Representation of robot motion control skill

Development of skilled robotics draws clues from model based theories of human motor control. Thus, a comprehensive anthropomorphic background is given. Skills in robotics are viewed as a tool for fast and efficient real time control that can handle complexity and nonlinearity of robots, generally aiming at robot autonomy. In particular, a skill of redundancy resolution is addressed through a skill representation problem based on Function Approximator. The task of the robot is approximated by a set of parameterized motion primitives. Adopted parameters are also parameters of the function approximator, i.e., skill used. Redundancy is resolved during skill learning based on available expert knowledge, yielding parameterized joint motions. The approximation procedure (Successive Approximations), a major contribution of the paper, is used for batch compilation of parameterized examples, resulting in a parameterized skill model. Such skill enables a user, inexpert in redundancy resolution, to gain benefits from redundant robots. All properties of the Successive Approximations procedure such as accuracy in interpolation and extrapolation, acceleration in redundancy resolution and upgrading to new skill regarding the task variation, are discussed in the example of a five degrees-of-freedom planar redundant robot, performing parameterized ellipse as motion primitive.

[1]  Reza Shadmehr,et al.  Catastrophic Interference in Human Motor Learning , 1994, NIPS.

[2]  Yangsheng Xu,et al.  On the fidelity of human skill models , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[3]  M. Kawato,et al.  Multiple internal models in the cerebellum: A functional MRI study , 1998, Neuroscience Research.

[4]  J. Adams.  Historical review and appraisal of research on the learning, retention, and transfer of human motor skills. , 1987 .

[5]  Charles W. Wampler,et al.  On the Inverse Kinematics of Redundant Manipulators , 1988, Int. J. Robotics Res..

[6]  Sadao Kawamura,et al.  Interpolations for Input Torque Patterns Obtained through Learning Control and Its Application to a Conveyor System , 1996 .

[7]  Kuu-Young Young,et al.  An approach to enlarge learning space coverage for robot learning control , 1997, IEEE Trans. Fuzzy Syst..

[8]  Pradeep K. Khosla,et al.  Sensorimotor primitives for robotic assembly skills , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[9]  Helge Ritter,et al.  Learning of Visuomotor Coordination of a Robot Arm with Redundant Degrees of Freedon , 1989 .

[10]  Cristina Baroglio,et al.  Learning Controllers for Industrial Robots , 2005, Machine Learning.

[11]  Roderic A. Grupen,et al.  Learning admittance mappings for force-guided assembly , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[12]  T. Suehiro,et al.  A model-based manipulation system with skill-based execution in unstructured environment , 1991 .

[13]  N. A. Bernshteĭn.  The co-ordination and regulation of movements , 1967 .

[14]  Yoshihiko Nakamura,et al.  Advanced robotics - redundancy and optimization , 1990 .

[15]  Polly K. Pook,et al.  Teleassistance: using deictic gestures to control robot action , 1996 .

[16]  Margit Kinder,et al.  Path Planning for Six-joint Manipulators by Generalization from Example Paths , 1994 .

[17]  Shigeoki Hirai,et al.  Integration of a task knowledge base and a cooperative maneuvering system for the telerobot 'MEISTER' , 1990, EEE International Workshop on Intelligent Robots and Systems, Towards a New Frontier of Applications.

[18]  M. Kaiser.  Hierarchical learning of e cient skill application for autonomous robots ? , 1995 .

[19]  H. Friedrich,et al.  In: Probramming by Demonstration vs. Learning from Examples Workshop at Ml'95 Obtaining Good Performance from a Bad Teacher , 1995 .

[20]  Ales Ude,et al.  Acquisition of Elementary Robot Skills from Human Demonstration , 1995 .

[21]  Kenneth Kreutz-Delgado,et al.  Issues in learning global properties of the robot kinematic mapping , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[22]  Geir Hovland,et al.  Skill acquisition from human demonstration using a hidden Markov model , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[23]  Sheng Liu,et al.  Task-Level Robot Adaptive Control Based on Human Teaching Data and Its Application to Deburring , 1993, 1993 American Control Conference.

[24]  M. Kaiser,et al.  Time-delay neural networks for control , 1994 .

[25]  Terence D. Sanger.  Optimal Movement Primitives , 1994, NIPS.

[26]  Begnaud Francis Hildebrand,et al.  Introduction to numerical analysis: 2nd edition , 1987 .

[27]  Richard S. Sutton,et al.  Neuronlike adaptive elements that can solve difficult learning control problems , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[28]  William H. Press,et al.  Numerical recipes in C , 2002 .

[29]  Charles W. Wampler.  The Inverse Function Approach to Kinematic Control of Redundant Manipulators , 1988, 1988 American Control Conference.

[30]  F. Girosi,et al.  Networks for approximation and learning , 1990, Proc. IEEE.

