developing this concept, we are in the process of designing and testing the end-caps for SUPERball (Spherical Underactuated Planetary Exploration Robot), a project at the Dynamic Tensegrity Robotics Lab (DTRL) within NASA Ames's Intelligent Robotics Group. This work discusses the evolving design concepts and test results that have gone into the structural, mechanical, and sensing aspects of SUPERball. This representative tensegrity end-cap design supports robust and repeatable untethered mobility tests of the SUPERball, while providing high force, high displacement actuation, with a low-friction, compliant cabling system.

Coevolving advances in animal flight and aerial robotics

PubMed Central

Lentink, David

2017-01-01

Our understanding of animal flight has inspired the design of new aerial robots with more effective flight capacities through the process of biomimetics and bioinspiration. The aerodynamic origin of the elevated performance of flying animals remains, however, poorly understood. In this themed issue, animal flight research and aerial robot development coalesce to offer a broader perspective on the current advances and future directions in these coevolving fields of research. Together, four reviews summarize and 14 reports contribute to our understanding of low Reynolds number flight. This area of applied aerodynamics research is challenging to dissect due to the complicated flow phenomena that include laminar–turbulent flow transition, laminar separation bubbles, delayed stall and nonlinear vortex dynamics. Our mechanistic understanding of low Reynolds number flight has perhaps been advanced most by the development of dynamically scaled robot models and new specialized wind tunnel facilities: in particular, the tiltable Lund flight tunnel for animal migration research and the recently developed AFAR hypobaric wind tunnel for high-altitude animal flight studies. These world-class facilities are now complemented with a specialized low Reynolds number wind tunnel for studying the effect of turbulence on animal and robot flight in much greater detail than previously possible. This is particular timely, because the study of flight in extremely laminar versus turbulent flow opens a new frontier in our understanding of animal flight. Advancing this new area will offer inspiration for developing more efficient high-altitude aerial robots and removes roadblocks for aerial robots operating in turbulent urban environments.

Actuation control of a PiezoMEMS biomimetic robotic jellyfish

NASA Astrophysics Data System (ADS)

Alejandre, Alvaro; Olszewski, Oskar; Jackson, Nathan

2017-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2006-10-01

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

Adaptive Control Strategies for Interlimb Coordination in Legged Robots: A Review

PubMed Central

Aoi, Shinya; Manoonpong, Poramate; Ambe, Yuichi; Matsuno, Fumitoshi; Wörgötter, Florentin

2017-01-01

Walking animals produce adaptive interlimb coordination during locomotion in accordance with their situation. Interlimb coordination is generated through the dynamic interactions of the neural system, the musculoskeletal system, and the environment, although the underlying mechanisms remain unclear. Recently, investigations of the adaptation mechanisms of living beings have attracted attention, and bio-inspired control systems based on neurophysiological findings regarding sensorimotor interactions are being developed for legged robots. In this review, we introduce adaptive interlimb coordination for legged robots induced by various factors (locomotion speed, environmental situation, body properties, and task). In addition, we show characteristic properties of adaptive interlimb coordination, such as gait hysteresis and different time-scale adaptations. We also discuss the underlying mechanisms and control strategies to achieve adaptive interlimb coordination and the design principle for the control system of legged robots. PMID:28878645

A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm.

PubMed

Wei, Kun; Ren, Bingyin

2018-02-13

In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.

Movement Characteristics Analysis and Dynamic Simulation of Collaborative Measuring Robot

NASA Astrophysics Data System (ADS)

guoqing, MA; li, LIU; zhenglin, YU; guohua, CAO; yanbin, ZHENG

2017-03-01

Human-machine collaboration is becoming increasingly more necessary, and so collaborative robot applications are also in high demand. We selected a UR10 robot as our research subject for this study. First, we applied D-H coordinate transformation of the robot to establish a link system, and we then used inverse transformation to solve the robot’s inverse kinematics and find all the joints. Use Lagrange method to analysis UR robot dynamics; use ADAMS multibody dynamics simulation software to dynamic simulation; verifying the correctness of the derived kinetic models.

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.

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.

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.

Robopedia: Leveraging Sensorpedia for Web-Enabled Robot Control

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

Resseguie, David R

There is a growing interest in building Internetscale sensor networks that integrate sensors from around the world into a single unified system. In contrast, robotics application development has primarily focused on building specialized systems. These specialized systems take scalability and reliability into consideration, but generally neglect exploring the key components required to build a large scale system. Integrating robotic applications with Internet-scale sensor networks will unify specialized robotics applications and provide answers to large scale implementation concerns. We focus on utilizing Internet-scale sensor network technology to construct a framework for unifying robotic systems. Our framework web-enables a surveillance robot smore » sensor observations and provides a webinterface to the robot s actuators. This lets robots seamlessly integrate into web applications. In addition, the framework eliminates most prerequisite robotics knowledge, allowing for the creation of general web-based robotics applications. The framework also provides mechanisms to create applications that can interface with any robot. Frameworks such as this one are key to solving large scale mobile robotics implementation problems. We provide an overview of previous Internetscale sensor networks, Sensorpedia (an ad-hoc Internet-scale sensor network), our framework for integrating robots with Sensorpedia, two applications which illustrate our frameworks ability to support general web-based robotic control, and offer experimental results that illustrate our framework s scalability, feasibility, and resource requirements.« less

Small-scale soft-bodied robot with multimodal locomotion.

PubMed

Hu, Wenqi; Lum, Guo Zhan; Mastrangeli, Massimo; Sitti, Metin

2018-02-01

Untethered small-scale (from several millimetres down to a few micrometres in all dimensions) robots that can non-invasively access confined, enclosed spaces may enable applications in microfactories such as the construction of tissue scaffolds by robotic assembly, in bioengineering such as single-cell manipulation and biosensing, and in healthcare such as targeted drug delivery and minimally invasive surgery. Existing small-scale robots, however, have very limited mobility because they are unable to negotiate obstacles and changes in texture or material in unstructured environments. Of these small-scale robots, soft robots have greater potential to realize high mobility via multimodal locomotion, because such machines have higher degrees of freedom than their rigid counterparts. Here we demonstrate magneto-elastic soft millimetre-scale robots that can swim inside and on the surface of liquids, climb liquid menisci, roll and walk on solid surfaces, jump over obstacles, and crawl within narrow tunnels. These robots can transit reversibly between different liquid and solid terrains, as well as switch between locomotive modes. They can additionally execute pick-and-place and cargo-release tasks. We also present theoretical models to explain how the robots move. Like the large-scale robots that can be used to study locomotion, these soft small-scale robots could be used to study soft-bodied locomotion produced by small organisms.

Small-scale soft-bodied robot with multimodal locomotion

NASA Astrophysics Data System (ADS)

Hu, Wenqi; Lum, Guo Zhan; Mastrangeli, Massimo; Sitti, Metin

2018-02-01

Untethered small-scale (from several millimetres down to a few micrometres in all dimensions) robots that can non-invasively access confined, enclosed spaces may enable applications in microfactories such as the construction of tissue scaffolds by robotic assembly, in bioengineering such as single-cell manipulation and biosensing, and in healthcare such as targeted drug delivery and minimally invasive surgery. Existing small-scale robots, however, have very limited mobility because they are unable to negotiate obstacles and changes in texture or material in unstructured environments. Of these small-scale robots, soft robots have greater potential to realize high mobility via multimodal locomotion, because such machines have higher degrees of freedom than their rigid counterparts. Here we demonstrate magneto-elastic soft millimetre-scale robots that can swim inside and on the surface of liquids, climb liquid menisci, roll and walk on solid surfaces, jump over obstacles, and crawl within narrow tunnels. These robots can transit reversibly between different liquid and solid terrains, as well as switch between locomotive modes. They can additionally execute pick-and-place and cargo-release tasks. We also present theoretical models to explain how the robots move. Like the large-scale robots that can be used to study locomotion, these soft small-scale robots could be used to study soft-bodied locomotion produced by small organisms.

Computing Dynamics Of A Robot Of 6+n Degrees Of Freedom

NASA Technical Reports Server (NTRS)

Quiocho, Leslie J.; Bailey, Robert W.

1995-01-01

Improved formulation speeds and simplifies computation of dynamics of robot arm of n rotational degrees of freedom mounted on platform having three translational and three rotational degrees of freedom. Intended for use in dynamical modeling of robotic manipulators attached to such moving bases as spacecraft, aircraft, vessel, or land vehicle. Such modeling important part of simulation and control of robotic motions.

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.

Kinematics and dynamics analysis of a quadruped walking robot with parallel leg mechanism

NASA Astrophysics Data System (ADS)

Wang, Hongbo; Sang, Lingfeng; Hu, Xing; Zhang, Dianfan; Yu, Hongnian

2013-09-01

It is desired to require a walking robot for the elderly and the disabled to have large capacity, high stiffness, stability, etc. However, the existing walking robots cannot achieve these requirements because of the weight-payload ratio and simple function. Therefore, Improvement of enhancing capacity and functions of the walking robot is an important research issue. According to walking requirements and combining modularization and reconfigurable ideas, a quadruped/biped reconfigurable walking robot with parallel leg mechanism is proposed. The proposed robot can be used for both a biped and a quadruped walking robot. The kinematics and performance analysis of a 3-UPU parallel mechanism which is the basic leg mechanism of a quadruped walking robot are conducted and the structural parameters are optimized. The results show that performance of the walking robot is optimal when the circumradius R, r of the upper and lower platform of leg mechanism are 161.7 mm, 57.7 mm, respectively. Based on the optimal results, the kinematics and dynamics of the quadruped walking robot in the static walking mode are derived with the application of parallel mechanism and influence coefficient theory, and the optimal coordination distribution of the dynamic load for the quadruped walking robot with over-determinate inputs is analyzed, which solves dynamic load coupling caused by the branches’ constraint of the robot in the walk process. Besides laying a theoretical foundation for development of the prototype, the kinematics and dynamics studies on the quadruped walking robot also boost the theoretical research of the quadruped walking and the practical applications of parallel mechanism.

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

NASA Astrophysics Data System (ADS)

Liu, Dalong; Xu, Lijuan

2018-01-01

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

Dynamic Modelling Of A SCARA Robot

NASA Astrophysics Data System (ADS)

Turiel, J. Perez; Calleja, R. Grossi; Diez, V. Gutierrez

1987-10-01

This paper describes a method for modelling industrial robots that considers dynamic approach to manipulation systems motion generation, obtaining the complete dynamic model for the mechanic part of the robot and taking into account the dynamic effect of actuators acting at the joints. For a four degree of freedom SCARA robot we obtain the dynamic model for the basic (minimal) configuration, that is, the three degrees of freedom that allow us to place the robot end effector in a desired point, using the Lagrange Method to obtain the dynamic equations in matrix form. The manipulator is considered to be a set of rigid bodies inter-connected by joints in the form of simple kinematic pairs. Then, the state space model is obtained for the actuators that move the robot joints, uniting the models of the single actuators, that is, two DC permanent magnet servomotors and an electrohydraulic actuator. Finally, using a computer simulation program written in FORTRAN language, we can compute the matrices of the complete model.

Mathematical model for adaptive control system of ASEA robot at Kennedy Space Center

NASA Technical Reports Server (NTRS)

Zia, Omar

1989-01-01

The dynamic properties and the mathematical model for the adaptive control of the robotic system presently under investigation at Robotic Application and Development Laboratory at Kennedy Space Center are discussed. NASA is currently investigating the use of robotic manipulators for mating and demating of fuel lines to the Space Shuttle Vehicle prior to launch. The Robotic system used as a testbed for this purpose is an ASEA IRB-90 industrial robot with adaptive control capabilities. The system was tested and it's performance with respect to stability was improved by using an analogue force controller. The objective of this research project is to determine the mathematical model of the system operating under force feedback control with varying dynamic internal perturbation in order to provide continuous stable operation under variable load conditions. A series of lumped parameter models are developed. The models include some effects of robot structural dynamics, sensor compliance, and workpiece dynamics.

KC-135 materials handling robotics

NASA Technical Reports Server (NTRS)

Workman, Gary L.

1991-01-01

Robot dynamics and control will become an important issue for implementing productive platforms in space. Robotic operations will become necessary for man-tended stations and for efficient performance of routine operations in a manned platform. The current constraints on the use of robotic devices in a microgravity environment appears to be due to an anticipated increase in acceleration levels due to manipulator motion and for safety concerns. The objective of this study will be to provide baseline data to meet that need. Most texts and papers dealing with the kinematics and dynamics of robots assume that the manipulator is composed of joints separated by rigid links. However, in recent years several groups have begun to study the dynamics of flexible manipulators, primarily for applying robots in space and for improving the efficiency and precision of robotic systems. Robotic systems which are being planned for implementation in space have a number of constraints to overcome. Additional concepts which have to be worked out in any robotic implementation for a space platform include teleoperation and degree of autonomous control. Some significant results in developing a robotic workcell for performing robotics research on the KC-135 aircraft in preperation for space-based robotics applications in the future were generated. In addition, it was shown that TREETOPS can be used to simulate the dynamics of robot manipulators for both space and ground-based applications.

ANYmal - A Highly Mobile and Dynamic Quadrupedal Robot

DTIC Science & Technology

2016-10-09

ANYmal - A Highly Mobile and Dynamic Quadrupedal Robot * Marco Hutter1, Christian Gehring2, Dominic Jud1, Andreas Lauber1, C. Dario Bellicoso1...Abstract— This paper introduces ANYmal, a quadrupedal robot that features outstanding mobility and dynamic motion capability. Thanks to novel...compliant joint modules with integrated electronics, the 30 kg, 0.5 m tall robotic dog is torque controllable and very robust against impulsive loads during

Dynamic characterization of contact interactions of micro-robotic leg structures

NASA Astrophysics Data System (ADS)

Ryou, Jeong Hoon; Oldham, Kenn Richard

2014-05-01

Contact dynamics of microelectromechanical systems (MEMS) are typically complicated and it is consequently difficult to model all dynamic characteristics observed in time-domain responses involving impact. This issue becomes worse when a device, such as a mobile micro-robot, is not clamped to a substrate and has a complex mechanical structure. To characterize such a contact interaction situation, two walking micro-robot prototypes are tested having intentionally simple structures with different dimensions (21.2 mm × 16.3 mm × 0.75 mm and 32 mm × 25.4 mm × 4.1 mm) and weights (0.16 and 2.7 g). Contact interaction behaviors are characterized by analyzing experimental data under various excitation signals. A numerical approach was used to derive a novel contact model consisting of a coefficient of restitution matrix that uses modal vibration information. Experimental validation of the simulation model shows that it captures various dynamic features of the contact interaction when simulating leg behavior more accurately than previous contact models, such as single-point coefficient of restitution or compliant ground models. In addition, this paper shows that small-scale forces can be added to the simulation to improve model accuracy, resulting in average errors across driving conditions on the order of 2-6% for bounce frequency, maximum foot height, and average foot height, although there is substantial variation from case to case.

Fast Dynamical Coupling Enhances Frequency Adaptation of Oscillators for Robotic Locomotion Control

PubMed Central

Nachstedt, Timo; Tetzlaff, Christian; Manoonpong, Poramate

2017-01-01

Rhythmic neural signals serve as basis of many brain processes, in particular of locomotion control and generation of rhythmic movements. It has been found that specific neural circuits, named central pattern generators (CPGs), are able to autonomously produce such rhythmic activities. In order to tune, shape and coordinate the produced rhythmic activity, CPGs require sensory feedback, i.e., external signals. Nonlinear oscillators are a standard model of CPGs and are used in various robotic applications. A special class of nonlinear oscillators are adaptive frequency oscillators (AFOs). AFOs are able to adapt their frequency toward the frequency of an external periodic signal and to keep this learned frequency once the external signal vanishes. AFOs have been successfully used, for instance, for resonant tuning of robotic locomotion control. However, the choice of parameters for a standard AFO is characterized by a trade-off between the speed of the adaptation and its precision and, additionally, is strongly dependent on the range of frequencies the AFO is confronted with. As a result, AFOs are typically tuned such that they require a comparably long time for their adaptation. To overcome the problem, here, we improve the standard AFO by introducing a novel adaptation mechanism based on dynamical coupling strengths. The dynamical adaptation mechanism enhances both the speed and precision of the frequency adaptation. In contrast to standard AFOs, in this system, the interplay of dynamics on short and long time scales enables fast as well as precise adaptation of the oscillator for a wide range of frequencies. Amongst others, a very natural implementation of this mechanism is in terms of neural networks. The proposed system enables robotic applications which require fast retuning of locomotion control in order to react to environmental changes or conditions. PMID:28377710

Research on modeling and motion simulation of a spherical space robot with telescopic manipulator based on virtual prototype technology

NASA Astrophysics Data System (ADS)

Shi, Chengkun; Sun, Hanxu; Jia, Qingxuan; Zhao, Kailiang

2009-05-01

For realizing omni-directional movement and operating task of spherical space robot system, this paper describes an innovated prototype and analyzes dynamic characteristics of a spherical rolling robot with telescopic manipulator. Based on the Newton-Euler equations, the kinematics and dynamic equations of the spherical robot's motion are instructed detailedly. Then the motion simulations of the robot in different environments are developed with ADAMS. The simulation results validate the mathematics model of the system. And the dynamic model establishes theoretical basis for the latter job.

Reconciliation of diverse telepathology system designs. Historic issues and implications for emerging markets and new applications.

PubMed

Weinstein, Ronald S; Graham, Anna R; Lian, Fangru; Braunhut, Beth L; Barker, Gail R; Krupinski, Elizabeth A; Bhattacharyya, Achyut K

2012-04-01

Telepathology, the distant service component of digital pathology, is a growth industry. The word "telepathology" was introduced into the English Language in 1986. Initially, two different, competing imaging modalities were used for telepathology. These were dynamic (real time) robotic telepathology and static image (store-and-forward) telepathology. In 1989, a hybrid dynamic robotic/static image telepathology system was developed in Norway. This hybrid imaging system bundled these two primary pathology imaging modalities into a single multi-modality pathology imaging system. Similar hybrid systems were subsequently developed and marketed in other countries as well. It is noteworthy that hybrid dynamic robotic/static image telepathology systems provided the infrastructure for the first truly sustainable telepathology services. Since then, impressive progress has been made in developing another telepathology technology, so-called "virtual microscopy" telepathology (also called "whole slide image" telepathology or "WSI" telepathology). Over the past decade, WSI has appeared to be emerging as the preferred digital telepathology digital imaging modality. However, recently, there has been a re-emergence of interest in dynamic-robotic telepathology driven, in part, by concerns over the lack of a means for up-and-down focusing (i.e., Z-axis focusing) using early WSI processors. In 2010, the initial two U.S. patents for robotic telepathology (issued in 1993 and 1994) expired enabling many digital pathology equipment companies to incorporate dynamic-robotic telepathology modules into their WSI products for the first time. The dynamic-robotic telepathology module provided a solution to the up-and-down focusing issue. WSI and dynamic robotic telepathology are now, rapidly, being bundled into a new class of telepathology/digital pathology imaging system, the "WSI-enhanced dynamic robotic telepathology system". To date, six major WSI processor equipment companies have embraced the approach and developed WSI-enhanced dynamic-robotic digital telepathology systems, marketed under a variety of labels. Successful commercialization of such systems could help overcome the current resistance of some pathologists to incorporate digital pathology, and telepathology, into their routine and esoteric laboratory services. Also, WSI-enhanced dynamic robotic telepathology could be useful for providing general pathology and subspecialty pathology services to many of the world's underserved populations in the decades ahead. This could become an important enabler for the delivery of patient-centered healthcare in the future. © 2012 The Authors APMIS © 2012 APMIS.

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.

A Dynamic Non Energy Storing Guidance Constraint with Motion Redirection for Robot Assisted Surgery

DTIC Science & Technology

2016-12-01

Abstract— Haptically enabled hands-on or tele-operated surgical robotic systems provide a unique opportunity to integrate pre- and intra... robot -assisted surgical systems aim at improving and extending human capabilities, by exploiting the advantages of robotic systems while keeping the...move during the operation. Robot -assisted beating heart surgery is an example of procedures that can benefit from dynamic constraints. Their

Dynamic photogrammetric calibration of industrial robots

NASA Astrophysics Data System (ADS)

Maas, Hans-Gerd

1997-07-01

Today's developments in industrial robots focus on aims like gain of flexibility, improvement of the interaction between robots and reduction of down-times. A very important method to achieve these goals are off-line programming techniques. In contrast to conventional teach-in-robot programming techniques, where sequences of actions are defined step-by- step via remote control on the real object, off-line programming techniques design complete robot (inter-)action programs in a CAD/CAM environment. This poses high requirements to the geometric accuracy of a robot. While the repeatability of robot poses in the teach-in mode is often better than 0.1 mm, the absolute pose accuracy potential of industrial robots is usually much worse due to tolerances, eccentricities, elasticities, play, wear-out, load, temperature and insufficient knowledge of model parameters for the transformation from poses into robot axis angles. This fact necessitates robot calibration techniques, including the formulation of a robot model describing kinematics and dynamics of the robot, and a measurement technique to provide reference data. Digital photogrammetry as an accurate, economic technique with realtime potential offers itself for this purpose. The paper analyzes the requirements posed to a measurement technique by industrial robot calibration tasks. After an overview on measurement techniques used for robot calibration purposes in the past, a photogrammetric robot calibration system based on off-the- shelf lowcost hardware components will be shown and results of pilot studies will be discussed. Besides aspects of accuracy, reliability and self-calibration in a fully automatic dynamic photogrammetric system, realtime capabilities are discussed. In the pilot studies, standard deviations of 0.05 - 0.25 mm in the three coordinate directions could be achieved over a robot work range of 1.7 X 1.5 X 1.0 m3. The realtime capabilities of the technique allow to go beyond kinematic robot calibration and perform dynamic robot calibration as well as photogrammetric on-line control of a robot in action.

Learning and adaptation: neural and behavioural mechanisms behind behaviour change

NASA Astrophysics Data System (ADS)

Lowe, Robert; Sandamirskaya, Yulia

2018-01-01

This special issue presents perspectives on learning and adaptation as they apply to a number of cognitive phenomena including pupil dilation in humans and attention in robots, natural language acquisition and production in embodied agents (robots), human-robot game play and social interaction, neural-dynamic modelling of active perception and neural-dynamic modelling of infant development in the Piagetian A-not-B task. The aim of the special issue, through its contributions, is to highlight some of the critical neural-dynamic and behavioural aspects of learning as it grounds adaptive responses in robotic- and neural-dynamic systems.

Dynamical modelling of coordinated multiple robot systems

NASA Technical Reports Server (NTRS)

Hayati, Samad

1987-01-01

The state of the art in the modeling of the dynamics of coordinated multiple robot manipulators is summarized and various problems related to this subject are discussed. It is recognized that dynamics modeling is a component used in the design of controllers for multiple cooperating robots. As such, the discussion addresses some problems related to the control of multiple robots. The techniques used to date in the modeling of closed kinematic chains are summarized. Various efforts made to date for the control of coordinated multiple manipulators is summarized.

A laser tracking dynamic robot metrology instrument

NASA Technical Reports Server (NTRS)

Parker, G. A.; Mayer, J. R. R.

1989-01-01

Research work over several years has resulted in the development of a laser tracking instrument capable of dynamic 3-D measurements of robot end-effector trajectories. The instrument characteristics and experiments to measure the static and dynamic performance of a robot in an industrial manufacturing environment are described. The use of this technology for space applications is examined.

Optimal bipedal interactions with dynamic terrain: synthesis and analysis via nonlinear programming

NASA Astrophysics Data System (ADS)

Hubicki, Christian; Goldman, Daniel; Ames, Aaron

In terrestrial locomotion, gait dynamics and motor control behaviors are tuned to interact efficiently and stably with the dynamics of the terrain (i.e. terradynamics). This controlled interaction must be particularly thoughtful in bipeds, as their reduced contact points render them highly susceptible to falls. While bipedalism under rigid terrain assumptions is well-studied, insights for two-legged locomotion on soft terrain, such as sand and dirt, are comparatively sparse. We seek an understanding of how biological bipeds stably and economically negotiate granular media, with an eye toward imbuing those abilities in bipedal robots. We present a trajectory optimization method for controlled systems subject to granular intrusion. By formulating a large-scale nonlinear program (NLP) with reduced-order resistive force theory (RFT) models and jamming cone dynamics, the optimized motions are informed and shaped by the dynamics of the terrain. Using a variant of direct collocation methods, we can express all optimization objectives and constraints in closed-form, resulting in rapid solving by standard NLP solvers, such as IPOPT. We employ this tool to analyze emergent features of bipedal locomotion in granular media, with an eye toward robotic implementation.

Dynamics and control of robot for capturing objects in space

NASA Astrophysics Data System (ADS)

Huang, Panfeng

Space robots are expected to perform intricate tasks in future space services, such as satellite maintenance, refueling, and replacing the orbital replacement unit (ORU). To realize these missions, the capturing operation may not be avoided. Such operations will encounter some challenges because space robots have some unique characteristics unfound on ground-based robots, such as, dynamic singularities, dynamic coupling between manipulator and space base, limited energy supply and working without a fixed base, and so on. In addition, since contacts and impacts may not be avoided during capturing operation. Therefore, dynamics and control problems of space robot for capturing objects are significant research topics if the robots are to be deployed for the space services. A typical servicing operation mainly includes three phases: capturing the object, berthing and docking the object, then repairing the target. Therefore, this thesis will focus on resolving some challenging problems during capturing the object, berthing and docking, and so on. In this thesis, I study and analyze the dynamics and control problems of space robot for capturing objects. This work has potential impact in space robotic applications. I first study the contact and impact dynamics of space robot and objects. I specifically focus on analyzing the impact dynamics and mapping the relationship of influence and speed. Then, I develop the fundamental theory for planning the minimum-collision based trajectory of space robot and designing the configuration of space robot at the moment of capture. To compensate for the attitude of the space base during the capturing approach operation, a new balance control concept which can effectively balance the attitude of the space base using the dynamic couplings is developed. The developed balance control concept helps to understand of the nature of space dynamic coupling, and can be readily applied to compensate or minimize the disturbance to the space base. After capturing the object, the space robot must complete the following two tasks: one is to berth the object, and the other is to re-orientate the attitude of the whole robot system for communication and power supply. Therefore, I propose a method to accomplish these two tasks simultaneously using manipulator motion only. The ultimate goal of space services is to realize the capture and manipulation autonomously. Therefore, I propose an affective approach based on learning human skill to track and capture the objects automatically in space. With human-teaching demonstration, the space robot is able to learn and abstract human tracking and capturing skill using an efficient neural-network learning architecture that combines flexible Cascade Neural Networks with Node Decoupled Extended Kalman Filtering (CNN-NDEKF). The simulation results attest that this approach is useful and feasible in tracking trajectory planning and capturing of space robot. Finally I propose a novel approach based on Genetic Algorithms (GAs) to optimize the approach trajectory of space robots in order to realize effective and stable operations. I complete the minimum-torque path planning in order to save the limited energy in space, and design the minimum jerk trajectory for the stabilization of the space manipulator and its space base. These optimal algorithms are very important and useful for the application of space robot.

Modelling of Dynamics of a Wheeled Mobile Robot with Mecanum Wheels with the use of Lagrange Equations of the Second Kind

NASA Astrophysics Data System (ADS)

Hendzel, Z.; Rykała, Ł.

2017-02-01

The work presents the dynamic equations of motion of a wheeled mobile robot with mecanum wheels derived with the use of Lagrange equations of the second kind. Mecanum wheels are a new type of wheels used in wheeled mobile robots and they consist of freely rotating rollers attached to the circumference of the wheels. In order to derive dynamic equations of motion of a wheeled mobile robot, the kinetic energy of the system is determined, as well as the generalised forces affecting the system. The resulting mathematical model of a wheeled mobile robot was generated with the use of Maple V software. The results of a solution of inverse and forward problems of dynamics of the discussed object are also published.

Cartesian control of redundant robots

NASA Technical Reports Server (NTRS)

Colbaugh, R.; Glass, K.

1989-01-01

A Cartesian-space position/force controller is presented for redundant robots. The proposed control structure partitions the control problem into a nonredundant position/force trajectory tracking problem and a redundant mapping problem between Cartesian control input F is a set member of the set R(sup m) and robot actuator torque T is a set member of the set R(sup n) (for redundant robots, m is less than n). The underdetermined nature of the F yields T map is exploited so that the robot redundancy is utilized to improve the dynamic response of the robot. This dynamically optimal F yields T map is implemented locally (in time) so that it is computationally efficient for on-line control; however, it is shown that the map possesses globally optimal characteristics. Additionally, it is demonstrated that the dynamically optimal F yields T map can be modified so that the robot redundancy is used to simultaneously improve the dynamic response and realize any specified kinematic performance objective (e.g., manipulability maximization or obstacle avoidance). Computer simulation results are given for a four degree of freedom planar redundant robot under Cartesian control, and demonstrate that position/force trajectory tracking and effective redundancy utilization can be achieved simultaneously with the proposed controller.

Adaptive output feedback control of flexible-joint robots using neural networks: dynamic surface design approach.

PubMed

Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

2008-10-01

In this paper, we propose a new robust output feedback control approach for flexible-joint electrically driven (FJED) robots via the observer dynamic surface design technique. The proposed method only requires position measurements of the FJED robots. To estimate the link and actuator velocity information of the FJED robots with model uncertainties, we develop an adaptive observer using self-recurrent wavelet neural networks (SRWNNs). The SRWNNs are used to approximate model uncertainties in both robot (link) dynamics and actuator dynamics, and all their weights are trained online. Based on the designed observer, the link position tracking controller using the estimated states is induced from the dynamic surface design procedure. Therefore, the proposed controller can be designed more simply than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop adaptive system are uniformly ultimately bounded. Finally, the simulation results on a three-link FJED robot are presented to validate the good position tracking performance and robustness of the proposed control system against payload uncertainties and external disturbances.

Evaluation of the power consumption of a high-speed parallel robot

NASA Astrophysics Data System (ADS)

Han, Gang; Xie, Fugui; Liu, Xin-Jun

2018-06-01

An inverse dynamic model of a high-speed parallel robot is established based on the virtual work principle. With this dynamic model, a new evaluation method is proposed to measure the power consumption of the robot during pick-and-place tasks. The power vector is extended in this method and used to represent the collinear velocity and acceleration of the moving platform. Afterward, several dynamic performance indices, which are homogenous and possess obvious physical meanings, are proposed. These indices can evaluate the power input and output transmissibility of the robot in a workspace. The distributions of the power input and output transmissibility of the high-speed parallel robot are derived with these indices and clearly illustrated in atlases. Furtherly, a low-power-consumption workspace is selected for the robot.

Motion synthesis and force distribution analysis for a biped robot.

PubMed

Trojnacki, Maciej T; Zielińska, Teresa

2011-01-01

In this paper, the method of generating biped robot motion using recorded human gait is presented. The recorded data were modified taking into account the velocity available for robot drives. Data includes only selected joint angles, therefore the missing values were obtained considering the dynamic postural stability of the robot, which means obtaining an adequate motion trajectory of the so-called Zero Moment Point (ZMT). Also, the method of determining the ground reaction forces' distribution during the biped robot's dynamic stable walk is described. The method was developed by the authors. Following the description of equations characterizing the dynamics of robot's motion, the values of the components of ground reaction forces were symbolically determined as well as the coordinates of the points of robot's feet contact with the ground. The theoretical considerations have been supported by computer simulation and animation of the robot's motion. This was done using Matlab/Simulink package and Simulink 3D Animation Toolbox, and it has proved the proposed method.

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.

The effect of robot dynamics on smoothness during wrist pointing.

PubMed

Erwin, Andrew; Pezent, Evan; Bradley, Joshua; O'Malley, Marcia K

2017-07-01

The improvement of movement smoothness over the course of therapy is one of the positive outcomes observed during robotic rehabilitation. Although movements are generally robust to disturbances, certain perturbations might disrupt an individual's ability to produce these smooth movements. In this paper, we explore how a rehabilitation robot's inherent dynamics impact movement smoothness during pointing tasks. Able-bodied participants made wrist pointing movements under four different operating conditions. Despite the relative transparency of the device, inherent dynamic characteristics negatively impacted movement smoothness. Active compensation for Coulomb friction effects failed to mitigate the degradation in smoothness. Assessment of movements that involved coupled motions of the robot's joints reduced the bias seen in single degree of freedom movements. When using robotic devices for assessment of movement quality, the impact of the inherent dynamics must be considered.

Robot soccer anywhere: achieving persistent autonomous navigation, mapping, and object vision tracking in dynamic environments

NASA Astrophysics Data System (ADS)

Dragone, Mauro; O'Donoghue, Ruadhan; Leonard, John J.; O'Hare, Gregory; Duffy, Brian; Patrikalakis, Andrew; Leederkerken, Jacques

2005-06-01

The paper describes an ongoing effort to enable autonomous mobile robots to play soccer in unstructured, everyday environments. Unlike conventional robot soccer competitions that are usually held on purpose-built robot soccer "fields", in our work we seek to develop the capability for robots to demonstrate aspects of soccer-playing in more diverse environments, such as schools, hospitals, or shopping malls, with static obstacles (furniture) and dynamic natural obstacles (people). This problem of "Soccer Anywhere" presents numerous research challenges including: (1) Simultaneous Localization and Mapping (SLAM) in dynamic, unstructured environments, (2) software control architectures for decentralized, distributed control of mobile agents, (3) integration of vision-based object tracking with dynamic control, and (4) social interaction with human participants. In addition to the intrinsic research merit of these topics, we believe that this capability would prove useful for outreach activities, in demonstrating robotics technology to primary and secondary school students, to motivate them to pursue careers in science and engineering.

Strategies for the stabilization of longitudinal forward flapping flight revealed using a dynamically-scaled robotic fly.

PubMed

Elzinga, Michael J; van Breugel, Floris; Dickinson, Michael H

2014-06-01

The ability to regulate forward speed is an essential requirement for flying animals. Here, we use a dynamically-scaled robot to study how flapping insects adjust their wing kinematics to regulate and stabilize forward flight. The results suggest that the steady-state lift and thrust requirements at different speeds may be accomplished with quite subtle changes in hovering kinematics, and that these adjustments act primarily by altering the pitch moment. This finding is consistent with prior hypotheses regarding the relationship between body pitch and flight speed in fruit flies. Adjusting the mean stroke position of the wings is a likely mechanism for trimming the pitch moment at all speeds, whereas changes in the mean angle of attack may be required at higher speeds. To ensure stability, the flapping system requires additional pitch damping that increases in magnitude with flight speed. A compensatory reflex driven by fast feedback of pitch rate from the halteres could provide such damping, and would automatically exhibit gain scheduling with flight speed if pitch torque was regulated via changes in stroke deviation. Such a control scheme would provide an elegant solution for stabilization across a wide range of forward flight speeds.

Unsupervised and self-mapping category formation and semantic object recognition for mobile robot vision used in an actual environment

NASA Astrophysics Data System (ADS)

Madokoro, H.; Tsukada, M.; Sato, K.

2013-07-01

This paper presents an unsupervised learning-based object category formation and recognition method for mobile robot vision. Our method has the following features: detection of feature points and description of features using a scale-invariant feature transform (SIFT), selection of target feature points using one class support vector machines (OC-SVMs), generation of visual words using self-organizing maps (SOMs), formation of labels using adaptive resonance theory 2 (ART-2), and creation and classification of categories on a category map of counter propagation networks (CPNs) for visualizing spatial relations between categories. Classification results of dynamic images using time-series images obtained using two different-size robots and according to movements respectively demonstrate that our method can visualize spatial relations of categories while maintaining time-series characteristics. Moreover, we emphasize the effectiveness of our method for category formation of appearance changes of objects.

Neuromorphic walking gait control.

PubMed

Still, Susanne; Hepp, Klaus; Douglas, Rodney J

2006-03-01

We present a neuromorphic pattern generator for controlling the walking gaits of four-legged robots which is inspired by central pattern generators found in the nervous system and which is implemented as a very large scale integrated (VLSI) chip. The chip contains oscillator circuits that mimic the output of motor neurons in a strongly simplified way. We show that four coupled oscillators can produce rhythmic patterns with phase relationships that are appropriate to generate all four-legged animal walking gaits. These phase relationships together with frequency and duty cycle of the oscillators determine the walking behavior of a robot driven by the chip, and they depend on a small set of stationary bias voltages. We give analytic expressions for these dependencies. This chip reduces the complex, dynamic inter-leg control problem associated with walking gait generation to the problem of setting a few stationary parameters. It provides a compact and low power solution for walking gait control in robots.

Adapting an Ant Colony Metaphor for Multi-Robot Chemical Plume Tracing

PubMed Central

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Li, Fei; Zeng, Ming

2012-01-01

We consider chemical plume tracing (CPT) in time-varying airflow environments using multiple mobile robots. The purpose of CPT is to approach a gas source with a previously unknown location in a given area. Therefore, the CPT could be considered as a dynamic optimization problem in continuous domains. The traditional ant colony optimization (ACO) algorithm has been successfully used for combinatorial optimization problems in discrete domains. To adapt the ant colony metaphor to the multi-robot CPT problem, the two-dimension continuous search area is discretized into grids and the virtual pheromone is updated according to both the gas concentration and wind information. To prevent the adapted ACO algorithm from being prematurely trapped in a local optimum, the upwind surge behavior is adopted by the robots with relatively higher gas concentration in order to explore more areas. The spiral surge (SS) algorithm is also examined for comparison. Experimental results using multiple real robots in two indoor natural ventilated airflow environments show that the proposed CPT method performs better than the SS algorithm. The simulation results for large-scale advection-diffusion plume environments show that the proposed method could also work in outdoor meandering plume environments. PMID:22666056

Adapting an ant colony metaphor for multi-robot chemical plume tracing.

PubMed

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Li, Fei; Zeng, Ming

2012-01-01

We consider chemical plume tracing (CPT) in time-varying airflow environments using multiple mobile robots. The purpose of CPT is to approach a gas source with a previously unknown location in a given area. Therefore, the CPT could be considered as a dynamic optimization problem in continuous domains. The traditional ant colony optimization (ACO) algorithm has been successfully used for combinatorial optimization problems in discrete domains. To adapt the ant colony metaphor to the multi-robot CPT problem, the two-dimension continuous search area is discretized into grids and the virtual pheromone is updated according to both the gas concentration and wind information. To prevent the adapted ACO algorithm from being prematurely trapped in a local optimum, the upwind surge behavior is adopted by the robots with relatively higher gas concentration in order to explore more areas. The spiral surge (SS) algorithm is also examined for comparison. Experimental results using multiple real robots in two indoor natural ventilated airflow environments show that the proposed CPT method performs better than the SS algorithm. The simulation results for large-scale advection-diffusion plume environments show that the proposed method could also work in outdoor meandering plume environments.

Lifelong Transfer Learning for Heterogeneous Teams of Agents in Sequential Decision Processes

DTIC Science & Technology

2016-06-01

making (SDM) tasks in dynamic environments with simulated and physical robots . 15. SUBJECT TERMS Sequential decision making, lifelong learning, transfer...sequential decision-making (SDM) tasks in dynamic environments with both simple benchmark tasks and more complex aerial and ground robot tasks. Our work...and ground robots in the presence of disturbances: We applied our methods to the problem of learning controllers for robots with novel disturbances in

Dynamics and control for Constrained Multibody Systems modeled with Maggi's equation: Application to Differential Mobile Robots Partll

NASA Astrophysics Data System (ADS)

Amengonu, Yawo H.; Kakad, Yogendra P.

2014-07-01

Quasivelocity techniques were applied to derive the dynamics of a Differential Wheeled Mobile Robot (DWMR) in the companion paper. The present paper formulates a control system design for trajectory tracking of this class of robots. The method develops a feedback linearization technique for the nonlinear system using dynamic extension algorithm. The effectiveness of the nonlinear controller is illustrated with simulation example.

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.

Adaptive dynamic surface control of flexible-joint robots using self-recurrent wavelet neural networks.

PubMed

Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

2006-12-01

A new method for the robust control of flexible-joint (FJ) robots with model uncertainties in both robot dynamics and actuator dynamics is proposed. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self-recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides the ability to overcome the "explosion of complexity" problem in backstepping controllers. The SRWNNs are used to observe the arbitrary model uncertainties of FJ robots, and all their weights are trained online. From the Lyapunov stability analysis, their adaptation laws are induced, and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a three-link FJ robot are utilized to validate the good position tracking performance and robustness against payload uncertainties and external disturbances of the proposed control system.

Dynamics and control of cable-suspended parallel robots for giant telescopes

NASA Astrophysics Data System (ADS)

Zhuang, Peng; Yao, Zhengqiu

2006-06-01

A cable-suspended parallel robot utilizes the basic idea of Stewart platform but replaces parallel links with cables and linear actuators with winches. It has many advantages over a conventional crane. The concept of applying a cable-suspended parallel robot into the construction and maintenance of giant telescope is presented in this paper. Compared with the mass and travel of the moving platform of the robot, the mass and deformation of the cables can be disregarded. Based on the premises, the kinematic and dynamic models of the robot are built. Through simulation, the inertia and gravity of moving platform are found to have dominant effect on the dynamic characteristic of the robot, while the dynamics of actuators can be disregarded, so a simplified dynamic model applicable to real-time control is obtained. Moreover, according to control-law partitioning approach and optimization theory, a workspace model-based controller is proposed considering the characteristic that the cables can only pull but not push. The simulation results indicate that the controller possesses good accuracy in pose and speed tracking, and keeps the cables in reliable tension by maintaining the minimum strain above a certain given value, thus ensures smooth motion and accurate localization for moving platform.

Constrained motion model of mobile robots and its applications.

PubMed

Zhang, Fei; Xi, Yugeng; Lin, Zongli; Chen, Weidong

2009-06-01

Target detecting and dynamic coverage are fundamental tasks in mobile robotics and represent two important features of mobile robots: mobility and perceptivity. This paper establishes the constrained motion model and sensor model of a mobile robot to represent these two features and defines the k -step reachable region to describe the states that the robot may reach. We show that the calculation of the k-step reachable region can be reduced from that of 2(k) reachable regions with the fixed motion styles to k + 1 such regions and provide an algorithm for its calculation. Based on the constrained motion model and the k -step reachable region, the problems associated with target detecting and dynamic coverage are formulated and solved. For target detecting, the k-step detectable region is used to describe the area that the robot may detect, and an algorithm for detecting a target and planning the optimal path is proposed. For dynamic coverage, the k-step detected region is used to represent the area that the robot has detected during its motion, and the dynamic-coverage strategy and algorithm are proposed. Simulation results demonstrate the efficiency of the coverage algorithm in both convex and concave environments.

From embodied mind to embodied robotics: humanities and system theoretical aspects.

PubMed

Mainzer, Klaus

2009-01-01

After an introduction (1) the article analyzes the evolution of the embodied mind (2), the innovation of embodied robotics (3), and finally discusses conclusions of embodied robotics for human responsibility (4). Considering the evolution of the embodied mind (2), we start with an introduction of complex systems and nonlinear dynamics (2.1), apply this approach to neural self-organization (2.2), distinguish degrees of complexity of the brain (2.3), explain the emergence of cognitive states by complex systems dynamics (2.4), and discuss criteria for modeling the brain as complex nonlinear system (2.5). The innovation of embodied robotics (3) is a challenge of future technology. We start with the distinction of symbolic and embodied AI (3.1) and explain embodied robots as dynamical systems (3.2). Self-organization needs self-control of technical systems (3.3). Cellular neural networks (CNN) are an example of self-organizing technical systems offering new avenues for neurobionics (3.4). In general, technical neural networks support different kinds of learning robots (3.5). Finally, embodied robotics aim at the development of cognitive and conscious robots (3.6).

A General, Adaptive, Roadmap-Based Algorithm for Protein Motion Computation.

PubMed

Molloy, Kevin; Shehu, Amarda

2016-03-01

Precious information on protein function can be extracted from a detailed characterization of protein equilibrium dynamics. This remains elusive in wet and dry laboratories, as function-modulating transitions of a protein between functionally-relevant, thermodynamically-stable and meta-stable structural states often span disparate time scales. In this paper we propose a novel, robotics-inspired algorithm that circumvents time-scale challenges by drawing analogies between protein motion and robot motion. The algorithm adapts the popular roadmap-based framework in robot motion computation to handle the more complex protein conformation space and its underlying rugged energy surface. Given known structures representing stable and meta-stable states of a protein, the algorithm yields a time- and energy-prioritized list of transition paths between the structures, with each path represented as a series of conformations. The algorithm balances computational resources between a global search aimed at obtaining a global view of the network of protein conformations and their connectivity and a detailed local search focused on realizing such connections with physically-realistic models. Promising results are presented on a variety of proteins that demonstrate the general utility of the algorithm and its capability to improve the state of the art without employing system-specific insight.

A robotic platform for studying sea lion thrust production

NASA Astrophysics Data System (ADS)

Leftwich, Megan; Patel, Rahi; Kulkarni, Aditya; Friedman, Chen

California Sea Lions are agile swimmers and, uniquely, use their foreflippers (rather than hind flipper undulation) to generate thrust. Recently, a sea lion flipper from a deceased subject was externally scanned in high detail for fluid dynamics research. The flipper's geometry is used in this work to build an accurate scaled down flipper model (approximately 68% of the full size span). The flipper model is placed in a water flume to obtain lift and drag force measurements. The unique trailing edge features are then examined for their effect on the measured forces by comparing to similar flipper models with a smooth trailing edge, sinusoidal trailing edge, and a saw-tooth trailing edge. Additionally, a robotic flipper is being designed and built, replicating the sea lion foreflipper anatomical structure. The robot is actuated by a set of servo motors and replicates the sea lion flipper clap motion based on previously extracted kinematics. The flipper tip speed is designed to match typical full scale Reynolds numbers for an acceleration from rest maneuver. The model is tested in the water flume as well to obtain the forces and flow structures during the thrust production phase of the flipper motion.

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.

[Haptic tracking control for minimally invasive robotic surgery].

PubMed

Xu, Zhaohong; Song, Chengli; Wu, Wenwu

2012-06-01

Haptic feedback plays a significant role in minimally invasive robotic surgery (MIRS). A major deficiency of the current MIRS is the lack of haptic perception for the surgeon, including the commercially available robot da Vinci surgical system. In this paper, a dynamics model of a haptic robot is established based on Newton-Euler method. Because it took some period of time in exact dynamics solution, we used a digital PID arithmetic dependent on robot dynamics to ensure real-time bilateral control, and it could improve tracking precision and real-time control efficiency. To prove the proposed method, an experimental system in which two Novint Falcon haptic devices acting as master-slave system has been developed. Simulations and experiments showed proposed methods could give instrument force feedbacks to operator, and bilateral control strategy is an effective method to master-slave MIRS. The proposed methods could be used to tele-robotic system.

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

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

Telemanipulation of cooperative robots: a case of study

NASA Astrophysics Data System (ADS)

Pliego-Jiménez, Javier; Arteaga-Pérez, Marco

2018-06-01

This article addresses the problem of dexterous robotic grasping by means of a telemanipulation system composed of a single master and two slave robot manipulators. The slave robots are analysed as a cooperative system where it is assumed that the robots can push but not pull the object. In order to achieve a stable rigid grasp, a centralised adaptive position-force control algorithm for the slave robots is proposed. On the other hand, a linear velocity observer for the master robot is developed to avoid numerical differentiation. A set of experiments with different human operators were carried out to show the good performance and capabilities of the proposed control-observer algorithm. In addition, the dynamic model and closed-loop dynamics of the telemanipulation is presented.

The contact condition influence on stability and energy efficiency of quadruped robot

NASA Astrophysics Data System (ADS)

Lei, Jingtao; Wang, Tianmiao; Gao, Feng

2008-10-01

Quadruped robot has attribute of serial and parallel manipulator with multi-loop mechanism, with more DOF of each leg and intermittent contact with ground during walking, the trot gait of quadruped robot belongs to dynamic waking, compared to the crawl gait, the walking speed is higher, but the robot becomes unstable, it is difficult to keep dynamically stable walking. In this paper, we mainly analyze the condition for the quadruped robot to realize dynamically stable walking, establish centroid orbit equation based on ZMP (Zero Moment Point) stability theory, on the other hand , we study contact impact and friction influence on stability and energy efficiency. Because of the periodic contact between foots and ground, the contact impact and friction are considered to establish spring-damp nonlinear dynamics model. Robot need to be controlled to meet ZMP stability condition and contact constraint condition. Based on the virtual prototyping model, we study control algorithm considering contact condition, the contact compensator and friction compensator are adopted. The contact force and the influence of different contact conditions on the energy efficiency during whole gait cycle are obtained.

Effect of body weight support variation on muscle activities during robot assisted gait: a dynamic simulation study.

PubMed

Hussain, Shahid; Jamwal, Prashant K; Ghayesh, Mergen H

2017-05-01

While body weight support (BWS) intonation is vital during conventional gait training of neurologically challenged subjects, it is important to evaluate its effect during robot assisted gait training. In the present research we have studied the effect of BWS intonation on muscle activities during robotic gait training using dynamic simulations. Two dimensional (2-D) musculoskeletal model of human gait was developed conjointly with another 2-D model of a robotic orthosis capable of actuating hip, knee and ankle joints simultaneously. The musculoskeletal model consists of eight major muscle groups namely; soleus (SOL), gastrocnemius (GAS), tibialis anterior (TA), hamstrings (HAM), vasti (VAS), gluteus maximus (GLU), uniarticular hip flexors (iliopsoas, IP), and Rectus Femoris (RF). BWS was provided at levels of 0, 20, 40 and 60% during the simulations. In order to obtain a feasible set of muscle activities during subsequent gait cycles, an inverse dynamics algorithm along with a quadratic minimization algorithm was implemented. The dynamic parameters of the robot assisted human gait such as joint angle trajectories, ground contact force (GCF), human limb joint torques and robot induced torques at different levels of BWS were derived. The patterns of muscle activities at variable BWS were derived and analysed. For most part of the gait cycle (GC) the muscle activation patterns are quite similar for all levels of BWS as is apparent from the mean of muscle activities for the complete GC. Effect of BWS variation during robot assisted gait on muscle activities was studied by developing dynamic simulation. It is expected that the proposed dynamic simulation approach will provide important inferences and information about the muscle function variations consequent upon a change in BWS during robot assisted gait. This information shall be quite important while investigating the influence of BWS intonation on neuromuscular parameters of interest during robotic gait training.

An integrated collision prediction and avoidance scheme for mobile robots in non-stationary environments

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1993-01-01

A formulation that makes possible the integration of collision prediction and avoidance stages for mobile robots moving in general terrains containing moving obstacles is presented. A dynamic model of the mobile robot and the dynamic constraints are derived. Collision avoidance is guaranteed if the distance between the robot and a moving obstacle is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. A feedback control is developed and local asymptotic stability is proved if the velocity of the moving obstacle is bounded. Furthermore, a solution to the problem of inverse dynamics for the mobile robot is given. Simulation results verify the value of the proposed strategy.

