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Incremental learning of gestures by imitation in a humanoid robot

Published: 10 March 2007 Publication History

Abstract

We present an approach to teach incrementally human gestures to a humanoid robot. By using active teaching methods that puts the human teacher "in the loop" of the robot's learning, we show that the essential characteristics of a gesture can be efficiently transferred by interacting socially with the robot. In a first phase, the robot observes the user demonstrating the skill while wearing motion sensors. The motion of his/her two arms and head are recorded by the robot, projected in a latent space of motion and encoded bprobabilistically in a Gaussian Mixture Model (GMM). In a second phase, the user helps the robot refine its gesture by kinesthetic teaching, i.e. by grabbing and moving its arms throughout the movement to provide the appropriate scaffolds. To update the model of the gesture, we compare the performance of two incremental training procedures against a batch training procedure. We present experiments to show that different modalities can be combined efficiently to teach incrementally basketball officials' signals to a HOAP-3 humanoid robot.

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cover image ACM Conferences
HRI '07: Proceedings of the ACM/IEEE international conference on Human-robot interaction
March 2007
392 pages
ISBN:9781595936172
DOI:10.1145/1228716
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 10 March 2007

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Author Tags

  1. gaussian mixture model
  2. imitation learning
  3. incremental learning
  4. programming by demonstration

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HRI07
HRI07: International Conference on Human Robot Interaction
March 10 - 12, 2007
Virginia, Arlington, USA

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HRI '07 Paper Acceptance Rate 22 of 101 submissions, 22%;
Overall Acceptance Rate 268 of 1,124 submissions, 24%

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Cited By

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  • (2024)Analysis of a Visual Imitation Algorithm on a Robot SwarmDüzce Üniversitesi Bilim ve Teknoloji Dergisi10.29130/dubited.139003612:4(1789-1803)Online publication date: 23-Oct-2024
  • (2024)State-of-the-Art Elderly Service Robot: Environmental Perception, Compliance Control, Intention Recognition, and Research ChallengesIEEE Systems, Man, and Cybernetics Magazine10.1109/MSMC.2023.323885510:1(2-16)Online publication date: Jan-2024
  • (2024)Self-supervised 6-DoF Robot Grasping by Demonstration via Augmented Reality Teleoperation System2024 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA57147.2024.10611721(7819-7826)Online publication date: 13-May-2024
  • (2024)Incremental Learning of Full-Pose Via-Point Movement Primitives on Riemannian Manifolds2024 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA57147.2024.10610275(2317-2323)Online publication date: 13-May-2024
  • (2024)A Novel Shared Control Framework Based on Imitation Learning2024 IEEE International Conference on Industrial Technology (ICIT)10.1109/ICIT58233.2024.10540824(1-6)Online publication date: 25-Mar-2024
  • (2024)Robot Learning from Demonstration based on Human-in-the-loop Reinforcement Learning2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)10.1109/CASE59546.2024.10711559(2633-2638)Online publication date: 28-Aug-2024
  • (2024)Imitation Learning Based Manipulator Skill Training for Home Environment2024 China Automation Congress (CAC)10.1109/CAC63892.2024.10865776(6110-6115)Online publication date: 1-Nov-2024
  • (2024)Identifying Anomaly in IoT Traffic Flow With Locality Sensitive HashesIEEE Access10.1109/ACCESS.2024.342023812(89467-89478)Online publication date: 2024
  • (2024)A survey of demonstration learningRobotics and Autonomous Systems10.1016/j.robot.2024.104812182(104812)Online publication date: Dec-2024
  • (2023)Biomimetic Approaches for Human Arm Motion Generation: Literature Review and Future DirectionsSensors10.3390/s2308391223:8(3912)Online publication date: 12-Apr-2023
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