[31]  Andrew A. Goldenberg,et al.  Learning approximation of feedforward control dependence on the task parameters with application to direct-drive manipulator tracking , 1997, IEEE Trans. Robotics Autom..

[32]  Sadao Kawamura,et al.  A time-scale interpolation for input torque patterns obtained through learning control on constrained robot motions , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[33]  Friedrich Lange,et al.  Learning to improve the path accuracy of position controlled robots , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[34]  Yong-San Yoon,et al.  Practical inverse kinematics of a kinematically redundant robot using a neural network , 1991, Adv. Robotics.

[35]  Sheng Liu,et al.  Transfer of Human Skills to Robots: Learning from Human Demonstrations for Building an Adaptive Control System , 1992, 1992 American Control Conference.

[36]  Thomas H. Speeter.  Primitive based control of the Utah/MIT dextrous hand , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[37]  Charles A. Klein,et al.  Review of pseudoinverse control for use with kinematically redundant manipulators , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[38]  J. Albus.  Mechanisms of planning and problem solving in the brain , 1979 .

[39]  Ruzena Bajcsy,et al.  Robotic sensorimotor learning in continuous domains , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[40]  Judy Chen,et al.  Robot skill discovery bases on observed data. , 1996 .

[41]  Masayuki Inaba,et al.  Learning by watching: extracting reusable task knowledge from visual observation of human performance , 1994, IEEE Trans. Robotics Autom..

[42]  Yangsheng Xu,et al.  Fuzzy inverse kinematic mapping: rule generation, efficiency, and implementation , 1993, Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93).

[43]  Huan Liu,et al.  Knowledge-based control of grasping in robot hands using heuristics from human motor skills , 1993, IEEE Trans. Robotics Autom..

[44]  David J. Reinkensmeyer,et al.  Using associative content-addressable memories to control robots , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[45]  Vijaykumar Gullapalli,et al.  Reinforcement learning and its application to control , 1992 .

[46]  Tamar Flash,et al.  Computational approaches to motor control , 2001, Current Opinion in Neurobiology.

[47]  Pradeep K. Khosla,et al.  Sensorimotor primitives for programming robotic assembly skills , 1997 .

[48]  Gene H. Golub,et al.  Matrix computations , 1983 .

[49]  Nathan Delson,et al.  Robot programming by human demonstration: adaptation and inconsistency in constrained motion , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[50]  Pradeep K. Khosla,et al.  Manipulation task primitives for composing robot skills , 1997, Proceedings of International Conference on Robotics and Automation.

[51]  Jahangir Rastegar,et al.  A new model-based tracking controller for robot manipulators using trajectory pattern inverse dynamics , 1992, IEEE Trans. Robotics Autom..

[52]  Nathan Delson,et al.  Robot programming by human demonstration: the use of human variation in identifying obstacle free trajectories , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[53]  Olac Fuentes,et al.  The virtual tool approach to dextrous telemanipulation , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[54]  Andrew W. Moore,et al.  Efficient memory-based learning for robot control , 1990 .

[55]  Patrick van der Smagt,et al.  Introduction to neural networks , 1995, The Lancet.

[56]  Jie Yang,et al.  Towards human-robot coordination: skill modeling and transferring via hidden Markov model , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[57]  H. Harry Asada,et al.  Skill acquisition from human experts through pattern processing of teaching data , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[58]  C. L. Philip Chen,et al.  Robot kinematics learning computations using polynomial neural networks , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[59]  James S. Albus,et al.  Theory and Practice of Hierarchical Control , 1981 .

[60]  W. Thomas Miller,et al.  Sensor-based control of robotic manipulators using a general learning algorithm , 1987, IEEE J. Robotics Autom..

[61]  Michael I. Jordan,et al.  An internal model for sensorimotor integration. , 1995, Science.

[62]  Nan Zeng,et al.  A Neural Network Based Inverse Kinematics Solution In Robotics , 1993 .

[63]  Marnix Nuttin,et al.  Integrated Acquisition, Execution, Evaluation, and Tuning of Elementary Skills for Intelligent robots , 1994, AIRTC.

[64]  Francis L. Merat,et al.  Introduction to robotics: Mechanics and control , 1987, IEEE J. Robotics Autom..

[65]  Reza Shadmehr,et al.  Evidence for a Forward Dynamics Model in Human Adaptive Motor Control , 1998, NIPS.

[66]  F A Mussa-Ivaldi,et al.  Adaptive representation of dynamics during learning of a motor task , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[67]  Takanori Shibata,et al.  Motion planning of a redundant manipulator based on criteria of skilled operators , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[68]  Bruno Siciliano,et al.  Modeling and Control of Robot Manipulators , 1995 .

[69]  Dragoljub Surdilovic,et al.  Learning of inverse kinematics behavior of redundant robot , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[70]  Klaus Schulten,et al.  Topology-conserving maps for learning visuo-motor-coordination , 1989, Neural Networks.