Dynamical network interactions in distributed control of robots

NASA Astrophysics Data System (ADS)

Buscarino, Arturo; Fortuna, Luigi; Frasca, Mattia; Rizzo, Alessandro

2006-03-01

In this paper the dynamical network model of the interactions within a group of mobile robots is investigated and proposed as a possible strategy for controlling the robots without central coordination. Motivated by the results of the analysis of our simple model, we show that the system performance in the presence of noise can be improved by including long-range connections between the robots. Finally, a suitable strategy based on this model to control exploration and transport is introduced.

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

NASA Astrophysics Data System (ADS)

Zarzhitsky, Dimitri

2008-07-01

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

A stability-based mechanism for hysteresis in the walk–trot transition in quadruped locomotion

PubMed Central

Aoi, Shinya; Katayama, Daiki; Fujiki, Soichiro; Tomita, Nozomi; Funato, Tetsuro; Yamashita, Tsuyoshi; Senda, Kei; Tsuchiya, Kazuo

2013-01-01

Quadrupeds vary their gaits in accordance with their locomotion speed. Such gait transitions exhibit hysteresis. However, the underlying mechanism for this hysteresis remains largely unclear. It has been suggested that gaits correspond to attractors in their dynamics and that gait transitions are non-equilibrium phase transitions that are accompanied by a loss in stability. In the present study, we used a robotic platform to investigate the dynamic stability of gaits and to clarify the hysteresis mechanism in the walk–trot transition of quadrupeds. Specifically, we used a quadruped robot as the body mechanical model and an oscillator network for the nervous system model to emulate dynamic locomotion of a quadruped. Experiments using this robot revealed that dynamic interactions among the robot mechanical system, the oscillator network, and the environment generate walk and trot gaits depending on the locomotion speed. In addition, a walk–trot transition that exhibited hysteresis was observed when the locomotion speed was changed. We evaluated the gait changes of the robot by measuring the locomotion of dogs. Furthermore, we investigated the stability structure during the gait transition of the robot by constructing a potential function from the return map of the relative phase of the legs and clarified the physical characteristics inherent to the gait transition in terms of the dynamics. PMID:23389894

A stability-based mechanism for hysteresis in the walk-trot transition in quadruped locomotion.

PubMed

Aoi, Shinya; Katayama, Daiki; Fujiki, Soichiro; Tomita, Nozomi; Funato, Tetsuro; Yamashita, Tsuyoshi; Senda, Kei; Tsuchiya, Kazuo

2013-04-06

Quadrupeds vary their gaits in accordance with their locomotion speed. Such gait transitions exhibit hysteresis. However, the underlying mechanism for this hysteresis remains largely unclear. It has been suggested that gaits correspond to attractors in their dynamics and that gait transitions are non-equilibrium phase transitions that are accompanied by a loss in stability. In the present study, we used a robotic platform to investigate the dynamic stability of gaits and to clarify the hysteresis mechanism in the walk-trot transition of quadrupeds. Specifically, we used a quadruped robot as the body mechanical model and an oscillator network for the nervous system model to emulate dynamic locomotion of a quadruped. Experiments using this robot revealed that dynamic interactions among the robot mechanical system, the oscillator network, and the environment generate walk and trot gaits depending on the locomotion speed. In addition, a walk-trot transition that exhibited hysteresis was observed when the locomotion speed was changed. We evaluated the gait changes of the robot by measuring the locomotion of dogs. Furthermore, we investigated the stability structure during the gait transition of the robot by constructing a potential function from the return map of the relative phase of the legs and clarified the physical characteristics inherent to the gait transition in terms of the dynamics.

A Robot-Driven Computational Model for Estimating Passive Ankle Torque With Subject-Specific Adaptation.

PubMed

Zhang, Mingming; Meng, Wei; Davies, T Claire; Zhang, Yanxin; Xie, Sheng Q

2016-04-01

Robot-assisted ankle assessment could potentially be conducted using sensor-based and model-based methods. Existing ankle rehabilitation robots usually use torquemeters and multiaxis load cells for measuring joint dynamics. These measurements are accurate, but the contribution as a result of muscles and ligaments is not taken into account. Some computational ankle models have been developed to evaluate ligament strain and joint torque. These models do not include muscles and, thus, are not suitable for an overall ankle assessment in robot-assisted therapy. This study proposed a computational ankle model for use in robot-assisted therapy with three rotational degrees of freedom, 12 muscles, and seven ligaments. This model is driven by robotics, uses three independent position variables as inputs, and outputs an overall ankle assessment. Subject-specific adaptations by geometric and strength scaling were also made to allow for a universal model. This model was evaluated using published results and experimental data from 11 participants. Results show a high accuracy in the evaluation of ligament neutral length and passive joint torque. The subject-specific adaptation performance is high, with each normalized root-mean-square deviation value less than 10%. This model could be used for ankle assessment, especially in evaluating passive ankle torque, for a specific individual. The characteristic that is unique to this model is the use of three independent position variables that can be measured in real time as inputs, which makes it advantageous over other models when combined with robot-assisted therapy.

Views from Within a Narrative: Evaluating Long-Term Human-Robot Interaction in a Naturalistic Environment Using Open-Ended Scenarios.

PubMed

Syrdal, Dag Sverre; Dautenhahn, Kerstin; Koay, Kheng Lee; Ho, Wan Ching

2014-01-01

This article describes the prototyping of human-robot interactions in the University of Hertfordshire (UH) Robot House. Twelve participants took part in a long-term study in which they interacted with robots in the UH Robot House once a week for a period of 10 weeks. A prototyping method using the narrative framing technique allowed participants to engage with the robots in episodic interactions that were framed using narrative to convey the impression of a continuous long-term interaction. The goal was to examine how participants responded to the scenarios and the robots as well as specific robot behaviours, such as agent migration and expressive behaviours. Evaluation of the robots and the scenarios were elicited using several measures, including the standardised System Usability Scale, an ad hoc Scenario Acceptance Scale, as well as single-item Likert scales, open-ended questionnaire items and a debriefing interview. Results suggest that participants felt that the use of this prototyping technique allowed them insight into the use of the robot, and that they accepted the use of the robot within the scenario.

Biobotic insect swarm based sensor networks for search and rescue

NASA Astrophysics Data System (ADS)

Bozkurt, Alper; Lobaton, Edgar; Sichitiu, Mihail; Hedrick, Tyson; Latif, Tahmid; Dirafzoon, Alireza; Whitmire, Eric; Verderber, Alexander; Marin, Juan; Xiong, Hong

2014-06-01

The potential benefits of distributed robotics systems in applications requiring situational awareness, such as search-and-rescue in emergency situations, are indisputable. The efficiency of such systems requires robotic agents capable of coping with uncertain and dynamic environmental conditions. For example, after an earthquake, a tremendous effort is spent for days to reach to surviving victims where robotic swarms or other distributed robotic systems might play a great role in achieving this faster. However, current technology falls short of offering centimeter scale mobile agents that can function effectively under such conditions. Insects, the inspiration of many robotic swarms, exhibit an unmatched ability to navigate through such environments while successfully maintaining control and stability. We have benefitted from recent developments in neural engineering and neuromuscular stimulation research to fuse the locomotory advantages of insects with the latest developments in wireless networking technologies to enable biobotic insect agents to function as search-and-rescue agents. Our research efforts towards this goal include development of biobot electronic backpack technologies, establishment of biobot tracking testbeds to evaluate locomotion control efficiency, investigation of biobotic control strategies with Gromphadorhina portentosa cockroaches and Manduca sexta moths, establishment of a localization and communication infrastructure, modeling and controlling collective motion by learning deterministic and stochastic motion models, topological motion modeling based on these models, and the development of a swarm robotic platform to be used as a testbed for our algorithms.

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.

Adaptive servo control for umbilical mating

NASA Technical Reports Server (NTRS)

Zia, Omar

1988-01-01

Robotic applications at Kennedy Space Center are unique and in many cases require the fime positioning of heavy loads in dynamic environments. Performing such operations is beyond the capabilities of an off-the-shelf industrial robot. Therefore Robotics Applications Development Laboratory at Kennedy Space Center has put together an integrated system that coordinates state of the art robotic system providing an excellent easy to use testbed for NASA sensor integration experiments. This paper reviews the ways of improving the dynamic response of the robot operating under force feedback with varying dynamic internal perturbations in order to provide continuous stable operations under variable load conditions. The goal is to improve the stability of the system with force feedback using the adaptive control feature of existing system over a wide range of random motions. The effect of load variations on the dynamics and the transfer function (order or values of the parameters) of the system has been investigated, more accurate models of the system have been determined and analyzed.

Dual adaptive dynamic control of mobile robots using neural networks.

PubMed

Bugeja, Marvin K; Fabri, Simon G; Camilleri, Liberato

2009-02-01

This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.

Robot environment expert system

NASA Technical Reports Server (NTRS)

Potter, J. L.

1985-01-01

The Robot Environment Expert System uses a hexidecimal tree data structure to model a complex robot environment where not only the robot arm moves, but also the robot itself and other objects may move. The hextree model allows dynamic updating, collision avoidance and path planning over time, to avoid moving objects.

Decentralized control algorithms of a group of vehicles in 2D space

NASA Astrophysics Data System (ADS)

Pshikhopov, V. K.; Medvedev, M. Y.; Fedorenko, R. V.; Gurenko, B. V.

2017-02-01

The problem of decentralized control of group of robots, described by kinematic and dynamic equations of motion in the plane, is considered. Group performs predetermined rectangular area passing at a fixed speed, keeping the line and a uniform distribution. The environment may contain a priori unknown moving or stationary obstacles. Decentralized control algorithms, based on the formation of repellers in the state space of robots, are proposed. These repellers form repulsive forces generated by dynamic subsystems that extend the state space of robots. These repulsive forces are dynamic functions of distances and velocities of robots in the area of operation of the group. The process of formation of repellers allows to take into account the dynamic properties of robots, such as the maximum speed and acceleration. The robots local control law formulas are derived based on positionally-trajectory control method, which allows to operate with non-linear models. Lyapunov function in the form of a quadratic function of the state variables is constructed to obtain a nonlinear closed-loop control system. Due to the fact that a closed system is decomposed into two independent subsystems Lyapunov function is also constructed as two independent functions. Numerical simulation of the motion of a group of five robots is presented. In this simulation obstacles are presented by the boundaries of working area and a movable object of a given radius, moving rectilinear and uniform. Obstacle speed is comparable to the speeds of the robots in a group. The advantage of the proposed method is ensuring the stability of the trajectories and consideration of the limitations on the speed and acceleration at the trajectory planning stage. Proposed approach can be used for more general robots' models, including robots in the three-dimensional environment.

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.

Research on Snake-Like Robot with Controllable Scales

NASA Astrophysics Data System (ADS)

Chen, Kailin; Zhao, Yuting; Chen, Shuping

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

Robot dynamics in reduced gravity environment

NASA Technical Reports Server (NTRS)

Workman, Gary L.; Grisham, Tollie; Hinman, Elaine; Coker, Cindy

1990-01-01

Robot dynamics and control will become an important issue for productive platforms in space. Robotic operations will be necessary for both man tended stations and for the efficient performance of routine operations in a manned platform. The current constraints on the use of robotic devices in a microgravity environment appears to be due to safety concerns and an anticipated increase in acceleration levels due to manipulator motion. The robot used for the initial studies was a UMI RTX robot, which was adapted to operate in a materials processing workcell to simulate sample changing in a microgravity environment. The robotic cell was flown several times on the KC-135 aircraft at Ellington Field. The primary objective of the initial flights was to determine operating characteristics of both the robot and the operator in the variable gravity of the KC-135 during parabolic maneuvers. It was demonstrated that the KC-135 aircraft can be used for observing dynamics of robotic manipulators. The difficulties associated with humans performing teleoperation tasks during varying G levels were also observed and can provide insight into some areas in which the use of artificial techniques would provide improved system performance. Additionally a graphic simulation of the workcell was developed on a Silicon Graphics Workstation using the IGRIP simulation language from Deneb Robotics. The simulation is intended to be used for predictive displays of the robot operating on the aircraft. It is also anticipated that this simulation can be useful for off-line programming of tasks in the future.

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.

Robust Planning for Autonomous Navigation of Mobile Robots in Unstructured, Dynamic Environments: An LDRD Final Report

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

EISLER, G. RICHARD

This report summarizes the analytical and experimental efforts for the Laboratory Directed Research and Development (LDRD) project entitled ''Robust Planning for Autonomous Navigation of Mobile Robots In Unstructured, Dynamic Environments (AutoNav)''. The project goal was to develop an algorithmic-driven, multi-spectral approach to point-to-point navigation characterized by: segmented on-board trajectory planning, self-contained operation without human support for mission duration, and the development of appropriate sensors and algorithms to navigate unattended. The project was partially successful in achieving gains in sensing, path planning, navigation, and guidance. One of three experimental platforms, the Minimalist Autonomous Testbed, used a repetitive sense-and-re-plan combination to demonstratemore » the majority of elements necessary for autonomous navigation. However, a critical goal for overall success in arbitrary terrain, that of developing a sensor that is able to distinguish true obstacles that need to be avoided as a function of vehicle scale, still needs substantial research to bring to fruition.« less

Kinematics and dynamics of a six-degree-of-freedom robot manipulator with closed kinematic chain mechanism

NASA Technical Reports Server (NTRS)

Nguyen, Charles C.; Pooran, Farhad J.

1989-01-01

This paper deals with a class of robot manipulators built based on the kinematic chain mechanism (CKCM). This class of CKCM manipulators consists of a fixed and a moving platform coupled together via a number of in-parallel actuators. A closed-form solution is derived for the inverse kinematic problem of a six-degre-of-freedom CKCM manipulator designed to study robotic applications in space. Iterative Newton-Raphson method is employed to solve the forward kinematic problem. Dynamics of the above manipulator is derived using the Lagrangian approach. Computer simulation of the dynamical equations shows that the actuating forces are strongly dependent on the mass and centroid of the robot links.

FPGA-based fused smart sensor for dynamic and vibration parameter extraction in industrial robot links.

PubMed

Rodriguez-Donate, Carlos; Morales-Velazquez, Luis; Osornio-Rios, Roque Alfredo; Herrera-Ruiz, Gilberto; de Jesus Romero-Troncoso, Rene

2010-01-01

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA).

FPGA-Based Fused Smart Sensor for Dynamic and Vibration Parameter Extraction in Industrial Robot Links

PubMed Central

Rodriguez-Donate, Carlos; Morales-Velazquez, Luis; Osornio-Rios, Roque Alfredo; Herrera-Ruiz, Gilberto; de Jesus Romero-Troncoso, Rene

2010-01-01

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA). PMID:22319345

Robots, systems, and methods for hazard evaluation and visualization

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

Nielsen, Curtis W.; Bruemmer, David J.; Walton, Miles C.

A robot includes a hazard sensor, a locomotor, and a system controller. The robot senses a hazard intensity at a location of the robot, moves to a new location in response to the hazard intensity, and autonomously repeats the sensing and moving to determine multiple hazard levels at multiple locations. The robot may also include a communicator to communicate the multiple hazard levels to a remote controller. The remote controller includes a communicator for sending user commands to the robot and receiving the hazard levels from the robot. A graphical user interface displays an environment map of the environment proximatemore » the robot and a scale for indicating a hazard intensity. A hazard indicator corresponds to a robot position in the environment map and graphically indicates the hazard intensity at the robot position relative to the scale.« less

Framework and Implications of Virtual Neurorobotics

PubMed Central

Goodman, Philip H.; Zou, Quan; Dascalu, Sergiu-Mihai

2008-01-01

Despite decades of societal investment in artificial learning systems, truly “intelligent” systems have yet to be realized. These traditional models are based on input-output pattern optimization and/or cognitive production rule modeling. One response has been social robotics, using the interaction of human and robot to capture important cognitive dynamics such as cooperation and emotion; to date, these systems still incorporate traditional learning algorithms. More recently, investigators are focusing on the core assumptions of the brain “algorithm” itself—trying to replicate uniquely “neuromorphic” dynamics such as action potential spiking and synaptic learning. Only now are large-scale neuromorphic models becoming feasible, due to the availability of powerful supercomputers and an expanding supply of parameters derived from research into the brain's interdependent electrophysiological, metabolomic and genomic networks. Personal computer technology has also led to the acceptance of computer-generated humanoid images, or “avatars”, to represent intelligent actors in virtual realities. In a recent paper, we proposed a method of virtual neurorobotics (VNR) in which the approaches above (social-emotional robotics, neuromorphic brain architectures, and virtual reality projection) are hybridized to rapidly forward-engineer and develop increasingly complex, intrinsically intelligent systems. In this paper, we synthesize our research and related work in the field and provide a framework for VNR, with wider implications for research and practical applications. PMID:18982115

Dynamic parameter identification of robot arms with servo-controlled electrical motors

NASA Astrophysics Data System (ADS)

Jiang, Zhao-Hui; Senda, Hiroshi

2005-12-01

This paper addresses the issue of dynamic parameter identification of the robot manipulator with servo-controlled electrical motors. An assumption is made that all kinematical parameters, such as link lengths, are known, and only dynamic parameters containing mass, moment of inertia, and their functions need to be identified. First, we derive dynamics of the robot arm with a linear form of the unknown dynamic parameters by taking dynamic characteristics of the motor and servo unit into consideration. Then, we implement the parameter identification approach to identify the unknown parameters with respect to individual link separately. A pseudo-inverse matrix is used for formulation of the parameter identification. The optimal solution is guaranteed in a sense of least-squares of the mean errors. A Direct Drive (DD) SCARA type industrial robot arm AdeptOne is used as an application example of the parameter identification. Simulations and experiments for both open loop and close loop controls are carried out. Comparison of the results confirms the correctness and usefulness of the parameter identification and the derived dynamic model.

Dynamics simulation and controller interfacing for legged robots

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

Reichler, J.A.; Delcomyn, F.

2000-01-01

Dynamics simulation can play a critical role in the engineering of robotic control code, and there exist a variety of strategies both for building physical models and for interacting with these models. This paper presents an approach to dynamics simulation and controller interfacing for legged robots, and contrasts it to existing approaches. The authors describe dynamics algorithms and contact-resolution strategies for multibody articulated mobile robots based on the decoupled tree-structure approach, and present a novel scripting language that provides a unified framework for control-code interfacing, user-interface design, and data analysis. Special emphasis is placed on facilitating the rapid integration ofmore » control algorithms written in a standard object-oriented language (C++), the production of modular, distributed, reusable controllers, and the use of parameterized signal-transmission properties such as delay, sampling rate, and noise.« less

Neuromorphic meets neuromechanics, part I: the methodology and implementation

NASA Astrophysics Data System (ADS)

Niu, Chuanxin M.; Jalaleddini, Kian; Sohn, Won Joon; Rocamora, John; Sanger, Terence D.; Valero-Cuevas, Francisco J.

2017-04-01

Objective: One goal of neuromorphic engineering is to create ‘realistic’ robotic systems that interact with the physical world by adopting neuromechanical principles from biology. Critical to this is the methodology to implement the spinal circuitry responsible for the behavior of afferented muscles. At its core, muscle afferentation is the closed-loop behavior arising from the interactions among populations of muscle spindle afferents, alpha and gamma motoneurons, and muscle fibers to enable useful behaviors. Approach. We used programmable very- large-scale-circuit (VLSI) hardware to implement simple models of spiking neurons, skeletal muscles, muscle spindle proprioceptors, alpha-motoneuron recruitment, gamma motoneuron control of spindle sensitivity, and the monosynaptic circuitry connecting them. This multi-scale system of populations of spiking neurons emulated the physiological properties of a pair of antagonistic afferented mammalian muscles (each simulated by 1024 alpha- and gamma-motoneurones) acting on a joint via long tendons. Main results. This integrated system was able to maintain a joint angle, and reproduced stretch reflex responses even when driving the nonlinear biomechanics of an actual cadaveric finger. Moreover, this system allowed us to explore numerous values and combinations of gamma-static and gamma-dynamic gains when driving a robotic finger, some of which replicated some human pathological conditions. Lastly, we explored the behavioral consequences of adopting three alternative models of isometric muscle force production. We found that the dynamic responses to rate-coded spike trains produce force ramps that can be very sensitive to tendon elasticity, especially at high force output. Significance. Our methodology produced, to our knowledge, the first example of an autonomous, multi-scale, neuromorphic, neuromechanical system capable of creating realistic reflex behavior in cadaveric fingers. This research platform allows us to explore the mechanisms behind healthy and pathological sensorimotor function in the physical world by building them from first principles, and it is a precursor to neuromorphic robotic systems.

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

PubMed Central

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

2013-01-01

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

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.

The aerodynamics of free-flight maneuvers in Drosophila.

PubMed

Fry, Steven N; Sayaman, Rosalyn; Dickinson, Michael H

2003-04-18

Using three-dimensional infrared high-speed video, we captured the wing and body kinematics of free-flying fruit flies as they performed rapid flight maneuvers. We then "replayed" the wing kinematics on a dynamically scaled robotic model to measure the aerodynamic forces produced by the wings. The results show that a fly generates rapid turns with surprisingly subtle modifications in wing motion, which nonetheless generate sufficient torque for the fly to rotate its body through each turn. The magnitude and time course of the torque and body motion during rapid turns indicate that inertia, not friction, dominates the flight dynamics of insects.

Maintaining Limited-Range Connectivity Among Second-Order Agents

DTIC Science & Technology

2016-07-07

we consider ad-hoc networks of robotic agents with double integrator dynamics. For such networks, the connectivity maintenance problems are: (i) do...hoc networks of mobile autonomous agents. This loose ter- minology refers to groups of robotic agents with limited mobility and communica- tion...connectivity can be preserved. 3.1. Networks of robotic agents with second-order dynamics and the connectivity maintenance problem. We begin by

Positive effects of robotic exoskeleton training of upper limb reaching movements after stroke

PubMed Central

2012-01-01

This study, conducted in a group of nine chronic patients with right-side hemiparesis after stroke, investigated the effects of a robotic-assisted rehabilitation training with an upper limb robotic exoskeleton for the restoration of motor function in spatial reaching movements. The robotic assisted rehabilitation training was administered for a period of 6 weeks including reaching and spatial antigravity movements. To assess the carry-over of the observed improvements in movement during training into improved function, a kinesiologic assessment of the effects of the training was performed by means of motion and dynamic electromyographic analysis of reaching movements performed before and after training. The same kinesiologic measurements were performed in a healthy control group of seven volunteers, to determine a benchmark for the experimental observations in the patients’ group. Moreover degree of functional impairment at the enrolment and discharge was measured by clinical evaluation with upper limb Fugl-Meyer Assessment scale (FMA, 0–66 points), Modified Ashworth scale (MA, 0–60 pts) and active ranges of motion. The robot aided training induced, independently by time of stroke, statistical significant improvements of kinesiologic (movement time, smoothness of motion) and clinical (4.6 ± 4.2 increase in FMA, 3.2 ± 2.1 decrease in MA) parameters, as a result of the increased active ranges of motion and improved co-contraction index for shoulder extension/flexion. Kinesiologic parameters correlated significantly with clinical assessment values, and their changes after the training were affected by the direction of motion (inward vs. outward movement) and position of target to be reached (ipsilateral, central and contralateral peripersonal space). These changes can be explained as a result of the motor recovery induced by the robotic training, in terms of regained ability to execute single joint movements and of improved interjoint coordination of elbow and shoulder joints. PMID:22681653

Implementation issues for a compact 6 degree of freedom force reflecting handcontroller with cueing of modes

NASA Technical Reports Server (NTRS)

Jacobus, Heidi; Riggs, Alan J.; Jacobus, Charles; Weinstein, Yechiel

1991-01-01

Teleoperated control requires a master human interface device that can provide haptic input and output which reflect the responses of a slave robotic system. The effort reported in this paper addresses the design and prototyping of a six degree-of-freedom (DOF) Cartesian coordinate hand controller for this purpose. The device design recommended is an XYZ stage attached to a three-roll wrist which positions a flight-type handgrip. Six degrees of freedom are transduced and control brushless DC motor servo electronics similar in design to those used in computer controlled robotic manipulators. This general approach supports scaled force, velocity, and position feedback to aid an operator in achieving telepresence. The generality of the device and control system characteristics allow the use of inverse dynamics robotic control methodology to project slave robot system forces and inertias to the operator (in scaled form) and at the same time to reduce the apparent inertia of the robotic handcontroller itself. The current control design, which is not multiple fault tolerant, can be extended to make flight control or space use possible. The proposed handcontroller will have advantages in space-based applications where an operator must control several robot arms in a simultaneous and coordinated fashion. It will also have applications in intravehicular activities (within the Space Station) such as microgravity experiments in metallurgy and biological experiments that require isolation from the astronauts' environment. For ground applications, the handcontroller will be useful in underwater activities where the generality of the proposed handcontroller becomes an asset for operation of many different manipulator types. Also applications will emerge in the Military, Construction, and Maintenance/Manufacturing areas including ordnance handling, mine removal, NBC (Nuclear, Chemical, Biological) operations, control of vehicles, and operating strength and agility enhanced machines. Future avionics applications including advanced helicopter and aircraft control may also become important.

Soft brain-machine interfaces for assistive robotics: A novel control approach.

PubMed

Schiatti, Lucia; Tessadori, Jacopo; Barresi, Giacinto; Mattos, Leonardo S; Ajoudani, Arash

2017-07-01

Robotic systems offer the possibility of improving the life quality of people with severe motor disabilities, enhancing the individual's degree of independence and interaction with the external environment. In this direction, the operator's residual functions must be exploited for the control of the robot movements and the underlying dynamic interaction through intuitive and effective human-robot interfaces. Towards this end, this work aims at exploring the potential of a novel Soft Brain-Machine Interface (BMI), suitable for dynamic execution of remote manipulation tasks for a wide range of patients. The interface is composed of an eye-tracking system, for an intuitive and reliable control of a robotic arm system's trajectories, and a Brain-Computer Interface (BCI) unit, for the control of the robot Cartesian stiffness, which determines the interaction forces between the robot and environment. The latter control is achieved by estimating in real-time a unidimensional index from user's electroencephalographic (EEG) signals, which provides the probability of a neutral or active state. This estimated state is then translated into a stiffness value for the robotic arm, allowing a reliable modulation of the robot's impedance. A preliminary evaluation of this hybrid interface concept provided evidence on the effective execution of tasks with dynamic uncertainties, demonstrating the great potential of this control method in BMI applications for self-service and clinical care.

Design and Dynamic Model of a Frog-inspired Swimming Robot Powered by Pneumatic Muscles

NASA Astrophysics Data System (ADS)

Fan, Ji-Zhuang; Zhang, Wei; Kong, Peng-Cheng; Cai, He-Gao; Liu, Gang-Feng

2017-09-01

Pneumatic muscles with similar characteristics to biological muscles have been widely used in robots, and thus are promising drivers for frog inspired robots. However, the application and nonlinearity of the pneumatic system limit the advance. On the basis of the swimming mechanism of the frog, a frog-inspired robot based on pneumatic muscles is developed. To realize the independent tasks by the robot, a pneumatic system with internal chambers, micro air pump, and valves is implemented. The micro pump is used to maintain the pressure difference between the source and exhaust chambers. The pneumatic muscles are controlled by high-speed switch valves which can reduce the robot cost, volume, and mass. A dynamic model of the pneumatic system is established for the simulation to estimate the system, including the chamber, muscle, and pneumatic circuit models. The robot design is verified by the robot swimming experiments and the dynamic model is verified through the experiments and simulations of the pneumatic system. The simulation results are compared to analyze the functions of the source pressure, internal volume of the muscle, and circuit flow rate which is proved the main factor that limits the response of muscle pressure. The proposed research provides the application of the pneumatic muscles in the frog inspired robot and the pneumatic model to study muscle controller.

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

Attitudes towards care robots among Finnish home care personnel - a comparison of two approaches.

PubMed

Rantanen, Teemu; Lehto, Paula; Vuorinen, Pertti; Coco, Kirsi

2017-08-22

The significance of care robotics has been highlighted in recent years. The article examines the adoption of care robots in home care settings, and in particular Finnish home care personnel's attitudes towards robots. The study compares the importance of the Negative Attitudes towards Robots Scale advanced by Nomura and specific positive attitudes related to the usefulness of care robots for different tasks in the home care. A cross-sectional study conducted by questionnaire. The research data were gathered from a survey of Finnish home care personnel (n = 200). Exploratory factor analysis, Pearson's correlation coefficient and linear regression analysis. The Negative Attitudes towards Robots Scale (NARS), by Nomura, with a specific behavioural intention scale based on Ajzen's theory of planned behaviour, and a measure of positive attitudes towards the usefulness of care robots for different tasks in home care and the promotion of independent living of older persons. The study shows that NARS helps to explain psychological resistance related to the introduction of care robots, although the scale is susceptible to cultural differences. Care personnel's behavioural intentions related to the introduction of robot applications are influenced also by the perception of the usefulness of care robots. The study is based only on a Finnish sample, and the response rate of the study was relatively small (18.2%), which limits the generalisability of the results. The study shows that the examination of home care personnel's attitudes towards robots is not justified to focus only on one aspect, but a better explanation is achieved by combining the perspectives of societal attitudes, attitudes related to psychological reactions and the practical care and promotion of the independent living of older people. © 2017 Nordic College of Caring Science.

An efficient formulation of robot arm dynamics for control and computer simulation

NASA Astrophysics Data System (ADS)

Lee, C. S. G.; Nigam, R.

This paper describes an efficient formulation of the dynamic equations of motion of industrial robots based on the Lagrange formulation of d'Alembert's principle. This formulation, as applied to a PUMA robot arm, results in a set of closed form second order differential equations with cross product terms. They are not as efficient in computation as those formulated by the Newton-Euler method, but provide a better analytical model for control analysis and computer simulation. Computational complexities of this dynamic model together with other models are tabulated for discussion.

Integration of Gravitational Torques in Cerebellar Pathways Allows for the Dynamic Inverse Computation of Vertical Pointing Movements of a Robot Arm

PubMed Central

Gentili, Rodolphe J.; Papaxanthis, Charalambos; Ebadzadeh, Mehdi; Eskiizmirliler, Selim; Ouanezar, Sofiane; Darlot, Christian

2009-01-01

Background Several authors suggested that gravitational forces are centrally represented in the brain for planning, control and sensorimotor predictions of movements. Furthermore, some studies proposed that the cerebellum computes the inverse dynamics (internal inverse model) whereas others suggested that it computes sensorimotor predictions (internal forward model). Methodology/Principal Findings This study proposes a model of cerebellar pathways deduced from both biological and physical constraints. The model learns the dynamic inverse computation of the effect of gravitational torques from its sensorimotor predictions without calculating an explicit inverse computation. By using supervised learning, this model learns to control an anthropomorphic robot arm actuated by two antagonists McKibben artificial muscles. This was achieved by using internal parallel feedback loops containing neural networks which anticipate the sensorimotor consequences of the neural commands. The artificial neural networks architecture was similar to the large-scale connectivity of the cerebellar cortex. Movements in the sagittal plane were performed during three sessions combining different initial positions, amplitudes and directions of movements to vary the effects of the gravitational torques applied to the robotic arm. The results show that this model acquired an internal representation of the gravitational effects during vertical arm pointing movements. Conclusions/Significance This is consistent with the proposal that the cerebellar cortex contains an internal representation of gravitational torques which is encoded through a learning process. Furthermore, this model suggests that the cerebellum performs the inverse dynamics computation based on sensorimotor predictions. This highlights the importance of sensorimotor predictions of gravitational torques acting on upper limb movements performed in the gravitational field. PMID:19384420

Robot assistance of motor learning: A neuro-cognitive perspective.

PubMed

Heuer, Herbert; Lüttgen, Jenna

2015-09-01

The last several years have seen a number of approaches to robot assistance of motor learning. Experimental studies have produced a range of findings from beneficial effects through null-effects to detrimental effects of robot assistance. In this review we seek an answer to the question under which conditions which outcomes should be expected. For this purpose we derive tentative predictions based on a classification of learning tasks in terms of the products of learning, the mechanisms involved, and the modulation of these mechanisms by robot assistance. Consistent with these predictions, the learning of dynamic features of trajectories is facilitated and the learning of kinematic and dynamic transformations is impeded by robotic guidance, whereas the learning of dynamic transformations can profit from robot assistance with error-amplifying forces. Deviating from the predictions, learning of spatial features of trajectories is impeded by haptic guidance, but can be facilitated by divergent force fields. The deviations point to the existence of additional effects of robot assistance beyond the modulation of learning mechanisms, e.g., the induction of a passive role of the motor system during practice with haptic guidance. Copyright © 2015 Elsevier Ltd. All rights reserved.

System Design and Locomotion of Superball, an Untethered Tensegrity Robot

NASA Technical Reports Server (NTRS)

Sabelhaus, Andrew P.; Bruce, Jonathan; Caluwaerts, Ken; Manovi, Pavlo; Firoozi, Roya Fallah; Dobi, Sarah; Agogino, Alice M.; Sunspiral, Vytas

2015-01-01

The Spherical Underactuated Planetary Exploration Robot ball (SUPERball) is an ongoing project within NASA Ames Research Center's Intelligent Robotics Group and the Dynamic Tensegrity Robotics Lab (DTRL). The current SUPERball is the first full prototype of this tensegrity robot platform, eventually destined for space exploration missions. This work, building on prior published discussions of individual components, presents the fully-constructed robot. Various design improvements are discussed, as well as testing results of the sensors and actuators that illustrate system performance. Basic low-level motor position controls are implemented and validated against sensor data, which show SUPERball to be uniquely suited for highly dynamic state trajectory tracking. Finally, SUPERball is shown in a simple example of locomotion. This implementation of a basic motion primitive shows SUPERball in untethered control.

Development of a revolute-joint robot for the precision positioning of an x-ray detector

NASA Astrophysics Data System (ADS)

Preissner, Curt A.; Royston, Thomas J.; Shu, Deming

2003-10-01

This paper profiles the initial phase in the development of a six degree-of-freedom robot, with 1 μm dynamic positioning uncertainty, for the manipulation of x-ray detectors or test specimens at the Advanced Photon Source (APS). While revolute-joint robot manipulators exhibit a smaller footprint along with increased positioning flexibility compared to Cartesian manipulators, commercially available revolute-joint manipulators do not meet our size, positioning, or environmental specifications. Currently, a robot with 20 μm dynamic positioning uncertainty is functioning at the APS for cryogenic crystallography sample pick-and-place operation. Theoretical, computational and experimental procedures are being used to (1) identify and (2) simulate the dynamics of the present robot system using a multibody approach, including the mechanics and control architecture, and eventually to (3) design an improved version with a 1 μm dynamic positioning uncertainty. We expect that the preceding experimental and theoretical techniques will be useful design and analysis tools as multi-degree-of-freedom manipulators become more prevalent on synchrotron beamlines.

Acquisition of Robotic Giant-swing Motion Using Reinforcement Learning and Its Consideration of Motion Forms

NASA Astrophysics Data System (ADS)

Sakai, Naoki; Kawabe, Naoto; Hara, Masayuki; Toyoda, Nozomi; Yabuta, Tetsuro

This paper argues how a compact humanoid robot can acquire a giant-swing motion without any robotic models by using Q-Learning method. Generally, it is widely said that Q-Learning is not appropriated for learning dynamic motions because Markov property is not necessarily guaranteed during the dynamic task. However, we tried to solve this problem by embedding the angular velocity state into state definition and averaging Q-Learning method to reduce dynamic effects, although there remain non-Markov effects in the learning results. The result shows how the robot can acquire a giant-swing motion by using Q-Learning algorithm. The successful acquired motions are analyzed in the view point of dynamics in order to realize a functionally giant-swing motion. Finally, the result shows how this method can avoid the stagnant action loop at around the bottom of the horizontal bar during the early stage of giant-swing motion.

Adaptive control of an exoskeleton robot with uncertainties on kinematics and dynamics.

PubMed

Brahmi, Brahim; Saad, Maarouf; Ochoa-Luna, Cristobal; Rahman, Mohammad H

2017-07-01

In this paper, we propose a new adaptive control technique based on nonlinear sliding mode control (JSTDE) taking into account kinematics and dynamics uncertainties. This approach is applied to an exoskeleton robot with uncertain kinematics and dynamics. The adaptation design is based on Time Delay Estimation (TDE). The proposed strategy does not necessitate the well-defined dynamic and kinematic models of the system robot. The updated laws are designed using Lyapunov-function to solve the adaptation problem systematically, proving the close loop stability and ensuring the convergence asymptotically of the outputs tracking errors. Experiments results show the effectiveness and feasibility of JSTDE technique to deal with the variation of the unknown nonlinear dynamics and kinematics of the exoskeleton model.

An adaptive actuator failure compensation scheme for two linked 2WD mobile robots

NASA Astrophysics Data System (ADS)

Ma, Yajie; Al-Dujaili, Ayad; Cocquempot, Vincent; El Badaoui El Najjar, Maan

2017-01-01

This paper develops a new adaptive compensation control scheme for two linked mobile robots with actuator failurs. A configuration with two linked two-wheel drive (2WD) mobile robots is proposed, and the modelling of its kinematics and dynamics are given. An adaptive failure compensation scheme is developed to compensate actuator failures, consisting of a kinematic controller and a multi-design integration based dynamic controller. The kinematic controller is a virtual one, and based on which, multiple adaptive dynamic control signals are designed which covers all possible failure cases. By combing these dynamic control signals, the dynamic controller is designed, which ensures system stability and asymptotic tracking properties. Simulation results verify the effectiveness of the proposed adaptive failure compensation scheme.

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.

Fruit fly scale robots can hover longer with flapping wings than with spinning wings.

PubMed

Hawkes, Elliot W; Lentink, David

2016-10-01

Hovering flies generate exceptionally high lift, because their wings generate a stable leading edge vortex. Micro flying robots with a similar wing design can generate similar high lift by either flapping or spinning their wings. While it requires less power to spin a wing, the overall efficiency depends also on the actuator system driving the wing. Here, we present the first holistic analysis to calculate how long a fly-inspired micro robot can hover with flapping versus spinning wings across scales. We integrate aerodynamic data with data-driven scaling laws for actuator, electronics and mechanism performance from fruit fly to hummingbird scales. Our analysis finds that spinning wings driven by rotary actuators are superior for robots with wingspans similar to hummingbirds, yet flapping wings driven by oscillatory actuators are superior at fruit fly scale. This crossover is driven by the reduction in performance of rotary compared with oscillatory actuators at smaller scale. Our calculations emphasize that a systems-level analysis is essential for trading-off flapping versus spinning wings for micro flying robots. © 2016 The Author(s).

Fruit fly scale robots can hover longer with flapping wings than with spinning wings

PubMed Central

Lentink, David

2016-01-01

Hovering flies generate exceptionally high lift, because their wings generate a stable leading edge vortex. Micro flying robots with a similar wing design can generate similar high lift by either flapping or spinning their wings. While it requires less power to spin a wing, the overall efficiency depends also on the actuator system driving the wing. Here, we present the first holistic analysis to calculate how long a fly-inspired micro robot can hover with flapping versus spinning wings across scales. We integrate aerodynamic data with data-driven scaling laws for actuator, electronics and mechanism performance from fruit fly to hummingbird scales. Our analysis finds that spinning wings driven by rotary actuators are superior for robots with wingspans similar to hummingbirds, yet flapping wings driven by oscillatory actuators are superior at fruit fly scale. This crossover is driven by the reduction in performance of rotary compared with oscillatory actuators at smaller scale. Our calculations emphasize that a systems-level analysis is essential for trading-off flapping versus spinning wings for micro flying robots. PMID:27707903

Drift-Free Humanoid State Estimation fusing Kinematic, Inertial and LIDAR Sensing

DTIC Science & Technology

2014-08-01

registration to this map and other objects in the robot’s vicinity while also contributing to direct low-level control of a Boston Dynamics Atlas robot ...requirements. I. INTRODUCTION Dynamic locomotion of legged robotic systems remains an open and challenging research problem whose solution will enable...humanoids to perform tasks and reach places inaccessible to wheeled or tracked robots . Several research institutions are developing walking and running

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.

Jerk-level synchronous repetitive motion scheme with gradient-type and zeroing-type dynamics algorithms applied to dual-arm redundant robot system control

NASA Astrophysics Data System (ADS)

Chen, Dechao; Zhang, Yunong

2017-10-01

Dual-arm redundant robot systems are usually required to handle primary tasks, repetitively and synchronously in practical applications. In this paper, a jerk-level synchronous repetitive motion scheme is proposed to remedy the joint-angle drift phenomenon and achieve the synchronous control of a dual-arm redundant robot system. The proposed scheme is novelly resolved at jerk level, which makes the joint variables, i.e. joint angles, joint velocities and joint accelerations, smooth and bounded. In addition, two types of dynamics algorithms, i.e. gradient-type (G-type) and zeroing-type (Z-type) dynamics algorithms, for the design of repetitive motion variable vectors, are presented in detail with the corresponding circuit schematics. Subsequently, the proposed scheme is reformulated as two dynamical quadratic programs (DQPs) and further integrated into a unified DQP (UDQP) for the synchronous control of a dual-arm robot system. The optimal solution of the UDQP is found by the piecewise-linear projection equation neural network. Moreover, simulations and comparisons based on a six-degrees-of-freedom planar dual-arm redundant robot system substantiate the operation effectiveness and tracking accuracy of the robot system with the proposed scheme for repetitive motion and synchronous control.

Measurement of hand dynamics in a microsurgery environment: Preliminary data in the design of a bimanual telemicro-operation test bed

NASA Technical Reports Server (NTRS)

Charles, Steve; Williams, Roy

1989-01-01

Data describing the microsurgeon's hand dynamics was recorded and analyzed in order to provide an accurate model for the telemicrosurgery application of the Bimanual Telemicro-operation Test Bed. The model, in turn, will guide the development of algorithms for the control of robotic systems in bimanual telemicro-operation tasks. Measurements were made at the hand-tool interface and include position, acceleration and force between the tool-finger interface. Position information was captured using an orthogonal pulsed magnetic field positioning system resulting in measurements in all six degrees-of-freedom (DOF). Acceleration data at the hands was obtained using accelerometers positioned in a triaxial arrangement on the back of the hand allowing measurements in all three cartesian-coordinate axes. Force data was obtained by using miniature load cells positioned between the tool and the finger and included those forces experienced perpendicular to the tool shaft and those transferred from the tool-tissue site. Position data will provide a minimum/maximum reference frame for the robotic system's work space or envelope. Acceleration data will define the response times needed by the robotic system in order to emulate and subsequently outperform the human operator's tool movements. The force measurements will aid in designing a force-reflective, force-scaling system as well as defining the range of forces the robotic system will encounter. All analog data was acquired by a 16-channel analog-to-digital conversion system residing in a IBM PC/AT-compatible computer at the Center's laboratory. The same system was also used to analyze and present the data.

Achieving bioinspired flapping wing hovering flight solutions on Mars via wing scaling.

PubMed

Bluman, James E; Pohly, Jeremy; Sridhar, Madhu; Kang, Chang-Kwon; Landrum, David Brian; Fahimi, Farbod; Aono, Hikaru

2018-05-29

Achieving atmospheric flight on Mars is challenging due to the low density of the Martian atmosphere. Aerodynamic forces are proportional to the atmospheric density, which limits the use of conventional aircraft designs on Mars. Here, we show using numerical simulations that a flapping wing robot can fly on Mars via bioinspired dynamic scaling. Trimmed, hovering flight is possible in a simulated Martian environment when dynamic similarity with insects on earth is achieved by preserving the relevant dimensionless parameters while scaling up the wings three to four times its normal size. The analysis is performed using a well-validated two-dimensional Navier-Stokes equation solver, coupled to a three-dimensional flight dynamics model to simulate free flight. The majority of power required is due to the inertia of the wing because of the ultra-low density. The inertial flap power can be substantially reduced through the use of a torsional spring. The minimum total power consumption is 188 W/kg when the torsional spring is driven at its natural frequency. © 2018 IOP Publishing Ltd.

Dynamic force signal processing system of a robot manipulator

NASA Technical Reports Server (NTRS)

Uchiyama, M.; Kitagaki, K.; Hakomori, K.

1987-01-01

If dynamic noises such as those caused by the inertia forces of the hand can be eliminated from the signal of the force sensor installed on the wrist of the robot manipulator and if the necessary information of the external force can be detected with high sensitivity and high accuracy, a fine force feedback control for robots used in high speed and various fields will be possible. As the dynamic force sensing system, an external force estimate method with the extended Kalman filter is suggested and simulations and tests for a one axis force were performed. Later a dynamic signal processing system of six axes was composed and tested. The results are presented.

Dynamic modeling and optimal joint torque coordination of advanced robotic systems

NASA Astrophysics Data System (ADS)

Kang, Hee-Jun

The development is documented of an efficient dynamic modeling algorithm and the subsequent optimal joint input load coordination of advanced robotic systems for industrial application. A closed-form dynamic modeling algorithm for the general closed-chain robotic linkage systems is presented. The algorithm is based on the transfer of system dependence from a set of open chain Lagrangian coordinates to any desired system generalized coordinate set of the closed-chain. Three different techniques for evaluation of the kinematic closed chain constraints allow the representation of the dynamic modeling parameters in terms of system generalized coordinates and have no restriction with regard to kinematic redundancy. The total computational requirement of the closed-chain system model is largely dependent on the computation required for the dynamic model of an open kinematic chain. In order to improve computational efficiency, modification of an existing open-chain KIC based dynamic formulation is made by the introduction of the generalized augmented body concept. This algorithm allows a 44 pct. computational saving over the current optimized one (O(N4), 5995 when N = 6). As means of resolving redundancies in advanced robotic systems, local joint torque optimization is applied for effectively using actuator power while avoiding joint torque limits. The stability problem in local joint torque optimization schemes is eliminated by using fictitious dissipating forces which act in the necessary null space. The performance index representing the global torque norm is shown to be satisfactory. In addition, the resulting joint motion trajectory becomes conservative, after a transient stage, for repetitive cyclic end-effector trajectories. The effectiveness of the null space damping method is shown. The modular robot, which is built of well defined structural modules from a finite-size inventory and is controlled by one general computer system, is another class of evolving, highly versatile, advanced robotic systems. Therefore, finally, a module based dynamic modeling algorithm is presented for the dynamic coordination of such reconfigurable modular robotic systems. A user interactive module based manipulator analysis program (MBMAP) has been coded in C language running on 4D/70 Silicon Graphics.

Towards quantifying dynamic human-human physical interactions for robot assisted stroke therapy.

PubMed

Mohan, Mayumi; Mendonca, Rochelle; Johnson, Michelle J

2017-07-01

Human-Robot Interaction is a prominent field of robotics today. Knowledge of human-human physical interaction can prove vital in creating dynamic physical interactions between human and robots. Most of the current work in studying this interaction has been from a haptic perspective. Through this paper, we present metrics that can be used to identify if a physical interaction occurred between two people using kinematics. We present a simple Activity of Daily Living (ADL) task which involves a simple interaction. We show that we can use these metrics to successfully identify interactions.

Dynamic traversal of large gaps by insects and legged robots reveals a template.

PubMed

Gart, Sean W; Yan, Changxin; Othayoth, Ratan; Ren, Zhiyi; Li, Chen

2018-02-02

It is well known that animals can use neural and sensory feedback via vision, tactile sensing, and echolocation to negotiate obstacles. Similarly, most robots use deliberate or reactive planning to avoid obstacles, which relies on prior knowledge or high-fidelity sensing of the environment. However, during dynamic locomotion in complex, novel, 3D terrains, such as a forest floor and building rubble, sensing and planning suffer bandwidth limitation and large noise and are sometimes even impossible. Here, we study rapid locomotion over a large gap-a simple, ubiquitous obstacle-to begin to discover the general principles of the dynamic traversal of large 3D obstacles. We challenged the discoid cockroach and an open-loop six-legged robot to traverse a large gap of varying length. Both the animal and the robot could dynamically traverse a gap as large as one body length by bridging the gap with its head, but traversal probability decreased with gap length. Based on these observations, we developed a template that accurately captured body dynamics and quantitatively predicted traversal performance. Our template revealed that a high approach speed, initial body pitch, and initial body pitch angular velocity facilitated dynamic traversal, and successfully predicted a new strategy for using body pitch control that increased the robot's maximal traversal gap length by 50%. Our study established the first template of dynamic locomotion beyond planar surfaces, and is an important step in expanding terradynamics into complex 3D terrains.

A review on the mechanical design elements of ankle rehabilitation robot.

PubMed

Khalid, Yusuf M; Gouwanda, Darwin; Parasuraman, Subramanian

2015-06-01

Ankle rehabilitation robots are developed to enhance ankle strength, flexibility and proprioception after injury and to promote motor learning and ankle plasticity in patients with drop foot. This article reviews the design elements that have been incorporated into the existing robots, for example, backdrivability, safety measures and type of actuation. It also discusses numerous challenges faced by engineers in designing this robot, including robot stability and its dynamic characteristics, universal evaluation criteria to assess end-user comfort, safety and training performance and the scientific basis on the optimal rehabilitation strategies to improve ankle condition. This article can serve as a reference to design robot with better stability and dynamic characteristics and good safety measures against internal and external events. It can also serve as a guideline for the engineers to report their designs and findings. © IMechE 2015.

Robot path planning algorithm based on symbolic tags in dynamic environment

NASA Astrophysics Data System (ADS)

Vokhmintsev, A.; Timchenko, M.; Melnikov, A.; Kozko, A.; Makovetskii, A.

2017-09-01

The present work will propose a new heuristic algorithms for path planning of a mobile robot in an unknown dynamic space that have theoretically approved estimates of computational complexity and are approbated for solving specific applied problems.

The application of virtual prototyping methods to determine the dynamic parameters of mobile robot

NASA Astrophysics Data System (ADS)

Kurc, Krzysztof; Szybicki, Dariusz; Burghardt, Andrzej; Muszyńska, Magdalena

2016-04-01

The paper presents methods used to determine the parameters necessary to build a mathematical model of an underwater robot with a crawler drive. The parameters present in the dynamics equation will be determined by means of advanced mechatronic design tools, including: CAD/CAE software andMES modules. The virtual prototyping process is described as well as the various possible uses (design adaptability) depending on the optional accessories added to the vehicle. A mathematical model is presented to show the kinematics and dynamics of the underwater crawler robot, essential for the design stage.

