Extensive human training for robot skill synthesis: Validation on a robotic hand

Erhan Oztop, Li Heng Lin, Mitsuo Kawato, Gordon Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

We propose a framework for skill synthesis for robots that exploits the human capacity to learn novel control tasks. The conceptual idea is to incorporate the target robotic platform into the experimenter's body schema so that it can be controlled effortlessly as if the robot were a part of the body. Once this stage is achieved, the dexterity on a task exhibited with the new external limb -the robot- can be used for designing controllers for the task under consideration. This article exemplifies the proposed framework by showing the derivation of an effective open-loop controller that can manipulate two balls with the fingers of a 16-DOF robotic hand.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Robotics and Automation, ICRA'07
Pages1788-1793
Number of pages6
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 IEEE International Conference on Robotics and Automation, ICRA'07 - Rome, Italy
Duration: 10 Apr 200714 Apr 2007

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2007 IEEE International Conference on Robotics and Automation, ICRA'07
Country/TerritoryItaly
CityRome
Period10/04/0714/04/07

Keywords

  • Body schema
  • Hand control
  • Skill synthesis

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