Learning task space control through goal directed exploration

Lorenzo Jamone, Lorenzo Natale, Kenji Hashimoto, Giulio Sandini, Atsuo Takanishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

We present an autonomous goal-directed strategy to learn how to control a redundant robot in the task space. We discuss the advantages of exploring the state space through goal-directed actions defined in the task space (i.e. learning by trying to do) instead of performing motor babbling in the joints space, and we stress the importance of learning to be performed online, without any separation between training and execution. Our solution relies on learning the forward model and then inverting it for the control; different approaches to learn the forward model are described and compared. Experimental results on a simulated humanoid robot are provided to support our claims. The robot learns autonomously how to perform reaching actions directed toward 3D targets in task space by using arm and waist motion, not relying on any prior knowledge or initial motor babbling. To test the ability of the system to adapt to sudden changes both in the robot structure and in the perceived environment we artificially introduce two different kinds of kinematic perturbations: a modification of the length of one link and a rotation of the task space reference frame. Results demonstrate that the online update of the model allows the robot to cope with such situations.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Robotics and Biomimetics, ROBIO 2011
Pages702-708
Number of pages7
DOIs
Publication statusPublished - 2011 Dec 1
Event2011 IEEE International Conference on Robotics and Biomimetics, ROBIO 2011 - Phuket, Thailand
Duration: 2011 Dec 72011 Dec 11

Publication series

Name2011 IEEE International Conference on Robotics and Biomimetics, ROBIO 2011

Conference

Conference2011 IEEE International Conference on Robotics and Biomimetics, ROBIO 2011
CountryThailand
CityPhuket
Period11/12/711/12/11

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Learning task space control through goal directed exploration'. Together they form a unique fingerprint.

  • Cite this

    Jamone, L., Natale, L., Hashimoto, K., Sandini, G., & Takanishi, A. (2011). Learning task space control through goal directed exploration. In 2011 IEEE International Conference on Robotics and Biomimetics, ROBIO 2011 (pp. 702-708). [6181368] (2011 IEEE International Conference on Robotics and Biomimetics, ROBIO 2011). https://doi.org/10.1109/ROBIO.2011.6181368