Dimensionality Reduction in Controlling Articulated Snake Robot for Endoscopy Under Dynamic Active Constraints

PubMed Central

Kwok, Ka-Wai; Tsoi, Kuen Hung; Vitiello, Valentina; Clark, James; Chow, Gary C. T.; Luk, Wayne; Yang, Guang-Zhong

2014-01-01

This paper presents a real-time control framework for a snake robot with hyper-kinematic redundancy under dynamic active constraints for minimally invasive surgery. A proximity query (PQ) formulation is proposed to compute the deviation of the robot motion from predefined anatomical constraints. The proposed method is generic and can be applied to any snake robot represented as a set of control vertices. The proposed PQ formulation is implemented on a graphic processing unit, allowing for fast updates over 1 kHz. We also demonstrate that the robot joint space can be characterized into lower dimensional space for smooth articulation. A novel motion parameterization scheme in polar coordinates is proposed to describe the transition of motion, thus allowing for direct manual control of the robot using standard interface devices with limited degrees of freedom. Under the proposed framework, the correct alignment between the visual and motor axes is ensured, and haptic guidance is provided to prevent excessive force applied to the tissue by the robot body. A resistance force is further incorporated to enhance smooth pursuit movement matched to the dynamic response and actuation limit of the robot. To demonstrate the practical value of the proposed platform with enhanced ergonomic control, detailed quantitative performance evaluation was conducted on a group of subjects performing simulated intraluminal and intracavity endoscopic tasks. PMID:24741371

Dynamic modeling of parallel robots for computed-torque control implementation

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

Codourey, A.

1998-12-01

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

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

Experimental Robot Model Adjustments Based on Force–Torque Sensor Information

PubMed Central

2018-01-01

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

Simulating the dynamic interaction of a robotic arm and the Space Shuttle remote manipulator system. M.S. Thesis - George Washington Univ., Dec. 1994

NASA Technical Reports Server (NTRS)

Garrahan, Steven L.; Tolson, Robert H.; Williams, Robert L., II

1995-01-01

Industrial robots are usually attached to a rigid base. Placing the robot on a compliant base introduces dynamic coupling between the two systems. The Vehicle Emulation System (VES) is a six DOF platform that is capable of modeling this interaction. The VES employs a force-torque sensor as the interface between robot and base. A computer simulation of the VES is presented. Each of the hardware and software components is described and Simulink is used as the programming environment. The simulation performance is compared with experimental results to validate accuracy. A second simulation which models the dynamic interaction of a robot and a flexible base acts as a comparison to the simulated motion of the VES. Results are presented that compare the simulated VES motion with the motion of the VES hardware using the same admittance model. The two computer simulations are compared to determine how well the VES is expected to emulate the desired motion. Simulation results are given for robots mounted to the end effector of the Space Shuttle Remote Manipulator System (SRMS). It is shown that for fast motions of the two robots studied, the SRMS experiences disturbances on the order of centimeters. Larger disturbances are possible if different manipulators are used.

The use of the articulated total body model as a robot dynamics simulation tool

NASA Technical Reports Server (NTRS)

Obergfell, Louise A.; Avula, Xavier J. R.; Kalegs, Ints

1988-01-01

The Articulated Total Body (ATB) model is a computer sumulation program which was originally developed for the study of aircrew member dynamics during ejection from high-speed aircraft. This model is totally three-dimensional and is based on the rigid body dynamics of coupled systems which use Euler's equations of motion with constraint relations of the type employed in the Lagrange method. In this paper the use of the ATB model as a robot dynamics simulation tool is discussed and various simulations are demonstrated. For this purpose the ATB model has been modified to allow for the application of torques at the joints as functions of state variables of the system. Specifically, the motion of a robotic arm with six revolute articulations with joint torques prescribed as functions of angular displacement and angular velocity are demonstrated. The simulation procedures developed in this work may serve as valuable tools for analyzing robotic mechanisms, dynamic effects, joint load transmissions, feed-back control algorithms employed in the actuator control and end-effector trajectories.

Robot Control Based On Spatial-Operator Algebra

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo; Kreutz, Kenneth K.; Jain, Abhinandan

1992-01-01

Method for mathematical modeling and control of robotic manipulators based on spatial-operator algebra providing concise representation and simple, high-level theoretical frame-work for solution of kinematical and dynamical problems involving complicated temporal and spatial relationships. Recursive algorithms derived immediately from abstract spatial-operator expressions by inspection. Transition from abstract formulation through abstract solution to detailed implementation of specific algorithms to compute solution greatly simplified. Complicated dynamical problems like two cooperating robot arms solved more easily.

Study on general theory of kinematics and dynamics of wheeled mobile robots

NASA Astrophysics Data System (ADS)

Tsukishima, Takahiro; Sasaki, Ken; Takano, Masaharu; Inoue, Kenji

1992-03-01

This paper proposes a general theory of kinematics and dynamics of wheeled mobile robots (WMRs). Unlike robotic manipulators which are modeled as 3-dimensional serial link mechanism, WMRs will be modeled as planar linkage mechanism with multiple links branching out from the base and/or another link. Since this model resembles a tree with branches, it will be called 'tree-structured-link'. The end of each link corresponds to the wheel which is in contact with the floor. In dynamics of WMR, equation of motion of a WMR is derived from joint input torques incorporating wheel dynamics. The wheel dynamics determines forces and moments acting on wheels as a function of slip velocity. This slippage of wheels is essential in dynamics of WMR. It will also be shown that the dynamics of WMR reduces to kinematics when slippage of wheels is neglected. Furthermore, the equation of dynamics is rewritten in velocity input form, since most of industrial motors are velocity controlled.

Workspace Safe Operation of a Force- or Impedance-Controlled Robot

NASA Technical Reports Server (NTRS)

Abdallah, Muhammad E. (Inventor); Hargrave, Brian (Inventor); Strawser, Philip A. (Inventor); Yamokoski, John D. (Inventor)

2013-01-01

A method of controlling a robotic manipulator of a force- or impedance-controlled robot within an unstructured workspace includes imposing a saturation limit on a static force applied by the manipulator to its surrounding environment, and may include determining a contact force between the manipulator and an object in the unstructured workspace, and executing a dynamic reflex when the contact force exceeds a threshold to thereby alleviate an inertial impulse not addressed by the saturation limited static force. The method may include calculating a required reflex torque to be imparted by a joint actuator to a robotic joint. A robotic system includes a robotic manipulator having an unstructured workspace and a controller that is electrically connected to the manipulator, and which controls the manipulator using force- or impedance-based commands. The controller, which is also disclosed herein, automatically imposes the saturation limit and may execute the dynamic reflex noted above.

Ndarts

NASA Technical Reports Server (NTRS)

Jain, Abhinandan

2011-01-01

Ndarts software provides algorithms for computing quantities associated with the dynamics of articulated, rigid-link, multibody systems. It is designed as a general-purpose dynamics library that can be used for the modeling of robotic platforms, space vehicles, molecular dynamics, and other such applications. The architecture and algorithms in Ndarts are based on the Spatial Operator Algebra (SOA) theory for computational multibody and robot dynamics developed at JPL. It uses minimal, internal coordinate models. The algorithms are low-order, recursive scatter/ gather algorithms. In comparison with the earlier Darts++ software, this version has a more general and cleaner design needed to support a larger class of computational dynamics needs. It includes a frames infrastructure, allows algorithms to operate on subgraphs of the system, and implements lazy and deferred computation for better efficiency. Dynamics modeling modules such as Ndarts are core building blocks of control and simulation software for space, robotic, mechanism, bio-molecular, and material systems modeling.

New Factorization Techniques and Parallel (log N) Algorithms for Forward Dynamics Solution of Single Closed-Chain Robot Manipulators

NASA Technical Reports Server (NTRS)

Fijany, Amir

1993-01-01

In this paper parallel 0(log N) algorithms for dynamic simulation of single closed-chain rigid multibody system as specialized to the case of a robot manipulatoar in contact with the environment are developed.

Control of articulated snake robot under dynamic active constraints.

PubMed

Kwok, Ka-Wai; Vitiello, Valentina; Yang, Guang-Zhong

2010-01-01

Flexible, ergonomically enhanced surgical robots have important applications to transluminal endoscopic surgery, for which path-following and dynamic shape conformance are essential. In this paper, kinematic control of a snake robot for motion stabilisation under dynamic active constraints is addressed. The main objective is to enable the robot to track the visual target accurately and steadily on deforming tissue whilst conforming to pre-defined anatomical constraints. The motion tracking can also be augmented with manual control. By taking into account the physical limits in terms of maximum frequency response of the system (manifested as a delay between the input of the manipulator and the movement of the end-effector), we show the importance of visual-motor synchronisation for performing accurate smooth pursuit movements. Detailed user experiments are performed to demonstrate the practical value of the proposed control mechanism.

Nanoliter-Scale Protein Crystallization and Screening with a Microfluidic Droplet Robot

PubMed Central

Zhu, Ying; Zhu, Li-Na; Guo, Rui; Cui, Heng-Jun; Ye, Sheng; Fang, Qun

2014-01-01

Large-scale screening of hundreds or even thousands of crystallization conditions while with low sample consumption is in urgent need, in current structural biology research. Here we describe a fully-automated droplet robot for nanoliter-scale crystallization screening that combines the advantages of both automated robotics technique for protein crystallization screening and the droplet-based microfluidic technique. A semi-contact dispensing method was developed to achieve flexible, programmable and reliable liquid-handling operations for nanoliter-scale protein crystallization experiments. We applied the droplet robot in large-scale screening of crystallization conditions of five soluble proteins and one membrane protein with 35–96 different crystallization conditions, study of volume effects on protein crystallization, and determination of phase diagrams of two proteins. The volume for each droplet reactor is only ca. 4–8 nL. The protein consumption significantly reduces 50–500 fold compared with current crystallization stations. PMID:24854085

Nanoliter-scale protein crystallization and screening with a microfluidic droplet robot.

PubMed

Zhu, Ying; Zhu, Li-Na; Guo, Rui; Cui, Heng-Jun; Ye, Sheng; Fang, Qun

2014-05-23

Large-scale screening of hundreds or even thousands of crystallization conditions while with low sample consumption is in urgent need, in current structural biology research. Here we describe a fully-automated droplet robot for nanoliter-scale crystallization screening that combines the advantages of both automated robotics technique for protein crystallization screening and the droplet-based microfluidic technique. A semi-contact dispensing method was developed to achieve flexible, programmable and reliable liquid-handling operations for nanoliter-scale protein crystallization experiments. We applied the droplet robot in large-scale screening of crystallization conditions of five soluble proteins and one membrane protein with 35-96 different crystallization conditions, study of volume effects on protein crystallization, and determination of phase diagrams of two proteins. The volume for each droplet reactor is only ca. 4-8 nL. The protein consumption significantly reduces 50-500 fold compared with current crystallization stations.

Development and application of a microarray meter tool to optimize microarray experiments

PubMed Central

Rouse, Richard JD; Field, Katrine; Lapira, Jennifer; Lee, Allen; Wick, Ivan; Eckhardt, Colleen; Bhasker, C Ramana; Soverchia, Laura; Hardiman, Gary

2008-01-01

Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization) using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray) manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of variability of the spot morphologies. PMID:18710498

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.

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

NASA Astrophysics Data System (ADS)

Cao, Zhengcai; Yin, Longjie; Fu, Yili

2013-01-01

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

Autonomy in robots and other agents.

PubMed

Smithers, T

1997-06-01

The word "autonomous" has become widely used in artificial intelligence, robotics, and, more recently, artificial life and is typically used to qualify types of systems, agents, or robots: we see terms like "autonomous systems," "autonomous agents," and "autonomous robots." Its use in these fields is, however, both weak, with no distinctions being made that are not better and more precisely made with other existing terms, and varied, with no single underlying concept being involved. This ill-disciplined usage contrasts strongly with the use of the same term in other fields such as biology, philosophy, ethics, law, and human rights, for example. In all these quite different areas the concept of autonomy is essentially the same, though the language used and the aspects and issues of concern, of course, differ. In all these cases the underlying notion is one of self-law making and the closely related concept of self-identity. In this paper I argue that the loose and varied use of the term autonomous in artificial intelligence, robotics, and artificial life has effectively robbed these fields of an important concept. A concept essentially the same as we find it in biology, philosophy, ethics, and law, and one that is needed to distinguish a particular kind of agent or robot from those developed and built so far. I suggest that robots and other agents will have to be autonomous, i.e., self-law making, not just self-regulating, if they are to be able effectively to deal with the kinds of environments in which we live and work: environments which have significant large scale spatial and temporal invariant structure, but which also have large amounts of local spatial and temporal dynamic variation and unpredictability, and which lead to the frequent occurrence of previously unexperienced situations for the agents that interact with them.

The dynamics and control of a spherical robot with an internal omniwheel platform

NASA Astrophysics Data System (ADS)

Karavaev, Yury L.; Kilin, Alexander A.

2015-03-01

This paper deals with the problem of a spherical robot propelled by an internal omniwheel platform and rolling without slipping on a plane. The problem of control of spherical robot motion along an arbitrary trajectory is solved within the framework of a kinematic model and a dynamic model. A number of particular cases of motion are identified, and their stability is investigated. An algorithm for constructing elementary maneuvers (gaits) providing the transition from one steady-state motion to another is presented for the dynamic model. A number of experiments have been carried out confirming the adequacy of the proposed kinematic model.

Simulation of cooperating robot manipulators on a mobile platform

NASA Technical Reports Server (NTRS)

Murphy, Stephen H.; Wen, John Ting-Yung; Saridis, George N.

1991-01-01

The dynamic equations of motion are presented for two or more cooperating manipulators on a freely moving mobile platform. The system of cooperating robot manipulators forms a closed kinematic chain where the force of interaction must be included in the formulation of robot and platform dynamics. The formulation includes the full dynamic interactions from arms to platform and arm tip to arm tip, and the possible translation and rotation of the platform. The equations of motion are shown to be identical in structure to the fixed-platform cooperative manipulator dynamics. The number of DOFs of the system is sufficiently large to make recursive dynamic calculation methods potentially more efficient than closed-form solutions. A complete simulation with two 6-DOF manipulators of a free-floating platform is presented along a with a multiple-arm controller to position the common load.

Task path planning, scheduling and learning for free-ranging robot systems

NASA Technical Reports Server (NTRS)

Wakefield, G. Steve

1987-01-01

The development of robotics applications for space operations is often restricted by the limited movement available to guided robots. Free ranging robots can offer greater flexibility than physically guided robots in these applications. Presented here is an object oriented approach to path planning and task scheduling for free-ranging robots that allows the dynamic determination of paths based on the current environment. The system also provides task learning for repetitive jobs. This approach provides a basis for the design of free-ranging robot systems which are adaptable to various environments and tasks.

An integrated gait rehabilitation training based on Functional Electrical Stimulation cycling and overground robotic exoskeleton in complete spinal cord injury patients: Preliminary results.

PubMed

Mazzoleni, S; Battini, E; Rustici, A; Stampacchia, G

2017-07-01

The aim of this study is to investigate the effects of an integrated gait rehabilitation training based on Functional Electrical Stimulation (FES)-cycling and overground robotic exoskeleton in a group of seven complete spinal cord injury patients on spasticity and patient-robot interaction. They underwent a robot-assisted rehabilitation training based on two phases: n=20 sessions of FES-cycling followed by n= 20 sessions of robot-assisted gait training based on an overground robotic exoskeleton. The following clinical outcome measures were used: Modified Ashworth Scale (MAS), Numerical Rating Scale (NRS) on spasticity, Penn Spasm Frequency Scale (PSFS), Spinal Cord Independence Measure Scale (SCIM), NRS on pain and International Spinal Cord Injury Pain Data Set (ISCI). Clinical outcome measures were assessed before (T0) after (T1) the FES-cycling training and after (T2) the powered overground gait training. The ability to walk when using exoskeleton was assessed by means of 10 Meter Walk Test (10MWT), 6 Minute Walk Test (6MWT), Timed Up and Go test (TUG), standing time, walking time and number of steps. Statistically significant changes were found on the MAS score, NRS-spasticity, 6MWT, TUG, standing time and number of steps. The preliminary results of this study show that an integrated gait rehabilitation training based on FES-cycling and overground robotic exoskeleton in complete SCI patients can provide a significant reduction of spasticity and improvements in terms of patient-robot interaction.

Investigations Into Internal and External Aspects of Dynamic Agent-Environment Couplings

NASA Astrophysics Data System (ADS)

Dautenhahn, Kerstin

This paper originates from my work on `social agents'. An issue which I consider important to this kind of research is the dynamic coupling of an agent with its social and non-social environment. I hypothesize `internal dynamics' inside an agent as a basic step towards understanding. The paper therefore focuses on the internal and external dynamics which couple an agent to its environment. The issue of embodiment in animals and artifacts and its relation to `social dynamics' is discussed first. I argue that embodiment is linked to a concept of a body and is not necessarily given when running a control program on robot hardware. I stress the individual characteristics of an embodied cognitive system, as well as its social embeddedness. I outline the framework of a physical-psychological state space which changes dynamically in a self-modifying way as a holistic approach towards embodied human and artificial cognition. This framework is meant to discuss internal and external dynamics of an embodied, natural or artificial agent. In order to stress the importance of a dynamic memory I introduce the concept of an `autobiographical agent'. The second part of the paper gives an example of the implementation of a physical agent, a robot, which is dynamically coupled to its environment by balancing on a seesaw. For the control of the robot a behavior-oriented approach using the dynamical systems metaphor is used. The problem is studied through building a complete and co-adapted robot-environment system. A seesaw which varies its orientation with one or two degrees of freedom is used as the artificial `habitat'. The problem of stabilizing the body axis by active motion on a seesaw is solved by using two inclination sensors and a parallel, behavior-oriented control architecture. Some experiments are described which demonstrate the exploitation of the dynamics of the robot-environment system.

Robotic surgery training: construct validity of Global Evaluative Assessment of Robotic Skills (GEARS).

PubMed

Sánchez, Renata; Rodríguez, Omaira; Rosciano, José; Vegas, Liumariel; Bond, Verónica; Rojas, Aram; Sanchez-Ismayel, Alexis

2016-09-01

The objective of this study is to determine the ability of the GEARS scale (Global Evaluative Assessment of Robotic Skills) to differentiate individuals with different levels of experience in robotic surgery, as a fundamental validation. This is a cross-sectional study that included three groups of individuals with different levels of experience in robotic surgery (expert, intermediate, novice) their performance were assessed by GEARS applied by two reviewers. The difference between groups was determined by Mann-Whitney test and the consistency between the reviewers was studied by Kendall W coefficient. The agreement between the reviewers of the scale GEARS was 0.96. The score was 29.8 ± 0.4 to experts, 24 ± 2.8 to intermediates and 16 ± 3 to novices, with a statistically significant difference between all of them (p < 0.05). All parameters from the scale allow discriminating between different levels of experience, with exception of the depth perception item. We conclude that the scale GEARS was able to differentiate between individuals with different levels of experience in robotic surgery and, therefore, is a validated and useful tool to evaluate surgeons in training.

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

Analysis and experimental kinematics of a skid-steering wheeled robot based on a laser scanner sensor.

PubMed

Wang, Tianmiao; Wu, Yao; Liang, Jianhong; Han, Chenhao; Chen, Jiao; Zhao, Qiteng

2015-04-24

Skid-steering mobile robots are widely used because of their simple mechanism and robustness. However, due to the complex wheel-ground interactions and the kinematic constraints, it is a challenge to understand the kinematics and dynamics of such a robotic platform. In this paper, we develop an analysis and experimental kinematic scheme for a skid-steering wheeled vehicle based-on a laser scanner sensor. The kinematics model is established based on the boundedness of the instantaneous centers of rotation (ICR) of treads on the 2D motion plane. The kinematic parameters (the ICR coefficient , the path curvature variable and robot speed ), including the effect of vehicle dynamics, are introduced to describe the kinematics model. Then, an exact but costly dynamic model is used and the simulation of this model's stationary response for the vehicle shows a qualitative relationship for the specified parameters and . Moreover, the parameters of the kinematic model are determined based-on a laser scanner localization experimental analysis method with a skid-steering robotic platform, Pioneer P3-AT. The relationship between the ICR coefficient and two physical factors is studied, i.e., the radius of the path curvature and the robot speed . An empirical function-based relationship between the ICR coefficient of the robot and the path parameters is derived. To validate the obtained results, it is empirically demonstrated that the proposed kinematics model significantly improves the dead-reckoning performance of this skid-steering robot.

Optimizing Motion Planning for Hyper Dynamic Manipulator

NASA Astrophysics Data System (ADS)

Aboura, Souhila; Omari, Abdelhafid; Meguenni, Kadda Zemalache

2012-01-01

This paper investigates the optimal motion planning for an hyper dynamic manipulator. As case study, we consider a golf swing robot which is consisting with two actuated joint and a mechanical stoppers. Genetic Algorithm (GA) technique is proposed to solve the optimal golf swing motion which is generated by Fourier series approximation. The objective function for GA approach is to minimizing the intermediate and final state, minimizing the robot's energy consummation and maximizing the robot's speed. Obtained simulation results show the effectiveness of the proposed scheme.

Interaction dynamics of multiple autonomous mobile robots in bounded spatial domains

NASA Technical Reports Server (NTRS)

Wang, P. K. C.

1989-01-01

A general navigation strategy for multiple autonomous robots in a bounded domain is developed analytically. Each robot is modeled as a spherical particle (i.e., an effective spatial domain about the center of mass); its interactions with other robots or with obstacles and domain boundaries are described in terms of the classical many-body problem; and a collision-avoidance strategy is derived and combined with homing, robot-robot, and robot-obstacle collision-avoidance strategies. Results from homing simulations involving (1) a single robot in a circular domain, (2) two robots in a circular domain, and (3) one robot in a domain with an obstacle are presented in graphs and briefly characterized.

Scaling law and enhancement of lift generation of an insect-size hovering flexible wing

PubMed Central

Kang, Chang-kwon; Shyy, Wei

2013-01-01

We report a comprehensive scaling law and novel lift generation mechanisms relevant to the aerodynamic functions of structural flexibility in insect flight. Using a Navier–Stokes equation solver, fully coupled to a structural dynamics solver, we consider the hovering motion of a wing of insect size, in which the dynamics of fluid–structure interaction leads to passive wing rotation. Lift generated on the flexible wing scales with the relative shape deformation parameter, whereas the optimal lift is obtained when the wing deformation synchronizes with the imposed translation, consistent with previously reported observations for fruit flies and honeybees. Systematic comparisons with rigid wings illustrate that the nonlinear response in wing motion results in a greater peak angle compared with a simple harmonic motion, yielding higher lift. Moreover, the compliant wing streamlines its shape via camber deformation to mitigate the nonlinear lift-degrading wing–wake interaction to further enhance lift. These bioinspired aeroelastic mechanisms can be used in the development of flapping wing micro-robots. PMID:23760300

Effects of robotic manipulators on movements of novices and surgeons.

PubMed

Nisky, Ilana; Okamura, Allison M; Hsieh, Michael H

2014-07-01

Robot-assisted surgery is widely adopted for many procedures but has not realized its full potential to date. Based on human motor control theories, the authors hypothesized that the dynamics of the master manipulators impose challenges on the motor system of the user and may impair performance and slow down learning. Although studies have shown that robotic outcomes are correlated with the case experience of the surgeon, the relative contribution of cognitive versus motor skill is unknown. This study quantified the effects of da Vinci Si master manipulator dynamics on movements of novice users and experienced surgeons and suggests possible implications for training and robot design. In the reported study, six experienced robotic surgeons and ten novice nonmedical users performed movements under two conditions: teleoperation of a da Vinci Si Surgical system and freehand. A linear mixed model was applied to nine kinematic metrics (including endpoint error, movement time, peak speed, initial jerk, and deviation from a straight line) to assess the effects of teleoperation and expertise. To assess learning effects, t tests between the first and last movements of each type were used. All the users moved slower during teleoperation than during freehand movements (F(1,9343) = 345; p < 0.001). The experienced surgeons had smaller errors than the novices (F(1,14) = 36.8; p < 0.001). The straightness of movements depended on their direction (F(7,9343) = 117; p < 0.001). Learning effects were observed in all conditions. Novice users first learned the task and then the dynamics of the manipulator. The findings showed differences between the novices and the experienced surgeons for extremely simple point-to-point movements. The study demonstrated that manipulator dynamics affect user movements, suggesting that these dynamics could be improved in future robot designs. The authors showed the partial adaptation of novice users to the dynamics. Future studies are needed to evaluate whether it will be beneficial to include early training sessions dedicated to learning the dynamics of the manipulator.

Dynamic analysis of space robot remote control system

NASA Astrophysics Data System (ADS)

Kulakov, Felix; Alferov, Gennady; Sokolov, Boris; Gorovenko, Polina; Sharlay, Artem

2018-05-01

The article presents analysis on construction of two-stage remote control for space robots. This control ensures efficiency of the robot control system at large delays in transmission of control signals from the ground control center to the local control system of the space robot. The conditions for control stability of and high transparency are found.

Robotic assessment of neuromuscular characteristics using musculoskeletal models: A pilot study.

PubMed

Jayaneththi, V R; Viloria, J; Wiedemann, L G; Jarrett, C; McDaid, A J

2017-07-01

Non-invasive neuromuscular characterization aims to provide greater insight into the effectiveness of existing and emerging rehabilitation therapies by quantifying neuromuscular characteristics relating to force production, muscle viscoelasticity and voluntary neural activation. In this paper, we propose a novel approach to evaluate neuromuscular characteristics, such as muscle fiber stiffness and viscosity, by combining robotic and HD-sEMG measurements with computational musculoskeletal modeling. This pilot study investigates the efficacy of this approach on a healthy population and provides new insight on potential limitations of conventional musculoskeletal models for this application. Subject-specific neuromuscular characteristics of the biceps and triceps brachii were evaluated using robot-measured kinetics, kinematics and EMG activity as inputs to a musculoskeletal model. Repeatability experiments in five participants revealed large variability within each subjects evaluated characteristics, with almost all experiencing variation greater than 50% of full scale when repeating the same task. The use of robotics and HD-sEMG, in conjunction with musculoskeletal modeling, to quantify neuromuscular characteristics has been explored. Despite the ability to predict joint kinematics with relatively high accuracy, parameter characterization was inconsistent i.e. many parameter combinations gave rise to minimal kinematic error. The proposed technique is a novel approach for in vivo neuromuscular characterization and is a step towards the realization of objective in-home robot-assisted rehabilitation. Importantly, the results have confirmed the technical (robot and HD-sEMG) feasibility while highlighting the need to develop new musculoskeletal models and optimization techniques capable of achieving consistent results across a range of dynamic tasks. Copyright © 2017 Elsevier Ltd. All rights reserved.

Do robots need to sleep?

PubMed

Fouks, J D; Besnard, S; Signac, L; Meurice, J C; Neau, J P; Paquereau, J

2004-04-01

The present paper exposes algorithmic results providing a vision about sleep functions which complements biological theory and experiments. Derived from the algorithmic theory of information, the theory of adaptation aims at quantifying how an inherited or acquired piece of knowledge helps individuals to survive. It gives a scale of complexity for survival problems and proves that some of them can only be solved by a dynamical management of memory associating continuous learning and forgetting methods. In this paper we explain how a virtual robot "Picota" has been designed to simulate the behavior of a living hen. In order to survive in its synthetical environment, our robot must recognize good seeds from bad ones, and should take rest during night periods. Within this frame, and facing the rapid evolution of to-be-recognized forms, the best way to equilibrate the energetic needs of the robot and ensure survival is to use the nightly rest to reorganize the pieces of data acquired during the daily learning, and to trash the less useful ones. Thanks to this time sharing, the same circuits can be used for both daily learning and nightly forgetting and thus costs are lower; however, this also forces the system to "paralyse" the virtual robot, and therefore the night algorithm is reminiscent of paradoxical (REM) sleep. The algorithm of the robot takes advantage of the alternation between wakefulness or activity and the rest period. This diagram quite accurately recalls the REM period. In the future, the convergence between the neurophysiology of sleep and the theory of complexity may give us a new line of research in order to elucidate sleep functions.

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.

Conjugate Gradient Algorithms For Manipulator Simulation

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheid, Robert E.

1991-01-01

Report discusses applicability of conjugate-gradient algorithms to computation of forward dynamics of robotic manipulators. Rapid computation of forward dynamics essential to teleoperation and other advanced robotic applications. Part of continuing effort to find algorithms meeting requirements for increased computational efficiency and speed. Method used for iterative solution of systems of linear equations.

Task driven optimal leg trajectories in insect-scale legged microrobots

NASA Astrophysics Data System (ADS)

Doshi, Neel; Goldberg, Benjamin; Jayaram, Kaushik; Wood, Robert

Origami inspired layered manufacturing techniques and 3D-printing have enabled the development of highly articulated legged robots at the insect-scale, including the 1.43g Harvard Ambulatory MicroRobot (HAMR). Research on these platforms has expanded its focus from manufacturing aspects to include design optimization and control for application-driven tasks. Consequently, the choice of gait selection, body morphology, leg trajectory, foot design, etc. have become areas of active research. HAMR has two controlled degrees-of-freedom per leg, making it an ideal candidate for exploring leg trajectory. We will discuss our work towards optimizing HAMR's leg trajectories for two different tasks: climbing using electroadhesives and level ground running (5-10 BL/s). These tasks demonstrate the ability of single platform to adapt to vastly different locomotive scenarios: quasi-static climbing with controlled ground contact, and dynamic running with un-controlled ground contact. We will utilize trajectory optimization methods informed by existing models and experimental studies to determine leg trajectories for each task. We also plan to discuss how task specifications and choice of objective function have contributed to the shape of these optimal leg trajectories.

Biological Soft Robotics.

PubMed

Feinberg, Adam W

2015-01-01

In nature, nanometer-scale molecular motors are used to generate force within cells for diverse processes from transcription and transport to muscle contraction. This adaptability and scalability across wide temporal, spatial, and force regimes have spurred the development of biological soft robotic systems that seek to mimic and extend these capabilities. This review describes how molecular motors are hierarchically organized into larger-scale structures in order to provide a basic understanding of how these systems work in nature and the complexity and functionality we hope to replicate in biological soft robotics. These span the subcellular scale to macroscale, and this article focuses on the integration of biological components with synthetic materials, coupled with bioinspired robotic design. Key examples include nanoscale molecular motor-powered actuators, microscale bacteria-controlled devices, and macroscale muscle-powered robots that grasp, walk, and swim. Finally, the current challenges and future opportunities in the field are addressed.

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.

Space robot simulator vehicle

NASA Technical Reports Server (NTRS)

Cannon, R. H., Jr.; Alexander, H.

1985-01-01

A Space Robot Simulator Vehicle (SRSV) was constructed to model a free-flying robot capable of doing construction, manipulation and repair work in space. The SRSV is intended as a test bed for development of dynamic and static control methods for space robots. The vehicle is built around a two-foot-diameter air-cushion vehicle that carries batteries, power supplies, gas tanks, computer, reaction jets and radio equipment. It is fitted with one or two two-link manipulators, which may be of many possible designs, including flexible-link versions. Both the vehicle body and its first arm are nearly complete. Inverse dynamic control of the robot's manipulator has been successfully simulated using equations generated by the dynamic simulation package SDEXACT. In this mode, the position of the manipulator tip is controlled not by fixing the vehicle base through thruster operation, but by controlling the manipulator joint torques to achieve the desired tip motion, while allowing for the free motion of the vehicle base. One of the primary goals is to minimize use of the thrusters in favor of intelligent control of the manipulator. Ways to reduce the computational burden of control are described.

Perception-action map learning in controlled multiscroll systems applied to robot navigation.

PubMed

Arena, Paolo; De Fiore, Sebastiano; Fortuna, Luigi; Patané, Luca

2008-12-01

In this paper a new technique for action-oriented perception in robots is presented. The paper starts from exploiting the successful implementation of the basic idea that perceptual states can be embedded into chaotic attractors whose dynamical evolution can be associated with sensorial stimuli. In this way, it can be possible to encode, into the chaotic dynamics, environment-dependent patterns. These have to be suitably linked to an action, executed by the robot, to fulfill an assigned mission. This task is addressed here: the action-oriented perception loop is closed by introducing a simple unsupervised learning stage, implemented via a bio-inspired structure based on the motor map paradigm. In this way, perceptual meanings, useful for solving a given task, can be autonomously learned, based on the environment-dependent patterns embedded into the controlled chaotic dynamics. The presented framework has been tested on a simulated robot and the performance have been successfully compared with other traditional navigation control paradigms. Moreover an implementation of the proposed architecture on a Field Programmable Gate Array is briefly outlined and preliminary experimental results on a roving robot are also reported.

Human-Inspired Eigenmovement Concept Provides Coupling-Free Sensorimotor Control in Humanoid Robot.

PubMed

Alexandrov, Alexei V; Lippi, Vittorio; Mergner, Thomas; Frolov, Alexander A; Hettich, Georg; Husek, Dusan

2017-01-01

Control of a multi-body system in both robots and humans may face the problem of destabilizing dynamic coupling effects arising between linked body segments. The state of the art solutions in robotics are full state feedback controllers. For human hip-ankle coordination, a more parsimonious and theoretically stable alternative to the robotics solution has been suggested in terms of the Eigenmovement (EM) control. Eigenmovements are kinematic synergies designed to describe the multi DoF system, and its control, with a set of independent, and hence coupling-free , scalar equations. This paper investigates whether the EM alternative shows "real-world robustness" against noisy and inaccurate sensors, mechanical non-linearities such as dead zones, and human-like feedback time delays when controlling hip-ankle movements of a balancing humanoid robot. The EM concept and the EM controller are introduced, the robot's dynamics are identified using a biomechanical approach, and robot tests are performed in a human posture control laboratory. The tests show that the EM controller provides stable control of the robot with proactive ("voluntary") movements and reactive balancing of stance during support surface tilts and translations. Although a preliminary robot-human comparison reveals similarities and differences, we conclude (i) the Eigenmovement concept is a valid candidate when different concepts of human sensorimotor control are considered, and (ii) that human-inspired robot experiments may help to decide in future the choice among the candidates and to improve the design of humanoid robots and robotic rehabilitation devices.

Human-Inspired Eigenmovement Concept Provides Coupling-Free Sensorimotor Control in Humanoid Robot

PubMed Central

Alexandrov, Alexei V.; Lippi, Vittorio; Mergner, Thomas; Frolov, Alexander A.; Hettich, Georg; Husek, Dusan

2017-01-01

Control of a multi-body system in both robots and humans may face the problem of destabilizing dynamic coupling effects arising between linked body segments. The state of the art solutions in robotics are full state feedback controllers. For human hip-ankle coordination, a more parsimonious and theoretically stable alternative to the robotics solution has been suggested in terms of the Eigenmovement (EM) control. Eigenmovements are kinematic synergies designed to describe the multi DoF system, and its control, with a set of independent, and hence coupling-free, scalar equations. This paper investigates whether the EM alternative shows “real-world robustness” against noisy and inaccurate sensors, mechanical non-linearities such as dead zones, and human-like feedback time delays when controlling hip-ankle movements of a balancing humanoid robot. The EM concept and the EM controller are introduced, the robot's dynamics are identified using a biomechanical approach, and robot tests are performed in a human posture control laboratory. The tests show that the EM controller provides stable control of the robot with proactive (“voluntary”) movements and reactive balancing of stance during support surface tilts and translations. Although a preliminary robot-human comparison reveals similarities and differences, we conclude (i) the Eigenmovement concept is a valid candidate when different concepts of human sensorimotor control are considered, and (ii) that human-inspired robot experiments may help to decide in future the choice among the candidates and to improve the design of humanoid robots and robotic rehabilitation devices. PMID:28487646

Three-dimensional construction and omni-directional rolling analysis of a novel frame-like lattice modular robot

NASA Astrophysics Data System (ADS)

Ding, Wan; Wu, Jianxu; Yao, Yan'an

2015-07-01

Lattice modular robots possess diversity actuation methods, such as electric telescopic rod, gear rack, magnet, robot arm, etc. The researches on lattice modular robots mainly focus on their hardware descriptions and reconfiguration algorithms. Meanwhile, their design architectures and actuation methods perform slow telescopic and moving speeds, relative low actuation force verse weight ratio, and without internal space to carry objects. To improve the mechanical performance and reveal the locomotion and reconfiguration binary essences of the lattice modular robots, a novel cube-shaped, frame-like, pneumatic-based reconfigurable robot module called pneumatic expandable cube(PE-Cube) is proposed. The three-dimensional(3D) expanding construction and omni-directional rolling analysis of the constructed robots are the main focuses. The PE-Cube with three degrees of freedom(DoFs) is assembled by replacing the twelve edges of a cube with pneumatic cylinders. The proposed symmetric construction condition makes the constructed robots possess the same properties in each supporting state, and a binary control strategy cooperated with binary actuator(pneumatic cylinder) is directly adopted to control the PE-Cube. Taking an eight PE-Cube modules' construction as example, its dynamic rolling simulation, static rolling condition, and turning gait are illustrated and discussed. To testify telescopic synchronization, respond speed, locomotion feasibility, and repeatability and reliability of hardware system, an experimental pneumatic-based robotic system is built and the rolling and turning experiments of the eight PE-Cube modules' construction are carried out. As an extension, the locomotion feasibility of a thirty-two PE-Cube modules' construction is analyzed and proved, including dynamic rolling simulation, static rolling condition, and dynamic analysis in free tipping process. The proposed PE-Cube module, construction method, and locomotion analysis enrich the family of the lattice modular robot and provide the instruction to design the lattice modular robot.

Task allocation among multiple intelligent robots

NASA Technical Reports Server (NTRS)

Gasser, L.; Bekey, G.

1987-01-01

Researchers describe the design of a decentralized mechanism for allocating assembly tasks in a multiple robot assembly workstation. Currently, the approach focuses on distributed allocation to explore its feasibility and its potential for adaptability to changing circumstances, rather than for optimizing throughput. Individual greedy robots make their own local allocation decisions using both dynamic allocation policies which propagate through a network of allocation goals, and local static and dynamic constraints describing which robots are elibible for which assembly tasks. Global coherence is achieved by proper weighting of allocation pressures propagating through the assembly plan. Deadlock avoidance and synchronization is achieved using periodic reassessments of local allocation decisions, ageing of allocation goals, and short-term allocation locks on goals.

Fuzzy integral-based gaze control architecture incorporated with modified-univector field-based navigation for humanoid robots.

PubMed

Yoo, Jeong-Ki; Kim, Jong-Hwan

2012-02-01

When a humanoid robot moves in a dynamic environment, a simple process of planning and following a path may not guarantee competent performance for dynamic obstacle avoidance because the robot acquires limited information from the environment using a local vision sensor. Thus, it is essential to update its local map as frequently as possible to obtain more information through gaze control while walking. This paper proposes a fuzzy integral-based gaze control architecture incorporated with the modified-univector field-based navigation for humanoid robots. To determine the gaze direction, four criteria based on local map confidence, waypoint, self-localization, and obstacles, are defined along with their corresponding partial evaluation functions. Using the partial evaluation values and the degree of consideration for criteria, fuzzy integral is applied to each candidate gaze direction for global evaluation. For the effective dynamic obstacle avoidance, partial evaluation functions about self-localization error and surrounding obstacles are also used for generating virtual dynamic obstacle for the modified-univector field method which generates the path and velocity of robot toward the next waypoint. The proposed architecture is verified through the comparison with the conventional weighted sum-based approach with the simulations using a developed simulator for HanSaRam-IX (HSR-IX).

Searching Dynamic Agents with a Team of Mobile Robots

PubMed Central

Juliá, Miguel; Gil, Arturo; Reinoso, Oscar

2012-01-01

This paper presents a new algorithm that allows a team of robots to cooperatively search for a set of moving targets. An estimation of the areas of the environment that are more likely to hold a target agent is obtained using a grid-based Bayesian filter. The robot sensor readings and the maximum speed of the moving targets are used in order to update the grid. This representation is used in a search algorithm that commands the robots to those areas that are more likely to present target agents. This algorithm splits the environment in a tree of connected regions using dynamic programming. This tree is used in order to decide the destination for each robot in a coordinated manner. The algorithm has been successfully tested in known and unknown environments showing the validity of the approach. PMID:23012519

Searching dynamic agents with a team of mobile robots.

PubMed

Juliá, Miguel; Gil, Arturo; Reinoso, Oscar

2012-01-01

This paper presents a new algorithm that allows a team of robots to cooperatively search for a set of moving targets. An estimation of the areas of the environment that are more likely to hold a target agent is obtained using a grid-based Bayesian filter. The robot sensor readings and the maximum speed of the moving targets are used in order to update the grid. This representation is used in a search algorithm that commands the robots to those areas that are more likely to present target agents. This algorithm splits the environment in a tree of connected regions using dynamic programming. This tree is used in order to decide the destination for each robot in a coordinated manner. The algorithm has been successfully tested in known and unknown environments showing the validity of the approach.

Event detection and localization for small mobile robots using reservoir computing.

PubMed

Antonelo, E A; Schrauwen, B; Stroobandt, D

2008-08-01

Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability, where only a linear static readout output layer is trained by standard linear regression methods. In this work, RC is used for detecting complex events in autonomous robot navigation. This can be extended to robot localization tasks which are solely based on a few low-range, high-noise sensory data. The robot thus builds an implicit map of the environment (after learning) that is used for efficient localization by simply processing the input stream of distance sensors. These techniques are demonstrated in both a simple simulation environment and in the physically realistic Webots simulation of the commercially available e-puck robot, using several complex and even dynamic environments.

Dual-Schemata Model

NASA Astrophysics Data System (ADS)

Taniguchi, Tadahiro; Sawaragi, Tetsuo

In this paper, a new machine-learning method, called Dual-Schemata model, is presented. Dual-Schemata model is a kind of self-organizational machine learning methods for an autonomous robot interacting with an unknown dynamical environment. This is based on Piaget's Schema model, that is a classical psychological model to explain memory and cognitive development of human beings. Our Dual-Schemata model is developed as a computational model of Piaget's Schema model, especially focusing on sensori-motor developing period. This developmental process is characterized by a couple of two mutually-interacting dynamics; one is a dynamics formed by assimilation and accommodation, and the other dynamics is formed by equilibration and differentiation. By these dynamics schema system enables an agent to act well in a real world. This schema's differentiation process corresponds to a symbol formation process occurring within an autonomous agent when it interacts with an unknown, dynamically changing environment. Experiment results obtained from an autonomous facial robot in which our model is embedded are presented; an autonomous facial robot becomes able to chase a ball moving in various ways without any rewards nor teaching signals from outside. Moreover, emergence of concepts on the target movements within a robot is shown and discussed in terms of fuzzy logics on set-subset inclusive relationships.

US Army Research Laboratory (ARL) Robotics Collaborative Technology Alliance 2014 Capstone Experiment

DTIC Science & Technology

2016-07-01

ARL-TR-7729 ● JULY 2016 US Army Research Laboratory US Army Research Laboratory (ARL) Robotics Collaborative Technology Alliance...TR-7729 ● JULY 2016 US Army Research Laboratory US Army Research Laboratory (ARL) Robotics Collaborative Technology Alliance 2014 Capstone...National Robotics Engineering Center, Pittsburgh, PA Robert Dean, Terence Keegan, and Chip Diberardino General Dynamics Land Systems, Westminster

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.

Experiments in cooperative-arm object manipulation with a two-armed free-flying robot. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Koningstein, Ross

1990-01-01

Developing computed-torque controllers for complex manipulator systems using current techniques and tools is difficult because they address the issues pertinent to simulation, as opposed to control. A new formulation of computed-torque (CT) control that leads to an automated computer-torque robot controller program is presented. This automated tool is used for simulations and experimental demonstrations of endpoint and object control from a free-flying robot. A new computed-torque formulation states the multibody control problem in an elegant, homogeneous, and practical form. A recursive dynamics algorithm is presented that numerically evaluates kinematics and dynamics terms for multibody systems given a topological description. Manipulators may be free-flying, and may have closed-chain constraints. With the exception of object squeeze-force control, the algorithm does not deal with actuator redundancy. The algorithm is used to implement an automated 2D computed-torque dynamics and control package that allows joint, endpoint, orientation, momentum, and object squeeze-force control. This package obviates the need for hand-derivation of kinematics and dynamics, and is used for both simulation and experimental control. Endpoint control experiments are performed on a laboratory robot that has two arms to manipulate payloads, and uses an air bearing to achieve very-low drag characteristics. Simulations and experimental data for endpoint and object controllers are presented for the experimental robot - a complex dynamic system. There is a certain rather wide set of conditions under which CT endpoint controllers can neglect robot base accelerations (but not motions) and achieve comparable performance including base accelerations in the model. The regime over which this simplification holds is explored by simulation and experiment.

Experimental determination of dynamic parameters of an industrial robot

NASA Astrophysics Data System (ADS)

Banas, W.; Cwikła, G.; Foit, K.; Gwiazda, A.; Monica, Z.; Sekala, A.

2017-08-01

In an industry increasingly used are industrial robots. Commonly used are two basic methods of programming, on-line programming and off-line programming. In both cases, the programming consists in getting to the selected points record this position, and set the order of movement of the robot, and the introduction of logical tests. Such a program is easy to write, and it is suitable for most industrial applications. Especially when the process is known, respectively slow and unchanging. In this case, the program is being prepared for a universal model of the robot with the appropriate geometry and are checked only collisions. Is not taken into account the dynamics of the robot and how it will really behave while in motion. For this reason, the robot programmed to be tested at a reduced speed, which is raised gradually to the final value. Depending on the complexity of the move and the proximity of the elements it takes a lot of time. It is easy to notice that the robot at different speeds have different trajectories and behaves differently.

Continuously distributed magnetization profile for millimeter-scale elastomeric undulatory swimming

NASA Astrophysics Data System (ADS)

Diller, Eric; Zhuang, Jiang; Zhan Lum, Guo; Edwards, Matthew R.; Sitti, Metin

2014-04-01

We have developed a millimeter-scale magnetically driven swimming robot for untethered motion at mid to low Reynolds numbers. The robot is propelled by continuous undulatory deformation, which is enabled by the distributed magnetization profile of a flexible sheet. We demonstrate control of a prototype device and measure deformation and speed as a function of magnetic field strength and frequency. Experimental results are compared with simple magnetoelastic and fluid propulsion models. The presented mechanism provides an efficient remote actuation method at the millimeter scale that may be suitable for further scaling down in size for micro-robotics applications in biotechnology and healthcare.

Generating high-speed dynamic running gaits in a quadruped robot using an evolutionary search.

PubMed

Krasny, Darren P; Orin, David E

2004-08-01

Over the past several decades, there has been a considerable interest in investigating high-speed dynamic gaits for legged robots. While much research has been published, both in the biomechanics and engineering fields regarding the analysis of these gaits, no single study has adequately characterized the dynamics of high-speed running as can be achieved in a realistic, yet simple, robotic system. The goal of this paper is to find the most energy-efficient, natural, and unconstrained gallop that can be achieved using a simulated quadrupedal robot with articulated legs, asymmetric mass distribution, and compliant legs. For comparison purposes, we also implement the bound and canter. The model used here is planar, although we will show that it captures much of the predominant dynamic characteristics observed in animals. While it is not our goal to prove anything about biological locomotion, the dynamic similarities between the gaits we produce and those found in animals does indicate a similar underlying dynamic mechanism. Thus, we will show that achieving natural, efficient high-speed locomotion is possible even with a fairly simple robotic system. To generate the high-speed gaits, we use an efficient evolutionary algorithm called set-based stochastic optimization. This algorithm finds open-loop control parameters to generate periodic trajectories for the body. Several alternative methods are tested to generate periodic trajectories for the legs. The combined solutions found by the evolutionary search and the periodic-leg methods, over a range of speeds up to 10.0 m/s, reveal "biological" characteristics that are emergent properties of the underlying gaits.

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

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

Parker, L.E.

1995-02-01

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

Control strategies for robots in contact

NASA Astrophysics Data System (ADS)

Park, Jaeheung

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

Measuring information transfer in a soft robotic arm.

PubMed

Nakajima, K; Schmidt, N; Pfeifer, R

2015-05-13

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

Extracting motor synergies from random movements for low-dimensional task-space control of musculoskeletal robots.

PubMed

Fu, Kin Chung Denny; Dalla Libera, Fabio; Ishiguro, Hiroshi

2015-10-08

In the field of human motor control, the motor synergy hypothesis explains how humans simplify body control dimensionality by coordinating groups of muscles, called motor synergies, instead of controlling muscles independently. In most applications of motor synergies to low-dimensional control in robotics, motor synergies are extracted from given optimal control signals. In this paper, we address the problems of how to extract motor synergies without optimal data given, and how to apply motor synergies to achieve low-dimensional task-space tracking control of a human-like robotic arm actuated by redundant muscles, without prior knowledge of the robot. We propose to extract motor synergies from a subset of randomly generated reaching-like movement data. The essence is to first approximate the corresponding optimal control signals, using estimations of the robot's forward dynamics, and to extract the motor synergies subsequently. In order to avoid modeling difficulties, a learning-based control approach is adopted such that control is accomplished via estimations of the robot's inverse dynamics. We present a kernel-based regression formulation to estimate the forward and the inverse dynamics, and a sliding controller in order to cope with estimation error. Numerical evaluations show that the proposed method enables extraction of motor synergies for low-dimensional task-space control.

Dynamics of underwater legged locomotion: modeling and experiments on an octopus-inspired robot.

PubMed

Calisti, M; Corucci, F; Arienti, A; Laschi, C

2015-07-30

This paper studies underwater legged locomotion (ULL) by means of a robotic octopus-inspired prototype and its associated model. Two different types of propulsive actions are embedded into the robot model: reaction forces due to leg contact with the ground and hydrodynamic forces such as the drag arising from the sculling motion of the legs. Dynamic parameters of the model are estimated by means of evolutionary techniques and subsequently the model is exploited to highlight some distinctive features of ULL. Specifically, the separation between the center of buoyancy (CoB)/center of mass and density affect the stability and speed of the robot, whereas the sculling movements contribute to propelling the robot even when its legs are detached from the ground. The relevance of these effects is demonstrated through robotic experiments and model simulations; moreover, by slightly changing the position of the CoB in the presence of the same feed-forward activation, a number of different behaviors (i.e. forward and backward locomotion at different speeds) are achieved.

Formation tracker design of multiple mobile robots with wheel perturbations: adaptive output-feedback approach

NASA Astrophysics Data System (ADS)

Yoo, Sung Jin

2016-11-01

This paper presents a theoretical design approach for output-feedback formation tracking of multiple mobile robots under wheel perturbations. It is assumed that these perturbations are unknown and the linear and angular velocities of the robots are unmeasurable. First, adaptive state observers for estimating unmeasurable velocities of the robots are developed under the robots' kinematics and dynamics including wheel perturbation effects. Then, we derive a virtual-structure-based formation tracker scheme according to the observer dynamic surface design procedure. The main difficulty of the output-feedback control design is to manage the coupling problems between unmeasurable velocities and unknown wheel perturbation effects. These problems are avoided by using the adaptive technique and the function approximation property based on fuzzy logic systems. From the Lyapunov stability analysis, it is shown that point tracking errors of each robot and synchronisation errors for the desired formation converge to an adjustable neighbourhood of the origin, while all signals in the controlled closed-loop system are semiglobally uniformly ultimately bounded.

