Human hand motion retargeting for dexterous robotic hand

Jedrzej Orbik, Shile Li, Dongheui Lee

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

4 Scopus citations

Abstract

One way to achieve dexterous manipulation autonomously with natural input is through learning by demonstration. Unfortunately, grasping an object with a complex dexterous hand is a complicated task. To facilitate the demo acquisition process, we propose a low-cost framework to map the human hand motion from a single RGB-D camera using inverse kinematics. This framework has been implemented in a CoppeliaSim simulation environment. We evaluate two multi-task handling methods and a low-pass filter using two obtained trajectories. Empirically, the proposed framework can successfully perform grasping task imitations. An exemplary video of the object manipulation is presented on the project website: https://sites.google.com/view/retargeting-for-dexterous-hand

Original languageEnglish
Title of host publication2021 18th International Conference on Ubiquitous Robots, UR 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages264-270
Number of pages7
ISBN (Electronic)9781665438995
DOIs
StatePublished - 12 Jul 2021
Externally publishedYes
Event18th International Conference on Ubiquitous Robots, UR 2021 - Gangneung-si, Gangwon-do, Korea, Republic of
Duration: 12 Jul 202114 Jul 2021

Publication series

Name2021 18th International Conference on Ubiquitous Robots, UR 2021

Conference

Conference18th International Conference on Ubiquitous Robots, UR 2021
Country/TerritoryKorea, Republic of
CityGangneung-si, Gangwon-do
Period12/07/2114/07/21

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