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Learning task-oriented dexterous grasping from human knowledge
conference contribution
posted on 2023-06-09, 23:12 authored by Hui Li, Yinlong Zhang, Yanan LiYanan Li, Hongsheng HeIndustrial automation requires robot dexterity to automate many processes such as product assembling, packaging, and material handling. The existing robotic systems lack the capability to determining proper grasp strategies in the context of object affordances and task designations. In this paper, a framework of task-oriented dexterous grasping is proposed to learn grasp knowledge from human experience and to deploy the grasp strategies while adapting to grasp context. Grasp topology is defined and grasp strategies are learned from an established dataset for task-oriented dexterous manipulation. To adapt to various grasp context, a reinforcement-learning based grasping policy was implement to deploy different task-oriented strategies. The performances of the system was evaluated in a simulated grasping environment by using an AR10 anthropomorphic hand installed in a Sawyer robotic arm. The proposed framework achieved a hit rate of 100% for grasp strategies and an overall top-3 match rate of 95.6%. The success rate of grasping was 85.6% during 2700 grasping experiments for manipulation tasks given in natural-language instructions.
Funding
The Game Theory of Human-Robot Interaction - HRIgame; G2929; EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCIL
History
Publication status
- Published
File Version
- Accepted version
Journal
IEEE International Conference on Robotics and Automation (ICRA)ISSN
1050-4729Publisher
IEEEExternal DOI
Event name
2021 IEEE International Conference on Robotics and Automation (ICRA)Event location
Xi'an, ChinaEvent type
conferenceEvent date
May 30 - June 5 2021ISBN
9781728190785Department affiliated with
- Engineering and Design Publications
Notes
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksFull text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2021-03-02First Open Access (FOA) Date
2021-04-09First Compliant Deposit (FCD) Date
2021-03-02Usage metrics
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