Hierarchical Bio-Inspired Cooperative Control for Nonlinear Dynamical Systems and Hardware Demonstration

DTIC Science & Technology

2013-04-03

cooperative control, LEGO robotic testbed, non-linear dynamics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES...testbed The architecture of the LEGO robots (® LEGO is a trademark and/or copyright of the LEGO Group) used in tests were based off the quick-start

Robotic Telecytology for Remote Cytologic Evaluation without an On-site Cytotechnologist or Cytopathologist: A Tale of Implementation and Review of Constraints

PubMed Central

Sirintrapun, Sahussapont Joseph; Rudomina, Dorota; Mazzella, Allix; Feratovic, Rusmir; Alago, William; Siegelbaum, Robert; Lin, Oscar

2017-01-01

Background: The first satellite center to offer interventional radiology procedures at Memorial Sloan Kettering Cancer Center opened in October 2014. Two of the procedures offered, fine needle aspirations and core biopsies, required rapid on-site cytologic evaluation of smears and biopsy touch imprints for cellular content and adequacy. The volume and frequency of such evaluations did not justify hiring on-site cytotechnologists, and therefore, a dynamic robotic telecytology (TC) solution was created. In this technical article, we present a detailed description of our implementation of robotic TC. Methods: Pathology devised the remote robotic TC solution after acknowledging that it would not be cost effective to staff cytotechnologists on-site at the satellite location. Sakura VisionTek was selected as our robotic TC solution. In addition to configuration of the dynamic robotic TC solution, pathology realized integrating the technology solution into operations would require a multidisciplinary effort and reevaluation of existing staffing and workflows. Results: Extensively described are the architectural framework and multidisciplinary process re-design, created to navigate the constraints of our technical, cultural, and organizational environment. Also reviewed are the benefits and challenges associated with available desktop sharing solutions, particularly accounting for information security concerns. Conclusions: Dynamic robotic TC is effective for immediate evaluations performed without on-site cytotechnology staff. Our goal is providing an extensive perspective of the implementation process, particularly technical, cultural, and operational constraints. Through this perspective, our template can serve as an extensible blueprint for other centers interested in implementing robotic TC without on-site cytotechnologists. PMID:28966832

Robotic Telecytology for Remote Cytologic Evaluation without an On-site Cytotechnologist or Cytopathologist: A Tale of Implementation and Review of Constraints.

PubMed

Sirintrapun, Sahussapont Joseph; Rudomina, Dorota; Mazzella, Allix; Feratovic, Rusmir; Alago, William; Siegelbaum, Robert; Lin, Oscar

2017-01-01

The first satellite center to offer interventional radiology procedures at Memorial Sloan Kettering Cancer Center opened in October 2014. Two of the procedures offered, fine needle aspirations and core biopsies, required rapid on-site cytologic evaluation of smears and biopsy touch imprints for cellular content and adequacy. The volume and frequency of such evaluations did not justify hiring on-site cytotechnologists, and therefore, a dynamic robotic telecytology (TC) solution was created. In this technical article, we present a detailed description of our implementation of robotic TC. Pathology devised the remote robotic TC solution after acknowledging that it would not be cost effective to staff cytotechnologists on-site at the satellite location. Sakura VisionTek was selected as our robotic TC solution. In addition to configuration of the dynamic robotic TC solution, pathology realized integrating the technology solution into operations would require a multidisciplinary effort and reevaluation of existing staffing and workflows. Extensively described are the architectural framework and multidisciplinary process re-design, created to navigate the constraints of our technical, cultural, and organizational environment. Also reviewed are the benefits and challenges associated with available desktop sharing solutions, particularly accounting for information security concerns. Dynamic robotic TC is effective for immediate evaluations performed without on-site cytotechnology staff. Our goal is providing an extensive perspective of the implementation process, particularly technical, cultural, and operational constraints. Through this perspective, our template can serve as an extensible blueprint for other centers interested in implementing robotic TC without on-site cytotechnologists.

Analysis and Experimental Kinematics of a Skid-Steering Wheeled Robot Based on a Laser Scanner Sensor

PubMed Central

Wang, Tianmiao; Wu, Yao; Liang, Jianhong; Han, Chenhao; Chen, Jiao; Zhao, Qiteng

2015-01-01

Skid-steering mobile robots are widely used because of their simple mechanism and robustness. However, due to the complex wheel-ground interactions and the kinematic constraints, it is a challenge to understand the kinematics and dynamics of such a robotic platform. In this paper, we develop an analysis and experimental kinematic scheme for a skid-steering wheeled vehicle based-on a laser scanner sensor. The kinematics model is established based on the boundedness of the instantaneous centers of rotation (ICR) of treads on the 2D motion plane. The kinematic parameters (the ICR coefficient χ, the path curvature variable λ and robot speed v), including the effect of vehicle dynamics, are introduced to describe the kinematics model. Then, an exact but costly dynamic model is used and the simulation of this model’s stationary response for the vehicle shows a qualitative relationship for the specified parameters χ and λ. Moreover, the parameters of the kinematic model are determined based-on a laser scanner localization experimental analysis method with a skid-steering robotic platform, Pioneer P3-AT. The relationship between the ICR coefficient χ and two physical factors is studied, i.e., the radius of the path curvature λ and the robot speed v. An empirical function-based relationship between the ICR coefficient of the robot and the path parameters is derived. To validate the obtained results, it is empirically demonstrated that the proposed kinematics model significantly improves the dead-reckoning performance of this skid–steering robot. PMID:25919370

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.

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

NASA Technical Reports Server (NTRS)

Erickson, Jon D. (Editor)

1992-01-01

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

Evaluation of linearly solvable Markov decision process with dynamic model learning in a mobile robot navigation task.

PubMed

Kinjo, Ken; Uchibe, Eiji; Doya, Kenji

2013-01-01

Linearly solvable Markov Decision Process (LMDP) is a class of optimal control problem in which the Bellman's equation can be converted into a linear equation by an exponential transformation of the state value function (Todorov, 2009b). In an LMDP, the optimal value function and the corresponding control policy are obtained by solving an eigenvalue problem in a discrete state space or an eigenfunction problem in a continuous state using the knowledge of the system dynamics and the action, state, and terminal cost functions. In this study, we evaluate the effectiveness of the LMDP framework in real robot control, in which the dynamics of the body and the environment have to be learned from experience. We first perform a simulation study of a pole swing-up task to evaluate the effect of the accuracy of the learned dynamics model on the derived the action policy. The result shows that a crude linear approximation of the non-linear dynamics can still allow solution of the task, despite with a higher total cost. We then perform real robot experiments of a battery-catching task using our Spring Dog mobile robot platform. The state is given by the position and the size of a battery in its camera view and two neck joint angles. The action is the velocities of two wheels, while the neck joints were controlled by a visual servo controller. We test linear and bilinear dynamic models in tasks with quadratic and Guassian state cost functions. In the quadratic cost task, the LMDP controller derived from a learned linear dynamics model performed equivalently with the optimal linear quadratic regulator (LQR). In the non-quadratic task, the LMDP controller with a linear dynamics model showed the best performance. The results demonstrate the usefulness of the LMDP framework in real robot control even when simple linear models are used for dynamics learning.

Portable and Reconfigurable Wrist Robot Improves Hand Function for Post-Stroke Subjects.

PubMed

Khor, Kang Xiang; Chin, Patrick Jun Hua; Yeong, Che Fai; Su, Eileen Lee Ming; Narayanan, Aqilah Leela T; Abdul Rahman, Hisyam; Khan, Qamer Iqbal

2017-10-01

Rehabilitation robots have become increasingly popular for stroke rehabilitation. However, the high cost of robots hampers their implementation on a large scale. This paper implements the concept of a modular and reconfigurable robot, reducing its cost and size by adopting different therapeutic end effectors for different training movements using a single robot. The challenge is to increase the robot's portability and identify appropriate kinds of modular tools and configurations. Because literature on the effectiveness of this kind of rehabilitation robot is still scarce, this paper presents the design of a portable and reconfigurable rehabilitation robot and describes its use with a group of post-stroke patients for wrist and forearm training. Seven stroke subjects received training using a reconfigurable robot for 30 sessions, lasting 30 min per session. Post-training, statistical analysis showed significant improvement of 3.29 points (16.20%, p = 0.027) on the Fugl-Meyer assessment scale for forearm and wrist components. Significant improvement of active range of motion was detected in both pronation-supination (75.59%, p = 0.018) and wrist flexion-extension (56.12%, p = 0.018) after the training. These preliminary results demonstrate that the developed reconfigurable robot could improve subjects' wrist and forearm movement.

Dynamics, control and sensor issues pertinent to robotic hands for the EVA retriever system

NASA Technical Reports Server (NTRS)

Mclauchlan, Robert A.

1987-01-01

Basic dynamics, sensor, control, and related artificial intelligence issues pertinent to smart robotic hands for the Extra Vehicular Activity (EVA) Retriever system are summarized and discussed. These smart hands are to be used as end effectors on arms attached to manned maneuvering units (MMU). The Retriever robotic systems comprised of MMU, arm and smart hands, are being developed to aid crewmen in the performance of routine EVA tasks including tool and object retrieval. The ultimate goal is to enhance the effectiveness of EVA crewmen.

Experimental Research Regarding The Motion Capacity Of A Robotic Arm

NASA Astrophysics Data System (ADS)

Dumitru, Violeta Cristina

2015-09-01

This paper refers to the development of necessary experiments which obtained dynamic parameters (force, displacement) for a modular mechanism with multiple vertebrae. This mechanism performs functions of inspection and intervention in small spaces. Mechanical structure allows functional parameters to achieve precise movements to an imposed target. Will be analyzed the dynamic of the mechanisms using simulation instruments DimamicaRobot.tst under TestPoint programming environment and the elasticity of the tension cables. It will be changes on the mechanism so that spatial movement of the robotic arm is optimal.

Passive dynamics is a good basis for robot design and control, not!

NASA Astrophysics Data System (ADS)

Ruina, Andy

Many airplanes can, or nearly can, glide stably without control. So, it seems natural that the first successful powered flight followed from mastery of gliding. Many bicycles can, or nearly can, balance themselves when in motion. Bicycle design seems to have evolved to gain this feature. Also, we can make toys and 'robots' that, like a stable glider or coasting bicycle, stably walk without motors or control in a remarkably human-like way. Again, it seems to make sense to use `passive-dynamics' as a core for developing the control of walking robots and to gain understanding of the control of walking people. That's what I used to think. But, so far, this has not led to robust walking robots. What about human evolution? We didn't evolve dynamic bodies and then learn to control them. Rather, people had elaborate control systems way back when we were fish and even worms. However: if control is paramount, why is it that uncontrolled passive-dynamic walkers walk so much like humans? It seems that energy optimal, yet robust, control, perhaps a proxy for evolutionary development, arrives at solutions that have some features in common with passive-dynamics. Rather than thinking of good powered walking as passive walking with a small amount of control added, I now think of good powered walking, human or robotic, as highly controlled, while optimized for, in part, minimal actuator use. Thus, much of the motor effort, always at the ready, is usually titrated out.

A spatial operator algebra for manipulator modeling and control

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Kreutz, K.; Milman, M.

1988-01-01

A powerful new spatial operator algebra for modeling, control, and trajectory design of manipulators is discussed along with its implementation in the Ada programming language. Applications of this algebra to robotics include an operator representation of the manipulator Jacobian matrix; the robot dynamical equations formulated in terms of the spatial algebra, showing the complete equivalence between the recursive Newton-Euler formulations to robot dynamics; the operator factorization and inversion of the manipulator mass matrix which immediately results in O(N) recursive forward dynamics algorithms; the joint accelerations of a manipulator due to a tip contact force; the recursive computation of the equivalent mass matrix as seen at the tip of a manipulator; and recursive forward dynamics of a closed chain system. Finally, additional applications and current research involving the use of the spatial operator algebra are discussed in general terms.

Development of robotic mobile platform with the universal chassis system

NASA Astrophysics Data System (ADS)

Ryadchikov, I.; Nikulchev, E.; Sechenev, S.; Drobotenko, M.; Svidlov, A.; Volkodav, P.; Feshin, A.

2018-02-01

The problem of stabilizing the position of mobile devices is extremely relevant at the modern level of technology development. This includes the problem of stabilizing aircraft and stabilizing the pitching of ships. In the laboratory of robotics and mechatronics of the Kuban State University, a robot is developed. The robot has additional internal degrees of freedom, responsible for compensating for deflections - the dynamic stabilization system.

Adaptive Integration of Nonsmooth Dynamical Systems

DTIC Science & Technology

2017-10-11

controlled time stepping method to interactively design running robots. [1] John Shepherd, Samuel Zapolsky, and Evan M. Drumwright, “Fast multi-body...software like this to test software running on my robots. Started working in simulation after attempting to use software like this to test software... running on my robots. The libraries that produce these beautiful results have failed at simulating robotic manipulation. Postulate: It is easier to

Current Limitations of Surgical Robotics in Reconstructive Plastic Microsurgery.

PubMed

Tan, Youri P A; Liverneaux, Philippe; Wong, Jason K F

2018-01-01

Surgical robots have the potential to provide surgeons with increased capabilities, such as removing physiologic tremor, scaling motion and increasing manual dexterity. Several surgical specialties have subsequently integrated robotic surgery into common clinical practice. Plastic and reconstructive microsurgical procedures have not yet  benefitted significantly from technical developments observed over the last two decades. Several studies have successfully demonstrated the feasibility of utilising surgical robots in plastic surgery procedures, yet limited work has been done to identify and analyse current barriers that have prevented wide-scale adaptation of surgical robots for microsurgery. Therefore, a systematic review using PubMed, MEDLINE, Embase and Web of Science databases was performed, in order to evaluate current state of surgical robotics within the field of reconstructive microsurgery and their limitations. Despite the theoretical potential of surgical robots, current commercially available robotic systems are suboptimal for plastic or reconstructive microsurgery. Absence of bespoke microsurgical instruments, increases in operating time, and high costs associated with robotic-assisted provide a barrier to using such systems effectively for reconstructive microsurgery. Consequently, surgical robots provide currently little overall advantage over conventional microsurgery. Nevertheless, if current barriers can be addressed and systems are specifically designed for microsurgery, surgical robots may have the potential of meaningful impact on clinical outcomes within  this surgical subspeciality.

Current Limitations of Surgical Robotics in Reconstructive Plastic Microsurgery

PubMed Central

Tan, Youri P. A.; Liverneaux, Philippe; Wong, Jason K. F.

2018-01-01

Surgical robots have the potential to provide surgeons with increased capabilities, such as removing physiologic tremor, scaling motion and increasing manual dexterity. Several surgical specialties have subsequently integrated robotic surgery into common clinical practice. Plastic and reconstructive microsurgical procedures have not yet  benefitted significantly from technical developments observed over the last two decades. Several studies have successfully demonstrated the feasibility of utilising surgical robots in plastic surgery procedures, yet limited work has been done to identify and analyse current barriers that have prevented wide-scale adaptation of surgical robots for microsurgery. Therefore, a systematic review using PubMed, MEDLINE, Embase and Web of Science databases was performed, in order to evaluate current state of surgical robotics within the field of reconstructive microsurgery and their limitations. Despite the theoretical potential of surgical robots, current commercially available robotic systems are suboptimal for plastic or reconstructive microsurgery. Absence of bespoke microsurgical instruments, increases in operating time, and high costs associated with robotic-assisted provide a barrier to using such systems effectively for reconstructive microsurgery. Consequently, surgical robots provide currently little overall advantage over conventional microsurgery. Nevertheless, if current barriers can be addressed and systems are specifically designed for microsurgery, surgical robots may have the potential of meaningful impact on clinical outcomes within  this surgical subspeciality. PMID:29740585

Dynamic bending of bionic flexible body driven by pneumatic artificial muscles(PAMs) for spinning gait of quadruped robot

NASA Astrophysics Data System (ADS)

Lei, Jingtao; Yu, Huangying; Wang, Tianmiao

2016-01-01

The body of quadruped robot is generally developed with the rigid structure. The mobility of quadruped robot depends on the mechanical properties of the body mechanism. It is difficult for quadruped robot with rigid structure to achieve better mobility walking or running in the unstructured environment. A kind of bionic flexible body mechanism for quadruped robot is proposed, which is composed of one bionic spine and four pneumatic artificial muscles(PAMs). This kind of body imitates the four-legged creatures' kinematical structure and physical properties, which has the characteristic of changeable stiffness, lightweight, flexible and better bionics. The kinematics of body bending is derived, and the coordinated movement between the flexible body and legs is analyzed. The relationship between the body bending angle and the PAM length is obtained. The dynamics of the body bending is derived by the floating coordinate method and Lagrangian method, and the driving force of PAM is determined. The experiment of body bending is conducted, and the dynamic bending characteristic of bionic flexible body is evaluated. Experimental results show that the bending angle of the bionic flexible body can reach 18°. An innovation body mechanism for quadruped robot is proposed, which has the characteristic of flexibility and achieve bending by changing gas pressure of PAMs. The coordinated movement of the body and legs can achieve spinning gait in order to improve the mobility of quadruped robot.

Measurement of the Robot Motor Capability of a Robot Motor System: A Fitts's-Law-Inspired Approach

PubMed Central

Lin, Hsien-I; George Lee, C. S.

2013-01-01

Robot motor capability is a crucial factor for a robot, because it affects how accurately and rapidly a robot can perform a motion to accomplish a task constrained by spatial and temporal conditions. In this paper, we propose and derive a pseudo-index of motor performance (pIp) to characterize robot motor capability with robot kinematics, dynamics and control taken into consideration. The proposed pIp provides a quantitative measure for a robot with revolute joints, which is inspired from an index of performance in Fitts's law of human skills. Computer simulations and experiments on a PUMA 560 industrial robot were conducted to validate the proposed pIp for performing a motion accurately and rapidly. PMID:23820745

Measurement of the robot motor capability of a robot motor system: a Fitts's-law-inspired approach.

PubMed

Lin, Hsien-I; Lee, C S George

2013-07-02

Robot motor capability is a crucial factor for a robot, because it affects how accurately and rapidly a robot can perform a motion to accomplish a task constrained by spatial and temporal conditions. In this paper, we propose and derive a pseudo-index of motor performance (pIp) to characterize robot motor capability with robot kinematics, dynamics and control taken into consideration. The proposed pIp provides a quantitative measure for a robot with revolute joints, which is inspired from an index of performance in Fitts's law of human skills. Computer simulations and experiments on a PUMA 560 industrial robot were conducted to validate the proposed pIp for performing a motion accurately and rapidly.

Man-Robot Symbiosis: A Framework For Cooperative Intelligence And Control

NASA Astrophysics Data System (ADS)

Parker, Lynne E.; Pin, Francois G.

1988-10-01

The man-robot symbiosis concept has the fundamental objective of bridging the gap between fully human-controlled and fully autonomous systems to achieve true man-robot cooperative control and intelligence. Such a system would allow improved speed, accuracy, and efficiency of task execution, while retaining the man in the loop for innovative reasoning and decision-making. The symbiont would have capabilities for supervised and unsupervised learning, allowing an increase of expertise in a wide task domain. This paper describes a robotic system architecture facilitating the symbiotic integration of teleoperative and automated modes of task execution. The architecture reflects a unique blend of many disciplines of artificial intelligence into a working system, including job or mission planning, dynamic task allocation, man-robot communication, automated monitoring, and machine learning. These disciplines are embodied in five major components of the symbiotic framework: the Job Planner, the Dynamic Task Allocator, the Presenter/Interpreter, the Automated Monitor, and the Learning System.

Filtering Data Based on Human-Inspired Forgetting.

PubMed

Freedman, S T; Adams, J A

2011-12-01

Robots are frequently presented with vast arrays of diverse data. Unfortunately, perfect memory and recall provides a mixed blessing. While flawless recollection of episodic data allows increased reasoning, photographic memory can hinder a robot's ability to operate in real-time dynamic environments. Human-inspired forgetting methods may enable robotic systems to rid themselves of out-dated, irrelevant, and erroneous data. This paper presents the use of human-inspired forgetting to act as a filter, removing unnecessary, erroneous, and out-of-date information. The novel ActSimple forgetting algorithm has been developed specifically to provide effective forgetting capabilities to robotic systems. This paper presents the ActSimple algorithm and how it was optimized and tested in a WiFi signal strength estimation task. The results generated by real-world testing suggest that human-inspired forgetting is an effective means of improving the ability of mobile robots to move and operate within complex and dynamic environments.

Dynamic path planning for mobile robot based on particle swarm optimization

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In the contemporary, robots are used in many fields, such as cleaning, medical treatment, space exploration, disaster relief and so on. The dynamic path planning of robot without collision is becoming more and more the focus of people's attention. A new method of path planning is proposed in this paper. Firstly, the motion space model of the robot is established by using the MAKLINK graph method. Then the A* algorithm is used to get the shortest path from the start point to the end point. Secondly, this paper proposes an effective method to detect and avoid obstacles. When an obstacle is detected on the shortest path, the robot will choose the nearest safety point to move. Moreover, calculate the next point which is nearest to the target. Finally, the particle swarm optimization algorithm is used to optimize the path. The experimental results can prove that the proposed method is more effective.

Research regarding stiffness optimization of wires used for joints actuation from an elephant's trunk robotic arm

NASA Astrophysics Data System (ADS)

Ciofu, C.; Stan, G.

2016-11-01

Elephant's trunk robotic arms driven by wires and pulley mechanisms have issues with wires stiffness because of the entailed elastic deformations that is causing errors of positioning. Static and dynamic loads from each joint of the robotic arm affect the stiffness of driving wires and precision positioning. The influence of wires elastic deformation on precision positioning decreases with the increasing of wires stiffness by using different pre-tensioning devices. In this paper, we analyze the variation of driving wires stiffness particularly to each wire driven joint. We obtain optimum wires stiffness variation by using an analytical method that highlights the efficiency of pre-tensioning mechanism. The analysis of driving wires stiffness is necessary for taking appropriate optimization measures of robotic arm dynamic behavior and, thus, for decreasing positioning errors of the elephant's trunk robotic arm with inner actuation through wires/cables.

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.

Motion planning: A journey of robots, molecules, digital actors, and other artifacts

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

Latombe, J.C.

1999-11-01

During the past three decades, motion planning has emerged as a crucial and productive research area in robotics. In the mid-1980s, the most advanced planners were barely able to compute collision-free paths for objects crawling in planar workspaces. Today, planners efficiently deal with robots with many degrees of freedom in complex environments. Techniques also exist to generate quasi-optimal trajectories, coordinate multiple robots, deal with dynamic and kinematic constraints, and handle dynamic environments. This paper describes some of these achievements, presents new problems that have recently emerged, discusses applications likely to motivate future research, and finally gives expectations for the comingmore » years. It stresses the fact that nonrobotics applications (e.g., graphic animation, surgical planning, computational biology) are growing in importance and are likely to shape future motion-planning research more than robotics itself.« less

Dynamic analysis of a bio-inspired climbing robot using ADAMS-Simulink co-simulation

NASA Astrophysics Data System (ADS)

Chattopadhyay, P.; Dikshit, H.; Majumder, A.; Ghoshal, S.; Maity, A.

2018-04-01

Climbing robot has been an area of interest since the demand of inspection of pipeline, nuclear power plant, and various big structure is growing up rapidly. This paper represents the development of a bio-inspired modular robot which mimics inchworm locomotion during climbing. In the present paper, the climbing motion is achieved only on a flat vertical plane by magnetic adhesion principle. The robot is modelled as a 4-link planar mechanism with three revolute joints actuated by DC servo motors. Sinusoidal gait pattern is used to approximate the motion of an inchworm. The dynamics of the robot is presented by using ADAMS/MATLAB co-simulation methodology. The simulation result gives the maximum value of joint torque during one complete cycle of motion. This torque value is used for the selection of servo motor specifications required to build the prototype.

Design of a surgical robot with dynamic vision field control for Single Port Endoscopic Surgery.

PubMed

Kobayashi, Yo; Sekiguchi, Yuta; Tomono, Yu; Watanabe, Hiroki; Toyoda, Kazutaka; Konishi, Kozo; Tomikawa, Morimasa; Ieiri, Satoshi; Tanoue, Kazuo; Hashizume, Makoto; Fujie, Masaktsu G

2010-01-01

Recently, a robotic system was developed to assist Single Port Endoscopic Surgery (SPS). However, the existing system required a manual change of vision field, hindering the surgical task and increasing the degrees of freedom (DOFs) of the manipulator. We proposed a surgical robot for SPS with dynamic vision field control, the endoscope view being manipulated by a master controller. The prototype robot consisted of a positioning and sheath manipulator (6 DOF) for vision field control, and dual tool tissue manipulators (gripping: 5DOF, cautery: 3DOF). Feasibility of the robot was demonstrated in vitro. The "cut and vision field control" (using tool manipulators) is suitable for precise cutting tasks in risky areas while a "cut by vision field control" (using a vision field control manipulator) is effective for rapid macro cutting of tissues. A resection task was accomplished using a combination of both methods.

A Dynamic Compliance Cervix Phantom Robot for Latent Labor Simulation.

PubMed

Luk, Michelle Jennifer; Lobb, Derek; Smith, James Andrew

2018-06-01

Physical simulation systems are commonly used in training of midwifery and obstetrics students, but none of these systems offers a dynamic compliance aspect that would make them more truly representative of cervix ripening. In this study, we introduce a unique soft robot phantom that simulates the cervix softening during the latent labor phase of birth. This proof-of-concept robotic phantom can be dilated by 1 cm and effaced by 35% through the application of a Foley catheter-like loading mechanism. Furthermore, psychophysics trials demonstrate how untrained subjects can identify hard and soft states of the phantom with specificities of 91% and 87%, respectively. Both results indicated the appropriateness for application of this soft robot technology to birth training simulators.

Optimal motion planning for collision avoidance of mobile robots in non-stationary environments

NASA Technical Reports Server (NTRS)

Kyriakopoulos, K. J.; Saridis, G. N.

1992-01-01

An optimal control formulation of the problem of collision avoidance of mobile robots moving in general terrains containing moving obstacles is presented. A dynamic model of the mobile robot and the dynamic constraints are derived. Collision avoidance is guaranteed if the minimum distance between the robot and the object is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. Time consistency with the nominal plan is desirable. A numerical solution of the optimization problem is obtained. A perturbation control type of approach is used to update the optimal plan. Simulation results verify the value of the proposed strategy.

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.

Kinematic control of robot with degenerate wrist

NASA Technical Reports Server (NTRS)

Barker, L. K.; Moore, M. C.

1984-01-01

Kinematic resolved rate equations allow an operator with visual feedback to dynamically control a robot hand. When the robot wrist is degenerate, the computed joint angle rates exceed operational limits, and unwanted hand movements can result. The generalized matrix inverse solution can also produce unwanted responses. A method is introduced to control the robot hand in the region of the degenerate robot wrist. The method uses a coordinated movement of the first and third joints of the robot wrist to locate the second wrist joint axis for movement of the robot hand in the commanded direction. The method does not entail infinite joint angle rates.

Brief Report: Development of a Robotic Intervention Platform for Young Children with ASD

ERIC Educational Resources Information Center

Warren, Zachary; Zheng, Zhi; Das, Shuvajit; Young, Eric M.; Swanson, Amy; Weitlauf, Amy; Sarkar, Nilanjan

2015-01-01

Increasingly researchers are attempting to develop robotic technologies for children with autism spectrum disorder (ASD). This pilot study investigated the development and application of a novel robotic system capable of dynamic, adaptive, and autonomous interaction during imitation tasks with embedded real-time performance evaluation and…

Robust Neural Sliding Mode Control of Robot Manipulators

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

Nguyen Tran Hiep; Pham Thuong Cat

2009-03-05

This paper proposes a robust neural sliding mode control method for robot tracking problem to overcome the noises and large uncertainties in robot dynamics. The Lyapunov direct method has been used to prove the stability of the overall system. Simulation results are given to illustrate the applicability of the proposed method.

Adaptive Control Of Remote Manipulator

NASA Technical Reports Server (NTRS)

Seraji, Homayoun

1989-01-01

Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.

Nonlinear dynamics and chaotic motions in feedback-controlled two- and three-degree-of-freedom robots

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

Ravishankar, A.S. Ghosal, A.

1999-01-01

The dynamics of a feedback-controlled rigid robot is most commonly described by a set of nonlinear ordinary differential equations. In this paper, the authors analyze these equations, representing the feedback-controlled motion of two- and three-degrees-of-freedom rigid robots with revolute (R) and prismatic (P) joints in the absence of compliance, friction, and potential energy, for the possibility of chaotic motions. The authors first study the unforced or inertial motions of the robots, and show that when the Gaussian or Riemannian curvature of the configuration space of a robot is negative, the robot equations can exhibit chaos. If the curvature is zeromore » or positive, then the robot equations cannot exhibit chaos. The authors show that among the two-degrees-of-freedom robots, the PP and the PR robot have zero Gaussian curvature while the RP and RR robots have negative Gaussian curvatures. For the three-degrees-of-freedom robots, they analyze the two well-known RRP and RRR configurations of the Stanford arm and the PUMA manipulator, respectively, and derive the conditions for negative curvature and possible chaotic motions. The criteria of negative curvature cannot be used for the forced or feedback-controlled motions. For the forced motion, the authors resort to the well-known numerical techniques and compute chaos maps, Poincare maps, and bifurcation diagrams. Numerical results are presented for the two-degrees-of-freedom RP and RR robots, and the authors show that these robot equations can exhibit chaos for low controller gains and for large underestimated models. From the bifurcation diagrams, the route to chaos appears to be through period doubling.« less

Improved motor performance in chronic spinal cord injury following upper-limb robotic training.

PubMed

Cortes, Mar; Elder, Jessica; Rykman, Avrielle; Murray, Lynda; Avedissian, Manuel; Stampas, Argyrios; Thickbroom, Gary W; Pascual-Leone, Alvaro; Krebs, Hermano Igo; Valls-Sole, Josep; Edwards, Dylan J

2013-01-01

Recovering upper-limb motor function has important implications for improving independence of patients with tetraplegia after traumatic spinal cord injury (SCI). To evaluate the feasibility, safety and effectiveness of robotic-assisted training of upper limb in a chronic SCI population. A total of 10 chronic tetraplegic SCI patients (C4 to C6 level of injury, American Spinal Injury Association Impairment Scale, A to D) participated in a 6-week wrist-robot training protocol (1 hour/day 3 times/week). The following outcome measures were recorded at baseline and after the robotic training: a) motor performance, assessed by robot-measured kinematics, b) corticospinal excitability measured by transcranial magnetic stimulation (TMS), and c) changes in clinical scales: motor strength (Upper extremity motor score), pain level (Visual Analog Scale) and spasticity (Modified Ashworth scale). No adverse effects were observed during or after the robotic training. Statistically significant improvements were found in motor performance kinematics: aim (pre 1.17 ± 0.11 raduans, post 1.03 ± 0.08 raduans, p = 0.03) and smoothness of movement (pre 0.26 ± 0.03, post 0.31 ± 0.02, p = 0.03). These changes were not accompanied by changes in upper-extremity muscle strength or corticospinal excitability. No changes in pain or spasticity were found. Robotic-assisted training of the upper limb over six weeks is a feasible and safe intervention that can enhance movement kinematics without negatively affecting pain or spasticity in chronic SCI. In addition, robot-assisted devices are an excellent tool to quantify motor performance (kinematics) and can be used to sensitively measure changes after a given rehabilitative intervention.

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.

The use of soft robotics in cardiovascular therapy.

PubMed

Wamala, Isaac; Roche, Ellen T; Pigula, Frank A

2017-10-01

Robots have been employed in cardiovascular therapy as surgical tools and for automation of hospital systems. Soft robots are a new kind of robot made of soft deformable materials, that are uniquely suited for biomedical applications because they are inherently less likely to injure body tissues and more likely to adapt to biological environments. Awareness of the soft robotic systems under development will help promote clinician involvement in their successful clinical translation. Areas covered: The most advanced soft robotic systems, across the size scale from nano to macro, that have shown the most promise for clinical application in cardiovascular therapy because they offer solutions where a clear therapeutic need still exists. We discuss nano and micro scale technology that could help improve targeted therapy for cardiac regeneration in ischemic heart disease, and soft robots for mechanical circulatory support. Additionally, we suggest where the gaps in the technology currently lie. Expert commentary: Soft robotic technology has now matured from the proof-of-concept phase to successful animal testing. With further refinement in materials and clinician guided application, they will be a useful complement for cardiovascular therapy.

Design and Integration for High Performance Robotic Systems Based on Decomposition and Hybridization Approaches

PubMed Central

Zhang, Dan; Wei, Bin

2017-01-01

Currently, the uses of robotics are limited with respect to performance capabilities. Improving the performance of robotic mechanisms is and still will be the main research topic in the next decade. In this paper, design and integration for improving performance of robotic systems are achieved through three different approaches, i.e., structure synthesis design approach, dynamic balancing approach, and adaptive control approach. The purpose of robotic mechanism structure synthesis design is to propose certain mechanism that has better kinematic and dynamic performance as compared to the old ones. For the dynamic balancing design approach, it is normally accomplished based on employing counterweights or counter-rotations. The potential issue is that more weight and inertia will be included in the system. Here, reactionless based on the reconfiguration concept is put forward, which can address the mentioned problem. With the mechanism reconfiguration, the control system needs to be adapted thereafter. One way to address control system adaptation is by applying the “divide and conquer” methodology. It entails modularizing the functionalities: breaking up the control functions into small functional modules, and from those modules assembling the control system according to the changing needs of the mechanism. PMID:28075360

History-Based Response Threshold Model for Division of Labor in Multi-Agent Systems

PubMed Central

Lee, Wonki; Kim, DaeEun

2017-01-01

Dynamic task allocation is a necessity in a group of robots. Each member should decide its own task such that it is most commensurate with its current state in the overall system. In this work, the response threshold model is applied to a dynamic foraging task. Each robot employs a task switching function based on the local task demand obtained from the surrounding environment, and no communication occurs between the robots. Each individual member has a constant-sized task demand history that reflects the global demand. In addition, it has response threshold values for all of the tasks and manages the task switching process depending on the stimuli of the task demands. The robot then determines the task to be executed to regulate the overall division of labor. This task selection induces a specialized tendency for performing a specific task and regulates the division of labor. In particular, maintaining a history of the task demands is very effective for the dynamic foraging task. Various experiments are performed using a simulation with multiple robots, and the results show that the proposed algorithm is more effective as compared to the conventional model. PMID:28555031

From medical images to minimally invasive intervention: Computer assistance for robotic surgery.

PubMed

Lee, Su-Lin; Lerotic, Mirna; Vitiello, Valentina; Giannarou, Stamatia; Kwok, Ka-Wai; Visentini-Scarzanella, Marco; Yang, Guang-Zhong

2010-01-01

Minimally invasive surgery has been established as an important way forward in surgery for reducing patient trauma and hospitalization with improved prognosis. The introduction of robotic assistance enhances the manual dexterity and accuracy of instrument manipulation. Further development of the field in using pre- and intra-operative imaging guidance requires the integration of the general anatomy of the patient with clear pathologic indications and geometrical information for preoperative planning and intra-operative manipulation. It also requires effective visualization and the recreation of haptic and tactile sensing with dynamic active constraints to improve consistency and safety of the surgical procedures. This paper describes key technical considerations of tissue deformation tracking, 3D reconstruction, subject-specific modeling, image guidance and augmented reality for robotic assisted minimally invasive surgery. It highlights the importance of adapting preoperative surgical planning according to intra-operative data and illustrates how dynamic information such as tissue deformation can be incorporated into the surgical navigation framework. Some of the recent trends are discussed in terms of instrument design and the usage of dynamic active constraints and human-robot perceptual docking for robotic assisted minimally invasive surgery. Copyright 2009 Elsevier Ltd. All rights reserved.

Goal-oriented robot navigation learning using a multi-scale space representation.

PubMed

Llofriu, M; Tejera, G; Contreras, M; Pelc, T; Fellous, J M; Weitzenfeld, A

2015-12-01

There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells. The task consists of a circular arena with a fixed goal location, in which a robot is trained to find the shortest path to the goal after a number of learning trials. Synaptic connections are modified using a reinforcement learning paradigm adapted to the place cells multi-scale architecture. The model is evaluated in both simulation and physical robots. We find that larger scale and combined multi-scale representations favor goal-oriented navigation task learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Numerical integration and optimization of motions for multibody dynamic systems

NASA Astrophysics Data System (ADS)

Aguilar Mayans, Joan

This thesis considers the optimization and simulation of motions involving rigid body systems. It does so in three distinct parts, with the following topics: optimization and analysis of human high-diving motions, efficient numerical integration of rigid body dynamics with contacts, and motion optimization of a two-link robot arm using Finite-Time Lyapunov Analysis. The first part introduces the concept of eigenpostures, which we use to simulate and analyze human high-diving motions. Eigenpostures are used in two different ways: first, to reduce the complexity of the optimal control problem that we solve to obtain such motions, and second, to generate an eigenposture space to which we map existing real world motions to better analyze them. The benefits of using eigenpostures are showcased through different examples. The second part reviews an extensive list of integration algorithms used for the integration of rigid body dynamics. We analyze the accuracy and stability of the different integrators in the three-dimensional space and the rotation space SO(3). Integrators with an accuracy higher than first order perform more efficiently than integrators with first order accuracy, even in the presence of contacts. The third part uses Finite-time Lyapunov Analysis to optimize motions for a two-link robot arm. Finite-Time Lyapunov Analysis diagnoses the presence of time-scale separation in the dynamics of the optimized motion and provides the information and methodology for obtaining an accurate approximation to the optimal solution, avoiding the complications that timescale separation causes for alternative solution methods.

Gait development on Minitaur, a direct drive quadrupedal robot

NASA Astrophysics Data System (ADS)

Blackman, Daniel J.; Nicholson, John V.; Ordonez, Camilo; Miller, Bruce D.; Clark, Jonathan E.

2016-05-01

This paper describes the development of a dynamic, quadrupedal robot designed for rapid traversal and interaction in human environments. We explore improvements to both physical and control methods to a legged robot (Minitaur) in order to improve the speed and stability of its gaits and increase the range of obstacles that it can overcome, with an eye toward negotiating man-made terrains such as stairs. These modifications include an analysis of physical compliance, an investigation of foot and leg design, and the implementation of ground and obstacle contact sensing for inclusion in the control schemes. Structural and mechanical improvements were made to reduce undesired compliance for more consistent agreement with dynamic models, which necessitated refinement of foot design for greater durability. Contact sensing was implemented into the control scheme for identifying obstacles and deviations in surface level for negotiation of varying terrain. Overall the incorporation of these features greatly enhances the mobility of the dynamic quadrupedal robot and helps to establish a basis for overcoming obstacles.

Passive mapping and intermittent exploration for mobile robots

NASA Technical Reports Server (NTRS)

Engleson, Sean P.

1994-01-01

An adaptive state space architecture is combined with diktiometric representation to provide the framework for designing a robot mapping system with flexible navigation planning tasks. This involves indexing waypoints described as expectations, geometric indexing, and perceptual indexing. Matching and updating the robot's projected position and sensory inputs with indexing waypoints involves matchers, dynamic priorities, transients, and waypoint restructuring. The robot's map learning can be opganized around the principles of passive mapping.

Validation of a robotic balance system for investigations in the control of human standing balance.

PubMed

Luu, Billy L; Huryn, Thomas P; Van der Loos, H F Machiel; Croft, Elizabeth A; Blouin, Jean-Sébastien

2011-08-01

Previous studies have shown that human body sway during standing approximates the mechanics of an inverted pendulum pivoted at the ankle joints. In this study, a robotic balance system incorporating a Stewart platform base was developed to provide a new technique to investigate the neural mechanisms involved in standing balance. The robotic system, programmed with the mechanics of an inverted pendulum, controlled the motion of the body in response to a change in applied ankle torque. The ability of the robotic system to replicate the load properties of standing was validated by comparing the load stiffness generated when subjects balanced their own body to the robot's mechanical load programmed with a low (concentrated-mass model) or high (distributed-mass model) inertia. The results show that static load stiffness was not significantly (p > 0.05) different for standing and the robotic system. Dynamic load stiffness for the robotic system increased with the frequency of sway, as predicted by the mechanics of an inverted pendulum, with the higher inertia being accurately matched to the load properties of the human body. This robotic balance system accurately replicated the physical model of standing and represents a useful tool to simulate the dynamics of a standing person. © 2011 IEEE

Dynamic electronic institutions in agent oriented cloud robotic systems.

PubMed

Nagrath, Vineet; Morel, Olivier; Malik, Aamir; Saad, Naufal; Meriaudeau, Fabrice

2015-01-01

The dot-com bubble bursted in the year 2000 followed by a swift movement towards resource virtualization and cloud computing business model. Cloud computing emerged not as new form of computing or network technology but a mere remoulding of existing technologies to suit a new business model. Cloud robotics is understood as adaptation of cloud computing ideas for robotic applications. Current efforts in cloud robotics stress upon developing robots that utilize computing and service infrastructure of the cloud, without debating on the underlying business model. HTM5 is an OMG's MDA based Meta-model for agent oriented development of cloud robotic systems. The trade-view of HTM5 promotes peer-to-peer trade amongst software agents. HTM5 agents represent various cloud entities and implement their business logic on cloud interactions. Trade in a peer-to-peer cloud robotic system is based on relationships and contracts amongst several agent subsets. Electronic Institutions are associations of heterogeneous intelligent agents which interact with each other following predefined norms. In Dynamic Electronic Institutions, the process of formation, reformation and dissolution of institutions is automated leading to run time adaptations in groups of agents. DEIs in agent oriented cloud robotic ecosystems bring order and group intellect. This article presents DEI implementations through HTM5 methodology.

People Detection by a Mobile Robot Using Stereo Vision in Dynamic Indoor Environments

NASA Astrophysics Data System (ADS)

Méndez-Polanco, José Alberto; Muñoz-Meléndez, Angélica; Morales, Eduardo F.

People detection and tracking is a key issue for social robot design and effective human robot interaction. This paper addresses the problem of detecting people with a mobile robot using a stereo camera. People detection using mobile robots is a difficult task because in real world scenarios it is common to find: unpredictable motion of people, dynamic environments, and different degrees of human body occlusion. Additionally, we cannot expect people to cooperate with the robot to perform its task. In our people detection method, first, an object segmentation method that uses the distance information provided by a stereo camera is used to separate people from the background. The segmentation method proposed in this work takes into account human body proportions to segment people and provides a first estimation of people location. After segmentation, an adaptive contour people model based on people distance to the robot is used to calculate a probability of detecting people. Finally, people are detected merging the probabilities of the contour people model and by evaluating evidence over time by applying a Bayesian scheme. We present experiments on detection of standing and sitting people, as well as people in frontal and side view with a mobile robot in real world scenarios.

Tactile surface classification for limbed robots using a pressure sensitive robot skin.

PubMed

Shill, Jacob J; Collins, Emmanuel G; Coyle, Eric; Clark, Jonathan

2015-02-02

This paper describes an approach to terrain identification based on pressure images generated through direct surface contact using a robot skin constructed around a high-resolution pressure sensing array. Terrain signatures for classification are formulated from the magnitude frequency responses of the pressure images. The initial experimental results for statically obtained images show that the approach yields classification accuracies [Formula: see text]. The methodology is extended to accommodate the dynamic pressure images anticipated when a robot is walking or running. Experiments with a one-legged hopping robot yield similar identification accuracies [Formula: see text]. In addition, the accuracies are independent with respect to changing robot dynamics (i.e., when using different leg gaits). The paper further shows that the high-resolution capabilities of the sensor enables similarly textured surfaces to be distinguished. A correcting filter is developed to accommodate for failures or faults that inevitably occur within the sensing array with continued use. Experimental results show using the correcting filter can extend the effective operational lifespan of a high-resolution sensing array over 6x in the presence of sensor damage. The results presented suggest this methodology can be extended to autonomous field robots, providing a robot with crucial information about the environment that can be used to aid stable and efficient mobility over rough and varying terrains.

A bio-inspired swarm robot coordination algorithm for multiple target searching

NASA Astrophysics Data System (ADS)

Meng, Yan; Gan, Jing; Desai, Sachi

2008-04-01

The coordination of a multi-robot system searching for multi targets is challenging under dynamic environment since the multi-robot system demands group coherence (agents need to have the incentive to work together faithfully) and group competence (agents need to know how to work together well). In our previous proposed bio-inspired coordination method, Local Interaction through Virtual Stigmergy (LIVS), one problem is the considerable randomness of the robot movement during coordination, which may lead to more power consumption and longer searching time. To address these issues, an adaptive LIVS (ALIVS) method is proposed in this paper, which not only considers the travel cost and target weight, but also predicting the target/robot ratio and potential robot redundancy with respect to the detected targets. Furthermore, a dynamic weight adjustment is also applied to improve the searching performance. This new method a truly distributed method where each robot makes its own decision based on its local sensing information and the information from its neighbors. Basically, each robot only communicates with its neighbors through a virtual stigmergy mechanism and makes its local movement decision based on a Particle Swarm Optimization (PSO) algorithm. The proposed ALIVS algorithm has been implemented on the embodied robot simulator, Player/Stage, in a searching target. The simulation results demonstrate the efficiency and robustness in a power-efficient manner with the real-world constraints.

Retention of laparoscopic and robotic skills among medical students: a randomized controlled trial.

PubMed

Orlando, Megan S; Thomaier, Lauren; Abernethy, Melinda G; Chen, Chi Chiung Grace

2017-08-01

Although simulation training beneficially contributes to traditional surgical training, there are less objective data on simulation skills retention. To investigate the retention of laparoscopic and robotic skills after simulation training. We present the second stage of a randomized single-blinded controlled trial in which 40 simulation-naïve medical students were randomly assigned to practice peg transfer tasks on either laparoscopic (N = 20, Fundamentals of Laparoscopic Surgery, Venture Technologies Inc., Waltham, MA) or robotic (N = 20, dV-Trainer, Mimic, Seattle, WA) platforms. In the first stage, two expert surgeons evaluated participants on both tasks before (Stage 1: Baseline) and immediately after training (Stage 1: Post-training) using a modified validated global rating scale of laparoscopic and robotic operative performance. In Stage 2, participants were evaluated on both tasks 11-20 weeks after training. Of the 40 students who participated in Stage 1, 23 (11 laparoscopic and 12 robotic) underwent repeat evaluation. During Stage 2, there were no significant differences between groups in objective or subjective measures for the laparoscopic task. Laparoscopic-trained participants' performances on the laparoscopic task were improved during Stage 2 compared to baseline measured by time to task completion, but not by the modified global rating scale. During the robotic task, the robotic-trained group demonstrated superior economy of motion (p = .017), Tissue Handling (p = .020), and fewer errors (p = .018) compared to the laparoscopic-trained group. Robotic skills acquisition from baseline with no significant deterioration as measured by modified global rating scale scores was observed among robotic-trained participants during Stage 2. Robotic skills acquired through simulation appear to be better maintained than laparoscopic simulation skills. This study is registered on ClinicalTrials.gov (NCT02370407).

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-12-01

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

Social humanoid robot SARA: development of the wrist mechanism

NASA Astrophysics Data System (ADS)

Penčić, M.; Rackov, M.; Čavić, M.; Kiss, I.; Cioată, V. G.

2018-01-01

This paper presents the development of a wrist mechanism for humanoid robots. The research was conducted within the project which develops social humanoid robot Sara - a mobile anthropomorphic platform for researching the social behaviour of robots. There are two basic ways for the realization of humanoid wrist. The first one is based on biologically inspired structures that have variable stiffness, and the second one on low backlash mechanisms that have high stiffness. Our solution is low backlash differential mechanism that requires small actuators. Based on the kinematic-dynamic requirements, a dynamic model of the robot wrist is formed. A dynamic simulation for several hand positions was performed and the driving torques of the wrist mechanism were determined. The realized wrist has 2 DOFs and enables movements in the direction of flexion/extension 115°, ulnar/radial deviation ±45° and the combination of these two movements. It consists of a differential mechanism with three spur bevel gears, two of which are driving and identical, while the last one is the driven gear to which the robot hand is attached. Power transmission and motion from the actuator to the input links of the differential mechanism is realized with two parallel placed identical gear mechanisms. The wrist mechanism has high carrying capacity and reliability, high efficiency, a compact design and low backlash that provides high positioning accuracy and repeatability of movements, which is essential for motion control.

High effective inverse dynamics modelling for dual-arm robot

NASA Astrophysics Data System (ADS)

Shen, Haoyu; Liu, Yanli; Wu, Hongtao

2018-05-01

To deal with the problem of inverse dynamics modelling for dual arm robot, a recursive inverse dynamics modelling method based on decoupled natural orthogonal complement is presented. In this model, the concepts and methods of Decoupled Natural Orthogonal Complement matrices are used to eliminate the constraint forces in the Newton-Euler kinematic equations, and the screws is used to express the kinematic and dynamics variables. On this basis, the paper has developed a special simulation program with symbol software of Mathematica and conducted a simulation research on the a dual-arm robot. Simulation results show that the proposed method based on decoupled natural orthogonal complement can save an enormous amount of CPU time that was spent in computing compared with the recursive Newton-Euler kinematic equations and the results is correct and reasonable, which can verify the reliability and efficiency of the method.

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.

Control of free-flying space robot manipulator systems

NASA Technical Reports Server (NTRS)

Cannon, Robert H., Jr.

1990-01-01

New control techniques for self contained, autonomous free flying space robots were developed and tested experimentally. Free flying robots are envisioned as a key element of any successful long term presence in space. These robots must be capable of performing the assembly, maintenance, and inspection, and repair tasks that currently require human extravehicular activity (EVA). A set of research projects were developed and carried out using lab models of satellite robots and a flexible manipulator. The second generation space robot models use air cushion vehicle (ACV) technology to simulate in 2-D the drag free, zero g conditions of space. The current work is divided into 5 major projects: Global Navigation and Control of a Free Floating Robot, Cooperative Manipulation from a Free Flying Robot, Multiple Robot Cooperation, Thrusterless Robotic Locomotion, and Dynamic Payload Manipulation. These projects are examined in detail.

Simultaneous application of multiple platforms (Glider, Scanfish, profiling mooring, CTD) to improve detection and quantification of temporal ocean dynamics

NASA Astrophysics Data System (ADS)

Meyer, D.; Prien, R. D.; Lips, U.; Naumann, M.; Liblik, T.; Schulz-Bull, D. E.