[71]  Arnold Neumaier,et al.  Introduction to Numerical Analysis , 2001 .

[72]  Suguru Arimoto,et al.  Bettering operation of Robots by learning , 1984, J. Field Robotics.

[73]  A. Barto,et al.  Models of the cerebellum and motor learning , 1996 .

[74]  David A. Cohn,et al.  Active Learning with Statistical Models , 1996, NIPS.

[75]  Filson H. Glanz,et al.  Application of a General Learning Algorithm to the Control of Robotic Manipulators , 1987 .

[76]  Reza Shadmehr,et al.  Computational nature of human adaptive control during learning of reaching movements in force fields , 1999, Biological Cybernetics.

[77]  M. Jeannerod.  The neural and behavioural organization of goal-directed movements , 1990, Psychological Medicine.

[78]  T. Flash,et al.  The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[79]  Luca Maria Gambardella,et al.  On the iterative learning control theory for robotic manipulators , 1988, IEEE J. Robotics Autom..

[80]  Christopher G. Atkeson,et al.  Using locally weighted regression for robot learning , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[81]  Vassilios Morellas,et al.  Neural network learning of the inverse kinematic relationships for a robot arm , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[82]  Sukhan Lee,et al.  Skill learning from observations , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[83]  V. Gullapalli,et al.  Acquiring robot skills via reinforcement learning , 1994, IEEE Control Systems.

[84]  D. Hern.  Neural Modeling of the Kinematics of RobotTrajectoriesM , 1992 .

[85]  Rüdiger Dillmann,et al.  Building elementary robot skills from human demonstration , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[86]  Timothy D. Lee,et al.  Motor Control and Learning: A Behavioral Emphasis , 1982 .

[87]  Jeff Schneider,et al.  Robot Skill Learning Through Intelligent Experimentation , 1995 .

[88]  Sukhan Lee,et al.  Robot skill discovery based on observed data(003) 5335512 , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[89]  J R Flanagan,et al.  The Role of Internal Models in Motion Planning and Control: Evidence from Grip Force Adjustments during Movements of Hand-Held Loads , 1997, The Journal of Neuroscience.

[90]  Ferdinando A. Mussa-Ivaldi,et al.  Interference in Learning Internal Models of Inverse Dynamics in Humans , 1994, NIPS.

[91]  Steven M. Finbeiner,et al.  The Neural and Behavioral Organization of Goal-Directed Movements , 1989, The Yale Journal of Biology and Medicine.

[92]  Yangsheng Xu,et al.  Learning and validation of human control strategies , 1998 .

[93]  Michael I. Jordan,et al.  Forward Models: Supervised Learning with a Distal Teacher , 1992, Cogn. Sci..

[94]  Rajiv V. Dubey,et al.  A weighted least-norm solution based scheme for avoiding joint limits for redundant joint manipulators , 1993, IEEE Trans. Robotics Autom..

[95]  Manfred Hiller,et al.  Dextrous motion control of a redundant SCARA robot , 1998, IECON '98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.98CH36200).

[96]  T. Poggio.  A theory of how the brain might work. , 1990, Cold Spring Harbor symposia on quantitative biology.

[97]  Yangsheng Xu,et al.  Hidden Markov model approach to skill learning and its application to telerobotics , 1993, IEEE Trans. Robotics Autom..

[98]  Terence D. Sanger,et al.  Neural network learning control of robot manipulators using gradually increasing task difficulty , 1994, IEEE Trans. Robotics Autom..

[99]  Ken-ichi Tanaka,et al.  A Method of Solution to an Inverse Kinematics Problem of a Redundant Manipulator Using Neural Networks , 1991 .

[100]  S. Keele,et al.  The Structure of Motor Programs , 1976 .

[101]  Terence D. Sanger.  A Practice Strategy for Robot Learning Control , 1992, NIPS.

[102]  Gerd Hirzinger,et al.  Sensor-based space robotics-ROTEX and its telerobotic features , 1993, IEEE Trans. Robotics Autom..

[103]  R. Lumia,et al.  Hierarchical Control of Intelligent Machines Applied to Space Station Telerobots , 1987 .

[104]  F. Pourboghrat,et al.  Neural networks for learning inverse kinematics of redundant manipulators , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

[105]  D. Wolpert,et al.  Internal models in the cerebellum , 1998, Trends in Cognitive Sciences.

[106]  V. Potkonjak,et al.  Skill acquiring in robotics by successive approximation of nominal control sequences , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[107]  Charles L. Lawson,et al.  Solving least squares problems , 1976, Classics in applied mathematics.

[108]  Hiroyuki Kano,et al.  A new approach to synthesizing free motions of robotic manipulators based on a concept of unit motions , 1995, IEEE Trans. Syst. Man Cybern..

[109]  K. Kreutz-Delgado,et al.  Inverse Kinematics of Dextrous Manipulators , 1997 .