Synchrony and perception in robotic imitation across embodiments

A. Alissandrakis, C.L. Nehaniv, K. Dautenhahn

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

13 Citations (Scopus)
34 Downloads (Pure)

Abstract

Social robotics opens up the possibility of individualized social intelligence in member robots of a community, and allows us to harness not only individual
learning by the individual robot, but also the acquisition of new skills by observing other members of the community (robot, human, or virtual).
We describe ALICE (Action Learning for Imitation via Correspondences between Embodiments), an implemented generic mechanism for solving
the correspondence problem between differently embodied robots. ALICE enables a robotic agent to learn a behavioral repertoire suitable to performing a
task by observing a model agent, possibly having a different type of body, joints, different number of degrees of freedom, etc. Previously we demonstrated that the character of imitation achieved will depend on the granularity
of subgoal matching, and on the metrics used to evaluate success
Original languageEnglish
Title of host publicationProcs of the 2003 IEEE Int Symposium on Computational Intelligence in Robotics and Automation
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages923-930
Publication statusPublished - 2003
EventIEEE Int Symp on Computational Intelligence in Robotics and Automation - Kobe, Japan
Duration: 16 Jul 200320 Jul 2003

Conference

ConferenceIEEE Int Symp on Computational Intelligence in Robotics and Automation
Country/TerritoryJapan
CityKobe
Period16/07/0320/07/03

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