2016-02-01

Ocean dynamics are difficult to observe given the broad spectrum of temporal and spatial scales. Robotic technology can be used to address this issue, and help to investigate the variability of physical and biogeochemical processes. This work focuses on ocean robots and in particular on glider technology which seems to be one of the most promising oceanographic tools for future marine research. In this context, we present the results of an observational program conducted in the Baltic Sea combining a profiling mooring (GODESS - Gotland Deep Environmental Sampling Station) and glider technology (Slocum). The temporal variability is captured by the mooring, while the spatial variability is obtained from the glider sampling the surrounding area. Furthermore, classical CTD-measurements and an underwater vehicle (Scanfish) are used simultaneously by two different research vessels to validate and complement the observing network. The main aim of the study is to identify possible synergies between the different platforms and to get a better understanding of maximizing the information content of the data collected by this network. The value and the quality of the data of each individual platform is analyzed and their contribution to the performance of the network itself evaluated.

The effect of inertial coupling in the dynamics and control of flexible robotic manipulators

NASA Technical Reports Server (NTRS)

Tesar, Delbert; Curran, Carol Cockrell; Graves, Philip Lee

1988-01-01

A general model of the dynamics of flexible robotic manipulators is presented, including the gross motion of the links, the vibrations of the links and joints, and the dynamic coupling between the gross motions and vibrations. The vibrations in the links may be modeled using lumped parameters, truncated modal summation, a component mode synthesis method, or a mixture of these methods. The local link inertia matrix is derived to obtain the coupling terms between the gross motion of the link and the vibrations of the link. Coupling between the motions of the links results from the kinematic model, which utilizes the method of kinematic influence. The model is used to simulate the dynamics of a flexible space-based robotic manipulator which is attached to a spacecraft, and is free to move with respect to the inertial reference frame. This model may be used to study the dynamic response of the manipulator to the motions of its joints, or to externally applied disturbances.

Virtual Passive Controller for Robot Systems Using Joint Torque Sensors

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.; Juang, Jer-Nan

1997-01-01

This paper presents a control method based on virtual passive dynamic control that will stabilize a robot manipulator using joint torque sensors and a simple joint model. The method does not require joint position or velocity feedback for stabilization. The proposed control method is stable in the sense of Lyaponov. The control method was implemented on several joints of a laboratory robot. The controller showed good stability robustness to system parameter error and to the exclusion of nonlinear dynamic effects on the joints. The controller enhanced position tracking performance and, in the absence of position control, dissipated joint energy.

Compliance control with embedded neural elements

NASA Technical Reports Server (NTRS)

Venkataraman, S. T.; Gulati, S.

1992-01-01

The authors discuss a control approach that embeds the neural elements within a model-based compliant control architecture for robotic tasks that involve contact with unstructured environments. Compliance control experiments have been performed on actual robotics hardware to demonstrate the performance of contact control schemes with neural elements. System parameters were identified under the assumption that environment dynamics have a fixed nonlinear structure. A robotics research arm, placed in contact with a single degree-of-freedom electromechanical environment dynamics emulator, was commanded to move through a desired trajectory. The command was implemented by using a compliant control strategy.

Learning gait of quadruped robot without prior knowledge of the environment

NASA Astrophysics Data System (ADS)

Xu, Tao; Chen, Qijun

2012-09-01

Walking is the basic skill of a legged robot, and one of the promising ways to improve the walking performance and its adaptation to environment changes is to let the robot learn its walking by itself. Currently, most of the walking learning methods are based on robot vision system or some external sensing equipment to estimate the walking performance of certain walking parameters, and therefore are usually only applicable under laboratory condition, where environment can be pre-defined. Inspired by the rhythmic swing movement during walking of legged animals and the behavior of their adjusting their walking gait on different walking surfaces, a concept of walking rhythmic pattern(WRP) is proposed to evaluate the walking specialty of legged robot, which is just based on the walking dynamics of the robot. Based on the onboard acceleration sensor data, a method to calculate WRP using power spectrum in frequency domain and diverse smooth filters is also presented. Since the evaluation of WRP is only based on the walking dynamics data of the robot's body, the proposed method doesn't require prior knowledge of environment and thus can be applied in unknown environment. A gait learning approach of legged robots based on WRP and evolution algorithm(EA) is introduced. By using the proposed approach, a quadruped robot can learn its locomotion by its onboard sensing in an unknown environment, where the robot has no prior knowledge about this place. The experimental result proves proportional relationship exits between WRP match score and walking performance of legged robot, which can be used to evaluate the walking performance in walking optimization under unknown environment.

Kinematical simulation of robotic complex operation for implementing full-scale additive technologies of high-end materials, composites, structures, and buildings

NASA Astrophysics Data System (ADS)

Antsiferov, S. I.; Eltsov, M. Iu; Khakhalev, P. A.

2018-03-01

This paper considers a newly designed electronic digital model of a robotic complex for implementing full-scale additive technologies, funded under a Federal Target Program. The electronic and digital model was used to solve the problem of simulating the movement of a robotic complex using the NX CAD/CAM/CAE system. The virtual mechanism was built and the main assemblies, joints, and drives were identified as part of solving the problem. In addition, the maximum allowed printable area size was identified for the robotic complex, and a simulation of printing a rectangular-shaped article was carried out.

Monitoring Ecosystem Dynamics Ecosystem Using Hyperspectral Reflectance and a Robotic Tram System in Barrow Alaska

NASA Astrophysics Data System (ADS)

Goswami, S.; Gamon, J. A.; Tweedie, C. E.

2012-12-01

Understanding the future state of the earth system requires improved knowledge of ecosystem dynamics and long term observations of how ecosystem structures and functions are being impacted by global change. Improving remote sensing methods is essential for such advancement because satellite remote sensing is the only means by which landscape to continental-scale change can be observed. The Arctic appears to be impacted by climate change more than any other region on Earth. Arctic terrestrial ecosystems comprise only 6% of the land surface area on Earth yet contain an estimated 25% of global soil organic carbon, most of which is stored in permafrost. If projected increases in plant productivity do not offset forecast losses of soil carbon to the atmosphere as greenhouse gases, regional to global greenhouse warming could be enhanced. Soil moisture is an important control of land-atmosphere carbon exchange in arctic terrestrial ecosystems. However, few studies to date have examined using remote sensing, or developed remote sensing methods for observing the complex interplay between soil moisture and plant phenology and productivity in arctic landscapes. This study was motivated by this knowledge gap and addressed the following questions as a contribution to a large scale, multi investigator flooding and draining experiment funded by the National Science Foundation near Barrow, Alaska from 2005 - 2009. 1. How can optical remote sensing be used to monitor the surface hydrology of arctic landscapes? 2. What are the spatio-temporal dynamics of land-surface phenology (NDVI) in the study area and do hydrological treatment has any effect on inter-annual patterns? A new spectral index, the normalized difference surface water index (NDSWI) was developed and tested at multiple spatial and temporal scales. NDSWI uses the 460nm (blue) and 1000nm (IR) bands and was developed to capture surface hydrological dynamics in the study area using the robotic tram system. When applied to high spatial resolution satellite imagery, NDSWI was also able to capture changes in surface hydrology at the landscape scale. Interannual patterns of landsurface phenology (measured with the normalized difference vegetation index - NDVI) unexpectedly lacked marked differences under experimental conditions. Measurement of NDVI was, however, compromised when WTD was above ground level. NDVI and NDSWI were negatively correlated when WTD was above ground level, which held when scaled to MODIS imagery collected from satellite, suggesting that published findings showing a 'greening of the Arctic' may be related to a 'drying of the Arctic' in landscapes dominated by vegetated landscapes where WTD is close to ground level.

ReACT!: An Interactive Educational Tool for AI Planning for Robotics

ERIC Educational Resources Information Center

Dogmus, Zeynep; Erdem, Esra; Patogulu, Volkan

2015-01-01

This paper presents ReAct!, an interactive educational tool for artificial intelligence (AI) planning for robotics. ReAct! enables students to describe robots' actions and change in dynamic domains without first having to know about the syntactic and semantic details of the underlying formalism, and to solve planning problems using…

Can Robots Help the Learning of Skilled Actions?

PubMed Central

Reinkensmeyer, David J.; Patton, James L.

2010-01-01

Learning to move skillfully requires that the motor system adjusts muscle commands based on ongoing performance errors, a process influenced by the dynamics of the task being practiced. Recent experiments from our laboratories show how robotic devices can temporarily alter task dynamics in ways that contribute to the motor learning experience, suggesting possible applications in rehabilitation and sports training. PMID:19098524

Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System

PubMed Central

Milde, Moritz B.; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

2017-01-01

Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware. PMID:28747883

A real-time spiking cerebellum model for learning robot control.

PubMed

Carrillo, Richard R; Ros, Eduardo; Boucheny, Christian; Coenen, Olivier J-M D

2008-01-01

We describe a neural network model of the cerebellum based on integrate-and-fire spiking neurons with conductance-based synapses. The neuron characteristics are derived from our earlier detailed models of the different cerebellar neurons. We tested the cerebellum model in a real-time control application with a robotic platform. Delays were introduced in the different sensorimotor pathways according to the biological system. The main plasticity in the cerebellar model is a spike-timing dependent plasticity (STDP) at the parallel fiber to Purkinje cell connections. This STDP is driven by the inferior olive (IO) activity, which encodes an error signal using a novel probabilistic low frequency model. We demonstrate the cerebellar model in a robot control system using a target-reaching task. We test whether the system learns to reach different target positions in a non-destructive way, therefore abstracting a general dynamics model. To test the system's ability to self-adapt to different dynamical situations, we present results obtained after changing the dynamics of the robotic platform significantly (its friction and load). The experimental results show that the cerebellar-based system is able to adapt dynamically to different contexts.

Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System.

PubMed

Milde, Moritz B; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

2017-01-01

Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware.

Robotic investigation on effect of stretch reflex and crossed inhibitory response on bipedal hopping

PubMed Central

Rosendo, Andre; Ikemoto, Shuhei; Shimizu, Masahiro; Hosoda, Koh

2018-01-01

To maintain balance during dynamic locomotion, the effects of proprioceptive sensory feedback control (e.g. reflexive control) should not be ignored because of its simple sensation and fast reaction time. Scientists have identified the pathways of reflexes; however, it is difficult to investigate their effects during locomotion because locomotion is controlled by a complex neural system and current technology does not allow us to change the control pathways in living humans. To understand these effects, we construct a musculoskeletal bipedal robot, which has similar body structure and dynamics to those of a human. By conducting experiments on this robot, we investigate the effects of reflexes (stretch reflex and crossed inhibitory response) on posture during hopping, a simple and representative bouncing gait with complex dynamics. Through over 300 hopping trials, we confirm that both the stretch reflex and crossed response can contribute to reducing the lateral inclination during hopping. These reflexive pathways do not use any prior knowledge of the dynamic information of the body such as its inclination. Beyond improving the understanding of the human neural system, this study provides roboticists with biomimetic ideas for robot locomotion control. PMID:29593088

Collective search by mobile robots using alpha-beta coordination

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

Goldsmith, S.Y.; Robinett, R. III

1998-04-01

One important application of mobile robots is searching a geographical region to locate the origin of a specific sensible phenomenon. Mapping mine fields, extraterrestrial and undersea exploration, the location of chemical and biological weapons, and the location of explosive devices are just a few potential applications. Teams of robotic bloodhounds have a simple common goal; to converge on the location of the source phenomenon, confirm its intensity, and to remain aggregated around it until directed to take some other action. In cases where human intervention through teleoperation is not possible, the robot team must be deployed in a territory withoutmore » supervision, requiring an autonomous decentralized coordination strategy. This paper presents the alpha beta coordination strategy, a family of collective search algorithms that are based on dynamic partitioning of the robotic team into two complementary social roles according to a sensor based status measure. Robots in the alpha role are risk takers, motivated to improve their status by exploring new regions of the search space. Robots in the beta role are motivated to improve but are conservative, and tend to remain aggregated and stationary until the alpha robots have identified better regions of the search space. Roles are determined dynamically by each member of the team based on the status of the individual robot relative to the current state of the collective. Partitioning the robot team into alpha and beta roles results in a balance between exploration and exploitation, and can yield collective energy savings and improved resistance to sensor noise and defectors. Alpha robots waste energy exploring new territory, and are more sensitive to the effects of ambient noise and to defectors reporting inflated status. Beta robots conserve energy by moving in a direct path to regions of confirmed high status.« less

When a robot is social: spatial arrangements and multimodal semiotic engagement in the practice of social robotics.

PubMed

Alac, Morana; Movellan, Javier; Tanaka, Fumihide

2011-12-01

Social roboticists design their robots to function as social agents in interaction with humans and other robots. Although we do not deny that the robot's design features are crucial for attaining this aim, we point to the relevance of spatial organization and coordination between the robot and the humans who interact with it. We recover these interactions through an observational study of a social robotics laboratory and examine them by applying a multimodal interactional analysis to two moments of robotics practice. We describe the vital role of roboticists and of the group of preverbal infants, who are involved in a robot's design activity, and we argue that the robot's social character is intrinsically related to the subtleties of human interactional moves in laboratories of social robotics. This human involvement in the robot's social agency is not simply controlled by individual will. Instead, the human-machine couplings are demanded by the situational dynamics in which the robot is lodged.

Kinematic equations for resolved-rate control of an industrial robot arm

NASA Technical Reports Server (NTRS)

Barker, L. K.

1983-01-01

An operator can use kinematic, resolved-rate equations to dynamically control a robot arm by watching its response to commanded inputs. Known resolved-rate equations for the control of a particular six-degree-of-freedom industrial robot arm and proceeds to simplify the equations for faster computations are derived. Methods for controlling the robot arm in regions which normally cause mathematical singularities in the resolved-rate equations are discussed.

US Army TARDEC Ground Vehicle Mobility: Dynamics Modeling, Simluation, and Research

DTIC Science & Technology

2011-10-24

DRIVEN. WARFIGHTER FOCUSED. For official use only Stair Climbing of a Small Robot Robotic Vehicle Step Climbing UNCLASSIFIED For official use only...NOTES NASA Jet Propulsion Laboratory, mobility, and robotics section. Briefing to the jet propulsion lab. 14. ABSTRACT N/A 15. SUBJECT TERMS 16...JLTV GCV M2 M915 ASV FTTS HMMWV Platforms Supported APDSmall Robot UNCLASSIFIED For official use only Mobility Events • Vehicle stability • Ride

Scaled position-force tracking for wireless teleoperation of miniaturized surgical robotic system.

PubMed

Guo, Jing; Liu, Chao; Poignet, Philippe

2014-01-01

Miniaturized surgical robotic system presents promising trend for reducing invasiveness during operation. However, cables used for power and communication may affect its performance. In this paper we chose Zigbee wireless communication as a means to replace communication cables for miniaturized surgical robot. Nevertheless, time delay caused by wireless communication presents a new challenge to performance and stability of the teleoperation system. We proposed a bilateral wireless teleoperation architecture taking into consideration of the effect of position-force scaling between operator and slave. Optimal position-force tracking performance is obtained and the overall system is shown to be passive with a simple condition on the scaling factors satisfied. Simulation studies verify the efficiency of the proposed scaled wireless teleoperation scheme.

Control strategy for a dual-arm maneuverable space robot

NASA Technical Reports Server (NTRS)

Wang, P. K. C.

1987-01-01

A simple strategy for the attitude control and arm coordination of a maneuverable space robot with dual arms is proposed. The basic task for the robot consists of the placement of marked rigid solid objects with specified pairs of gripping points and a specified direction of approach for gripping. The strategy consists of three phases each of which involves only elementary rotational and translational collision-free maneuvers of the robot body. Control laws for these elementary maneuvers are derived by using a body-referenced dynamic model of the dual-arm robot.

The use of computer graphic simulation in the development of on-orbit tele-robotic systems

NASA Technical Reports Server (NTRS)

Fernandez, Ken; Hinman, Elaine

1987-01-01

This paper describes the use of computer graphic simulation techniques to resolve critical design and operational issues for robotic systems used for on-orbit operations. These issues are robot motion control, robot path-planning/verification, and robot dynamics. The major design issues in developing effective telerobotic systems are discussed, and the use of ROBOSIM, a NASA-developed computer graphic simulation tool, to address these issues is presented. Simulation plans for the Space Station and the Orbital Maneuvering Vehicle are presented and discussed.

Mobile robot dynamic path planning based on improved genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.

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.

A unified perspective on robot control - The energy Lyapunov function approach

NASA Technical Reports Server (NTRS)

Wen, John T.

1990-01-01

A unified framework for the stability analysis of robot tracking control is presented. By using an energy-motivated Lyapunov function candidate, the closed-loop stability is shown for a large family of control laws sharing a common structure of proportional and derivative feedback and a model-based feedforward. The feedforward can be zero, partial or complete linearized dynamics, partial or complete nonlinear dynamics, or linearized or nonlinear dynamics with parameter adaptation. As result, the dichotomous approaches to the robot control problem based on the open-loop linearization and nonlinear Lyapunov analysis are both included in this treatment. Furthermore, quantitative estimates of the trade-offs between different schemes in terms of the tracking performance, steady state error, domain of convergence, realtime computation load and required a prior model information are derived.

Simulation of in vivo dynamics during robot assisted joint movement.

PubMed

Bobrowitsch, Evgenij; Lorenz, Andrea; Wülker, Nikolaus; Walter, Christian

2014-12-16

Robots are very useful tools in orthopedic research. They can provide force/torque controlled specimen motion with high repeatability and precision. A method to analyze dissipative energy outcome in an entire joint was developed in our group. In a previous study, a sheep knee was flexed while axial load remained constant during the measurement of dissipated energy. We intend to apply this method for the investigation of osteoarthritis. Additionally, the method should be improved by simulation of in vivo knee dynamics. Thus, a new biomechanical testing tool will be developed for analyzing in vitro joint properties after different treatments. Discretization of passive knee flexion was used to construct a complex flexion movement by a robot and simulate altering axial load similar to in vivo sheep knee dynamics described in a previous experimental study. The robot applied an in vivo like axial force profile with high reproducibility during the corresponding knee flexion (total standard deviation of 0.025 body weight (BW)). A total residual error between the in vivo and simulated axial force was 0.16 BW. Posterior-anterior and medio-lateral forces were detected by the robot as a backlash of joint structures. Their curve forms were similar to curve forms of corresponding in vivo measured forces, but in contrast to the axial force, they showed higher total standard deviation of 0.118 and 0.203 BW and higher total residual error of 0.79 and 0.21 BW for posterior-anterior and medio-lateral forces respectively. We developed and evaluated an algorithm for the robotic simulation of complex in vivo joint dynamics using a joint specimen. This should be a new biomechanical testing tool for analyzing joint properties after different treatments.

Robotics On-Board Trainer (ROBoT)

NASA Technical Reports Server (NTRS)

Johnson, Genevieve; Alexander, Greg

2013-01-01

ROBoT is an on-orbit version of the ground-based Dynamics Skills Trainer (DST) that astronauts use for training on a frequent basis. This software consists of two primary software groups. The first series of components is responsible for displaying the graphical scenes. The remaining components are responsible for simulating the Mobile Servicing System (MSS), the Japanese Experiment Module Remote Manipulator System (JEMRMS), and the H-II Transfer Vehicle (HTV) Free Flyer Robotics Operations. The MSS simulation software includes: Robotic Workstation (RWS) simulation, a simulation of the Space Station Remote Manipulator System (SSRMS), a simulation of the ISS Command and Control System (CCS), and a portion of the Portable Computer System (PCS) software necessary for MSS operations. These components all run under the CentOS4.5 Linux operating system. The JEMRMS simulation software includes real-time, HIL, dynamics, manipulator multi-body dynamics, and a moving object contact model with Tricks discrete time scheduling. The JEMRMS DST will be used as a functional proficiency and skills trainer for flight crews. The HTV Free Flyer Robotics Operations simulation software adds a functional simulation of HTV vehicle controllers, sensors, and data to the MSS simulation software. These components are intended to support HTV ISS visiting vehicle analysis and training. The scene generation software will use DOUG (Dynamic On-orbit Ubiquitous Graphics) to render the graphical scenes. DOUG runs on a laptop running the CentOS4.5 Linux operating system. DOUG is an Open GL-based 3D computer graphics rendering package. It uses pre-built three-dimensional models of on-orbit ISS and space shuttle systems elements, and provides realtime views of various station and shuttle configurations.

Cognitive Mapping Based on Conjunctive Representations of Space and Movement

PubMed Central

Zeng, Taiping; Si, Bailu

2017-01-01

It is a challenge to build robust simultaneous localization and mapping (SLAM) system in dynamical large-scale environments. Inspired by recent findings in the entorhinal–hippocampal neuronal circuits, we propose a cognitive mapping model that includes continuous attractor networks of head-direction cells and conjunctive grid cells to integrate velocity information by conjunctive encodings of space and movement. Visual inputs from the local view cells in the model provide feedback cues to correct drifting errors of the attractors caused by the noisy velocity inputs. We demonstrate the mapping performance of the proposed cognitive mapping model on an open-source dataset of 66 km car journey in a 3 km × 1.6 km urban area. Experimental results show that the proposed model is robust in building a coherent semi-metric topological map of the entire urban area using a monocular camera, even though the image inputs contain various changes caused by different light conditions and terrains. The results in this study could inspire both neuroscience and robotic research to better understand the neural computational mechanisms of spatial cognition and to build robust robotic navigation systems in large-scale environments. PMID:29213234

Laparoscopic and robotic skills are transferable in a simulation setting: a randomized controlled trial.

PubMed

Thomaier, Lauren; Orlando, Megan; Abernethy, Melinda; Paka, Chandhana; Chen, Chi Chiung Grace

2017-08-01

Although surgical simulation provides an effective supplement to traditional training, it is not known whether skills are transferable between minimally invasive surgical modalities. The purpose of this study was to assess the transferability of skills between minimally invasive surgical simulation platforms among simulation-naïve participants. Forty simulation-naïve medical students were enrolled in this randomized single-blinded controlled trial. Participants completed a baseline evaluation on laparoscopic (Fundamentals of Laparoscopic Surgery Program, Los Angeles, CA) and robotic (dV-Trainer, Mimic, Seattle, WA) simulation peg transfer tasks. Participants were then randomized to perform a practice session on either the robotic (N = 20) or laparoscopic (N = 20) simulator. Two blinded, expert minimally invasive surgeons evaluated participants before and after training using a modified previously validated subjective global rating scale. Objective measures including time to task completion and Mimic dV-Trainer motion metrics were also recorded. At baseline, there were no significant differences between the training groups as measured by objective and subjective measures for either simulation task. After training, participants randomized to the laparoscopic practice group completed the laparoscopic task faster (p < 0.003) and with higher global rating scale scores (p < 0.001) than the robotic group. Robotic-trained participants performed the robotic task faster (p < 0.001), with improved economy of motion (p < 0.001), and with higher global rating scale scores (p = 0.006) than the laparoscopic group. The robotic practice group also demonstrated significantly improved performance on the laparoscopic task (p = 0.02). Laparoscopic-trained participants also improved their robotic performance (p = 0.02), though the robotic group had a higher percent improvement on the robotic task (p = 0.037). Skills acquired through practice on either laparoscopic or robotic simulation platforms appear to be transferable between modalities. However, participants demonstrate superior skill in the modality in which they specifically train.

TROTER's (Tiny Robotic Operation Team Experiment): A new concept of space robots

NASA Technical Reports Server (NTRS)

Su, Renjeng

1990-01-01

In view of the future need of automation and robotics in space and the existing approaches to the problem, we proposed a new concept of robots for space construction. The new concept is based on the basic idea of decentralization. Decentralization occurs, on the one hand, in using teams of many cooperative robots for construction tasks. Redundancy and modular design are explored to achieve high reliability for team robotic operations. Reliability requirement on individual robots is greatly reduced. Another area of decentralization is manifested by the proposed control hierarchy which eventually includes humans in the loop. The control strategy is constrained by various time delays and calls for different levels of abstraction of the task dynamics. Such technology is needed for remote control of robots in an uncertain environment. Thus, concerns of human safety around robots are relaxed. This presentation also introduces the required technologies behind the new robotic concept.

Dealing with the time-varying parameter problem of robot manipulators performing path tracking tasks

NASA Technical Reports Server (NTRS)

Song, Y. D.; Middleton, R. H.

1992-01-01

Many robotic applications involve time-varying payloads during the operation of the robot. It is therefore of interest to consider control schemes that deal with time-varying parameters. Using the properties of the element by element (or Hadarmad) product of matrices, we obtain the robot dynamics in parameter-isolated form, from which a new control scheme is developed. The controller proposed yields zero asymptotic tracking errors when applied to robotic systems with time-varying parameters by using a switching type control law. The results obtained are global in the initial state of the robot, and can be applied to rapidly varying systems.

Two-legged walking robot prescribed motion on a rough cylinder

NASA Astrophysics Data System (ADS)

Golubev, Yury; Melkumova, Elena

2018-05-01

The motion of a walking robot with n legs, that ensure the desired motion of the robot body, is described using general dynamics theoretical framework. When each of the robot legs contacts the surface in a single foothold, the momentum and angular momentum theorems yield a system of six differential equations that form a complete description of the robot motion. In the case of two-leg robot (n = 2) the problem of the existence of the solution can be reduced to a system of algebraic inequalities. Using numerical analysis, the classification of footholds positions for different values of the friction coefficient is obtained.

Simulation tools for robotics research and assessment

NASA Astrophysics Data System (ADS)

Fields, MaryAnne; Brewer, Ralph; Edge, Harris L.; Pusey, Jason L.; Weller, Ed; Patel, Dilip G.; DiBerardino, Charles A.

2016-05-01

The Robotics Collaborative Technology Alliance (RCTA) program focuses on four overlapping technology areas: Perception, Intelligence, Human-Robot Interaction (HRI), and Dexterous Manipulation and Unique Mobility (DMUM). In addition, the RCTA program has a requirement to assess progress of this research in standalone as well as integrated form. Since the research is evolving and the robotic platforms with unique mobility and dexterous manipulation are in the early development stage and very expensive, an alternate approach is needed for efficient assessment. Simulation of robotic systems, platforms, sensors, and algorithms, is an attractive alternative to expensive field-based testing. Simulation can provide insight during development and debugging unavailable by many other means. This paper explores the maturity of robotic simulation systems for applications to real-world problems in robotic systems research. Open source (such as Gazebo and Moby), commercial (Simulink, Actin, LMS), government (ANVEL/VANE), and the RCTA-developed RIVET simulation environments are examined with respect to their application in the robotic research domains of Perception, Intelligence, HRI, and DMUM. Tradeoffs for applications to representative problems from each domain are presented, along with known deficiencies and disadvantages. In particular, no single robotic simulation environment adequately covers the needs of the robotic researcher in all of the domains. Simulation for DMUM poses unique constraints on the development of physics-based computational models of the robot, the environment and objects within the environment, and the interactions between them. Most current robot simulations focus on quasi-static systems, but dynamic robotic motion places an increased emphasis on the accuracy of the computational models. In order to understand the interaction of dynamic multi-body systems, such as limbed robots, with the environment, it may be necessary to build component-level computational models to provide the necessary simulation fidelity for accuracy. However, the Perception domain remains the most problematic for adequate simulation performance due to the often cartoon nature of computer rendering and the inability to model realistic electromagnetic radiation effects, such as multiple reflections, in real-time.

Model-based Robotic Dynamic Motion Control for the Robonaut 2 Humanoid Robot

NASA Technical Reports Server (NTRS)

Badger, Julia M.; Hulse, Aaron M.; Taylor, Ross C.; Curtis, Andrew W.; Gooding, Dustin R.; Thackston, Allison

2013-01-01

Robonaut 2 (R2), an upper-body dexterous humanoid robot, has been undergoing experimental trials on board the International Space Station (ISS) for more than a year. R2 will soon be upgraded with two climbing appendages, or legs, as well as a new integrated model-based control system. This control system satisfies two important requirements; first, that the robot can allow humans to enter its workspace during operation and second, that the robot can move its large inertia with enough precision to attach to handrails and seat track while climbing around the ISS. This is achieved by a novel control architecture that features an embedded impedance control law on the motor drivers called Multi-Loop control which is tightly interfaced with a kinematic and dynamic coordinated control system nicknamed RoboDyn that resides on centralized processors. This paper presents the integrated control algorithm as well as several test results that illustrate R2's safety features and performance.

Path optimisation of a mobile robot using an artificial neural network controller

NASA Astrophysics Data System (ADS)

Singh, M. K.; Parhi, D. R.

2011-01-01

This article proposed a novel approach for design of an intelligent controller for an autonomous mobile robot using a multilayer feed forward neural network, which enables the robot to navigate in a real world dynamic environment. The inputs to the proposed neural controller consist of left, right and front obstacle distance with respect to its position and target angle. The output of the neural network is steering angle. A four layer neural network has been designed to solve the path and time optimisation problem of mobile robots, which deals with the cognitive tasks such as learning, adaptation, generalisation and optimisation. A back propagation algorithm is used to train the network. This article also analyses the kinematic design of mobile robots for dynamic movements. The simulation results are compared with experimental results, which are satisfactory and show very good agreement. The training of the neural nets and the control performance analysis has been done in a real experimental setup.

A soft biomimetic tongue: model reconstruction and motion tracking

NASA Astrophysics Data System (ADS)

Lu, Xuanming; Xu, Weiliang; Li, Xiaoning

2016-04-01

A bioinspired robotic tongue which is actuated by a network of compressed air is proposed for the purpose of mimicking the movements of human tongue. It can be applied in the fields such as medical science and food engineering. The robotic tongue is made of two kinds of silicone rubber Ecoflex 0030 and PDMS with the shape simplified from real human tongue. In order to characterize the robotic tongue, a series of experiments were carried out. Laser scan was applied to reconstruct the static model of robotic tongue when it was under pressurization. After each scan, the robotic tongue was scattered into dense points in the same 3D coordinate system and the coordinates of each point were recorded. Motion tracking system (OptiTrack) was used to track and record the whole process of deformation dynamically during the loading and unloading phase. In the experiments, five types of deformation were achieved including roll-up, roll-down, elongation, groove and twist. Utilizing the discrete points generated by laser scan, the accurate parameterized outline of robotic tongue under different pressure was obtained, which could help demonstrate the static characteristic of robotic tongue. The precise deformation process under one pressure was acquired through the OptiTrack system which contains a series of digital cameras, markers on the robotic tongue and a set of hardware and software for data processing. By means of tracking and recording different process of deformation under different pressure, the dynamic characteristic of robotic tongue could be achieved.

An Outdoor Navigation Platform with a 3D Scanner and Gyro-assisted Odometry

NASA Astrophysics Data System (ADS)

Yoshida, Tomoaki; Irie, Kiyoshi; Koyanagi, Eiji; Tomono, Masahiro

This paper proposes a light-weight navigation platform that consists of gyro-assisted odometry, a 3D laser scanner and map-based localization for human-scale robots. The gyro-assisted odometry provides highly accurate positioning only by dead-reckoning. The 3D laser scanner has a wide field of view and uniform measuring-point distribution. The map-based localization is robust and computationally inexpensive by utilizing a particle filter on a 2D grid map generated by projecting 3D points on to the ground. The system uses small and low-cost sensors, and can be applied to a variety of mobile robots in human-scale environments. Outdoor navigation experiments were conducted at the Tsukuba Challenge held in 2009 and 2010, which is an open proving ground for human-scale robots. Our robot successfully navigated the assigned 1-km courses in a fully autonomous mode multiple times.

Mobile robot motion estimation using Hough transform

NASA Astrophysics Data System (ADS)

Aldoshkin, D. N.; Yamskikh, T. N.; Tsarev, R. Yu

2018-05-01

This paper proposes an algorithm for estimation of mobile robot motion. The geometry of surrounding space is described with range scans (samples of distance measurements) taken by the mobile robot’s range sensors. A similar sample of space geometry in any arbitrary preceding moment of time or the environment map can be used as a reference. The suggested algorithm is invariant to isotropic scaling of samples or map that allows using samples measured in different units and maps made at different scales. The algorithm is based on Hough transform: it maps from measurement space to a straight-line parameters space. In the straight-line parameters, space the problems of estimating rotation, scaling and translation are solved separately breaking down a problem of estimating mobile robot localization into three smaller independent problems. The specific feature of the algorithm presented is its robustness to noise and outliers inherited from Hough transform. The prototype of the system of mobile robot orientation is described.

Soft Actuators for Small-Scale Robotics.

PubMed

Hines, Lindsey; Petersen, Kirstin; Lum, Guo Zhan; Sitti, Metin

2017-04-01

This review comprises a detailed survey of ongoing methodologies for soft actuators, highlighting approaches suitable for nanometer- to centimeter-scale robotic applications. Soft robots present a special design challenge in that their actuation and sensing mechanisms are often highly integrated with the robot body and overall functionality. When less than a centimeter, they belong to an even more special subcategory of robots or devices, in that they often lack on-board power, sensing, computation, and control. Soft, active materials are particularly well suited for this task, with a wide range of stimulants and a number of impressive examples, demonstrating large deformations, high motion complexities, and varied multifunctionality. Recent research includes both the development of new materials and composites, as well as novel implementations leveraging the unique properties of soft materials. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization-based Dynamic Human Walking Prediction

DTIC Science & Technology

2007-01-01

9(1), 1997, p 10-17. 3. Chevallereau, C. and Aousin, Y. Optimal reference trajectories for walking and running of a biped robot. Robotica , v 19...28, 2001, Arlington, Virginia. 13. Mu, XP. and Wu, Q. Synthesis of a complete sagittal gait cycle for a five-link biped robot. Robotica , v 21...gait cycles of a biped robot. Robotica , v 21(2), 2003, p 199-210. 16. Sardain, P. and Bessonnet, G. Forces acting on a biped robot. Center of

Development of automation and robotics for space via computer graphic simulation methods

NASA Technical Reports Server (NTRS)

Fernandez, Ken

1988-01-01

A robot simulation system, has been developed to perform automation and robotics system design studies. The system uses a procedure-oriented solid modeling language to produce a model of the robotic mechanism. The simulator generates the kinematics, inverse kinematics, dynamics, control, and real-time graphic simulations needed to evaluate the performance of the model. Simulation examples are presented, including simulation of the Space Station and the design of telerobotics for the Orbital Maneuvering Vehicle.

Robotic insects: Manufacturing, actuation, and power considerations

NASA Astrophysics Data System (ADS)

Wood, Robert

2015-12-01

As the characteristic size of a flying robot decreases, the challenges for successful flight revert to basic questions of fabrication, actuation, fluid mechanics, stabilization, and power - whereas such questions have in general been answered for larger aircraft. When developing a robot on the scale of a housefly, all hardware must be developed from scratch as there is nothing "off-the-shelf" which can be used for mechanisms, sensors, or computation that would satisfy the extreme mass and power limitations. With these challenges in mind, this talk will present progress in the essential technologies for insect-like robots with an emphasis on multi-scale manufacturing methods, high power density actuation, and energy-efficient power distribution.

Robotic Manufacturing of 18-ft (5.5m) Diameter Cryogenic Fuel Tank Dome Assemblies for the NASA Ares I Rocket

NASA Technical Reports Server (NTRS)

Jones, Ronald E.; Carter, Robert W.

2012-01-01

The Ares I rocket was the first launch vehicle scheduled for manufacture under the National Aeronautic and Space Administration's Constellation program. A series of full-scale Ares I development articles were constructed on the Robotic Weld Tool at the NASA George C. Marshall Space Flight Center in Huntsville, Alabama. The Robotic Weld Tool is a 100 ton, 7- axis, robotic manufacturing system capable of machining and friction stir welding large-scale space hardware. This paper will focus on the friction stir welding of 18-ft (5.5m) diameter cryogenic fuel tank components; specifically, the liquid hydrogen forward dome and two common bulkhead manufacturing development articles.

Robot vibration control using inertial damping forces

NASA Technical Reports Server (NTRS)

Lee, Soo Han; Book, Wayne J.

1991-01-01

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

Robot vibration control using inertial damping forces

NASA Technical Reports Server (NTRS)

Lee, Soo Han; Book, Wayne J.

1989-01-01

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

Structured Kernel Subspace Learning for Autonomous Robot Navigation.

PubMed

Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

2018-02-14

This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

Dynamics and locomotion of flexible foils in a frictional environment

NASA Astrophysics Data System (ADS)

Wang, Xiaolin; Alben, Silas

2018-01-01

Over the past few decades, oscillating flexible foils have been used to study the physics of organismal propulsion in different fluid environments. Here, we extend this work to a study of flexible foils in a frictional environment. When the foil is oscillated by heaving at one end but is not free to locomote, the dynamics change from periodic to non-periodic and chaotic as the heaving amplitude increases or the bending rigidity decreases. For friction coefficients lying in a certain range, the transition passes through a sequence of N-periodic and asymmetric states before reaching chaotic dynamics. Resonant peaks are damped and shifted by friction and large heaving amplitudes, leading to bistable states. When the foil is free to locomote, the horizontal motion smoothes the resonant behaviours. For moderate frictional coefficients, steady but slow locomotion is obtained. For large transverse friction and small tangential friction corresponding to wheeled snake robots, faster locomotion is obtained. Travelling wave motions arise spontaneously, and move with horizontal speeds that scale as transverse friction coefficient to the power 1/4 and input power that scales as the transverse friction coefficient to the power 5/12. These scalings are consistent with a boundary layer form of the solutions near the foil's leading edge.

Dynamics and locomotion of flexible foils in a frictional environment.

PubMed

Wang, Xiaolin; Alben, Silas

2018-01-01

Over the past few decades, oscillating flexible foils have been used to study the physics of organismal propulsion in different fluid environments. Here, we extend this work to a study of flexible foils in a frictional environment. When the foil is oscillated by heaving at one end but is not free to locomote, the dynamics change from periodic to non-periodic and chaotic as the heaving amplitude increases or the bending rigidity decreases. For friction coefficients lying in a certain range, the transition passes through a sequence of N -periodic and asymmetric states before reaching chaotic dynamics. Resonant peaks are damped and shifted by friction and large heaving amplitudes, leading to bistable states. When the foil is free to locomote, the horizontal motion smoothes the resonant behaviours. For moderate frictional coefficients, steady but slow locomotion is obtained. For large transverse friction and small tangential friction corresponding to wheeled snake robots, faster locomotion is obtained. Travelling wave motions arise spontaneously, and move with horizontal speeds that scale as transverse friction coefficient to the power 1/4 and input power that scales as the transverse friction coefficient to the power 5/12. These scalings are consistent with a boundary layer form of the solutions near the foil's leading edge.

Nanometer-scale displacement measurement with high resolution using dual cavity Fabry-Pérot interferometer for biomimetic robots.

PubMed

Lee, Jin-Hyuk; Kim, Dae-Hyun

2014-10-01

A sensor of a biomimetic robot has to measure very small environmental changes such as, nanometer scale strains or displacements. Fiber optic sensor can be also one of candidates for the biomimetic sensor because the sensor is like thread and the shape of the sensor is similar to muscle fiber. A fiber optic interferometer, which is an optical-based sensor, can measure displacement precisely, so such device has been widely studied for the measurement of displacement on a nanometer-scale. Especially, a Quadrature Phase-Shifted Fiber Fabry-Pérot interferometer (QPS-FFPI) uses phase-information for this measurement, allowing it to provide a precision result with high resolution. In theory, the QPS-FFPI generates two sinusoidal signals of which the phase difference should be 90 degrees for the exact measurement of the displacement. In order to guarantee the condition of the phase difference, the relative adjustment of the cavities of the optical fibers is required. However, with such precise adjustment it is very hard to fix the proper difference of the two cavities for quadrature-phase-shifting. In this paper, a dual-cavity FFPI is newly proposed to measure the displacement on a nanometer-scale with a specific type of signal processing. In the signal processing, a novel phase-compensation algorithm is applied to force the phase difference to be exactly 90 degrees without any physical adjustment. As a result, the paper shows that the phase-compensated dual-cavity FFPI can effectively measure nanometer-scale displacement with high resolution under dynamic conditions.

The effect of a robot-assisted surgical system on the kinematics of user movements.

PubMed

Nisky, Ilana; Hsieh, Michael H; Okamura, Allison M

2013-01-01

Teleoperated robot-assisted surgery (RAS) offers many advantages over traditional minimally invasive surgery. However, RAS has not yet realized its full potential, and it is not clear how to optimally train surgeons to use these systems. We hypothesize that the dynamics of the master manipulator impact the ability of users to make desired movements with the robot. We compared freehand and teleoperated movements of novices and experienced surgeons. To isolate the effects of dynamics from procedural knowledge, we chose simple movements rather than surgical tasks. We found statistically significant effects of teleoperation and user expertise in several aspects of motion, including target acquisition error, movement speed, and movement smoothness. Such quantitative assessment of human motor performance in RAS can impact the design of surgical robots, their control, and surgeon training methods, and eventually, improve patient outcomes.

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

PubMed

Rezazadeh, Siavash; Gregg, Robert D

2016-10-01

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

A traffic priority language for collision-free navigation of autonomous mobile robots in dynamic environments.

PubMed

Bourbakis, N G

1997-01-01

This paper presents a generic traffic priority language, called KYKLOFORTA, used by autonomous robots for collision-free navigation in a dynamic unknown or known navigation space. In a previous work by X. Grossmman (1988), a set of traffic control rules was developed for the navigation of the robots on the lines of a two-dimensional (2-D) grid and a control center coordinated and synchronized their movements. In this work, the robots are considered autonomous: they are moving anywhere and in any direction inside the free space, and there is no need of a central control to coordinate and synchronize them. The requirements for each robot are i) visual perception, ii) range sensors, and iii) the ability of each robot to detect other moving objects in the same free navigation space, define the other objects perceived size, their velocity and their directions. Based on these assumptions, a traffic priority language is needed for each robot, making it able to decide during the navigation and avoid possible collision with other moving objects. The traffic priority language proposed here is based on a set of primitive traffic priority alphabet and rules which compose pattern of corridors for the application of the traffic priority rules.

Reward-Modulated Hebbian Plasticity as Leverage for Partially Embodied Control in Compliant Robotics

PubMed Central

Burms, Jeroen; Caluwaerts, Ken; Dambre, Joni

2015-01-01

In embodied computation (or morphological computation), part of the complexity of motor control is offloaded to the body dynamics. We demonstrate that a simple Hebbian-like learning rule can be used to train systems with (partial) embodiment, and can be extended outside of the scope of traditional neural networks. To this end, we apply the learning rule to optimize the connection weights of recurrent neural networks with different topologies and for various tasks. We then apply this learning rule to a simulated compliant tensegrity robot by optimizing static feedback controllers that directly exploit the dynamics of the robot body. This leads to partially embodied controllers, i.e., hybrid controllers that naturally integrate the computations that are performed by the robot body into a neural network architecture. Our results demonstrate the universal applicability of reward-modulated Hebbian learning. Furthermore, they demonstrate the robustness of systems trained with the learning rule. This study strengthens our belief that compliant robots should or can be seen as computational units, instead of dumb hardware that needs a complex controller. This link between compliant robotics and neural networks is also the main reason for our search for simple universal learning rules for both neural networks and robotics. PMID:26347645

Adaptive walking of a quadrupedal robot based on layered biological reflexes

NASA Astrophysics Data System (ADS)

Zhang, Xiuli; Mingcheng, E.; Zeng, Xiangyu; Zheng, Haojun

2012-07-01

A multiple-legged robot is traditionally controlled by using its dynamic model. But the dynamic-model-based approach fails to acquire satisfactory performances when the robot faces rough terrains and unknown environments. Referring animals' neural control mechanisms, a control model is built for a quadruped robot walking adaptively. The basic rhythmic motion of the robot is controlled by a well-designed rhythmic motion controller(RMC) comprising a central pattern generator(CPG) for hip joints and a rhythmic coupler (RC) for knee joints. CPG and RC have relationships of motion-mapping and rhythmic couple. Multiple sensory-motor models, abstracted from the neural reflexes of a cat, are employed. These reflex models are organized and thus interact with the CPG in three layers, to meet different requirements of complexity and response time to the tasks. On the basis of the RMC and layered biological reflexes, a quadruped robot is constructed, which can clear obstacles and walk uphill and downhill autonomously, and make a turn voluntarily in uncertain environments, interacting with the environment in a way similar to that of an animal. The paper provides a biologically inspired architecture, with which a robot can walk adaptively in uncertain environments in a simple and effective way, and achieve better performances.

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

Collision recognition and direction changes for small scale fish robots by acceleration sensors

NASA Astrophysics Data System (ADS)

Na, Seung Y.; Shin, Daejung; Kim, Jin Y.; Lee, Bae-Ho

2005-05-01

Typical obstacles are walls, rocks, water plants and other nearby robots for a group of small scale fish robots and submersibles that have been constructed in our lab. Sonar sensors are not employed to make the robot structure simple enough. All of circuits, sensors and processor cards are contained in a box of 9 x 7 x 4 cm dimension except motors, fins and external covers. Therefore, image processing results are applied to avoid collisions. However, it is useful only when the obstacles are located far enough to give images processing time for detecting them. Otherwise, acceleration sensors are used to detect collision immediately after it happens. Two of 2-axes acceleration sensors are employed to measure the three components of collision angles, collision magnitudes, and the angles of robot propulsion. These data are integrated to calculate the amount of propulsion direction change. The angle of a collision incident upon an obstacle is the fundamental value to obtain a direction change needed to design a following path. But there is a significant amount of noise due to a caudal fin motor. Because caudal fin provides the main propulsion for a fish robot, there is a periodic swinging noise at the head of a robot. This noise provides a random acceleration effect on the measured acceleration data at the collision. We propose an algorithm which shows that the MEMS-type accelerometers are very effective to provide information for direction changes in spite of the intrinsic noise after the small scale fish robots have made obstacle collision.

Design, analysis and control of a novel tendon-driven magnetic resonance-guided robotic system for minimally invasive breast surgery.

PubMed

Jiang, Shan; Lou, Jinlong; Yang, Zhiyong; Dai, Jiansheng; Yu, Yan

2015-09-01

Biopsy and brachytherapy for small core breast cancer are always difficult medical problems in the field of cancer treatment. This research mainly develops a magnetic resonance imaging-guided high-precision robotic system for breast puncture treatment. First, a 5-degree-of-freedom tendon-based surgical robotic system is introduced in detail. What follows are the kinematic analysis and dynamical modeling of the robotic system, where a mathematic dynamic model is established using the Lagrange method and a lumped parameter tendon model is used to identify the nonlinear gain of the tendon-sheath transmission system. Based on the dynamical models, an adaptive proportional-integral-derivative controller with friction compensation is proposed for accurate position control. Through simulations using different sinusoidal input signals, we observe that the sinusoidal tracking error at 1/2π Hz is 0.41 mm. Finally, the experiments on tendon-sheath transmission and needle insertion performance are conducted, which show that the insertion precision is 0.68 mm in laboratory environment. © IMechE 2015.

An Adaptive Scheme for Robot Localization and Mapping with Dynamically Configurable Inter-Beacon Range Measurements

PubMed Central

Torres-González, Arturo; Martinez-de Dios, Jose Ramiro; Ollero, Anibal

2014-01-01

This work is motivated by robot-sensor network cooperation techniques where sensor nodes (beacons) are used as landmarks for range-only (RO) simultaneous localization and mapping (SLAM). This paper presents a RO-SLAM scheme that actuates over the measurement gathering process using mechanisms that dynamically modify the rate and variety of measurements that are integrated in the SLAM filter. It includes a measurement gathering module that can be configured to collect direct robot-beacon and inter-beacon measurements with different inter-beacon depth levels and at different rates. It also includes a supervision module that monitors the SLAM performance and dynamically selects the measurement gathering configuration balancing SLAM accuracy and resource consumption. The proposed scheme has been applied to an extended Kalman filter SLAM with auxiliary particle filters for beacon initialization (PF-EKF SLAM) and validated with experiments performed in the CONET Integrated Testbed. It achieved lower map and robot errors (34% and 14%, respectively) than traditional methods with a lower computational burden (16%) and similar beacon energy consumption. PMID:24776938

An adaptive scheme for robot localization and mapping with dynamically configurable inter-beacon range measurements.

PubMed

Torres-González, Arturo; Martinez-de Dios, Jose Ramiro; Ollero, Anibal

2014-04-25

This work is motivated by robot-sensor network cooperation techniques where sensor nodes (beacons) are used as landmarks for range-only (RO) simultaneous localization and mapping (SLAM). This paper presents a RO-SLAM scheme that actuates over the measurement gathering process using mechanisms that dynamically modify the rate and variety of measurements that are integrated in the SLAM filter. It includes a measurement gathering module that can be configured to collect direct robot-beacon and inter-beacon measurements with different inter-beacon depth levels and at different rates. It also includes a supervision module that monitors the SLAM performance and dynamically selects the measurement gathering configuration balancing SLAM accuracy and resource consumption. The proposed scheme has been applied to an extended Kalman filter SLAM with auxiliary particle filters for beacon initialization (PF-EKF SLAM) and validated with experiments performed in the CONET Integrated Testbed. It achieved lower map and robot errors (34% and 14%, respectively) than traditional methods with a lower computational burden (16%) and similar beacon energy consumption.

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include realtime, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify & other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include real-time, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identity other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

Real-time Detection of Moving Objects from Moving Vehicles Using Dense Stereo and Optical Flow

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2004-01-01

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time. dense stereo system to include realtime. dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop. computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

A fluid-structure interaction model of soft robotics using an active strain approach

NASA Astrophysics Data System (ADS)

Hess, Andrew; Lin, Zhaowu; Gao, Tong

2017-11-01

Soft robotic swimmers exhibit rich dynamics that stem from the non-linear interplay of the fluid and immersed soft elastic body. Due to the difficulty of handling the nonlinear two-way coupling of hydrodynamic flow and deforming elastic body, studies of flexible swimmers often employ either one-way coupling strategies with imposed motions of the solid body or some simplified elasticity models. To explore the nonlinear dynamics of soft robots powered by smart soft materials, we develop a computational model to deal with the two-way fluid/elastic structure interactions using the fictitious domain method. To mimic the dynamic response of the functional soft material under external actuations, we assume the solid phase to be neo-Hookean, and employ an active strain approach to incorporate actuation, which is based on the multiplicative decomposition of the deformation gradient tensor. We demonstrate the capability of our algorithm by performing a series of numerical explorations that manipulate an elastic structure with finite thickness, starting from simple rectangular or circular plates to soft robot prototypes such as stingrays and jellyfish.

Combining dynamic and static robotic telepathology: a report on 184 consecutive cases of frozen sections, histology and cytology.

