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On Learning, Representing, and Generalizing a Task in a Humanoid Robot
We present a programming-by-demonstration framework for generically extracting the relevant features of a given task and for addressing the problem of generalizing the acquired knowledge to differentExpand
Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models
A learning method is proposed, which is called Stable Estimator of Dynamical Systems (SEDS), to learn the parameters of the DS to ensure that all motions closely follow the demonstrations while ultimately reaching and stopping at the target. Expand
Robot Programming by Demonstration
Drawing on findings from robot control, human-robot interaction, applied machine learning, artificial intelligence, and developmental and cognitive psychology, the book contains a large set of didactic and illustrative examples. Expand
Computational approaches to motor learning by imitation.
This paper will primarily emphasize the motor side of imitation, assuming that a perceptual system has already identified important features of a demonstrated movement and created their corresponding spatial information. Expand
Robotic assistants in therapy and education of children with autism: can a small humanoid robot help encourage social interaction skills?
The results clearly demonstrate the need for, and benefits of, long-term studies in order to reveal the full potential of robots in the therapy and education of children with autism. Expand
Learning and Reproduction of Gestures by Imitation
An approach based on HMM, GMR, and dynamical systems to allow robots to acquire new skills by imitation was presented and evaluated and applications on different kinds of robots were presented to highlight the flexibility of the proposed approach. Expand
Incremental learning of gestures by imitation in a humanoid robot
  • S. Calinon, A. Billard
  • Computer Science
  • 2nd ACM/IEEE International Conference on Human…
  • 10 March 2007
It is shown that the essential characteristics of a gesture can be efficiently transferred by interacting socially with the robot by using active teaching methods that puts the human teacher “in the loop” of the robot's learning. Expand
Collaboration Through the Exploitation of Local Interactions in Autonomous Collective Robotics: The Stick Pulling Experiment
This article presents an experiment which investigates how collaboration in a group of simple reactive robots can be obtained through the exploitation of local interactions, and shows that, compared to homogeneous groups of robots without communication, heterogeneity and signalling can significantly increase the collaboration rate when there are fewer robots than sticks. Expand
Learning control Lyapunov function to ensure stability of dynamical system-based robot reaching motions
An imitation learning approach that exploits the power of Control Lyapunov Function (CLF) control scheme to ensure global asymptotic stability of nonlinear DS systems and allows learning a larger set of robot motions compared to existing methods that are based on quadratic LyAPunov functions. Expand
Discriminative and adaptive imitation in uni-manual and bi-manual tasks
A probabilistic method is used, based on Hidden Markov Models, for extracting the relative importance of reproducing either the gesture or the specific hand path in a given task, to determine a metric of imitation performance. Expand