Dynamical System Modulation for Robot Learning via Kinesthetic Demonstrations
We present a system for robust robot skill acquisition from kinesthetic demonstrations. This system allows a robot to learn a simple goal-directed gesture and correctly reproduce it despite changes in the initial conditions and perturbations in the environment. It combines a dynamical system control...
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| Published in: | IEEE transactions on robotics Vol. 24; no. 6; pp. 1463 - 1467 |
|---|---|
| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York, NY
IEEE
01.12.2008
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 1552-3098, 1941-0468 |
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| Abstract | We present a system for robust robot skill acquisition from kinesthetic demonstrations. This system allows a robot to learn a simple goal-directed gesture and correctly reproduce it despite changes in the initial conditions and perturbations in the environment. It combines a dynamical system control approach with tools of statistical learning theory and provides a solution to the inverse kinematics problem when dealing with a redundant manipulator. The system is validated on two experiments involving a humanoid robot: putting an object into a box and reaching for and grasping an object. |
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| AbstractList | We present a system for robust robot skill acquisition from kinesthetic demonstrations. This system allows a robot to learn a simple goal-directed gesture and correctly reproduce it despite changes in the initial conditions and perturbations in the environment. It combines a dynamical system control approach with tools of statistical learning theory and provides a solution to the inverse kinematics problem when dealing with a redundant manipulator. The system is validated on two experiments involving a humanoid robot: putting an object into a box and reaching for and grasping an object. We present a system for robust robot skill acquisition from kinesthetic demonstrations. This system allows a robot to learn a simple goal-directed gesture and correctly reproduce it despite changes in the initial conditions and perturbations in the environment. It combines a dynamical system control approach with tools of statistical learning theory and provides a solution to the inverse kinematics problem when dealing with a redundant manipulator. The system is validated on two experiments involving a humanoid robot: putting an object into a box and reaching for and grasping an object. [PUBLICATION ABSTRACT] We present a system for robust robot skill acquisition from kinesthetic demonstrations. This system allows a robot to learn a simple goal-directed gesture and correctly reproduce it despite changes in the initial conditions and perturbations [abstract truncated by publisher]. |
| Author | Hersch, M. Guenter, F. Billard, A. Calinon, S. |
| Author_xml | – sequence: 1 givenname: M. surname: Hersch fullname: Hersch, M. organization: Learning Algorithms & Syst. Lab., Ecole Polytech. Fed. de Lausanne, Lausanne – sequence: 2 givenname: F. surname: Guenter fullname: Guenter, F. organization: Learning Algorithms & Syst. Lab., Ecole Polytech. Fed. de Lausanne, Lausanne – sequence: 3 givenname: S. surname: Calinon fullname: Calinon, S. organization: Learning Algorithms & Syst. Lab., Ecole Polytech. Fed. de Lausanne, Lausanne – sequence: 4 givenname: A. surname: Billard fullname: Billard, A. organization: Learning Algorithms & Syst. Lab., Ecole Polytech. Fed. de Lausanne, Lausanne |
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| Keywords | Gaussian mixture regression Dynamical system control manipulators robot programming by demonstration (PbD) intelligent robots simple robotic manipulation hybrid joint and end-effector control Mixed distribution Gripping Redundancy Intelligent robot Dynamical system Robotics Manipulator Inverse problem Robot programming Humanoid robot Gripper Gesture Probability learning |
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| SubjectTerms | Applied sciences Artificial intelligence Computer science; control theory; systems Control systems Control theory. Systems Controllers Dealing Dynamical system control Dynamical systems Dynamics Exact sciences and technology Gaussian mixture regression Grasping Hidden Markov models Humans hybrid joint and end-effector control Initial conditions Intelligent robots Inverse kinematics Kinematics Manipulators Modelling and identification Modulation Robot control Robot programming robot programming by demonstration (PbD) Robot sensing systems Robotic assembly Robotics Robots simple robotic manipulation Spatiotemporal phenomena |
| Title | Dynamical System Modulation for Robot Learning via Kinesthetic Demonstrations |
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