PubMed

Della Mea, V; Cataldi, P; Pertoldi, B; Beltrami, C A

2000-01-01

The aim of this paper is to describe the experiments carried out to evaluate the diagnostic efficacy of a dynamic-robotic telepathology system for the delivery of pathology services to distant hospitals. The system provides static/dynamic features and the remote control of a robotized microscope over 4 ISDN lines. For evaluation purposes, 184 consecutive cases of frozen sections (60), gastrointestinal pathology (64), and urinary cytology (60) have been diagnosed at a distance using the system, and the telediagnosis obtained in this way has been compared with the traditional microscopic diagnosis. Diagnostic agreement ranged from 90% in urinary cytology to 100% in frozen sections. The results obtained suggest that such a system can be considered a useful tool for supporting the pathology practice in isolated hospitals.

Real-time maneuver optimization of space-based robots in a dynamic environment: Theory and on-orbit experiments

NASA Astrophysics Data System (ADS)

Chamitoff, Gregory E.; Saenz-Otero, Alvar; Katz, Jacob G.; Ulrich, Steve; Morrell, Benjamin J.; Gibbens, Peter W.

2018-01-01

This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of planning three dimensional trajectories for a robot to navigate within complex surroundings that include numerous static and dynamic obstacles, path constraints and performance limitations. The methodology employs a unique transformation that enables rapid generation of feasible solutions for complex geometries, making it suitable for application to real-time operations and dynamic environments. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and experimental testing was conducted onboard the ISS during Expedition 17 by the first author. Lessons learned from the on-orbit tests were used to further refine the algorithm for future implementations.

Design, fabrication and control of soft robots.

PubMed

Rus, Daniela; Tolley, Michael T

2015-05-28

Conventionally, engineers have employed rigid materials to fabricate precise, predictable robotic systems, which are easily modelled as rigid members connected at discrete joints. Natural systems, however, often match or exceed the performance of robotic systems with deformable bodies. Cephalopods, for example, achieve amazing feats of manipulation and locomotion without a skeleton; even vertebrates such as humans achieve dynamic gaits by storing elastic energy in their compliant bones and soft tissues. Inspired by nature, engineers have begun to explore the design and control of soft-bodied robots composed of compliant materials. This Review discusses recent developments in the emerging field of soft robotics.

Lyapunov vector function method in the motion stabilisation problem for nonholonomic mobile robot

NASA Astrophysics Data System (ADS)

Andreev, Aleksandr; Peregudova, Olga

2017-07-01

In this paper we propose a sampled-data control law in the stabilisation problem of nonstationary motion of nonholonomic mobile robot. We assume that the robot moves on a horizontal surface without slipping. The dynamical model of a mobile robot is considered. The robot has one front free wheel and two rear wheels which are controlled by two independent electric motors. We assume that the controls are piecewise constant signals. Controller design relies on the backstepping procedure with the use of Lyapunov vector-function method. Theoretical considerations are verified by numerical simulation.

Basic Operational Robotics Instructional System

NASA Technical Reports Server (NTRS)

Todd, Brian Keith; Fischer, James; Falgout, Jane; Schweers, John

2013-01-01

The Basic Operational Robotics Instructional System (BORIS) is a six-degree-of-freedom rotational robotic manipulator system simulation used for training of fundamental robotics concepts, with in-line shoulder, offset elbow, and offset wrist. BORIS is used to provide generic robotics training to aerospace professionals including flight crews, flight controllers, and robotics instructors. It uses forward kinematic and inverse kinematic algorithms to simulate joint and end-effector motion, combined with a multibody dynamics model, moving-object contact model, and X-Windows based graphical user interfaces, coordinated in the Trick Simulation modeling environment. The motivation for development of BORIS was the need for a generic system for basic robotics training. Before BORIS, introductory robotics training was done with either the SRMS (Shuttle Remote Manipulator System) or SSRMS (Space Station Remote Manipulator System) simulations. The unique construction of each of these systems required some specialized training that distracted students from the ideas and goals of the basic robotics instruction.

Developments in the Implementation of Acoustic Droplet Ejection for Protein Crystallography.

PubMed

Wu, Ping; Noland, Cameron; Ultsch, Mark; Edwards, Bonnie; Harris, David; Mayer, Robert; Harris, Seth F

2016-02-01

Acoustic droplet ejection (ADE) enables crystallization experiments at the low-nanoliter scale, resulting in rapid vapor diffusion equilibration dynamics and efficient reagent usage in the empirical discovery of structure-enabling protein crystallization conditions. We extend our validation of this technology applied to the diverse physicochemical property space of aqueous crystallization reagents where dynamic fluid analysis coupled to ADE aids in accurate and precise dispensations. Addition of crystallization seed stocks, chemical additives, or small-molecule ligands effectively modulates crystallization, and we here provide examples in optimization of crystal morphology and diffraction quality by the acoustic delivery of ultra-small volumes of these cofactors. Additional applications are discussed, including set up of in situ proteolysis and alternate geometries of crystallization that leverage the small scale afforded by acoustic delivery. Finally, we describe parameters of a system of automation in which the acoustic liquid handler is integrated with a robotic arm, plate centrifuge, peeler, sealer, and stacks, which allows unattended high-throughput crystallization experimentation. © 2015 Society for Laboratory Automation and Screening.

EAP artificial muscle actuators for bio-inspired intelligent social robotics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hanson, David F.

2017-04-01

Bio-inspired intelligent robots are coming of age in both research and industry, propelling market growth for robots and A.I. However, conventional motors limit bio-inspired robotics. EAP actuators and sensors could improve the simplicity, compliance, physical scaling, and offer bio-inspired advantages in robotic locomotion, grasping and manipulation, and social expressions. For EAP actuators to realize their transformative potential, further innovations are needed: the actuators must be robust, fast, powerful, manufacturable, and affordable. This presentation surveys progress, opportunities, and challenges in the author's latest work in social robots and EAP actuators, and proposes a roadmap for EAP actuators in bio-inspired intelligent robotics.

A focused bibliography on robotics

NASA Astrophysics Data System (ADS)

Mergler, H. W.

1983-08-01

The present bibliography focuses on eight robotics-related topics believed by the author to be of special interest to researchers in the field of industrial electronics: robots, sensors, kinematics, dynamics, control systems, actuators, vision, economics, and robot applications. This literature search was conducted through the 1970-present COMPENDEX data base, which provides world-wide coverage of nearly 3500 journals, conference proceedings and reports, and the 1969-1981 INSPEC data base, which is the largest for the English language in the fields of physics, electrotechnology, computers, and control.

Note: Dynamic analysis of a robotic fish motion with a caudal fin with vertical phase differences

NASA Astrophysics Data System (ADS)

Yun, Dongwon; Kim, Kyung-Soo; Kim, Soohyun; Kyung, Jinho; Lee, Sunghwi

2013-03-01

In this paper, a robotic fish with a caudal fin with vertical phase differences is studied, especially focusing on the energy consumption. Energies for thrusting a conventional robotic fish and one with caudal fin with vertical phase differences are obtained and compared each other. It is shown that a robotic fish with a caudal fin with vertical phase differences can save more energy, which implies the efficient thrusting via a vertically waving caudal fin.

Robotic joint experiments under ultravacuum

NASA Technical Reports Server (NTRS)

Borrien, A.; Petitjean, L.

1988-01-01

First, various aspects of a robotic joint development program, including gearbox technology, electromechanical components, lubrication, and test results, are discussed. Secondly, a test prototype of the joint allowing simulation of robotic arm dynamic effects is presented. This prototype is tested under vacuum with different types of motors and sensors to characterize the functional parameters: angular position error, mechanical backlash, gearbox efficiency, and lifetime.

Multi-Robot FastSLAM for Large Domains

DTIC Science & Technology

2007-03-01

Derr, D. Fox, A.B. Cremers , Integrating global position estimation and position tracking for mobile robots: The dynamic markov localization approach...Intelligence (AAAI), 2000. 53. Andrew J. Davison and David W. Murray. Simultaneous Localization and Map- Building Using Active Vision. IEEE...Wyeth, Michael Milford and David Prasser. A Modified Particle Filter for Simultaneous Robot Localization and Landmark Tracking in an Indoor

Modeling the maneuvering of a vehicle

NASA Astrophysics Data System (ADS)

Antonyuk, E. Ya.; Zabuga, A. T.

2012-07-01

A kinematic model of one- and two-link robotic vehicles with two or three steerable wheels is considered. A nonsmooth path in the form of an astroid enveloping the positions of the robot is planned. The motion of a two-link vehicle with such a trajectory is modeled. A numerical analysis of the dynamic of robots is performed determining the reactions of nonholonomic constraints

Dynamic Routing and Coordination in Multi-Agent Networks

DTIC Science & Technology

2016-06-10

SECURITY CLASSIFICATION OF: Supported by this project, we designed innovative routing, planning and coordination strategies for robotic networks and...tasks partitioned among robots , in what order are they to be performed, and along which deterministic routes or according to which stochastic rules do...individual robots move. The fundamental novelties and our recent breakthroughs supported by this project are manifold: (1) the application 1

Robot Comedy Lab: experimenting with the social dynamics of live performance

PubMed Central

Katevas, Kleomenis; Healey, Patrick G. T.; Harris, Matthew Tobias

2015-01-01

The success of live comedy depends on a performer's ability to “work” an audience. Ethnographic studies suggest that this involves the co-ordinated use of subtle social signals such as body orientation, gesture, gaze by both performers and audience members. Robots provide a unique opportunity to test the effects of these signals experimentally. Using a life-size humanoid robot, programmed to perform a stand-up comedy routine, we manipulated the robot's patterns of gesture and gaze and examined their effects on the real-time responses of a live audience. The strength and type of responses were captured using SHORE™computer vision analytics. The results highlight the complex, reciprocal social dynamics of performer and audience behavior. People respond more positively when the robot looks at them, negatively when it looks away and performative gestures also contribute to different patterns of audience response. This demonstrates how the responses of individual audience members depend on the specific interaction they're having with the performer. This work provides insights into how to design more effective, more socially engaging forms of robot interaction that can be used in a variety of service contexts. PMID:26379585

Numerical Modelling and Simulation of Dynamic Parameters for Vibration Driven Mobile Robot: Preliminary Study

NASA Astrophysics Data System (ADS)

Baharudin, M. E.; Nor, A. M.; Saad, A. R. M.; Yusof, A. M.

2018-03-01

The motion of vibration-driven robots is based on an internal oscillating mass which can move without legs or wheels. The oscillation of the unbalanced mass by a motor is translated into vibration which in turn produces vertical and horizontal forces. Both vertical and horizontal oscillations are of the same frequency but the phases are shifted. The vertical forces will deflect the bristles which cause the robot to move forward. In this paper, the horizontal motion direction caused by the vertically vibrated bristle is numerically simulated by tuning the frequency of their oscillatory actuation. As a preliminary work, basic equations for a simple off-centered vibration location on the robot platform and simulation model for vibration excitement are introduced. It involves both static and dynamic vibration analysis of robots and analysis of different type of parameters. In addition, the orientation of the bristles and oscillators are also analysed. Results from the numerical integration seem to be in good agreement with those achieved from the literature. The presented numerical integration modeling can be used for designing the bristles and controlling the speed and direction of the robot.

Active inference and robot control: a case study

PubMed Central

Nizard, Ange; Friston, Karl; Pezzulo, Giovanni

2016-01-01

Active inference is a general framework for perception and action that is gaining prominence in computational and systems neuroscience but is less known outside these fields. Here, we discuss a proof-of-principle implementation of the active inference scheme for the control or the 7-DoF arm of a (simulated) PR2 robot. By manipulating visual and proprioceptive noise levels, we show under which conditions robot control under the active inference scheme is accurate. Besides accurate control, our analysis of the internal system dynamics (e.g. the dynamics of the hidden states that are inferred during the inference) sheds light on key aspects of the framework such as the quintessentially multimodal nature of control and the differential roles of proprioception and vision. In the discussion, we consider the potential importance of being able to implement active inference in robots. In particular, we briefly review the opportunities for modelling psychophysiological phenomena such as sensory attenuation and related failures of gain control, of the sort seen in Parkinson's disease. We also consider the fundamental difference between active inference and optimal control formulations, showing that in the former the heavy lifting shifts from solving a dynamical inverse problem to creating deep forward or generative models with dynamics, whose attracting sets prescribe desired behaviours. PMID:27683002

Modeling and control of a dielectric elastomer actuator

NASA Astrophysics Data System (ADS)

Gupta, Ujjaval; Gu, Guo-Ying; Zhu, Jian

2016-04-01

The emerging field of soft robotics offers the prospect of applying soft actuators as artificial muscles in the robots, replacing traditional actuators based on hard materials, such as electric motors, piezoceramic actuators, etc. Dielectric elastomers are one class of soft actuators, which can deform in response to voltage and can resemble biological muscles in the aspects of large deformation, high energy density and fast response. Recent research into dielectric elastomers has mainly focused on issues regarding mechanics, physics, material designs and mechanical designs, whereas less importance is given to the control of these soft actuators. Strong nonlinearities due to large deformation and electromechanical coupling make control of the dielectric elastomer actuators challenging. This paper investigates feed-forward control of a dielectric elastomer actuator by using a nonlinear dynamic model. The material and physical parameters in the model are identified by quasi-static and dynamic experiments. A feed-forward controller is developed based on this nonlinear dynamic model. Experimental evidence shows that this controller can control the soft actuator to track the desired trajectories effectively. The present study confirms that dielectric elastomer actuators are capable of being precisely controlled with the nonlinear dynamic model despite the presence of material nonlinearity and electromechanical coupling. It is expected that the reported results can promote the applications of dielectric elastomer actuators to soft robots or biomimetic robots.

Use of symbolic computation in robotics education

NASA Technical Reports Server (NTRS)

Vira, Naren; Tunstel, Edward

1992-01-01

An application of symbolic computation in robotics education is described. A software package is presented which combines generality, user interaction, and user-friendliness with the systematic usage of symbolic computation and artificial intelligence techniques. The software utilizes MACSYMA, a LISP-based symbolic algebra language, to automatically generate closed-form expressions representing forward and inverse kinematics solutions, the Jacobian transformation matrices, robot pose error-compensation models equations, and Lagrange dynamics formulation for N degree-of-freedom, open chain robotic manipulators. The goal of such a package is to aid faculty and students in the robotics course by removing burdensome tasks of mathematical manipulations. The software package has been successfully tested for its accuracy using commercially available robots.

Robotic guidance benefits the learning of dynamic, but not of spatial movement characteristics.

PubMed

Lüttgen, Jenna; Heuer, Herbert

2012-10-01

Robotic guidance is an engineered form of haptic-guidance training and intended to enhance motor learning in rehabilitation, surgery, and sports. However, its benefits (and pitfalls) are still debated. Here, we investigate the effects of different presentation modes on the reproduction of a spatiotemporal movement pattern. In three different groups of participants, the movement was demonstrated in three different modalities, namely visual, haptic, and visuo-haptic. After demonstration, participants had to reproduce the movement in two alternating recall conditions: haptic and visuo-haptic. Performance of the three groups during recall was compared with regard to spatial and dynamic movement characteristics. After haptic presentation, participants showed superior dynamic accuracy, whereas after visual presentation, participants performed better with regard to spatial accuracy. Added visual feedback during recall always led to enhanced performance, independent of the movement characteristic and the presentation modality. These findings substantiate the different benefits of different presentation modes for different movement characteristics. In particular, robotic guidance is beneficial for the learning of dynamic, but not of spatial movement characteristics.

Efficient mapping algorithms for scheduling robot inverse dynamics computation on a multiprocessor system

NASA Technical Reports Server (NTRS)

Lee, C. S. G.; Chen, C. L.

1989-01-01

Two efficient mapping algorithms for scheduling the robot inverse dynamics computation consisting of m computational modules with precedence relationship to be executed on a multiprocessor system consisting of p identical homogeneous processors with processor and communication costs to achieve minimum computation time are presented. An objective function is defined in terms of the sum of the processor finishing time and the interprocessor communication time. The minimax optimization is performed on the objective function to obtain the best mapping. This mapping problem can be formulated as a combination of the graph partitioning and the scheduling problems; both have been known to be NP-complete. Thus, to speed up the searching for a solution, two heuristic algorithms were proposed to obtain fast but suboptimal mapping solutions. The first algorithm utilizes the level and the communication intensity of the task modules to construct an ordered priority list of ready modules and the module assignment is performed by a weighted bipartite matching algorithm. For a near-optimal mapping solution, the problem can be solved by the heuristic algorithm with simulated annealing. These proposed optimization algorithms can solve various large-scale problems within a reasonable time. Computer simulations were performed to evaluate and verify the performance and the validity of the proposed mapping algorithms. Finally, experiments for computing the inverse dynamics of a six-jointed PUMA-like manipulator based on the Newton-Euler dynamic equations were implemented on an NCUBE/ten hypercube computer to verify the proposed mapping algorithms. Computer simulation and experimental results are compared and discussed.

[Maintenance and improvement of quality of life among elderly patients using a pet-type robot].

PubMed

Kanamori, Masao; Suzuki, Mizue; Tanaka, Misao

2002-03-01

There have been reports of cases in which quality of life and loneliness of elderly people have been affected by interaction with the pet-type robot AIBO. In the present comparison between first and 20th sessions of activity with the pet-type robot, statistically significant improvements were observed in speech, emotional words and satisfaction index. The AKO loneliness scale value was 3.33 at the first session, and was 1.00 at the 20th session (statistically significant decrease). In a comparison of health-related QOL before and after interaction with AIBO, using the SF-36 survey, role function (RP) was statistically higher at the 20th session than at the first session. Evaluation by CgA, a mental stress index, showed a statistically significant decrease as the number of AIBO sessions increased. Case 1: The patient was a 68-year-old woman with chronic rheumatoid arthritis. Her AKO loneliness scale value was 4 on the first session and 1 on the 20th session. She said, "I do not think about anything while playing with the pet-type robot. It heals my mind." Case 2: The patient was a 74-year-old woman with cervical osteochondrosis. Her AKO loneliness scale value was 5 on the first session and 2 on the 20th session. She said, "The first time, I didn't like playing with the robot because I was depressed. After I had played with the robot several times, I felt good." Case 3: The patient was an 84-year-old man with cerebral apoplexy sequelae. His AKO loneliness scale value was 6 on the first session and 1 on the 20th session. He sang with the robot occasionally. The amount of conversation between him and his children greatly increased. Unlike animals, a pet robot does not carry the risk of bacterial infection. The present results suggest the possibility of using robots as a substitute for animal-assisted therapy and other psychosocial therapy in aseptic rooms, ICUs, children's wards, and special care wards for patients with dementia.

Efficient dynamic simulation for multiple chain robotic mechanisms

NASA Technical Reports Server (NTRS)

Lilly, Kathryn W.; Orin, David E.

1989-01-01

An efficient O(mN) algorithm for dynamic simulation of simple closed-chain robotic mechanisms is presented, where m is the number of chains, and N is the number of degrees of freedom for each chain. It is based on computation of the operational space inertia matrix (6 x 6) for each chain as seen by the body, load, or object. Also, computation of the chain dynamics, when opened at one end, is required, and the most efficient algorithm is used for this purpose. Parallel implementation of the dynamics for each chain results in an O(N) + O(log sub 2 m+1) algorithm.

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.

Seeking Teachers for Underwater Robotics PD Program

ERIC Educational Resources Information Center

McGrath, Beth; Sayres, Jason

2012-01-01

With funding from the National Science Foundation (NSF), ITEEA members will contribute to the development of a hybrid professional development program designed to facilitate the scale-up of an innovative underwater robotics curriculum. WaterBotics[TM] is an underwater robotics curriculum that targets students in middle and high school classrooms…

Energetics in robotic flight at small scales

PubMed Central

Kumar, Vijay

2017-01-01

Recent advances in design, sensing and control have led to aerial robots that offer great promise in a range of real-world applications. However, one critical open question centres on how to improve the energetic efficiency of aerial robots so that they can be useful in practical situations. This review paper provides a survey on small-scale aerial robots (i.e. less than 1 m2 area foot print, and less than 3 kg weight) from the point of view of energetics. The paper discusses methods to improve the efficiency of aerial vehicles, and reports on recent findings by the authors and other groups on modelling the impact of aerodynamics for the purpose of building energy-aware motion planners and controllers. PMID:28163880

Energetics in robotic flight at small scales.

PubMed

Karydis, Konstantinos; Kumar, Vijay

2017-02-06

Recent advances in design, sensing and control have led to aerial robots that offer great promise in a range of real-world applications. However, one critical open question centres on how to improve the energetic efficiency of aerial robots so that they can be useful in practical situations. This review paper provides a survey on small-scale aerial robots (i.e. less than 1 m 2 area foot print, and less than 3 kg weight) from the point of view of energetics. The paper discusses methods to improve the efficiency of aerial vehicles, and reports on recent findings by the authors and other groups on modelling the impact of aerodynamics for the purpose of building energy-aware motion planners and controllers.

Some aspects of robotics calibration, design and control

NASA Technical Reports Server (NTRS)

Tawfik, Hazem

1990-01-01

The main objective is to introduce techniques in the areas of testing and calibration, design, and control of robotic systems. A statistical technique is described that analyzes a robot's performance and provides quantitative three-dimensional evaluation of its repeatability, accuracy, and linearity. Based on this analysis, a corrective action should be taken to compensate for any existing errors and enhance the robot's overall accuracy and performance. A comparison between robotics simulation software packages that were commercially available (SILMA, IGRIP) and that of Kennedy Space Center (ROBSIM) is also included. These computer codes simulate the kinematics and dynamics patterns of various robot arm geometries to help the design engineer in sizing and building the robot manipulator and control system. A brief discussion on an adaptive control algorithm is provided.

A Hybrid Search Algorithm for Swarm Robots Searching in an Unknown Environment

PubMed Central

Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao

2014-01-01

This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency. PMID:25386855

A hybrid search algorithm for swarm robots searching in an unknown environment.

PubMed

Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao

2014-01-01

This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency.

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.

Nonholonomic Ofject Tracking with Optical Sensors and Ofject Recognition Feedback

NASA Technical Reports Server (NTRS)

Goddard, R. E.; Hadaegh, F.

1994-01-01

Robotic controllers frequently operate under constraints. Often, the constraints are imperfectly or completely unknown. In this paper, the Lagrangian dynamics of a planar robot arm are expressed as a function of a globally unknown consraint.

Geometric mechanics for modelling bioinspired robots locomotion: from rigid to continuous (soft) systems

NASA Astrophysics Data System (ADS)

Boyer, Frederic; Porez, Mathieu; Renda, Federico

This talk presents recent geometric tools developed to model the locomotion dynamics of bio-inspired robots. Starting from the model of discrete rigid multibody systems we will rapidly shift to the case of continuous systems inspired from snakes and fish. To that end, we will build on the model of Cosserat media. This extended picture of geometric locomotion dynamics (inspired from fields' theory) will allow us to introduce models of swimming recently used in biorobotics. We will show how modeling a fish as a one-dimensional Cosserat medium allows to recover and extend the Large Amplitude Elongated Body theory of J. Lighthill and to apply it to an eel-like robot. In the same vein, modeling the mantle of cephalopods as a two dimensional Cosserat medium will build a basis for studying the jet propelling of a soft octopus like robot.

Direct model reference adaptive control of robotic arms

NASA Technical Reports Server (NTRS)

Kaufman, Howard; Swift, David C.; Cummings, Steven T.; Shankey, Jeffrey R.

1993-01-01

The results of controlling A PUMA 560 Robotic Manipulator and the NASA shuttle Remote Manipulator System (RMS) using a Command Generator Tracker (CGT) based Model Reference Adaptive Controller (DMRAC) are presented. Initially, the DMRAC algorithm was run in simulation using a detailed dynamic model of the PUMA 560. The algorithm was tuned on the simulation and then used to control the manipulator using minimum jerk trajectories as the desired reference inputs. The ability to track a trajectory in the presence of load changes was also investigated in the simulation. Satisfactory performance was achieved in both simulation and on the actual robot. The obtained responses showed that the algorithm was robust in the presence of sudden load changes. Because these results indicate that the DMRAC algorithm can indeed be successfully applied to the control of robotic manipulators, additional testing was performed to validate the applicability of DMRAC to simulated dynamics of the shuttle RMS.

Adaptive neural control for dual-arm coordination of humanoid robot with unknown nonlinearities in output mechanism.

PubMed

Liu, Zhi; Chen, Ci; Zhang, Yun; Chen, C L P

2015-03-01

To achieve an excellent dual-arm coordination of the humanoid robot, it is essential to deal with the nonlinearities existing in the system dynamics. The literatures so far on the humanoid robot control have a common assumption that the problem of output hysteresis could be ignored. However, in the practical applications, the output hysteresis is widely spread; and its existing limits the motion/force performances of the robotic system. In this paper, an adaptive neural control scheme, which takes the unknown output hysteresis and computational efficiency into account, is presented and investigated. In the controller design, the prior knowledge of system dynamics is assumed to be unknown. The motion error is guaranteed to converge to a small neighborhood of the origin by Lyapunov's stability theory. Simultaneously, the internal force is kept bounded and its error can be made arbitrarily small.

Generation of Adaptive Gait Patterns for Quadruped Robot with CPG Network including Motor Dynamic Model

NASA Astrophysics Data System (ADS)

Son, Yurak; Kamano, Takuya; Yasuno, Takashi; Suzuki, Takayuki; Harada, Hironobu

This paper describes the generation of adaptive gait patterns using new Central Pattern Generators (CPGs) including motor dynamic models for a quadruped robot under various environment. The CPGs act as the flexible oscillators of the joints and make the desired angle of the joints. The CPGs are mutually connected each other, and the sets of their coupling parameters are adjusted by genetic algorithm so that the quadruped robot can realize the stable and adequate gait patterns. As a result of generation, the suitable CPG networks for not only a walking straight gait pattern but also rotation gait patterns are obtained. Experimental results demonstrate that the proposed CPG networks are effective to automatically adjust the adaptive gait patterns for the tested quadruped robot under various environment. Furthermore, the target tracking control based on image processing is achieved by combining the generated gait patterns.

Model of a Soft Robotic Actuator with Embedded Fluidic Network

NASA Astrophysics Data System (ADS)

Gamus, Benny; Or, Yizhar; Gat, Amir

2017-11-01

Soft robotics is an emerging bio-inspired concept of actuation, with promising applications for robotic locomotion and manipulation. Focusing on actuation by pressurized embedded fluidic networks, we present analytic formulation and closed-form solutions of an elastic actuator with pressurized fluidic networks. In this work we account for the effects of solid inertia and elasticity, as well as fluid viscosity, which allows modelling the system's step-response and frequency response as well as suggesting mode elimination and isolation techniques. We also present and model the application of viscous-peeling as an actuation mechanism, simplifying the fabrication process by eliminating the need for internal cavities. The theoretical results describing the viscous-elastic-inertial dynamics of the actuator are illustrated by experiments. The approach presented in this work may pave the way for the design and implementation of soft robotic legged locomotion that exploits dynamic effects.

An implementation of sensor-based force feedback in a compact laparoscopic surgery robot.

PubMed

Lee, Duk-Hee; Choi, Jaesoon; Park, Jun-Woo; Bach, Du-Jin; Song, Seung-Jun; Kim, Yoon-Ho; Jo, Yungho; Sun, Kyung

2009-01-01

Despite the rapid progress in the clinical application of laparoscopic surgery robots, many shortcomings have not yet been fully overcome, one of which is the lack of reliable haptic feedback. This study implemented a force-feedback structure in our compact laparoscopic surgery robot. The surgery robot is a master-slave configuration robot with 5 DOF (degree of freedom corresponding laparoscopic surgical motion. The force-feedback implementation was made in the robot with torque sensors and controllers installed in the pitch joint of the master and slave robots. A simple dynamic model of action-reaction force in the slave robot was used, through which the reflective force was estimated and fed back to the master robot. The results showed the system model could be identified with significant fidelity and the force feedback at the master robot was feasible. However, the qualitative human assessment of the fed-back force showed only limited level of object discrimination ability. Further developments are underway with this result as a framework.

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.

4D motion modeling of the coronary arteries from CT images for robotic assisted minimally invasive surgery

NASA Astrophysics Data System (ADS)

Zhang, Dong Ping; Edwards, Eddie; Mei, Lin; Rueckert, Daniel

2009-02-01

In this paper, we present a novel approach for coronary artery motion modeling from cardiac Computed Tomography( CT) images. The aim of this work is to develop a 4D motion model of the coronaries for image guidance in robotic-assisted totally endoscopic coronary artery bypass (TECAB) surgery. To utilize the pre-operative cardiac images to guide the minimally invasive surgery, it is essential to have a 4D cardiac motion model to be registered with the stereo endoscopic images acquired intraoperatively using the da Vinci robotic system. In this paper, we are investigating the extraction of the coronary arteries and the modelling of their motion from a dynamic sequence of cardiac CT. We use a multi-scale vesselness filter to enhance vessels in the cardiac CT images. The centerlines of the arteries are extracted using a ridge traversal algorithm. Using this method the coronaries can be extracted in near real-time as only local information is used in vessel tracking. To compute the deformation of the coronaries due to cardiac motion, the motion is extracted from a dynamic sequence of cardiac CT. Each timeframe in this sequence is registered to the end-diastole timeframe of the sequence using a non-rigid registration algorithm based on free-form deformations. Once the images have been registered a dynamic motion model of the coronaries can be obtained by applying the computed free-form deformations to the extracted coronary arteries. To validate the accuracy of the motion model we compare the actual position of the coronaries in each time frame with the predicted position of the coronaries as estimated from the non-rigid registration. We expect that this motion model of coronaries can facilitate the planning of TECAB surgery, and through the registration with real-time endoscopic video images it can reduce the conversion rate from TECAB to conventional procedures.

Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation

PubMed Central

Garrido, Jesús A.; Luque, Niceto R.; D'Angelo, Egidio; Ros, Eduardo

2013-01-01

Adaptable gain regulation is at the core of the forward controller operation performed by the cerebro-cerebellar loops and it allows the intensity of motor acts to be finely tuned in a predictive manner. In order to learn and store information about body-object dynamics and to generate an internal model of movement, the cerebellum is thought to employ long-term synaptic plasticity. LTD at the PF-PC synapse has classically been assumed to subserve this function (Marr, 1969). However, this plasticity alone cannot account for the broad dynamic ranges and time scales of cerebellar adaptation. We therefore tested the role of plasticity distributed over multiple synaptic sites (Hansel et al., 2001; Gao et al., 2012) by generating an analog cerebellar model embedded into a control loop connected to a robotic simulator. The robot used a three-joint arm and performed repetitive fast manipulations with different masses along an 8-shape trajectory. In accordance with biological evidence, the cerebellum model was endowed with both LTD and LTP at the PF-PC, MF-DCN and PC-DCN synapses. This resulted in a network scheme whose effectiveness was extended considerably compared to one including just PF-PC synaptic plasticity. Indeed, the system including distributed plasticity reliably self-adapted to manipulate different masses and to learn the arm-object dynamics over a time course that included fast learning and consolidation, along the lines of what has been observed in behavioral tests. In particular, PF-PC plasticity operated as a time correlator between the actual input state and the system error, while MF-DCN and PC-DCN plasticity played a key role in generating the gain controller. This model suggests that distributed synaptic plasticity allows generation of the complex learning properties of the cerebellum. The incorporation of further plasticity mechanisms and of spiking signal processing will allow this concept to be extended in a more realistic computational scenario. PMID:24130518

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.

A variational dynamic programming approach to robot-path planning with a distance-safety criterion

NASA Technical Reports Server (NTRS)

Suh, Suk-Hwan; Shin, Kang G.

1988-01-01

An approach to robot-path planning is developed by considering both the traveling distance and the safety of the robot. A computationally-efficient algorithm is developed to find a near-optimal path with a weighted distance-safety criterion by using a variational calculus and dynamic programming (VCDP) method. The algorithm is readily applicable to any factory environment by representing the free workspace as channels. A method for deriving these channels is also proposed. Although it is developed mainly for two-dimensional problems, this method can be easily extended to a class of three-dimensional problems. Numerical examples are presented to demonstrate the utility and power of this method.

Decentralized adaptive control of robot manipulators with robust stabilization design

NASA Technical Reports Server (NTRS)

Yuan, Bau-San; Book, Wayne J.

1988-01-01

Due to geometric nonlinearities and complex dynamics, a decentralized technique for adaptive control for multilink robot arms is attractive. Lyapunov-function theory for stability analysis provides an approach to robust stabilization. Each joint of the arm is treated as a component subsystem. The adaptive controller is made locally stable with servo signals including proportional and integral gains. This results in the bound on the dynamical interactions with other subsystems. A nonlinear controller which stabilizes the system with uniform boundedness is used to improve the robustness properties of the overall system. As a result, the robot tracks the reference trajectories with convergence. This strategy makes computation simple and therefore facilitates real-time implementation.

Nonlinear adaptive control of an elastic robotic arm

NASA Technical Reports Server (NTRS)

Singh, S. N.

1986-01-01

An approach to control of a class of nonlinear flexible robotic systems is presented. For simplicity, a robot arm (PUMA-type) with three rotational joints is considered. The third link is assumed to be elastic. An adaptive torquer control law is derived for controlling the joint angles. This controller includes a dynamic system in the feedback path, requires only joint angle and rate for feedback, and asymptotically decomposes the elastic dynamics into two subsystems representing the transverse vibrations of the elastic link in two orthogonal planes. To damp out the elastic vibration, a force control law using modal feedback is synthesized. The combination of the torque and force control laws accomplishes joint angle control and elastic mode stabilization.

A Fast Robot Identification and Mapping Algorithm Based on Kinect Sensor.

PubMed

Zhang, Liang; Shen, Peiyi; Zhu, Guangming; Wei, Wei; Song, Houbing

2015-08-14

Internet of Things (IoT) is driving innovation in an ever-growing set of application domains such as intelligent processing for autonomous robots. For an autonomous robot, one grand challenge is how to sense its surrounding environment effectively. The Simultaneous Localization and Mapping with RGB-D Kinect camera sensor on robot, called RGB-D SLAM, has been developed for this purpose but some technical challenges must be addressed. Firstly, the efficiency of the algorithm cannot satisfy real-time requirements; secondly, the accuracy of the algorithm is unacceptable. In order to address these challenges, this paper proposes a set of novel improvement methods as follows. Firstly, the ORiented Brief (ORB) method is used in feature detection and descriptor extraction. Secondly, a bidirectional Fast Library for Approximate Nearest Neighbors (FLANN) k-Nearest Neighbor (KNN) algorithm is applied to feature match. Then, the improved RANdom SAmple Consensus (RANSAC) estimation method is adopted in the motion transformation. In the meantime, high precision General Iterative Closest Points (GICP) is utilized to register a point cloud in the motion transformation optimization. To improve the accuracy of SLAM, the reduced dynamic covariance scaling (DCS) algorithm is formulated as a global optimization problem under the G2O framework. The effectiveness of the improved algorithm has been verified by testing on standard data and comparing with the ground truth obtained on Freiburg University's datasets. The Dr Robot X80 equipped with a Kinect camera is also applied in a building corridor to verify the correctness of the improved RGB-D SLAM algorithm. With the above experiments, it can be seen that the proposed algorithm achieves higher processing speed and better accuracy.

Robot-Arm Dynamic Control by Computer

NASA Technical Reports Server (NTRS)

Bejczy, Antal K.; Tarn, Tzyh J.; Chen, Yilong J.

1987-01-01

Feedforward and feedback schemes linearize responses to control inputs. Method for control of robot arm based on computed nonlinear feedback and state tranformations to linearize system and decouple robot end-effector motions along each of cartesian axes augmented with optimal scheme for correction of errors in workspace. Major new feature of control method is: optimal error-correction loop directly operates on task level and not on joint-servocontrol level.

Intelligent Adaptive Systems: Literature Research of Design Guidance for Intelligent Adaptive Automation and Interfaces

DTIC Science & Technology

2007-09-01

behaviour based on past experience of interacting with the operator), and mobile (i.e., can move themselves from one machine to another). Edwards argues that...Sofge, D., Bugajska, M., Adams, W., Perzanowski, D., and Schultz, A. (2003). Agent-based Multimodal Interface for Dynamically Autonomous Mobile Robots...based architecture can provide a natural and scalable approach to implementing a multimodal interface to control mobile robots through dynamic

Where neuroscience and dynamic system theory meet autonomous robotics: a contracting basal ganglia model for action selection.

PubMed

Girard, B; Tabareau, N; Pham, Q C; Berthoz, A; Slotine, J-J

2008-05-01

Action selection, the problem of choosing what to do next, is central to any autonomous agent architecture. We use here a multi-disciplinary approach at the convergence of neuroscience, dynamical system theory and autonomous robotics, in order to propose an efficient action selection mechanism based on a new model of the basal ganglia. We first describe new developments of contraction theory regarding locally projected dynamical systems. We exploit these results to design a stable computational model of the cortico-baso-thalamo-cortical loops. Based on recent anatomical data, we include usually neglected neural projections, which participate in performing accurate selection. Finally, the efficiency of this model as an autonomous robot action selection mechanism is assessed in a standard survival task. The model exhibits valuable dithering avoidance and energy-saving properties, when compared with a simple if-then-else decision rule.

Control of mechanical systems with rolling constraints: Application to dynamic control of mobile robots

NASA Technical Reports Server (NTRS)

Sarkar, Nilanjan; Yun, Xiaoping; Kumar, Vijay

1994-01-01

There are many examples of mechanical systems that require rolling contacts between two or more rigid bodies. Rolling contacts engender nonholonomic constraints in an otherwise holonomic system. In this article, we develop a unified approach to the control of mechanical systems subject to both holonomic and nonholonomic constraints. We first present a state space realization of a constrained system. We then discuss the input-output linearization and zero dynamics of the system. This approach is applied to the dynamic control of mobile robots. Two types of control algorithms for mobile robots are investigated: trajectory tracking and path following. In each case, a smooth nonlinear feedback is obtained to achieve asymptotic input-output stability and Lagrange stability of the overall system. Simulation results are presented to demonstrate the effectiveness of the control algorithms and to compare the performane of trajectory-tracking and path-following algorithms.

Technological advances in robotic-assisted laparoscopic surgery.

PubMed

Tan, Gerald Y; Goel, Raj K; Kaouk, Jihad H; Tewari, Ashutosh K

2009-05-01

In this article, the authors describe the evolution of urologic robotic systems and the current state-of-the-art features and existing limitations of the da Vinci S HD System (Intuitive Surgical, Inc.). They then review promising innovations in scaling down the footprint of robotic platforms, the early experience with mobile miniaturized in vivo robots, advances in endoscopic navigation systems using augmented reality technologies and tracking devices, the emergence of technologies for robotic natural orifice transluminal endoscopic surgery and single-port surgery, advances in flexible robotics and haptics, the development of new virtual reality simulator training platforms compatible with the existing da Vinci system, and recent experiences with remote robotic surgery and telestration.

Comparison of the effects on dynamic balance and aerobic capacity between objective and subjective methods of high-intensity robot-assisted gait training in chronic stroke patients: a randomized controlled trial.

PubMed

Bae, Young-Hyeon; Lee, Suk Min; Ko, Mansoo

2017-05-01

Robot-assisted gait training (RAGT) is effective for improving dynamic balance and aerobic capacity, but previous RAGT method does not set suitable training intensity. Recently, high-intensity treadmill gait training at 70% of heart rate reserve (HRR) was used for improving aerobic capacity and dynamic balance. This study was designed to compare the effectiveness between objective and subjective methods of high-intensity RAGT for improving dynamic balance and aerobic capacity in chronic stroke. Subjects were randomly allocated into experimental (n = 17) and control (n = 17) groups. The experimental group underwent high-intensity RAGT at 70% of HRR, whereas the control group underwent high-intensity RAGT at an RPE of 15. Both groups received their assigned training for 30 min per session, 3 days per week for 6 weeks. All subjects also received an additional 30 min of conventional physical therapy. Before and after each of the 18 sessions, the dynamic balance and aerobic capacity of all subjects were evaluated by a blinded examiner. After training, Berg Balance Scale (BBS) and Timed Up and Go Test scores, VO 2 max, and VO 2 max/kg were significantly increased in both groups (p < 0.05). These variables in experimental group were significantly greater than control group. However, the BBS score was not significantly different between both groups. All subjects completed high-intensity RAGT. No adverse effect of training was observed in both groups. High-intensity RAGT at 70% of HRR significantly improved dynamic balance and aerobic capacity more than RAGT at RPE of 15. These results suggest that high-intensity RAGT at 70% of HRR is safe and effective for improving dynamic balance and aerobic capacity in chronic stroke.

Development of compositional and contextual communicable congruence in robots by using dynamic neural network models.

PubMed

Park, Gibeom; Tani, Jun

2015-12-01

The current study presents neurorobotics experiments on acquisition of skills for "communicable congruence" with human via learning. A dynamic neural network model which is characterized by its multiple timescale dynamics property was utilized as a neuromorphic model for controlling a humanoid robot. In the experimental task, the humanoid robot was trained to generate specific sequential movement patterns as responding to various sequences of imperative gesture patterns demonstrated by the human subjects by following predefined compositional semantic rules. The experimental results showed that (1) the adopted MTRNN can achieve generalization by learning in the lower feature perception level by using a limited set of tutoring patterns, (2) the MTRNN can learn to extract compositional semantic rules with generalization in its higher level characterized by slow timescale dynamics, (3) the MTRNN can develop another type of cognitive capability for controlling the internal contextual processes as situated to on-going task sequences without being provided with cues for explicitly indicating task segmentation points. The analysis on the dynamic property developed in the MTRNN via learning indicated that the aforementioned cognitive mechanisms were achieved by self-organization of adequate functional hierarchy by utilizing the constraint of the multiple timescale property and the topological connectivity imposed on the network configuration. These results of the current research could contribute to developments of socially intelligent robots endowed with cognitive communicative competency similar to that of human. Copyright © 2015 Elsevier Ltd. All rights reserved.

Robotics-based synthesis of human motion.

PubMed

Khatib, O; Demircan, E; De Sapio, V; Sentis, L; Besier, T; Delp, S

2009-01-01

The synthesis of human motion is a complex procedure that involves accurate reconstruction of movement sequences, modeling of musculoskeletal kinematics, dynamics and actuation, and characterization of reliable performance criteria. Many of these processes have much in common with the problems found in robotics research. Task-based methods used in robotics may be leveraged to provide novel musculoskeletal modeling methods and physiologically accurate performance predictions. In this paper, we present (i) a new method for the real-time reconstruction of human motion trajectories using direct marker tracking, (ii) a task-driven muscular effort minimization criterion and (iii) new human performance metrics for dynamic characterization of athletic skills. Dynamic motion reconstruction is achieved through the control of a simulated human model to follow the captured marker trajectories in real-time. The operational space control and real-time simulation provide human dynamics at any configuration of the performance. A new criteria of muscular effort minimization has been introduced to analyze human static postures. Extensive motion capture experiments were conducted to validate the new minimization criterion. Finally, new human performance metrics were introduced to study in details an athletic skill. These metrics include the effort expenditure and the feasible set of operational space accelerations during the performance of the skill. The dynamic characterization takes into account skeletal kinematics as well as muscle routing kinematics and force generating capacities. The developments draw upon an advanced musculoskeletal modeling platform and a task-oriented framework for the effective integration of biomechanics and robotics methods.

Fractional-order active fault-tolerant force-position controller design for the legged robots using saturated actuator with unknown bias and gain degradation

NASA Astrophysics Data System (ADS)

Farid, Yousef; Majd, Vahid Johari; Ehsani-Seresht, Abbas

2018-05-01

In this paper, a novel fault accommodation strategy is proposed for the legged robots subject to the actuator faults including actuation bias and effective gain degradation as well as the actuator saturation. First, the combined dynamics of two coupled subsystems consisting of the dynamics of the legs subsystem and the body subsystem are developed. Then, the interaction of the robot with the environment is formulated as the contact force optimization problem with equality and inequality constraints. The desired force is obtained by a dynamic model. A robust super twisting fault estimator is proposed to precisely estimate the defective torque amplitude of the faulty actuator in finite time. Defining a novel fractional sliding surface, a fractional nonsingular terminal sliding mode control law is developed. Moreover, by introducing a suitable auxiliary system and using its state vector in the designed controller, the proposed fault-tolerant control (FTC) scheme guarantees the finite-time stability of the closed-loop control system. The robustness and finite-time convergence of the proposed control law is established using the Lyapunov stability theory. Finally, numerical simulations are performed on a quadruped robot to demonstrate the stable walking of the robot with and without actuator faults, and actuator saturation constraints, and the results are compared to results with an integer order fault-tolerant controller.

a New Golf-Swing Robot Model Utilizing Shaft Elasticity

NASA Astrophysics Data System (ADS)

Suzuki, S.; Inooka, H.

1998-10-01

The performance of golf clubs and balls is generally evaluated by using golf-swing robots that conventionally have two or three joints with completely interrelated motion. This interrelation allows the user of this robot to specify only the initial posture and swing velocity of the robot and therefore the swing motion of this type of robot cannot be subtly adjusted to the specific characteristics of individual golf clubs. Consequently, golf-swing robots cannot accurately emulate advanced golfers, and this causes serious problems for the evaluation of golf club performance. In this study, a new golf-swing robot that can adjust its motion to both a specified value of swing velocity and the specific characteristics of individual golf clubs was analytically investigated. This robot utilizes the dynamic interference force produced by its swing motion and by shaft vibration and can therefore emulate advanced golfers and perform highly reliable evaluations of golf clubs.

Building adaptive connectionist-based controllers: review of experiments in human-robot interaction, collective robotics, and computational neuroscience

NASA Astrophysics Data System (ADS)

Billard, Aude

2000-10-01

This paper summarizes a number of experiments in biologically inspired robotics. The common feature to all experiments is the use of artificial neural networks as the building blocks for the controllers. The experiments speak in favor of using a connectionist approach for designing adaptive and flexible robot controllers, and for modeling neurological processes. I present 1) DRAMA, a novel connectionist architecture, which has general property for learning time series and extracting spatio-temporal regularities in multi-modal and highly noisy data; 2) Robota, a doll-shaped robot, which imitates and learns a proto-language; 3) an experiment in collective robotics, where a group of 4 to 15 Khepera robots learn dynamically the topography of an environment whose features change frequently; 4) an abstract, computational model of primate ability to learn by imitation; 5) a model for the control of locomotor gaits in a quadruped legged robot.

Machine learning in motion control

NASA Technical Reports Server (NTRS)

Su, Renjeng; Kermiche, Noureddine

1989-01-01

The existing methodologies for robot programming originate primarily from robotic applications to manufacturing, where uncertainties of the robots and their task environment may be minimized by repeated off-line modeling and identification. In space application of robots, however, a higher degree of automation is required for robot programming because of the desire of minimizing the human intervention. We discuss a new paradigm of robotic programming which is based on the concept of machine learning. The goal is to let robots practice tasks by themselves and the operational data are used to automatically improve their motion performance. The underlying mathematical problem is to solve the problem of dynamical inverse by iterative methods. One of the key questions is how to ensure the convergence of the iterative process. There have been a few small steps taken into this important approach to robot programming. We give a representative result on the convergence problem.

Novel compliant actuator for wearable robotics applications.

PubMed

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

2013-01-01

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

Contact-force distribution optimization and control for quadruped robots using both gradient and adaptive neural networks.

PubMed

Li, Zhijun; Ge, Shuzhi Sam; Liu, Sibang

2014-08-01

This paper investigates optimal feet forces' distribution and control of quadruped robots under external disturbance forces. First, we formulate a constrained dynamics of quadruped robots and derive a reduced-order dynamical model of motion/force. Consider an external wrench on quadruped robots; the distribution of required forces and moments on the supporting legs of a quadruped robot is handled as a tip-point force distribution and used to equilibrate the external wrench. Then, a gradient neural network is adopted to deal with the optimized objective function formulated as to minimize this quadratic objective function subjected to linear equality and inequality constraints. For the obtained optimized tip-point force and the motion of legs, we propose the hybrid motion/force control based on an adaptive neural network to compensate for the perturbations in the environment and approximate feedforward force and impedance of the leg joints. The proposed control can confront the uncertainties including approximation error and external perturbation. The verification of the proposed control is conducted using a simulation.

Intelligent manipulation technique for multi-branch robotic systems

NASA Technical Reports Server (NTRS)

Chen, Alexander Y. K.; Chen, Eugene Y. S.

1990-01-01

New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.

Biologically Inspired SNN for Robot Control.

PubMed

Nichols, Eric; McDaid, Liam J; Siddique, Nazmul

2013-02-01

This paper proposes a spiking-neural-network-based robot controller inspired by the control structures of biological systems. Information is routed through the network using facilitating dynamic synapses with short-term plasticity. Learning occurs through long-term synaptic plasticity which is implemented using the temporal difference learning rule to enable the robot to learn to associate the correct movement with the appropriate input conditions. The network self-organizes to provide memories of environments that the robot encounters. A Pioneer robot simulator with laser and sonar proximity sensors is used to verify the performance of the network with a wall-following task, and the results are presented.

Unicompartmental knee arthroplasty: is robotic technology more accurate than conventional technique?

PubMed

Citak, Mustafa; Suero, Eduardo M; Citak, Musa; Dunbar, Nicholas J; Branch, Sharon H; Conditt, Michael A; Banks, Scott A; Pearle, Andrew D

2013-08-01

Robotic-assisted unicompartmental knee arthroplasty (UKA) with rigid bone fixation "can significantly improve implant placement and leg alignment. The aim of this cadaveric study was to determine whether the use of robotic systems with dynamic bone tracking would provide more accurate UKA implant positioning compared to the conventional manual technique. Three-dimensional CT-based preoperative plans were created to determine the desired position and orientation for the tibial and femoral components. For each pair of cadaver knees, UKA was performed using traditional instrumentation on the left side and using a haptic robotic system on the right side. Postoperative CT scans were obtained and 3D-to-3D iterative closest point registration was performed. Implant position and orientation were compared to the preoperative plan. Surgical RMS errors for femoral component placement were within 1.9 mm and 3.7° in all directions of the planned implant position for the robotic group, while RMS errors for the manual group were within 5.4mm and 10.2°. Average RMS errors for tibial component placement were within 1.4mm and 5.0° in all directions for the robotic group; while, for the manual group, RMS errors were within 5.7 mm and 19.2°. UKA was more precise using a semiactive robotic system with dynamic bone tracking technology compared to the manual technique. Copyright © 2012 Elsevier B.V. All rights reserved.

Angular analysis of the cyclic impacting oscillations in a robotic grinding process

NASA Astrophysics Data System (ADS)

Rafieian, Farzad; Girardin, François; Liu, Zhaoheng; Thomas, Marc; Hazel, Bruce

2014-02-01

In a robotic machining process, a light-weight cutter or grinder is usually held by an articulated robot arm. Material removal is achieved by the rotating cutting tool while the robot end effector ensures that the tool follows a programmed trajectory in order to work on complex curved surfaces or to access hard-to-reach areas. One typical application of such process is maintenance and repair work on hydropower equipment. This paper presents an experimental study of the dynamic characteristics of material removal in robotic grinding, which is unlike conventional grinding due to the lower structural stiffness of the tool-holder robot. The objective of the study is to explore the cyclic nature of this mechanical operation to provide the basis for future development of better process control strategies. Grinding tasks that minimize the number of iterations to converge to the target surface can be better planned based on a good understanding and modeling of the cyclic material removal mechanism. A single degree of freedom dynamic analysis of the process suggests that material removal is performed through high-frequency impacts that mainly last for only a small fraction of the grinding disk rotation period. To detect these discrete cutting events in practice, a grinder is equipped with a rotary encoder. The encoder's signal is acquired through the angular sampling technique. A running cyclic synchronous average is applied to the speed signal to remove its non-cyclic events. The measured instantaneous rotational frequency clearly indicates the impacting nature of the process and captures the transient response excited by these cyclic impacts. The technique also locates the angular positions of cutting impacts in revolution cycles. It is thus possible to draw conclusions about the cyclic nature of dynamic changes in impact-cutting behavior when grinding with a flexible robot. The dynamics of the impacting regime and transient responses to impact-cutting excitations captured synchronously using the angular sampling technique provide feedback that can be used to regulate the material removal process. The experimental results also make it possible to correlate the energy required to remove a chip of metal through impacting with the measured drop in angular speed during grinding.

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.

Miniaturized soft bio-hybrid robotics: a step forward into healthcare applications.

PubMed

Patino, T; Mestre, R; Sánchez, S

2016-10-07

Soft robotics is an emerging discipline that employs soft flexible materials such as fluids, gels and elastomers in order to enhance the use of robotics in healthcare applications. Compared to their rigid counterparts, soft robotic systems have flexible and rheological properties that are closely related to biological systems, thus allowing the development of adaptive and flexible interactions with complex dynamic environments. With new technologies arising in bioengineering, the integration of living cells into soft robotic systems offers the possibility of accomplishing multiple complex functions such as sensing and actuating upon external stimuli. These emerging bio-hybrid systems are showing promising outcomes and opening up new avenues in the field of soft robotics for applications in healthcare and other fields.

Experiments in autonomous robotics

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

Hamel, W.R.

1987-01-01

The Center for Engineering Systems Advanced Research (CESAR) is performing basic research in autonomous robotics for energy-related applications in hazardous environments. The CESAR research agenda includes a strong experimental component to assure practical evaluation of new concepts and theories. An evolutionary sequence of mobile research robots has been planned to support research in robot navigation, world sensing, and object manipulation. A number of experiments have been performed in studying robot navigation and path planning with planar sonar sensing. Future experiments will address more complex tasks involving three-dimensional sensing, dexterous manipulation, and human-scale operations.

Content and face validity of a comprehensive robotic skills training program for general surgery, urology, and gynecology.

PubMed

Dulan, Genevieve; Rege, Robert V; Hogg, Deborah C; Gilberg-Fisher, Kristine K; Tesfay, Seifu T; Scott, Daniel J

2012-04-01

The authors previously developed a comprehensive, proficiency-based robotic training curriculum that aimed to address 23 unique skills identified via task deconstruction of robotic operations. The purpose of this study was to determine the content and face validity of this curriculum. Expert robotic surgeons (n = 12) rated each deconstructed skill regarding relevance to robotic operations, were oriented to the curricular components, performed 3 to 5 repetitions on the 9 exercises, and rated each exercise. In terms of content validity, experts rated all 23 deconstructed skills as highly relevant (4.5 on a 5-point scale). Ratings for the 9 inanimate exercises indicated moderate to thorough measurement of designated skills. For face validity, experts indicated that each exercise effectively measured relevant skills (100% agreement) and was highly effective for training and assessment (4.5 on a 5-point scale). These data indicate that the 23 deconstructed skills accurately represent the appropriate content for robotic skills training and strongly support content and face validity for this curriculum. Copyright © 2012. Published by Elsevier Inc.

Combined virtual and real robotic test-bed for single operator control of multiple robots

NASA Astrophysics Data System (ADS)

Lee, Sam Y.-S.; Hunt, Shawn; Cao, Alex; Pandya, Abhilash

2010-04-01

Teams of heterogeneous robots with different dynamics or capabilities could perform a variety of tasks such as multipoint surveillance, cooperative transport and explorations in hazardous environments. In this study, we work with heterogeneous robots of semi-autonomous ground and aerial robots for contaminant localization. We developed a human interface system which linked every real robot to its virtual counterpart. A novel virtual interface has been integrated with Augmented Reality that can monitor the position and sensory information from video feed of ground and aerial robots in the 3D virtual environment, and improve user situational awareness. An operator can efficiently control the real multi-robots using the Drag-to-Move method on the virtual multi-robots. This enables an operator to control groups of heterogeneous robots in a collaborative way for allowing more contaminant sources to be pursued simultaneously. The advanced feature of the virtual interface system is guarded teleoperation. This can be used to prevent operators from accidently driving multiple robots into walls and other objects. Moreover, the feature of the image guidance and tracking is able to reduce operator workload.

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.

Advancing the Strategic Messages Affecting Robot Trust Effect: The Dynamic of User- and Robot-Generated Content on Human-Robot Trust and Interaction Outcomes.

PubMed

Liang, Yuhua Jake; Lee, Seungcheol Austin

2016-09-01

Human-robot interaction (HRI) will soon transform and shift the communication landscape such that people exchange messages with robots. However, successful HRI requires people to trust robots, and, in turn, the trust affects the interaction. Although prior research has examined the determinants of human-robot trust (HRT) during HRI, no research has examined the messages that people received before interacting with robots and their effect on HRT. We conceptualize these messages as SMART (Strategic Messages Affecting Robot Trust). Moreover, we posit that SMART can ultimately affect actual HRI outcomes (i.e., robot evaluations, robot credibility, participant mood) by affording the persuasive influences from user-generated content (UGC) on participatory Web sites. In Study 1, participants were assigned to one of two conditions (UGC/control) in an original experiment of HRT. Compared with the control (descriptive information only), results showed that UGC moderated the correlation between HRT and interaction outcomes in a positive direction (average Δr = +0.39) for robots as media and robots as tools. In Study 2, we explored the effect of robot-generated content but did not find similar moderation effects. These findings point to an important empirical potential to employ SMART in future robot deployment.

The potential of iRest in measuring the hand function performance of stroke patients.

PubMed

Abdul Rahman, Hisyam; Khor, Kang Xiang; Yeong, Che Fai; Su, Eileen Lee Ming; Narayanan, Aqilah Leela T

2017-01-01

Clinical scales such as Fugl-Meyer Assessment (FMA) and Motor Assessment Scale (MAS) are widely used to evaluate stroke patient's motor performance. However, there are several limitations with these assessment scales such as subjectivity, lack of repeatability, time-consuming and highly depend on the ability of the physiotherapy. In contrast, robot-based assessments are objective, repeatable, and could potentially reduce the assessment time. However, robot-based assessments are not as well established as conventional assessment scale and the correlation to conventional assessment scale is unclear. This study was carried out to identify important parameters in designing tasks that efficiently assess hand function of stroke patients and to quantify potential benefits of robotic assessment modules to predict the conventional assessment score with iRest. Twelve predictive variables were explored, relating to movement time, velocity, strategy, accuracy and smoothness from three robotic assessment modules which are Draw I, Draw Diamond and Draw Circle. Regression models using up to four predictors were developed to describe the MAS. Results show that the time given should be not too long and it would affect the trajectory error. Besides, result also shows that it is possible to use iRest in predicting MAS score. There is a potential of using iRest, a non-motorized device in predicting MAS score.

Vision-based Nano Robotic System for High-throughput Non-embedded Cell Cutting

NASA Astrophysics Data System (ADS)

Shang, Wanfeng; Lu, Haojian; Wan, Wenfeng; Fukuda, Toshio; Shen, Yajing

2016-03-01

Cell cutting is a significant task in biology study, but the highly productive non-embedded cell cutting is still a big challenge for current techniques. This paper proposes a vision-based nano robotic system and then realizes automatic non-embedded cell cutting with this system. First, the nano robotic system is developed and integrated with a nanoknife inside an environmental scanning electron microscopy (ESEM). Then, the positions of the nanoknife and the single cell are recognized, and the distance between them is calculated dynamically based on image processing. To guarantee the positioning accuracy and the working efficiency, we propose a distance-regulated speed adapting strategy, in which the moving speed is adjusted intelligently based on the distance between the nanoknife and the target cell. The results indicate that the automatic non-embedded cutting is able to be achieved within 1-2 mins with low invasion benefiting from the high precise nanorobot system and the sharp edge of nanoknife. This research paves a way for the high-throughput cell cutting at cell’s natural condition, which is expected to make significant impact on the biology studies, especially for the in-situ analysis at cellular and subcellular scale, such as cell interaction investigation, neural signal transduction and low invasive cell surgery.

Evolutionary Design and Simulation of a Tube Crawling Inspection Robot

NASA Technical Reports Server (NTRS)

Craft, Michael; Howsman, Tom; ONeil, Daniel; Howell, Joe T. (Technical Monitor)

2002-01-01

The Space Robotics Assembly Team Simulation (SpaceRATS) is an expansive concept that will hopefully lead to a space flight demonstration of a robotic team cooperatively assembling a system from its constitutive parts. A primary objective of the SpaceRATS project is to develop a generalized evolutionary design approach for multiple classes of robots. The portion of the overall SpaceRats program associated with the evolutionary design and simulation of an inspection robot's morphology is the subject of this paper. The vast majority of this effort has concentrated on the use and modification of Darwin2K, a robotic design and simulation software package, to analyze the design of a tube crawling robot. This robot is designed for carrying out inspection duties in relatively inaccessible locations within a liquid rocket engine similar to the SSME. A preliminary design of the tube crawler robot was completed, and the mechanical dynamics of the system were simulated. An evolutionary approach to optimizing a few parameters of the system was utilized, resulting in a more optimum design.

Decentralized Adaptive Control For Robots

NASA Technical Reports Server (NTRS)

Seraji, Homayoun

1989-01-01

Precise knowledge of dynamics not required. Proposed scheme for control of multijointed robotic manipulator calls for independent control subsystem for each joint, consisting of proportional/integral/derivative feedback controller and position/velocity/acceleration feedforward controller, both with adjustable gains. Independent joint controller compensates for unpredictable effects, gravitation, and dynamic coupling between motions of joints, while forcing joints to track reference trajectories. Scheme amenable to parallel processing in distributed computing system wherein each joint controlled by relatively simple algorithm on dedicated microprocessor.

Dynamic traversal of high bumps and large gaps by a small legged robot

NASA Astrophysics Data System (ADS)

Gart, Sean; Winey, Nastasia; de La Tijera Obert, Rafael; Li, Chen

Small animals encounter and negotiate diverse obstacles comparable in size or larger than themselves. In recent experiments, we found that cockroaches can dynamically traverse bumps up to 4 times hip height and gaps up to 1 body length. To better understand the physics that governs these locomotor transitions, we studied a small six-legged robot negotiating high bumps and large gaps and compared it to animal observations. We found that the robot was able to traverse bumps as large as 1 hip height and gaps as wide as 0.5 body length. For the bump, the robot often climbed over to traverse when initial body yaw was small, but was often deflected laterally and failed to traverse when initial body yaw was large. A simple locomotion energy landscape model explained these observations. For the gap, traversal probability decreased with gap width, which was well explained by a simple Lagrangian model of a forward-moving rigid body falling over the gap edge. For both the bump and the gap, animal performance far exceeded that of the robot, likely due to their relatively higher running speeds and larger rotational oscillations prior to and during obstacle traversal. Differences between animal and robot obstacle negotiation behaviors revealed that animals used active strategies to overcome potential energy barriers.

Locally optimal control under unknown dynamics with learnt cost function: application to industrial robot positioning

NASA Astrophysics Data System (ADS)

Guérin, Joris; Gibaru, Olivier; Thiery, Stéphane; Nyiri, Eric

2017-01-01

Recent methods of Reinforcement Learning have enabled to solve difficult, high dimensional, robotic tasks under unknown dynamics using iterative Linear Quadratic Gaussian control theory. These algorithms are based on building a local time-varying linear model of the dynamics from data gathered through interaction with the environment. In such tasks, the cost function is often expressed directly in terms of the state and control variables so that it can be locally quadratized to run the algorithm. If the cost is expressed in terms of other variables, a model is required to compute the cost function from the variables manipulated. We propose a method to learn the cost function directly from the data, in the same way as for the dynamics. This way, the cost function can be defined in terms of any measurable quantity and thus can be chosen more appropriately for the task to be carried out. With our method, any sensor information can be used to design the cost function. We demonstrate the efficiency of this method through simulating, with the V-REP software, the learning of a Cartesian positioning task on several industrial robots with different characteristics. The robots are controlled in joint space and no model is provided a priori. Our results are compared with another model free technique, consisting in writing the cost function as a state variable.

Cascaded Kalman and particle filters for photogrammetry based gyroscope drift and robot attitude estimation.

PubMed

Sadaghzadeh N, Nargess; Poshtan, Javad; Wagner, Achim; Nordheimer, Eugen; Badreddin, Essameddin

2014-03-01

Based on a cascaded Kalman-Particle Filtering, gyroscope drift and robot attitude estimation method is proposed in this paper. Due to noisy and erroneous measurements of MEMS gyroscope, it is combined with Photogrammetry based vision navigation scenario. Quaternions kinematics and robot angular velocity dynamics with augmented drift dynamics of gyroscope are employed as system state space model. Nonlinear attitude kinematics, drift and robot angular movement dynamics each in 3 dimensions result in a nonlinear high dimensional system. To reduce the complexity, we propose a decomposition of system to cascaded subsystems and then design separate cascaded observers. This design leads to an easier tuning and more precise debugging from the perspective of programming and such a setting is well suited for a cooperative modular system with noticeably reduced computation time. Kalman Filtering (KF) is employed for the linear and Gaussian subsystem consisting of angular velocity and drift dynamics together with gyroscope measurement. The estimated angular velocity is utilized as input of the second Particle Filtering (PF) based observer in two scenarios of stochastic and deterministic inputs. Simulation results are provided to show the efficiency of the proposed method. Moreover, the experimental results based on data from a 3D MEMS IMU and a 3D camera system are used to demonstrate the efficiency of the method. © 2013 ISA Published by ISA All rights reserved.

Robot Acting on Moving Bodies (RAMBO): Interaction with tumbling objects

NASA Technical Reports Server (NTRS)

Davis, Larry S.; Dementhon, Daniel; Bestul, Thor; Ziavras, Sotirios; Srinivasan, H. V.; Siddalingaiah, Madhu; Harwood, David

1989-01-01

Interaction with tumbling objects will become more common as human activities in space expand. Attempting to interact with a large complex object translating and rotating in space, a human operator using only his visual and mental capacities may not be able to estimate the object motion, plan actions or control those actions. A robot system (RAMBO) equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a tumbling object, is being developed. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations rearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enhancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using dynamic interpolations between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Dynamics and control of robotic aircraft with articulated wings

NASA Astrophysics Data System (ADS)

Paranjape, Aditya Avinash

There is a considerable interest in developing robotic aircraft, inspired by birds, for a variety of missions covering reconnaissance and surveillance. Flapping wing aircraft concepts have been put forth in light of the efficiency of flapping flight at small scales. These aircraft are naturally equipped with the ability to rotate their wings about the root, a form of wing articulation. This thesis covers some problems concerning the performance, stability and control of robotic aircraft with articulated wings in gliding flight. Specifically, we are interested in aircraft without a vertical tail, which would then use wing articulation for longitudinal as well as lateral-directional control. Although the dynamics and control of articulated wing aircraft share several common features with conventional fixed wing aircraft, the presence of wing articulation presents several unique benefits as well as limitations from the perspective of performance and control. One of the objective of this thesis is to understand these features using a combination of theoretical and numerical tools. The aircraft concept envisioned in this thesis uses the wing dihedral angles for longitudinal and lateral-directional control. Aircraft with flexible articulated wings are also investigated. We derive a complete nonlinear model of the flight dynamics incorporating dynamic CG location and the changing moment of inertia. We show that symmetric dihedral configuration, along with a conventional horizontal tail, can be used to control flight speed and flight path angle independently of each other. This characteristic is very useful for initiating an efficient perching maneuver. It is shown that wing dihedral angles alone can effectively regulate sideslip during rapid turns and generate a wide range of equilibrium turn rates while maintaining a constant flight speed and regulating sideslip. We compute the turning performance limitations that arise due to the use of wing dihedral for yaw control, and compare the steady state performance of rigid and flexible-winged aircraft. We present an intuitive but very useful notion, called the effective dihedral, which allows us to extend some of the stability and performance results derived for rigid aircraft to flexible aircraft. In the process, we identify the extent of flexibility needed to induce substantial performance benefits, and conversely the extent to which results derived for rigid aircraft apply to a flexible aircraft. We demonstrate, interestingly enough, that wing flexibility actually causes a deterioration in the maximum achievable turn rate when the sideslip is regulated. We also present experimental results which help demonstrate the capability of wing dihedral for control and for executing maneuvers such as slow, rapid descent and perching. Open loop as well as closed loop experiments are performed to demonstrate (a) the effectiveness of symmetric dihedral for flight path angle control, (b) yaw control using asymmetric dihedral, and (c) the elements of perching. Using a simple order of magnitude analysis, we derive conditions under which the wing is structurally statically stable, as well as conditions under which there exists time scale separation between the bending and twisting dynamics. We show that the time scale separation depends on the geometry of the wing cross section, the Poisson's ratio of the wing material, the flight speed and the aspect ratio of the wing. We design independent control laws for bending and twisting. A key contribution of this thesis is the formulation of a partial differential equation (PDE) boundary control problem for wing deformation. PDE-backstepping is used to derive tracking and exponentially stabilizing boundary control laws for wing twist which ensure that a weighted integral of the wing twist (net lift or the rolling moment) tracks the desired time-varying reference input. We show that a control law which only ensures tracking of a weighted integral improves the stability margin of the twisting dynamics sixteen fold. A tracking control law is derived for the wing tip displacement which uses motion planning and a novel two-stage perturbation observer. This work on PDE-based control of wing deformation allows for the use of highly flexible wings on MAVs. Put together, the thesis provides a comprehensive understanding of the flight dynamics of a robotic aircraft equipped with articulated wings, and provides a set of control laws for performing agile maneuvers and for honing the benefits of using highly flexible wings.

Stochastic control approaches for sensor management in search and exploitation

NASA Astrophysics Data System (ADS)

Hitchings, Darin Chester

Recent improvements in the capabilities of autonomous vehicles have motivated their increased use in such applications as defense, homeland security, environmental monitoring, and surveillance. To enhance performance in these applications, new algorithms are required to control teams of robots autonomously and through limited interactions with human operators. In this dissertation we develop new algorithms for control of robots performing information-seeking missions in unknown environments. These missions require robots to control their sensors in order to discover the presence of objects, keep track of the objects, and learn what these objects are, given a fixed sensing budget. Initially, we investigate control of multiple sensors, with a finite set of sensing options and finite-valued measurements, to locate and classify objects given a limited resource budget. The control problem is formulated as a Partially Observed Markov Decision Problem (POMDP), but its exact solution requires excessive computation. Under the assumption that sensor error statistics are independent and time-invariant, we develop a class of algorithms using Lagrangian Relaxation techniques to obtain optimal mixed strategies using performance bounds developed in previous research. We investigate alternative Receding Horizon (RH) controllers to convert the mixed strategies to feasible adaptive-sensing strategies and evaluate the relative performance of these controllers in simulation. The resulting controllers provide superior performance to alternative algorithms proposed in the literature and obtain solutions to large-scale POMDP problems several orders of magnitude faster than optimal Dynamic Programming (DP) approaches with comparable performance quality. We extend our results for finite action, finite measurement sensor control to scenarios with moving objects. We use Hidden Markov Models (HMMs) for the evolution of objects, according to the dynamics of a birth-death process. We develop a new lower bound on the performance of adaptive controllers in these scenarios, develop algorithms for computing solutions to this lower bound, and use these algorithms as part of a RH controller for sensor allocation in the presence of moving objects We also consider an adaptive Search problem where sensing actions are continuous and the underlying measurement space is also continuous. We extend our previous hierarchical decomposition approach based on performance bounds to this problem and develop novel implementations of Stochastic Dynamic Programming (SDP) techniques to solve this problem. Our algorithms are nearly two orders of magnitude faster than previously proposed approaches and yield solutions of comparable quality. For supervisory control, we discuss how human operators can work with and augment robotic teams performing these tasks. Our focus is on how tasks are partitioned among teams of robots and how a human operator can make intelligent decisions for task partitioning. We explore these questions through the design of a game that involves robot automata controlled by our algorithms and a human supervisor that partitions tasks based on different levels of support information. This game can be used with human subject experiments to explore the effect of information on quality of supervisory control.

Addressing the Movement of a Freescale Robotic Car Using Neural Network

NASA Astrophysics Data System (ADS)

Horváth, Dušan; Cuninka, Peter

2016-12-01

This article deals with the management of a Freescale small robotic car along the predefined guide line. Controlling of the direction of movement of the robot is performed by neural networks, and scales (memory) of neurons are calculated by Hebbian learning from the truth tables as learning with a teacher. Reflexive infrared sensors serves as inputs. The results are experiments, which are used to compare two methods of mobile robot control - tracking lines.

Exact nonlinear command generation and tracking for robot manipulators and spacecraft slewing maneuvers

NASA Technical Reports Server (NTRS)

Dywer, T. A. W., III; Lee, G. K. F.

1984-01-01

In connection with the current interest in agile spacecraft maneuvers, it has become necessary to consider the nonlinear coupling effects of multiaxial rotation in the treatment of command generation and tracking problems. Multiaxial maneuvers will be required in military missions involving a fast acquisition of moving targets in space. In addition, such maneuvers are also needed for the efficient operation of robot manipulators. Attention is given to details regarding the direct nonlinear command generation and tracking, an approach which has been successfully applied to the design of control systems for V/STOL aircraft, linearizing transformations for spacecraft controlled with external thrusters, the case of flexible spacecraft dynamics, examples from robot dynamics, and problems of implementation and testing.

Motion of an Articulated Vehicle with Two-Dimensional Sections Subject to Lateral Obstacles

NASA Astrophysics Data System (ADS)

Antonyuk, E. Ya.; Zabuga, A. T.

2016-07-01

Some aspects of the geometry, kinematics, and dynamics of a three-section robotic vehicle with a front steerable wheel are studied. The constraints between the wheels and the flat ground are assumed nonholonomic. The vehicle moves in a narrow L-shaped corridor. A path for the characteristic points of the sections of the robot is designed. A dynamic model of the system is developed. The maximum possible dimensions of the robot that allow its unimpeded and non-stop motion are determined. The kinetostatic analysis of the load on a three-section vehicle moving along a planned path is modeled. The holonomic and nonholonomic constraint reactions between the wheels and the ground and in the joints between the sections are determined

Markovian robots: Minimal navigation strategies for active particles

NASA Astrophysics Data System (ADS)

Nava, Luis Gómez; Großmann, Robert; Peruani, Fernando

2018-04-01

We explore minimal navigation strategies for active particles in complex, dynamical, external fields, introducing a class of autonomous, self-propelled particles which we call Markovian robots (MR). These machines are equipped with a navigation control system (NCS) that triggers random changes in the direction of self-propulsion of the robots. The internal state of the NCS is described by a Boolean variable that adopts two values. The temporal dynamics of this Boolean variable is dictated by a closed Markov chain—ensuring the absence of fixed points in the dynamics—with transition rates that may depend exclusively on the instantaneous, local value of the external field. Importantly, the NCS does not store past measurements of this value in continuous, internal variables. We show that despite the strong constraints, it is possible to conceive closed Markov chain motifs that lead to nontrivial motility behaviors of the MR in one, two, and three dimensions. By analytically reducing the complexity of the NCS dynamics, we obtain an effective description of the long-time motility behavior of the MR that allows us to identify the minimum requirements in the design of NCS motifs and transition rates to perform complex navigation tasks such as adaptive gradient following, detection of minima or maxima, or selection of a desired value in a dynamical, external field. We put these ideas in practice by assembling a robot that operates by the proposed minimalistic NCS to evaluate the robustness of MR, providing a proof of concept that is possible to navigate through complex information landscapes with such a simple NCS whose internal state can be stored in one bit. These ideas may prove useful for the engineering of miniaturized robots.

Transient inactivation of the anterior cingulate cortex in rats disrupts avoidance of a dynamic object.

PubMed

Svoboda, Jan; Lobellová, Veronika; Popelíková, Anna; Ahuja, Nikhil; Kelemen, Eduard; Stuchlík, Aleš

2017-03-01

Although animals often learn and monitor the spatial properties of relevant moving objects such as conspecifics and predators to properly organize their own spatial behavior, the underlying brain substrate has received little attention and hence remains elusive. Because the anterior cingulate cortex (ACC) participates in conflict monitoring and effort-based decision making, and ACC neurons respond to objects in the environment, it may also play a role in the monitoring of moving cues and exerting the appropriate spatial response. We used a robot avoidance task in which a rat had to maintain at least a 25cm distance from a small programmable robot to avoid a foot shock. In successive sessions, we trained ten Long Evans male rats to avoid a fast-moving robot (4cm/s), a stationary robot, and a slow-moving robot (1cm/s). In each condition, the ACC was transiently inactivated by bilateral injections of muscimol in the penultimate session and a control saline injection was given in the last session. Compared to the corresponding saline session, ACC-inactivated rats received more shocks when tested in the fast-moving condition, but not in the stationary or slow robot conditions. Furthermore, ACC-inactivated rats less frequently responded to an approaching robot with appropriate escape responses although their response to shock stimuli remained preserved. Since we observed no effect on slow or stationary robot avoidance, we conclude that the ACC may exert cognitive efforts for monitoring dynamic updating of the position of an object, a role complementary to the dorsal hippocampus. Copyright © 2017 Elsevier Inc. All rights reserved.

Terrain interaction with the quarter scale beam walker

NASA Technical Reports Server (NTRS)

Chun, Wendell H.; Price, S.; Spiessbach, A.

1990-01-01

Frame walkers are a class of mobile robots that are robust and capable mobility platforms. Variations of the frame walker robot are in commercial use today. Komatsu Ltd. of Japan developed the Remotely Controlled Underwater Surveyor (ReCUS) and Normed Shipyards of France developed the Marine Robot (RM3). Both applications of the frame walker concept satisfied robotic mobility requirements that could not be met by a wheeled or tracked design. One vehicle design concept that falls within this class of mobile robots is the walking beam. A one-quarter scale prototype of the walking beam was built by Martin Marietta to evaluate the potential merits of utilizing the vehicle as a planetary rover. The initial phase of prototype rover testing was structured to evaluate the mobility performance aspects of the vehicle. Performance parameters such as vehicle power, speed, and attitude control were evaluated as a function of the environment in which the prototype vehicle was tested. Subsequent testing phases will address the integrated performance of the vehicle and a local navigation system.

Terrain Interaction With The Quarter Scale Beam Walker

NASA Astrophysics Data System (ADS)

Chun, Wendell H.; Price, R. S.; Spiessbach, Andrew J.

1990-03-01

Frame walkers are a class of mobile robots that are robust and capable mobility platforms. Variations of the frame walker robot are in commercial use today. Komatsu Ltd. of Japan developed the Remotely Controlled Underwater Surveyor (ReCUS) and Normed Shipyards of France developed the Marine Robot (RM3). Both applications of the frame walker concept satisfied robotic mobility requirements that could not be met by a wheeled or tracked design. One vehicle design concept that falls within this class of mobile robots is the walking beam. A one-quarter scale prototype of the walking beam was built by Martin Marietta to evaluate the potential merits of utilizing the vehicle as a planetary rover. The initial phase of prototype rover testing was structured to evaluate the mobility performance aspects of the vehicle. Performance parameters such as vehicle power, speed, and attitude control were evaluated as a function of the environment in which the prototype vehicle was tested. Subsequent testing phases will address the integrated performance of the vehicle and a local navigation system.

Horse-like walking, trotting, and galloping derived from kinematic Motion Primitives (kMPs) and their application to walk/trot transitions in a compliant quadruped robot.

PubMed

Moro, Federico L; Spröwitz, Alexander; Tuleu, Alexandre; Vespignani, Massimo; Tsagarakis, Nikos G; Ijspeert, Auke J; Caldwell, Darwin G

2013-06-01

This manuscript proposes a method to directly transfer the features of horse walking, trotting, and galloping to a quadruped robot, with the aim of creating a much more natural (horse-like) locomotion profile. A principal component analysis on horse joint trajectories shows that walk, trot, and gallop can be described by a set of four kinematic Motion Primitives (kMPs). These kMPs are used to generate valid, stable gaits that are tested on a compliant quadruped robot. Tests on the effects of gait frequency scaling as follows: results indicate a speed optimal walking frequency around 3.4 Hz, and an optimal trotting frequency around 4 Hz. Following, a criterion to synthesize gait transitions is proposed, and the walk/trot transitions are successfully tested on the robot. The performance of the robot when the transitions are scaled in frequency is evaluated by means of roll and pitch angle phase plots.

Dynamic inverse models in human-cyber-physical systems

NASA Astrophysics Data System (ADS)

Robinson, Ryan M.; Scobee, Dexter R. R.; Burden, Samuel A.; Sastry, S. Shankar

2016-05-01

Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.

Brief Report: Development of a Robotic Intervention Platform for Young Children with ASD.

PubMed

Warren, Zachary; Zheng, Zhi; Das, Shuvajit; Young, Eric M; Swanson, Amy; Weitlauf, Amy; Sarkar, Nilanjan

2015-12-01

Increasingly researchers are attempting to develop robotic technologies for children with autism spectrum disorder (ASD). This pilot study investigated the development and application of a novel robotic system capable of dynamic, adaptive, and autonomous interaction during imitation tasks with embedded real-time performance evaluation and feedback. The system was designed to incorporate both a humanoid robot and a human examiner. We compared child performance within system across these conditions in a sample of preschool children with ASD (n = 8) and a control sample of typically developing children (n = 8). The system was well-tolerated in the sample, children with ASD exhibited greater attention to the robotic system than the human administrator, and for children with ASD imitation performance appeared superior during the robotic interaction.

Research and development at ORNL/CESAR towards cooperating robotic systems for hazardous environments

NASA Technical Reports Server (NTRS)

Mann, R. C.; Fujimura, K.; Unseren, M. A.

1992-01-01

One of the frontiers in intelligent machine research is the understanding of how constructive cooperation among multiple autonomous agents can be effected. The effort at the Center for Engineering Systems Advanced Research (CESAR) at the Oak Ridge National Laboratory (ORNL) focuses on two problem areas: (1) cooperation by multiple mobile robots in dynamic, incompletely known environments; and (2) cooperating robotic manipulators. Particular emphasis is placed on experimental evaluation of research and developments using the CESAR robot system testbeds, including three mobile robots, and a seven-axis, kinematically redundant mobile manipulator. This paper summarizes initial results of research addressing the decoupling of position and force control for two manipulators holding a common object, and the path planning for multiple robots in a common workspace.

Maneuverability and mobility in palm-sized legged robots

NASA Astrophysics Data System (ADS)

Kohut, Nicholas J.; Birkmeyer, Paul M.; Peterson, Kevin C.; Fearing, Ronald S.

2012-06-01

Palm sized legged robots show promise for military and civilian applications, including exploration of hazardous or difficult to reach places, search and rescue, espionage, and battlefield reconnaissance. However, they also face many technical obstacles, including- but not limited to- actuator performance, weight constraints, processing power, and power density. This paper presents an overview of several robots from the Biomimetic Millisystems Laboratory at UC Berkeley, including the OctoRoACH, a steerable, running legged robot capable of basic navigation and equipped with a camera and active tail; CLASH, a dynamic climbing robot; and BOLT, a hybrid crawling and flying robot. The paper also discusses, and presents some preliminary solutions to, the technical obstacles listed above plus issues such as robustness to unstructured environments, limited sensing and communication bandwidths, and system integration.

Robotic experiment with a force reflecting handcontroller onboard MIR space station

NASA Technical Reports Server (NTRS)

Delpech, M.; Matzakis, Y.

1994-01-01

During the French CASSIOPEE mission that will fly onboard MIR space station in 1996, ergonomic evaluations of a force reflecting handcontroller will be performed on a simulated robotic task. This handcontroller is a part of the COGNILAB payload that will be used also for experiments in neurophysiology. The purpose of the robotic experiment is the validation of a new control and design concept that would enhance the task performances for telemanipulating space robots. Besides the handcontroller and its control unit, the experimental system includes a simulator of the slave robot dynamics for both free and constrained motions, a flat display screen and a seat with special fixtures for holding the astronaut.

Control of a Robot Dancer for Enhancing Haptic Human-Robot Interaction in Waltz.

PubMed

Hongbo Wang; Kosuge, K

2012-01-01

Haptic interaction between a human leader and a robot follower in waltz is studied in this paper. An inverted pendulum model is used to approximate the human's body dynamics. With the feedbacks from the force sensor and laser range finders, the robot is able to estimate the human leader's state by using an extended Kalman filter (EKF). To reduce interaction force, two robot controllers, namely, admittance with virtual force controller, and inverted pendulum controller, are proposed and evaluated in experiments. The former controller failed the experiment; reasons for the failure are explained. At the same time, the use of the latter controller is validated by experiment results.

A Gait Generation for an Unlocked Joint Failure of the Quadruped Robot with Balance Weight

NASA Astrophysics Data System (ADS)

Cho, C. H.; Min, B. C.; Kim, D. H.

Assurance of a stability margin for a stabilized gait is the most important issue for the quadruped robot. Although various studies for dynamic stability of the quadruped robot have been studied, problems in which one of the legs has an unlocked joint failure haven’t been relatively studied so far. In this paper, assurance of stability margin for the unlocked joint failure of the quadruped robot is suggested by using gait stabilization and a control method of the moment of inertia. Then, efficiency of BW (balance weight) will be experimentally verified by comparing the two types of robot; one is equipped with the BW, the other is not equipped with BW.

Ultra-fast escape maneuver of an octopus-inspired robot.

PubMed

Weymouth, G D; Subramaniam, V; Triantafyllou, M S

2015-02-02

We design and test an octopus-inspired flexible hull robot that demonstrates outstanding fast-starting performance. The robot is hyper-inflated with water, and then rapidly deflates to expel the fluid so as to power the escape maneuver. Using this robot we verify for the first time in laboratory testing that rapid size-change can substantially reduce separation in bluff bodies traveling several body lengths, and recover fluid energy which can be employed to improve the propulsive performance. The robot is found to experience speeds over ten body lengths per second, exceeding that of a similarly propelled optimally streamlined rigid rocket. The peak net thrust force on the robot is more than 2.6 times that on an optimal rigid body performing the same maneuver, experimentally demonstrating large energy recovery and enabling acceleration greater than 14 body lengths per second squared. Finally, over 53% of the available energy is converted into payload kinetic energy, a performance that exceeds the estimated energy conversion efficiency of fast-starting fish. The Reynolds number based on final speed and robot length is [Formula: see text]. We use the experimental data to establish a fundamental deflation scaling parameter [Formula: see text] which characterizes the mechanisms of flow control via shape change. Based on this scaling parameter, we find that the fast-starting performance improves with increasing size.

How does a surgeon’s brain buzz? An EEG coherence study on the interaction between humans and robot

PubMed Central

2013-01-01

Introduction In humans, both primary and non-primary motor areas are involved in the control of voluntary movements. However, the dynamics of functional coupling among different motor areas have not been fully clarified yet. There is to date no research looking to the functional dynamics in the brain of surgeons working in laparoscopy compared with those trained and working in robotic surgery. Experimental procedures We enrolled 16 right-handed trained surgeons and assessed changes in intra- and inter-hemispheric EEG coherence with a 32-channels device during the same motor task with either a robotic or a laparoscopic approach. Estimates of auto and coherence spectra were calculated by a fast Fourier transform algorithm implemented on Matlab 5.3. Results We found increase of coherence in surgeons performing laparoscopy, especially in theta and lower alpha activity, in all experimental conditions (M1 vs. SMA, S1 vs. SMA, S1 vs. pre-SMA and M1 vs. S1; p < 0.001). Conversely, an increase in inter-hemispheric coherence in upper alpha and beta band was found in surgeons using the robotic procedure (right vs. left M1, right vs. left S1, right pre-SMA vs. left M1, left pre-SMA vs. right M1; p < 0.001). Discussion Our data provide a semi-quantitative evaluation of dynamics in functional coupling among different cortical areas in skilled surgeons performing laparoscopy or robotic surgery. These results suggest that motor and non-motor areas are differently activated and coordinated in surgeons performing the same task with different approaches. To the best of our knowledge, this is the first study that tried to assess semi-quantitative differences during the interaction between normal human brain and robotic devices. PMID:23607324

How does a surgeon's brain buzz? An EEG coherence study on the interaction between humans and robot.

PubMed

Bocci, Tommaso; Moretto, Carlo; Tognazzi, Silvia; Briscese, Lucia; Naraci, Megi; Leocani, Letizia; Mosca, Franco; Ferrari, Mauro; Sartucci, Ferdinando

2013-04-22

In humans, both primary and non-primary motor areas are involved in the control of voluntary movements. However, the dynamics of functional coupling among different motor areas have not been fully clarified yet. There is to date no research looking to the functional dynamics in the brain of surgeons working in laparoscopy compared with those trained and working in robotic surgery. We enrolled 16 right-handed trained surgeons and assessed changes in intra- and inter-hemispheric EEG coherence with a 32-channels device during the same motor task with either a robotic or a laparoscopic approach. Estimates of auto and coherence spectra were calculated by a fast Fourier transform algorithm implemented on Matlab 5.3. We found increase of coherence in surgeons performing laparoscopy, especially in theta and lower alpha activity, in all experimental conditions (M1 vs. SMA, S1 vs. SMA, S1 vs. pre-SMA and M1 vs. S1; p < 0.001). Conversely, an increase in inter-hemispheric coherence in upper alpha and beta band was found in surgeons using the robotic procedure (right vs. left M1, right vs. left S1, right pre-SMA vs. left M1, left pre-SMA vs. right M1; p < 0.001). Our data provide a semi-quantitative evaluation of dynamics in functional coupling among different cortical areas in skilled surgeons performing laparoscopy or robotic surgery. These results suggest that motor and non-motor areas are differently activated and coordinated in surgeons performing the same task with different approaches. To the best of our knowledge, this is the first study that tried to assess semi-quantitative differences during the interaction between normal human brain and robotic devices.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Research on Self-Reconfigurable Modular Robot System

NASA Astrophysics Data System (ADS)

Kamimura, Akiya; Murata, Satoshi; Yoshida, Eiichi; Kurokawa, Haruhisa; Tomita, Kohji; Kokaji, Shigeru

Growing complexity of artificial systems arises reliability and flexibility issues of large system design. Robots are not exception of this, and many attempts have been made to realize reliable and flexible robot systems. Distributed modular composition of robot is one of the most effective approaches to attain such abilities and has a potential to adapt to its surroundings by changing its configuration autonomously according to information of surroundings. In this paper, we propose a novel three-dimensional self-reconfigurable robotic module. Each module has a very simple structure that consists of two semi-cylindrical parts connected by a link. The modular system is capable of not only building static structure but also generating dynamic robotic motion. We present details of the mechanical/electrical design of the developed module and its control system architecture. Experiments using ten modules with centralized control demonstrate robotic configuration change, crawling locomotion and three types of quadruped locomotion.

A review on locomotion robophysics: the study of movement at the intersection of robotics, soft matter and dynamical systems.

PubMed

Aguilar, Jeffrey; Zhang, Tingnan; Qian, Feifei; Kingsbury, Mark; McInroe, Benjamin; Mazouchova, Nicole; Li, Chen; Maladen, Ryan; Gong, Chaohui; Travers, Matt; Hatton, Ross L; Choset, Howie; Umbanhowar, Paul B; Goldman, Daniel I

2016-11-01

Discovery of fundamental principles which govern and limit effective locomotion (self-propulsion) is of intellectual interest and practical importance. Human technology has created robotic moving systems that excel in movement on and within environments of societal interest: paved roads, open air and water. However, such devices cannot yet robustly and efficiently navigate (as animals do) the enormous diversity of natural environments which might be of future interest for autonomous robots; examples include vertical surfaces like trees and cliffs, heterogeneous ground like desert rubble and brush, turbulent flows found near seashores, and deformable/flowable substrates like sand, mud and soil. In this review we argue for the creation of a physics of moving systems-a 'locomotion robophysics'-which we define as the pursuit of principles of self-generated motion. Robophysics can provide an important intellectual complement to the discipline of robotics, largely the domain of researchers from engineering and computer science. The essential idea is that we must complement the study of complex robots in complex situations with systematic study of simplified robotic devices in controlled laboratory settings and in simplified theoretical models. We must thus use the methods of physics to examine both locomotor successes and failures using parameter space exploration, systematic control, and techniques from dynamical systems. Using examples from our and others' research, we will discuss how such robophysical studies have begun to aid engineers in the creation of devices that have begun to achieve life-like locomotor abilities on and within complex environments, have inspired interesting physics questions in low dimensional dynamical systems, geometric mechanics and soft matter physics, and have been useful to develop models for biological locomotion in complex terrain. The rapidly decreasing cost of constructing robot models with easy access to significant computational power bodes well for scientists and engineers to engage in a discipline which can readily integrate experiment, theory and computation.

A review on locomotion robophysics: the study of movement at the intersection of robotics, soft matter and dynamical systems

NASA Astrophysics Data System (ADS)

Aguilar, Jeffrey; Zhang, Tingnan; Qian, Feifei; Kingsbury, Mark; McInroe, Benjamin; Mazouchova, Nicole; Li, Chen; Maladen, Ryan; Gong, Chaohui; Travers, Matt; Hatton, Ross L.; Choset, Howie; Umbanhowar, Paul B.; Goldman, Daniel I.

2016-11-01

Discovery of fundamental principles which govern and limit effective locomotion (self-propulsion) is of intellectual interest and practical importance. Human technology has created robotic moving systems that excel in movement on and within environments of societal interest: paved roads, open air and water. However, such devices cannot yet robustly and efficiently navigate (as animals do) the enormous diversity of natural environments which might be of future interest for autonomous robots; examples include vertical surfaces like trees and cliffs, heterogeneous ground like desert rubble and brush, turbulent flows found near seashores, and deformable/flowable substrates like sand, mud and soil. In this review we argue for the creation of a physics of moving systems—a ‘locomotion robophysics’—which we define as the pursuit of principles of self-generated motion. Robophysics can provide an important intellectual complement to the discipline of robotics, largely the domain of researchers from engineering and computer science. The essential idea is that we must complement the study of complex robots in complex situations with systematic study of simplified robotic devices in controlled laboratory settings and in simplified theoretical models. We must thus use the methods of physics to examine both locomotor successes and failures using parameter space exploration, systematic control, and techniques from dynamical systems. Using examples from our and others’ research, we will discuss how such robophysical studies have begun to aid engineers in the creation of devices that have begun to achieve life-like locomotor abilities on and within complex environments, have inspired interesting physics questions in low dimensional dynamical systems, geometric mechanics and soft matter physics, and have been useful to develop models for biological locomotion in complex terrain. The rapidly decreasing cost of constructing robot models with easy access to significant computational power bodes well for scientists and engineers to engage in a discipline which can readily integrate experiment, theory and computation.

Trajectory planning and optimal tracking for an industrial mobile robot

NASA Astrophysics Data System (ADS)

Hu, Huosheng; Brady, J. Michael; Probert, Penelope J.

1994-02-01

This paper introduces a unified approach to trajectory planning and tracking for an industrial mobile robot subject to non-holonomic constraints. We show (1) how a smooth trajectory is generated that takes into account the constraints from the dynamic environment and the robot kinematics; and (2) how a general predictive controller works to provide optimal tracking capability for nonlinear systems. The tracking performance of the proposed guidance system is analyzed by simulation.

Robot Path Planning in Uncertain Environments: A Language Measure-theoretic Approach

DTIC Science & Technology

2014-01-01

Paper DS-14-1028 to appear in the Special Issue on Stochastic Models, Control and Algorithms in Robotics, ASME Journal of Dynamic Systems...Measurement and Control Robot Path Planning in Uncertain Environments: A Language Measure-theoretic Approach⋆ Devesh K. Jha† Yue Li† Thomas A. Wettergren‡† Asok...algorithm, called ν⋆, that was formulated in the framework of probabilistic finite state automata (PFSA) and language measure from a control -theoretic

Guaranteeing Spoof-Resilient Multi-Robot Networks

DTIC Science & Technology

2015-05-12

particularly challenging attack on this assumption is the so-called “Sybil attack.” In a Sybil attack a malicious agent can generate (or spoof) a large...cybersecurity in general multi-node networks (e.g. a wired LAN), the same is not true for multi- robot networks [14, 28], leaving them largely vulnerable...key passing or cryptographic authen- tication is difficult to maintain due to the highly dynamic and distributed nature of multi-robot teams where

Designing a Self-Stabilizing Robot for Dynamic Mobile Manipulation

DTIC Science & Technology

2006-01-01

Designing a Self-Stabilizing Robot For Dynamic Mobile Manipulation Patrick Deegan Bryan J. Thibodeau Roderic Grupen Laboratory for Perceptual... Craig and the Modified D-H standard[14]. Fig. 9. Increase in forces that can be applied to the environment using whole body postural control, for an end...4. This work was supported by NASA grant NNJ05HB61A-5710001842 and ARO grant W911NF-05-1- 0396. REFERENCES [1] B. J. Thibodeau, P. Deegan , and R

Computational structures for robotic computations

NASA Technical Reports Server (NTRS)

Lee, C. S. G.; Chang, P. R.

1987-01-01

The computational problem of inverse kinematics and inverse dynamics of robot manipulators by taking advantage of parallelism and pipelining architectures is discussed. For the computation of inverse kinematic position solution, a maximum pipelined CORDIC architecture has been designed based on a functional decomposition of the closed-form joint equations. For the inverse dynamics computation, an efficient p-fold parallel algorithm to overcome the recurrence problem of the Newton-Euler equations of motion to achieve the time lower bound of O(log sub 2 n) has also been developed.

Coordinating with Humans by Adjustable-Autonomy for Multirobot Pursuit (CHAMP)

NASA Astrophysics Data System (ADS)

Dumond, Danielle; Ayers, Jeanine; Schurr, Nathan; Carlin, Alan; Burke, Dustin; Rousseau, Jeffrey

2012-06-01

One of the primary challenges facing the modern small-unit tactical team is the ability of the unit to safely and effectively search, explore, clear and hold urbanized terrain that includes buildings, streets, and subterranean dwellings. Buildings provide cover and concealment to an enemy and restrict the movement of forces while diminishing their ability to engage the adversary. The use of robots has significant potential to reduce the risk to tactical teams and dramatically force multiply the small unit's footprint. Despite advances in robotic mobility, sensing capabilities, and human-robot interaction, the use of robots in room clearing operations remains nascent. CHAMP is a software system in development that integrates with a team of robotic platforms to enable them to coordinate with a human operator performing a search and pursuit task. In this way, the human operator can either give control to the robots to search autonomously, or can retain control and direct the robots where needed. CHAMP's autonomy is built upon a combination of adversarial pursuit algorithms and dynamic function allocation strategies that maximize the team's resources. Multi-modal interaction with CHAMP is achieved using novel gesture-recognition based capabilities to reduce the need for heads-down tele-operation. The Champ Coordination Algorithm addresses dynamic and limited team sizes, generates a novel map of the area, and takes into account mission goals, user preferences and team roles. In this paper we show results from preliminary simulated experiments and find that the CHAMP system performs faster than traditional search and pursuit algorithms.

Body-terrain interaction affects large bump traversal of insects and legged robots.

PubMed

Gart, Sean W; Li, Chen

2018-02-02

Small animals and robots must often rapidly traverse large bump-like obstacles when moving through complex 3D terrains, during which, in addition to leg-ground contact, their body inevitably comes into physical contact with the obstacles. However, we know little about the performance limits of large bump traversal and how body-terrain interaction affects traversal. To address these, we challenged the discoid cockroach and an open-loop six-legged robot to dynamically run into a large bump of varying height to discover the maximal traversal performance, and studied how locomotor modes and traversal performance are affected by body-terrain interaction. Remarkably, during rapid running, both the animal and the robot were capable of dynamically traversing a bump much higher than its hip height (up to 4 times the hip height for the animal and 3 times for the robot, respectively) at traversal speeds typical of running, with decreasing traversal probability with increasing bump height. A stability analysis using a novel locomotion energy landscape model explained why traversal was more likely when the animal or robot approached the bump with a low initial body yaw and a high initial body pitch, and why deflection was more likely otherwise. Inspired by these principles, we demonstrated a novel control strategy of active body pitching that increased the robot's maximal traversable bump height by 75%. Our study is a major step in establishing the framework of locomotion energy landscapes to understand locomotion in complex 3D terrains.

A fuzzy logic controller for an autonomous mobile robot

NASA Technical Reports Server (NTRS)

Yen, John; Pfluger, Nathan

1993-01-01

The ability of a mobile robot system to plan and move intelligently in a dynamic system is needed if robots are to be useful in areas other than controlled environments. An example of a use for this system is to control an autonomous mobile robot in a space station, or other isolated area where it is hard or impossible for human life to exist for long periods of time (e.g., Mars). The system would allow the robot to be programmed to carry out the duties normally accomplished by a human being. Some of the duties that could be accomplished include operating instruments, transporting objects, and maintenance of the environment. The main focus of our early work has been on developing a fuzzy controller that takes a path and adapts it to a given environment. The robot only uses information gathered from the sensors, but retains the ability to avoid dynamically placed obstacles near and along the path. Our fuzzy logic controller is based on the following algorithm: (1) determine the desired direction of travel; (2) determine the allowed direction of travel; and (3) combine the desired and allowed directions in order to determine a direciton that is both desired and allowed. The desired direction of travel is determined by projecting ahead to a point along the path that is closer to the goal. This gives a local direction of travel for the robot and helps to avoid obstacles.

Large-scale deep learning for robotically gathered imagery for science

NASA Astrophysics Data System (ADS)

Skinner, K.; Johnson-Roberson, M.; Li, J.; Iscar, E.

2016-12-01

With the explosion of computing power, the intelligence and capability of mobile robotics has dramatically increased over the last two decades. Today, we can deploy autonomous robots to achieve observations in a variety of environments ripe for scientific exploration. These platforms are capable of gathering a volume of data previously unimaginable. Additionally, optical cameras, driven by mobile phones and consumer photography, have rapidly improved in size, power consumption, and quality making their deployment cheaper and easier. Finally, in parallel we have seen the rise of large-scale machine learning approaches, particularly deep neural networks (DNNs), increasing the quality of the semantic understanding that can be automatically extracted from optical imagery. In concert this enables new science using a combination of machine learning and robotics. This work will discuss the application of new low-cost high-performance computing approaches and the associated software frameworks to enable scientists to rapidly extract useful science data from millions of robotically gathered images. The automated analysis of imagery on this scale opens up new avenues of inquiry unavailable using more traditional manual or semi-automated approaches. We will use a large archive of millions of benthic images gathered with an autonomous underwater vehicle to demonstrate how these tools enable new scientific questions to be posed.

Using articulated scene models for dynamic 3d scene analysis in vista spaces

NASA Astrophysics Data System (ADS)

Beuter, Niklas; Swadzba, Agnes; Kummert, Franz; Wachsmuth, Sven

2010-09-01

In this paper we describe an efficient but detailed new approach to analyze complex dynamic scenes directly in 3D. The arising information is important for mobile robots to solve tasks in the area of household robotics. In our work a mobile robot builds an articulated scene model by observing the environment in the visual field or rather in the so-called vista space. The articulated scene model consists of essential knowledge about the static background, about autonomously moving entities like humans or robots and finally, in contrast to existing approaches, information about articulated parts. These parts describe movable objects like chairs, doors or other tangible entities, which could be moved by an agent. The combination of the static scene, the self-moving entities and the movable objects in one articulated scene model enhances the calculation of each single part. The reconstruction process for parts of the static scene benefits from removal of the dynamic parts and in turn, the moving parts can be extracted more easily through the knowledge about the background. In our experiments we show, that the system delivers simultaneously an accurate static background model, moving persons and movable objects. This information of the articulated scene model enables a mobile robot to detect and keep track of interaction partners, to navigate safely through the environment and finally, to strengthen the interaction with the user through the knowledge about the 3D articulated objects and 3D scene analysis. [Figure not available: see fulltext.

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

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.

Attitude dynamics and control of a spacecraft like a robotic manipulator when implementing on-orbit servicing

NASA Astrophysics Data System (ADS)

Da Fonseca, Ijar M.; Goes, Luiz C. S.; Seito, Narumi; da Silva Duarte, Mayara K.; de Oliveira, Élcio Jeronimo

2017-08-01

In space the manipulators working space is characterized by the microgravity environment. In this environment the spacecraft floats and its rotational/translational motion may be excited by any internal and external disturbances. The complete system, i.e., the spacecraft and the associated robotic manipulator, floats and is sensitive to any reaction force and torque related to the manipulator's operation. In this sense the effort done by the robot may result in torque about the system center of mass and also in forces changing its translational motion. This paper analyzes the impact of the robot manipulator dynamics on the attitude motion and the associated control effort to keep the attitude stable during the manipulator's operation. The dynamics analysis is performed in the close proximity phase of rendezvous docking/berthing operation. In such scenario the linear system equations for the translation and attitude relative motions are appropriate. The computer simulations are implemented for the relative translational and rotational motion. The equations of motion have been simulated through computer by using the MatLab software. The LQR and the PID control laws are used for linear and nonlinear control, respectively, aiming to keep the attitude stable while the robot is in and out of service. The gravity-gradient and the residual magnetic torque are considered as external disturbances. The control efforts are analyzed for the manipulator in and out of service. The control laws allow the system stabilization and good performance when the manipulator is in service.

Application of neural models as controllers in mobile robot velocity control loop

NASA Astrophysics Data System (ADS)

Cerkala, Jakub; Jadlovska, Anna

2017-01-01

This paper presents the application of an inverse neural models used as controllers in comparison to classical PI controllers for velocity tracking control task used in two-wheel, differentially driven mobile robot. The PI controller synthesis is based on linear approximation of actuators with equivalent load. In order to obtain relevant datasets for training of feed-forward multi-layer perceptron based neural network used as neural model, the mathematical model of mobile robot, that combines its kinematic and dynamic properties such as chassis dimensions, center of gravity offset, friction and actuator parameters is used. Neural models are trained off-line to act as an inverse dynamics of DC motors with particular load using data collected in simulation experiment for motor input voltage step changes within bounded operating area. The performances of PI controllers versus inverse neural models in mobile robot internal velocity control loops are demonstrated and compared in simulation experiment of navigation control task for line segment motion in plane.

A survey on dielectric elastomer actuators for soft robots.

PubMed

Gu, Guo-Ying; Zhu, Jian; Zhu, Li-Min; Zhu, Xiangyang

2017-01-23

Conventional industrial robots with the rigid actuation technology have made great progress for humans in the fields of automation assembly and manufacturing. With an increasing number of robots needing to interact with humans and unstructured environments, there is a need for soft robots capable of sustaining large deformation while inducing little pressure or damage when maneuvering through confined spaces. The emergence of soft robotics offers the prospect of applying soft actuators as artificial muscles in robots, replacing traditional rigid actuators. Dielectric elastomer actuators (DEAs) are recognized as one of the most promising soft actuation technologies due to the facts that: i) dielectric elastomers are kind of soft, motion-generating materials that resemble natural muscle of humans in terms of force, strain (displacement per unit length or area) and actuation pressure/density; ii) dielectric elastomers can produce large voltage-induced deformation. In this survey, we first introduce the so-called DEAs emphasizing the key points of working principle, key components and electromechanical modeling approaches. Then, different DEA-driven soft robots, including wearable/humanoid robots, walking/serpentine robots, flying robots and swimming robots, are reviewed. Lastly, we summarize the challenges and opportunities for the further studies in terms of mechanism design, dynamics modeling and autonomous control.

Proceedings of the Goddard Space Flight Center Workshop on Robotics for Commercial Microelectronic Processes in Space

NASA Technical Reports Server (NTRS)

1987-01-01

Potential applications of robots for cost effective commercial microelectronic processes in space were studied and the associated robotic requirements were defined. Potential space application areas include advanced materials processing, bulk crystal growth, and epitaxial thin film growth and related processes. All possible automation of these processes was considered, along with energy and environmental requirements. Aspects of robot capabilities considered include system intelligence, ROM requirements, kinematic and dynamic specifications, sensor design and configuration, flexibility and maintainability. Support elements discussed included facilities, logistics, ground support, launch and recovery, and management systems.

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.

Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation. Volume 1: Study results

NASA Technical Reports Server (NTRS)

Lowrie, J. W.; Fermelia, A. J.; Haley, D. C.; Gremban, K. D.; Vanbaalen, J.; Walsh, R. W.

1982-01-01

A variety of artificial intelligence techniques which could be used with regard to NASA space applications and robotics were evaluated. The techniques studied were decision tree manipulators, problem solvers, rule based systems, logic programming languages, representation language languages, and expert systems. The overall structure of a robotic simulation tool was defined and a framework for that tool developed. Nonlinear and linearized dynamics equations were formulated for n link manipulator configurations. A framework for the robotic simulation was established which uses validated manipulator component models connected according to a user defined configuration.

Mechanism And Control Of The Quadruped Walking Robot

NASA Astrophysics Data System (ADS)

Adachi, Hironori; Nakano, Eiji; Koyachi, Noriho

1987-10-01

This paper provides a description of the quadruped walking robot "TURTLE-1". A new link mechanism named ASTBALLEM is used for the legs of this robot. With this mechanism highly rigid and easily controllable legs are constructed. Each leg has two degrees of freedom and is driven by two DC servo motors. The motion of the legs is controlled by a micro computer and various gaits are generated. Static stability is maintained as the robot walks. Moreover, its walk is quasi-dynamic; that is, it has a manner of walking that has a two legged supporting period.

Modeling of robotic fish propelled by an ionic polymer-metal composite caudal fin

NASA Astrophysics Data System (ADS)

Chen, Zheng; Shatara, Stephan; Tan, Xiaobo

2009-03-01

In this paper, a model is proposed for a biomimetic robotic fish propelled by an ionic polymer metal composite (IPMC) actuator with a rigid passive fin at the end. The model incorporates both IPMC actuation dynamics and the hydrodynamics, and predicts the steady-state speed of the robot under a periodic actuation voltage. Experimental results have shown that the proposed model can predict the fish motion for different tail dimensions. Since its parameters are expressed in terms of physical properties and geometric dimensions, the model is expected to be instrumental in optimal design of the robotic fish.

Parallel Robot for Lower Limb Rehabilitation Exercises.

PubMed

Rastegarpanah, Alireza; Saadat, Mozafar; Borboni, Alberto

2016-01-01

The aim of this study is to investigate the capability of a 6-DoF parallel robot to perform various rehabilitation exercises. The foot trajectories of twenty healthy participants have been measured by a Vicon system during the performing of four different exercises. Based on the kinematics and dynamics of a parallel robot, a MATLAB program was developed in order to calculate the length of the actuators, the actuators' forces, workspace, and singularity locus of the robot during the performing of the exercises. The calculated length of the actuators and the actuators' forces were used by motion analysis in SolidWorks in order to simulate different foot trajectories by the CAD model of the robot. A physical parallel robot prototype was built in order to simulate and execute the foot trajectories of the participants. Kinect camera was used to track the motion of the leg's model placed on the robot. The results demonstrate the robot's capability to perform a full range of various rehabilitation exercises.

Parallel Robot for Lower Limb Rehabilitation Exercises

PubMed Central

Saadat, Mozafar; Borboni, Alberto

2016-01-01

The aim of this study is to investigate the capability of a 6-DoF parallel robot to perform various rehabilitation exercises. The foot trajectories of twenty healthy participants have been measured by a Vicon system during the performing of four different exercises. Based on the kinematics and dynamics of a parallel robot, a MATLAB program was developed in order to calculate the length of the actuators, the actuators' forces, workspace, and singularity locus of the robot during the performing of the exercises. The calculated length of the actuators and the actuators' forces were used by motion analysis in SolidWorks in order to simulate different foot trajectories by the CAD model of the robot. A physical parallel robot prototype was built in order to simulate and execute the foot trajectories of the participants. Kinect camera was used to track the motion of the leg's model placed on the robot. The results demonstrate the robot's capability to perform a full range of various rehabilitation exercises. PMID:27799727

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.

Robotic Fish to Aid Animal Behavior Studies and Informal Science Learning

NASA Astrophysics Data System (ADS)

Phamduy, Paul

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

School-based use of a robotic arm system by children with disabilities.

PubMed

Cook, Albert M; Bentz, Brenda; Harbottle, Norma; Lynch, Cheryl; Miller, Brad

2005-12-01

A robotic arm system was developed for use by children who had very severe motor disabilities and varying levels of cognitive and language skills. The children used the robot in a three-task sequence routine to dig objects from a tub of dry macaroni. The robotic system was used in the child's school for 12-15 sessions over a period of four weeks. Goal attainment scaling indicated improvement in all children in operational competence of the robot, and varying levels of gain in functional skill development with the robot and in carryover to the classroom from the robot experiments. Teacher interviews revealed gains in classroom participation, expressive language (vocalizations, symbolic communication), and a high degree of interest by the children in the robot tasks. The teachers also recommended that the robot should have more color, contrast and character, as well as generating sounds and/or music for student cues. They also felt that the robotic system accuracy should be increased so that teacher assistance is not necessary to complete the task.

Comparison of Human and Humanoid Robot Control of Upright Stance

PubMed Central

Peterka, Robert J.

2009-01-01

There is considerable recent interest in developing humanoid robots. An important substrate for many motor actions in both humans and biped robots is the ability to maintain a statically or dynamically stable posture. Given the success of the human design, one would expect there are lessons to be learned in formulating a postural control mechanism for robots. In this study we limit ourselves to considering the problem of maintaining upright stance. Human stance control is compared to a suggested method for robot stance control called zero moment point (ZMP) compensation. Results from experimental and modeling studies suggest there are two important subsystems that account for the low- and mid-frequency (DC to ~1 Hz) dynamic characteristics of human stance control. These subsystems are 1) a “sensory integration” mechanism whereby orientation information from multiple sensory systems encoding body kinematics (i.e. position, velocity) is flexibly combined to provide an overall estimate of body orientation while allowing adjustments (sensory re-weighting) that compensate for changing environmental conditions, and 2) an “effort control” mechanism that uses kinetic-related (i.e., force-related) sensory information to reduce the mean deviation of body orientation from upright. Functionally, ZMP compensation is directly analogous to how humans appear to use kinetic feedback to modify the main sensory integration feedback loop controlling body orientation. However, a flexible sensory integration mechanism is missing from robot control leaving the robot vulnerable to instability in conditions were humans are able to maintain stance. We suggest the addition of a simple form of sensory integration to improve robot stance control. We also investigate how the biological constraint of feedback time delay influences the human stance control design. The human system may serve as a guide for improved robot control, but should not be directly copied because the constraints on robot and human control are different. PMID:19665564

Comparison of human and humanoid robot control of upright stance.

PubMed

Peterka, Robert J

2009-01-01

There is considerable recent interest in developing humanoid robots. An important substrate for many motor actions in both humans and biped robots is the ability to maintain a statically or dynamically stable posture. Given the success of the human design, one would expect there are lessons to be learned in formulating a postural control mechanism for robots. In this study we limit ourselves to considering the problem of maintaining upright stance. Human stance control is compared to a suggested method for robot stance control called zero moment point (ZMP) compensation. Results from experimental and modeling studies suggest there are two important subsystems that account for the low- and mid-frequency (DC to approximately 1Hz) dynamic characteristics of human stance control. These subsystems are (1) a "sensory integration" mechanism whereby orientation information from multiple sensory systems encoding body kinematics (i.e. position, velocity) is flexibly combined to provide an overall estimate of body orientation while allowing adjustments (sensory re-weighting) that compensate for changing environmental conditions and (2) an "effort control" mechanism that uses kinetic-related (i.e., force-related) sensory information to reduce the mean deviation of body orientation from upright. Functionally, ZMP compensation is directly analogous to how humans appear to use kinetic feedback to modify the main sensory integration feedback loop controlling body orientation. However, a flexible sensory integration mechanism is missing from robot control leaving the robot vulnerable to instability in conditions where humans are able to maintain stance. We suggest the addition of a simple form of sensory integration to improve robot stance control. We also investigate how the biological constraint of feedback time delay influences the human stance control design. The human system may serve as a guide for improved robot control, but should not be directly copied because the constraints on robot and human control are different.

Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

PubMed Central

Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

2017-01-01

Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. PMID:28208697

On discrete control of nonlinear systems with applications to robotics

NASA Technical Reports Server (NTRS)

Eslami, Mansour

1989-01-01

Much progress has been reported in the areas of modeling and control of nonlinear dynamic systems in a continuous-time framework. From implementation point of view, however, it is essential to study these nonlinear systems directly in a discrete setting that is amenable for interfacing with digital computers. But to develop discrete models and discrete controllers for a nonlinear system such as robot is a nontrivial task. Robot is also inherently a variable-inertia dynamic system involving additional complications. Not only the computer-oriented models of these systems must satisfy the usual requirements for such models, but these must also be compatible with the inherent capabilities of computers and must preserve the fundamental physical characteristics of continuous-time systems such as the conservation of energy and/or momentum. Preliminary issues regarding discrete systems in general and discrete models of a typical industrial robot that is developed with full consideration of the principle of conservation of energy are presented. Some research on the pertinent tactile information processing is reviewed. Finally, system control methods and how to integrate these issues in order to complete the task of discrete control of a robot manipulator are also reviewed.

Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control.

PubMed

Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

2017-02-08

Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

Free-floating dual-arm robots for space assembly

NASA Technical Reports Server (NTRS)

Agrawal, Sunil Kumar; Chen, M. Y.

1994-01-01

Freely moving systems in space conserve linear and angular momentum. As moving systems collide, the velocities get altered due to transfer of momentum. The development of strategies for assembly in a free-floating work environment requires a good understanding of primitives such as self motion of the robot, propulsion of the robot due to onboard thrusters, docking of the robot, retrieval of an object from a collection of objects, and release of an object in an object pool. The analytics of such assemblies involve not only kinematics and rigid body dynamics but also collision and impact dynamics of multibody systems. In an effort to understand such assemblies in zero gravity space environment, we are currently developing at Ohio University a free-floating assembly facility with a dual-arm planar robot equipped with thrusters, a free-floating material table, and a free-floating assembly table. The objective is to pick up workpieces from the material table and combine them into prespecified assemblies. This paper presents analytical models of assembly primitives and strategies for overall assembly. A computer simulation of an assembly is developed using the analytical models. The experiment facility will be used to verify the theoretical predictions.

Applications of three-dimensional (3D) printing for microswimmers and bio-hybrid robotics.

PubMed

Stanton, M M; Trichet-Paredes, C; Sánchez, S

2015-04-07

This article will focus on recent reports that have applied three-dimensional (3D) printing for designing millimeter to micrometer architecture for robotic motility. The utilization of 3D printing has rapidly grown in applications for medical prosthetics and scaffolds for organs and tissue, but more recently has been implemented for designing mobile robotics. With an increase in the demand for devices to perform in fragile and confined biological environments, it is crucial to develop new miniaturized, biocompatible 3D systems. Fabrication of materials at different scales with different properties makes 3D printing an ideal system for creating frameworks for small-scale robotics. 3D printing has been applied for the design of externally powered, artificial microswimmers and studying their locomotive capabilities in different fluids. Printed materials have also been incorporated with motile cells for bio-hybrid robots capable of functioning by cell contraction and swimming. These 3D devices offer new methods of robotic motility for biomedical applications requiring miniature structures. Traditional 3D printing methods, where a structure is fabricated in an additive process from a digital design, and non-traditional 3D printing methods, such as lithography and molding, will be discussed.

Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

NASA Astrophysics Data System (ADS)

Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

2018-04-01

In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

Neural-Dynamic-Method-Based Dual-Arm CMG Scheme With Time-Varying Constraints Applied to Humanoid Robots.

PubMed

Zhang, Zhijun; Li, Zhijun; Zhang, Yunong; Luo, Yamei; Li, Yuanqing

2015-12-01

We propose a dual-arm cyclic-motion-generation (DACMG) scheme by a neural-dynamic method, which can remedy the joint-angle-drift phenomenon of a humanoid robot. In particular, according to a neural-dynamic design method, first, a cyclic-motion performance index is exploited and applied. This cyclic-motion performance index is then integrated into a quadratic programming (QP)-type scheme with time-varying constraints, called the time-varying-constrained DACMG (TVC-DACMG) scheme. The scheme includes the kinematic motion equations of two arms and the time-varying joint limits. The scheme can not only generate the cyclic motion of two arms for a humanoid robot but also control the arms to move to the desired position. In addition, the scheme considers the physical limit avoidance. To solve the QP problem, a recurrent neural network is presented and used to obtain the optimal solutions. Computer simulations and physical experiments demonstrate the effectiveness and the accuracy of such a TVC-DACMG scheme and the neural network solver.

Design and simulation of a cable-pulley-based transmission for artificial ankle joints

NASA Astrophysics Data System (ADS)

Liu, Huaxin; Ceccarelli, Marco; Huang, Qiang

2016-06-01

In this paper, a mechanical transmission based on cable pulley is proposed for human-like actuation in the artificial ankle joints of human-scale. The anatomy articular characteristics of the human ankle is discussed for proper biomimetic inspiration in designing an accurate, efficient, and robust motion control of artificial ankle joint devices. The design procedure is presented through the inclusion of conceptual considerations and design details for an interactive solution of the transmission system. A mechanical design is elaborated for the ankle joint angular with pitch motion. A multi-body dynamic simulation model is elaborated accordingly and evaluated numerically in the ADAMS environment. Results of the numerical simulations are discussed to evaluate the dynamic performance of the proposed design solution and to investigate the feasibility of the proposed design in future applications for humanoid robots.

A tracked robot with novel bio-inspired passive "legs".

PubMed

Sun, Bo; Jing, Xingjian

2017-01-01

For track-based robots, an important aspect is the suppression design, which determines the trafficability and comfort of the whole system. The trafficability limits the robot's working capability, and the riding comfort limits the robot's working effectiveness, especially with some sensitive instruments mounted on or operated. To these aims, a track-based robot equipped with a novel passive bio-inspired suspension is designed and studied systematically in this paper. Animal or insects have very special leg or limb structures which are good for motion control and adaptable to different environments. Inspired by this, a new track-based robot is designed with novel "legs" for connecting the loading wheels to the robot body. Each leg is designed with passive structures and can achieve very high loading capacity but low dynamic stiffness such that the robot can move on rough ground similar to a multi-leg animal or insect. Therefore, the trafficability and riding comfort can be significantly improved without losing loading capacity. The new track-based robot can be well applied to various engineering tasks for providing a stable moving platform of high mobility, better trafficability and excellent loading capacity.

NONLINEAR FORCE PROFILE USED TO INCREASE THE PERFORMANCE OF A HAPTIC USER INTERFACE FOR TELEOPERATING A ROBOTIC HAND

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

Anthony L. Crawford

MODIFIED PAPER TITLE AND ABSTRACT DUE TO SLIGHTLY MODIFIED SCOPE: TITLE: Nonlinear Force Profile Used to Increase the Performance of a Haptic User Interface for Teleoperating a Robotic Hand Natural movements and force feedback are important elements in using teleoperated equipment if complex and speedy manipulation tasks are to be accomplished in hazardous environments, such as hot cells, glove boxes, decommissioning, explosives disarmament, and space. The research associated with this paper hypothesizes that a user interface and complementary radiation compatible robotic hand that integrates the human hand’s anthropometric properties, speed capability, nonlinear strength profile, reduction of active degrees of freedommore » during the transition from manipulation to grasping, and just noticeable difference force sensation characteristics will enhance a user’s teleoperation performance. The main contribution of this research is in that a system that concisely integrates all these factors has yet to be developed and furthermore has yet to be applied to a hazardous environment as those referenced above. In fact, the most prominent slave manipulator teleoperation technology in use today is based on a design patented in 1945 (Patent 2632574) [1]. The robotic hand/user interface systems of similar function as the one being developed in this research limit their design input requirements in the best case to only complementing the hand’s anthropometric properties, speed capability, and linearly scaled force application relationship (e.g. robotic force is a constant, 4 times that of the user). In this paper a nonlinear relationship between the force experienced between the user interface and the robotic hand was devised based on property differences of manipulation and grasping activities as they pertain to the human hand. The results show that such a relationship when subjected to a manipulation task and grasping task produces increased performance compared to the traditional linear scaling techniques used by other systems. Key Words: Teleoperation, Robotic Hand, Robotic Force Scaling« less

Decentralised consensus-based formation tracking of multiple differential drive robots

NASA Astrophysics Data System (ADS)

Chu, Xing; Peng, Zhaoxia; Wen, Guoguang; Rahmani, Ahmed

2017-11-01

This article investigates the control problem for formation tracking of multiple nonholonomic robots under distributed manner which means each robot only needs local information exchange. A class of general state and input transform is introduced to convert the formation-tracking issue of multi-robot systems into the consensus-like problem with time-varying reference. The distributed observer-based protocol with nonlinear dynamics is developed for each robot to achieve the consensus tracking of the new system, which namely means a group of nonholonomic mobile robots can form the desired formation configuration with its centroid moving along the predefined reference trajectory. The finite-time stability of observer and control law is analysed rigorously by using the Lyapunov direct method, algebraic graph theory and matrix analysis. Numerical examples are finally provided to illustrate the effectiveness of the theory results proposed in this paper.

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.

[Advanced Development for Space Robotics With Emphasis on Fault Tolerance Technology

NASA Technical Reports Server (NTRS)

Tesar, Delbert

1997-01-01

This report describes work developing fault tolerant redundant robotic architectures and adaptive control strategies for robotic manipulator systems which can dynamically accommodate drastic robot manipulator mechanism, sensor or control failures and maintain stable end-point trajectory control with minimum disturbance. Kinematic designs of redundant, modular, reconfigurable arms for fault tolerance were pursued at a fundamental level. The approach developed robotic testbeds to evaluate disturbance responses of fault tolerant concepts in robotic mechanisms and controllers. The development was implemented in various fault tolerant mechanism testbeds including duality in the joint servo motor modules, parallel and serial structural architectures, and dual arms. All have real-time adaptive controller technologies to react to mechanism or controller disturbances (failures) to perform real-time reconfiguration to continue the task operations. The developments fall into three main areas: hardware, software, and theoretical.

Robotics, motor learning, and neurologic recovery.

PubMed

Reinkensmeyer, David J; Emken, Jeremy L; Cramer, Steven C

2004-01-01

Robotic devices are helping shed light on human motor control in health and injury. By using robots to apply novel force fields to the arm, investigators are gaining insight into how the nervous system models its external dynamic environment. The nervous system builds internal models gradually by experience and uses them in combination with impedance and feedback control strategies. Internal models are robust to environmental and neural noise, generalized across space, implemented in multiple brain regions, and developed in childhood. Robots are also being used to assist in repetitive movement practice following neurologic injury, providing insight into movement recovery. Robots can haptically assess sensorimotor performance, administer training, quantify amount of training, and improve motor recovery. In addition to providing insight into motor control, robotic paradigms may eventually enhance motor learning and rehabilitation beyond the levels possible with conventional training techniques.

Connectivity-Preserving Approach for Distributed Adaptive Synchronized Tracking of Networked Uncertain Nonholonomic Mobile Robots.

PubMed

Yoo, Sung Jin; Park, Bong Seok

2017-09-06

This paper addresses a distributed connectivity-preserving synchronized tracking problem of multiple uncertain nonholonomic mobile robots with limited communication ranges. The information of the time-varying leader robot is assumed to be accessible to only a small fraction of follower robots. The main contribution of this paper is to introduce a new distributed nonlinear error surface for dealing with both the synchronized tracking and the preservation of the initial connectivity patterns among nonholonomic robots. Based on this nonlinear error surface, the recursive design methodology is presented to construct the approximation-based local adaptive tracking scheme at the robot dynamic level. Furthermore, a technical lemma is established to analyze the stability and the connectivity preservation of the total closed-loop control system in the Lyapunov sense. An example is provided to illustrate the effectiveness of the proposed methodology.

A Decentralized Scheduling Policy for a Dynamically Reconfigurable Production System

NASA Astrophysics Data System (ADS)

Giordani, Stefano; Lujak, Marin; Martinelli, Francesco

In this paper, the static layout of a traditional multi-machine factory producing a set of distinct goods is integrated with a set of mobile production units - robots. The robots dynamically change their work position to increment the product rate of the different typologies of products in respect to the fluctuations of the demands and production costs during a given time horizon. Assuming that the planning time horizon is subdivided into a finite number of time periods, this particularly flexible layout requires the definition and the solution of a complex scheduling problem, involving for each period of the planning time horizon, the determination of the position of the robots, i.e., the assignment to the respective tasks in order to minimize production costs given the product demand rates during the planning time horizon.

An adaptive Cartesian control scheme for manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.

Modelling of industrial robot in LabView Robotics

NASA Astrophysics Data System (ADS)

Banas, W.; Cwikła, G.; Foit, K.; Gwiazda, A.; Monica, Z.; Sekala, A.

2017-08-01

Currently can find many models of industrial systems including robots. These models differ from each other not only by the accuracy representation parameters, but the representation range. For example, CAD models describe the geometry of the robot and some even designate a mass parameters as mass, center of gravity, moment of inertia, etc. These models are used in the design of robotic lines and sockets. Also systems for off-line programming use these models and many of them can be exported to CAD. It is important to note that models for off-line programming describe not only the geometry but contain the information necessary to create a program for the robot. Exports from CAD to off-line programming system requires additional information. These models are used for static determination of reachability points, and testing collision. It’s enough to generate a program for the robot, and even check the interaction of elements of the production line, or robotic cell. Mathematical models allow robots to study the properties of kinematic and dynamic of robot movement. In these models the geometry is not so important, so are used only selected parameters such as the length of the robot arm, the center of gravity, moment of inertia. These parameters are introduced into the equations of motion of the robot and motion parameters are determined.

Whole-body Motion Planning with Simple Dynamics and Full Kinematics

DTIC Science & Technology

2014-08-01

optimizations can take an excessively long time to run, and may also suffer from local minima. Thus, this approach can become intractable for complex robots...motions like jumping and climbing. Additionally, the point-mass model suggests that the centroidal angular momentum is zero, which is not valid for motions...use in the DARPA Robotics Challenge. A. Jumping Our first example is to command the robot to jump off the ground, as illustrated in Fig.4. We assign

Unmanned Ground Vehicles in Support of Irregular War: A Non-lethal Approach

DTIC Science & Technology

2011-03-15

days to clear all buildings in a very fluid and dynamic operation.43 Given the fact that no UGV can climb stairs at the same rate a human can, one can...Naval Research Lab and Carnegie Mellon University’s Robotics Institute/National Robotics Engineering Consortium for designing the early test systems...Concept Technology Demonstrations (ACTD) paved the way for follow-on development of systems like the Modular Advanced Armed Robotic System (MAARS), an

Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

PubMed Central

Perez-Peña, Fernando; Morgado-Estevez, Arturo; Linares-Barranco, Alejandro; Jimenez-Fernandez, Angel; Gomez-Rodriguez, Francisco; Jimenez-Moreno, Gabriel; Lopez-Coronado, Juan

2013-01-01

In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina) to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE) that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM). All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6) and power requirements (3.4 W) to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6). It also evidences the suitable use of AER as a communication protocol between processing and actuation. PMID:24264330

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.

Neuro-inspired spike-based motion: from dynamic vision sensor to robot motor open-loop control through spike-VITE.

PubMed

Perez-Peña, Fernando; Morgado-Estevez, Arturo; Linares-Barranco, Alejandro; Jimenez-Fernandez, Angel; Gomez-Rodriguez, Francisco; Jimenez-Moreno, Gabriel; Lopez-Coronado, Juan

2013-11-20

In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina) to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE) that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM). All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6) and power requirements (3.4 W) to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6). It also evidences the suitable use of AER as a communication protocol between processing and actuation.

A Sit-to-Stand Training Robot and Its Performance Evaluation: Dynamic Analysis in Lower Limb Rehabilitation Activities

NASA Astrophysics Data System (ADS)

Cao, Enguo; Inoue, Yoshio; Liu, Tao; Shibata, Kyoko

In many countries in which the phenomenon of population aging is being experienced, motor function recovery activities have aroused much interest. In this paper, a sit-to-stand rehabilitation robot utilizing a double-rope system was developed, and the performance of the robot was evaluated by analyzing the dynamic parameters of human lower limbs. For the robot control program, an impedance control method with a training game was developed to increase the effectiveness and frequency of rehabilitation activities, and a calculation method was developed for evaluating the joint moments of hip, knee, and ankle. Test experiments were designed, and four subjects were requested to stand up from a chair with assistance from the rehabilitation robot. In the experiments, body segment rotational angles, trunk movement trajectories, rope tensile forces, ground reaction forces (GRF) and centers of pressure (COP) were measured by sensors, and the moments of ankle, knee and hip joint were real-time calculated using the sensor-measured data. The experiment results showed that the sit-to-stand rehabilitation robot with impedance control method could maintain the comfortable training postures of users, decrease the moments of limb joints, and enhance training effectiveness. Furthermore, the game control method could encourage collaboration between the brain and limbs, and allow for an increase in the frequency and intensity of rehabilitation activities.

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.

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.

Dynamic modeling, property investigation, and adaptive controller design of serial robotic manipulators modeled with structural compliance

NASA Technical Reports Server (NTRS)

Tesar, Delbert; Tosunoglu, Sabri; Lin, Shyng-Her

1990-01-01

Research results on general serial robotic manipulators modeled with structural compliances are presented. Two compliant manipulator modeling approaches, distributed and lumped parameter models, are used in this study. System dynamic equations for both compliant models are derived by using the first and second order influence coefficients. Also, the properties of compliant manipulator system dynamics are investigated. One of the properties, which is defined as inaccessibility of vibratory modes, is shown to display a distinct character associated with compliant manipulators. This property indicates the impact of robot geometry on the control of structural oscillations. Example studies are provided to illustrate the physical interpretation of inaccessibility of vibratory modes. Two types of controllers are designed for compliant manipulators modeled by either lumped or distributed parameter techniques. In order to maintain the generality of the results, neither linearization is introduced. Example simulations are given to demonstrate the controller performance. The second type controller is also built for general serial robot arms and is adaptive in nature which can estimate uncertain payload parameters on-line and simultaneously maintain trajectory tracking properties. The relation between manipulator motion tracking capability and convergence of parameter estimation properties is discussed through example case studies. The effect of control input update delays on adaptive controller performance is also studied.

Control Architecture for Robotic Agent Command and Sensing

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Aghazarian, Hrand; Estlin, Tara; Gaines, Daniel

2008-01-01

Control Architecture for Robotic Agent Command and Sensing (CARACaS) is a recent product of a continuing effort to develop architectures for controlling either a single autonomous robotic vehicle or multiple cooperating but otherwise autonomous robotic vehicles. CARACaS is potentially applicable to diverse robotic systems that could include aircraft, spacecraft, ground vehicles, surface water vessels, and/or underwater vessels. CARACaS incudes an integral combination of three coupled agents: a dynamic planning engine, a behavior engine, and a perception engine. The perception and dynamic planning en - gines are also coupled with a memory in the form of a world model. CARACaS is intended to satisfy the need for two major capabilities essential for proper functioning of an autonomous robotic system: a capability for deterministic reaction to unanticipated occurrences and a capability for re-planning in the face of changing goals, conditions, or resources. The behavior engine incorporates the multi-agent control architecture, called CAMPOUT, described in An Architecture for Controlling Multiple Robots (NPO-30345), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 65. CAMPOUT is used to develop behavior-composition and -coordination mechanisms. Real-time process algebra operators are used to compose a behavior network for any given mission scenario. These operators afford a capability for producing a formally correct kernel of behaviors that guarantee predictable performance. By use of a method based on multi-objective decision theory (MODT), recommendations from multiple behaviors are combined to form a set of control actions that represents their consensus. In this approach, all behaviors contribute simultaneously to the control of the robotic system in a cooperative rather than a competitive manner. This approach guarantees a solution that is good enough with respect to resolution of complex, possibly conflicting goals within the constraints of the mission to be accomplished by the vehicle(s).

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

Mann, R.C.; Fujimura, K.; Unseren, M.A.

One of the frontiers in intelligent machine research is the understanding of how constructive cooperation among multiple autonomous agents can be effected. The effort at the Center for Engineering Systems Advanced Research (CESAR)at the Oak Ridge National Laboratory (ORNL) focuses on two problem areas: (1) cooperation by multiple mobile robots in dynamic, incompletely known environments; and (2) cooperating robotic manipulators. Particular emphasis is placed on experimental evaluation of research and developments using the CESAR robot system testbeds, including three mobile robots, and a seven-axis, kinematically redundant mobile manipulator. This paper summarizes initial results of research addressing the decoupling of positionmore » and force control for two manipulators holding a common object, and the path planning for multiple robots in a common workspace. 15 refs., 3 figs.« less

Virtual- and real-world operation of mobile robotic manipulators: integrated simulation, visualization, and control environment

NASA Astrophysics Data System (ADS)

Chen, ChuXin; Trivedi, Mohan M.

1992-03-01

This research is focused on enhancing the overall productivity of an integrated human-robot system. A simulation, animation, visualization, and interactive control (SAVIC) environment has been developed for the design and operation of an integrated robotic manipulator system. This unique system possesses the abilities for multisensor simulation, kinematics and locomotion animation, dynamic motion and manipulation animation, transformation between real and virtual modes within the same graphics system, ease in exchanging software modules and hardware devices between real and virtual world operations, and interfacing with a real robotic system. This paper describes a working system and illustrates the concepts by presenting the simulation, animation, and control methodologies for a unique mobile robot with articulated tracks, a manipulator, and sensory modules.

Dynamics modelling and Hybrid Suppression Control of space robots performing cooperative object manipulation

NASA Astrophysics Data System (ADS)

Zarafshan, P.; Moosavian, S. Ali A.

2013-10-01

Dynamics modelling and control of multi-body space robotic systems composed of rigid and flexible elements is elaborated here. Control of such systems is highly complicated due to severe under-actuated condition caused by flexible elements, and an inherent uneven nonlinear dynamics. Therefore, developing a compact dynamics model with the requirement of limited computations is extremely useful for controller design, also to develop simulation studies in support of design improvement, and finally for practical implementations. In this paper, the Rigid-Flexible Interactive dynamics Modelling (RFIM) approach is introduced as a combination of Lagrange and Newton-Euler methods, in which the motion equations of rigid and flexible members are separately developed in an explicit closed form. These equations are then assembled and solved simultaneously at each time step by considering the mutual interaction and constraint forces. The proposed approach yields a compact model rather than common accumulation approach that leads to a massive set of equations in which the dynamics of flexible elements is united with the dynamics equations of rigid members. To reveal such merits of this new approach, a Hybrid Suppression Control (HSC) for a cooperative object manipulation task will be proposed, and applied to usual space systems. A Wheeled Mobile Robotic (WMR) system with flexible appendages as a typical space rover is considered which contains a rigid main body equipped with two manipulating arms and two flexible solar panels, and next a Space Free Flying Robotic system (SFFR) with flexible members is studied. Modelling verification of these complicated systems is vigorously performed using ANSYS and ADAMS programs, while the limited computations of RFIM approach provides an efficient tool for the proposed controller design. Furthermore, it will be shown that the vibrations of the flexible solar panels results in disturbing forces on the base which may produce undesirable errors and perturb the object manipulation task. So, it is shown that these effects can be significantly eliminated by the proposed Hybrid Suppression Control algorithm.

Robotic phrenic nerve harvest: a feasibility study in a pig model.

PubMed

Porto de Melo, P; Miyamoto, H; Serradori, T; Ruggiero Mantovani, G; Selber, J; Facca, S; Xu, W-D; Santelmo, N; Liverneaux, P

2014-10-01

The aim of this study was to report on the feasibility of robotic phrenic nerve harvest in a pig model. A surgical robot (Da Vinci S™ system, Intuitive Surgical(®), Sunnyvale, CA) was installed with three ports on the pig's left chest. The phrenic nerve was transected distally where it enters the diaphragm. The phrenic nerve harvest was successfully performed in 45 minutes without major complications. The advantages of robotic microsurgery for phrenic nerve harvest are the motion scaling up to 5 times, elimination of physiological tremor, and free movement of joint-equipped robotic arms. Robot-assisted neurolysis may be clinically useful for harvesting the phrenic nerve for brachial plexus reconstruction. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Human-Robot Teaming for Hydrologic Data Gathering at Multiple Scales

NASA Astrophysics Data System (ADS)

Peschel, J.; Young, S. N.

2017-12-01

The use of personal robot-assistive technology by researchers and practitioners for hydrologic data gathering has grown in recent years as barriers to platform capability, cost, and human-robot interaction have been overcome. One consequence to this growth is a broad availability of unmanned platforms that might or might not be suitable for a specific hydrologic investigation. Through multiple field studies, a set of recommendations has been developed to help guide novice through experienced users in choosing the appropriate unmanned platforms for a given application. This talk will present a series of hydrologic data sets gathered using a human-robot teaming approach that has leveraged unmanned aerial, ground, and surface vehicles over multiple scales. The field case studies discussed will be connected to the best practices, also provided in the presentation. This talk will be of interest to geoscience researchers and practitioners, in general, as well as those working in fields related to emerging technologies.

Using Generative Representations to Evolve Robots. Chapter 1

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.

2004-01-01

Recent research has demonstrated the ability of evolutionary algorithms to automatically design both the physical structure and software controller of real physical robots. One of the challenges for these automated design systems is to improve their ability to scale to the high complexities found in real-world problems. Here we claim that for automated design systems to scale in complexity they must use a representation which allows for the hierarchical creation and reuse of modules, which we call a generative representation. Not only is the ability to reuse modules necessary for functional scalability, but it is also valuable for improving efficiency in testing and construction. We then describe an evolutionary design system with a generative representation capable of hierarchical modularity and demonstrate it for the design of locomoting robots in simulation. Finally, results from our experiments show that evolution with our generative representation produces better robots than those evolved with a non-generative representation.

Modeling Leadership Styles in Human-Robot Team Dynamics

NASA Technical Reports Server (NTRS)

Cruz, Gerardo E.

2005-01-01

The recent proliferation of robotic systems in our society has placed questions regarding interaction between humans and intelligent machines at the forefront of robotics research. In response, our research attempts to understand the context in which particular types of interaction optimize efficiency in tasks undertaken by human-robot teams. It is our conjecture that applying previous research results regarding leadership paradigms in human organizations will lead us to a greater understanding of the human-robot interaction space. In doing so, we adapt four leadership styles prevalent in human organizations to human-robot teams. By noting which leadership style is more appropriately suited to what situation, as given by previous research, a mapping is created between the adapted leadership styles and human-robot interaction scenarios-a mapping which will presumably maximize efficiency in task completion for a human-robot team. In this research we test this mapping with two adapted leadership styles: directive and transactional. For testing, we have taken a virtual 3D interface and integrated it with a genetic algorithm for use in &le-operation of a physical robot. By developing team efficiency metrics, we can determine whether this mapping indeed prescribes interaction styles that will maximize efficiency in the teleoperation of a robot.

Perception for mobile robot navigation: A survey of the state of the art

NASA Technical Reports Server (NTRS)

Kortenkamp, David

1994-01-01

In order for mobile robots to navigate safely in unmapped and dynamic environments they must perceive their environment and decide on actions based on those perceptions. There are many different sensing modalities that can be used for mobile robot perception; the two most popular are ultrasonic sonar sensors and vision sensors. This paper examines the state-of-the-art in sensory-based mobile robot navigation. The first issue in mobile robot navigation is safety. This paper summarizes several competing sonar-based obstacle avoidance techniques and compares them. Another issue in mobile robot navigation is determining the robot's position and orientation (sometimes called the robot's pose) in the environment. This paper examines several different classes of vision-based approaches to pose determination. One class of approaches uses detailed, a prior models of the robot's environment. Another class of approaches triangulates using fixed, artificial landmarks. A third class of approaches builds maps using natural landmarks. Example implementations from each of these three classes are described and compared. Finally, the paper presents a completely implemented mobile robot system that integrates sonar-based obstacle avoidance with vision-based pose determination to perform a simple task.

Transmedia Dynamics in Education: The Case of Robot Heart Stories

ERIC Educational Resources Information Center

Gambarato, Renira Rampazzo; Dabagian, Lilit

2016-01-01

This article discusses the potentiality and risks of applying transmedia storytelling strategies in the realm of education. The empirical approach is used to analyze the experiential education project Robot Heart Stories, developed in 2011 in Canada and the United States. The theoretical framework focuses on the conceptualization of transmedia…

Solution to the SLAM problem in low dynamic environments using a pose graph and an RGB-D sensor.

PubMed

Lee, Donghwa; Myung, Hyun

2014-07-11

In this study, we propose a solution to the simultaneous localization and mapping (SLAM) problem in low dynamic environments by using a pose graph and an RGB-D (red-green-blue depth) sensor. The low dynamic environments refer to situations in which the positions of objects change over long intervals. Therefore, in the low dynamic environments, robots have difficulty recognizing the repositioning of objects unlike in highly dynamic environments in which relatively fast-moving objects can be detected using a variety of moving object detection algorithms. The changes in the environments then cause groups of false loop closing when the same moved objects are observed for a while, which means that conventional SLAM algorithms produce incorrect results. To address this problem, we propose a novel SLAM method that handles low dynamic environments. The proposed method uses a pose graph structure and an RGB-D sensor. First, to prune the falsely grouped constraints efficiently, nodes of the graph, that represent robot poses, are grouped according to the grouping rules with noise covariances. Next, false constraints of the pose graph are pruned according to an error metric based on the grouped nodes. The pose graph structure is reoptimized after eliminating the false information, and the corrected localization and mapping results are obtained. The performance of the method was validated in real experiments using a mobile robot system.

Robotic arm-assisted versus conventional unicompartmental knee arthroplasty: Exploratory secondary analysis of a randomised controlled trial.

PubMed

Blyth, M J G; Anthony, I; Rowe, P; Banger, M S; MacLean, A; Jones, B

2017-11-01

This study reports on a secondary exploratory analysis of the early clinical outcomes of a randomised clinical trial comparing robotic arm-assisted unicompartmental knee arthroplasty (UKA) for medial compartment osteoarthritis of the knee with manual UKA performed using traditional surgical jigs. This follows reporting of the primary outcomes of implant accuracy and gait analysis that showed significant advantages in the robotic arm-assisted group. A total of 139 patients were recruited from a single centre. Patients were randomised to receive either a manual UKA implanted with the aid of traditional surgical jigs, or a UKA implanted with the aid of a tactile guided robotic arm-assisted system. Outcome measures included the American Knee Society Score (AKSS), Oxford Knee Score (OKS), Forgotten Joint Score, Hospital Anxiety Depression Scale, University of California at Los Angeles (UCLA) activity scale, Short Form-12, Pain Catastrophising Scale, somatic disease (Primary Care Evaluation of Mental Disorders Score), Pain visual analogue scale, analgesic use, patient satisfaction, complications relating to surgery, 90-day pain diaries and the requirement for revision surgery. From the first post-operative day through to week 8 post-operatively, the median pain scores for the robotic arm-assisted group were 55.4% lower than those observed in the manual surgery group (p = 0.040).At three months post-operatively, the robotic arm-assisted group had better AKSS (robotic median 164, interquartile range (IQR) 131 to 178, manual median 143, IQR 132 to 166), although no difference was noted with the OKS.At one year post-operatively, the observed differences with the AKSS had narrowed from a median of 21 points to a median of seven points (p = 0.106) (robotic median 171, IQR 153 to 179; manual median 164, IQR 144 to 182). No difference was observed with the OKS, and almost half of each group reached the ceiling limit of the score (OKS > 43). A greater proportion of patients receiving robotic arm-assisted surgery improved their UCLA activity score.Binary logistic regression modelling for dichotomised outcome scores predicted the key factors associated with achieving excellent outcome on the AKSS: a pre-operative activity level > 5 on the UCLA activity score and use of robotic-arm surgery. For the same regression modelling, factors associated with a poor outcome were manual surgery and pre-operative depression. Robotic arm-assisted surgery results in improved early pain scores and early function scores in some patient-reported outcomes measures, but no difference was observed at one year post-operatively. Although improved results favoured the robotic arm-assisted group in active patients (i.e. UCLA ⩾ 5), these do not withstand adjustment for multiple comparisons. Cite this article : M. J. G. Blyth, I. Anthony, P. Rowe, M. S. Banger, A. MacLean, B. Jones. Robotic arm-assisted versus conventional unicompartmental knee arthroplasty: Exploratory secondary analysis of a randomised controlled trial. Bone Joint Res 2017;6:631-639. DOI: 10.1302/2046-3758.611.BJR-2017-0060.R1. © 2017 Blyth et al.

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.

Characterization of an acoustic actuation mechanism for robotic propulsion in low Reynolds number environments

NASA Astrophysics Data System (ADS)

House, Christopher; Armstrong, Jenelle; Burkhardt, John; Firebaugh, Samara

2014-06-01

With the end goal of medical applications such as non-invasive surgery and targeted drug delivery, an acoustically driven resonant structure is proposed for microrobotic propulsion. At the proposed scale, the low Reynolds number environment requires non-reciprocal motion from the robotic structure for propulsion; thus, a "flapper" with multiple, flexible joints, has been designed to produce excitation modes that involve the necessary flagella-like bending for non-reciprocal motion. The key design aspect of the flapper structure involves a very thin joint that allows bending in one (vertical) direction, but not the opposing direction. This allows for the second mass and joint to bend in a manner similar to a dolphin's "kick" at the bottom of their stroke, resulting in forward thrust. A 130 mm x 50 mm x 0.2 mm prototype of a swimming robot that utilizes the flapper was fabricated out of acrylic using a laser cutter. The robot was tested in water and in a water-glycerine solution designed to mimic microscale fluid conditions. The robot exhibited forward propulsion when excited by an underwater speaker at its resonance mode, with velocities up to 2.5 mm/s. The robot also displayed frequency selectivity, leading to the possibility of exploring a steering mechanism with alternatively tuned flappers. Additional tests were conducted with a robot at a reduced size scale.

Magnetic resonant wireless power transfer for propulsion of implantable micro-robot

NASA Astrophysics Data System (ADS)

Kim, D.; Kim, M.; Yoo, J.; Park, H.-H.; Ahn, S.

2015-05-01

Recently, various types of mobile micro-robots have been proposed for medical and industrial applications. Especially in medical applications, a motor system for propulsion cannot easily be used in a micro-robot due to their small size. Therefore, micro-robots are usually actuated by controlling the magnitude and direction of an external magnetic field. However, for micro-robots, these methods in general are only applicable for moving and drilling operations, but not for the undertaking of various missions. In this paper, we propose a new micro-robot concept, which uses wireless power transfer to deliver the propulsion force and electric power simultaneously. The mechanism of Lorentz force generation and the coil design methodologies are explained, and validation of the proposed propulsion system for a micro-robot is discussed thorough a simulation and with actual measurements with up-scaled test vehicles.

Human-robot cooperative movement training: learning a novel sensory motor transformation during walking with robotic assistance-as-needed.

PubMed

Emken, Jeremy L; Benitez, Raul; Reinkensmeyer, David J

2007-03-28

A prevailing paradigm of physical rehabilitation following neurologic injury is to "assist-as-needed" in completing desired movements. Several research groups are attempting to automate this principle with robotic movement training devices and patient cooperative algorithms that encourage voluntary participation. These attempts are currently not based on computational models of motor learning. Here we assume that motor recovery from a neurologic injury can be modelled as a process of learning a novel sensory motor transformation, which allows us to study a simplified experimental protocol amenable to mathematical description. Specifically, we use a robotic force field paradigm to impose a virtual impairment on the left leg of unimpaired subjects walking on a treadmill. We then derive an "assist-as-needed" robotic training algorithm to help subjects overcome the virtual impairment and walk normally. The problem is posed as an optimization of performance error and robotic assistance. The optimal robotic movement trainer becomes an error-based controller with a forgetting factor that bounds kinematic errors while systematically reducing its assistance when those errors are small. As humans have a natural range of movement variability, we introduce an error weighting function that causes the robotic trainer to disregard this variability. We experimentally validated the controller with ten unimpaired subjects by demonstrating how it helped the subjects learn the novel sensory motor transformation necessary to counteract the virtual impairment, while also preventing them from experiencing large kinematic errors. The addition of the error weighting function allowed the robot assistance to fade to zero even though the subjects' movements were variable. We also show that in order to assist-as-needed, the robot must relax its assistance at a rate faster than that of the learning human. The assist-as-needed algorithm proposed here can limit error during the learning of a dynamic motor task. The algorithm encourages learning by decreasing its assistance as a function of the ongoing progression of movement error. This type of algorithm is well suited for helping people learn dynamic tasks for which large kinematic errors are dangerous or discouraging, and thus may prove useful for robot-assisted movement training of walking or reaching following neurologic injury.