Journal
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 68, Issue 9, Pages 8657-8666Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2020.3016271
Keywords
Robot sensing systems; Force; Task analysis; Robot kinematics; Dynamics; Human-robot collaboration; motion synchronization; neural networks; observer; visual and force sensing
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Funding
- National Natural Science Foundation of China [62061160371, 62003032, 61873298]
- Beijing Natural Science Foundation [JQ20026]
- Beijing Top Discipline for Artificial Intelligent Science and Engineering, University Science and Technology Beijing
- Fundamental Research Funds for the China Central Universities of USTB [FRF-TP-19-001C2]
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This article proposes a hybrid framework using visual and force sensing for human-robot co-carrying tasks, achieving motion synchronization and stable interaction behavior between human and robot. The framework's effectiveness is validated through simulations and experiments.
In this article, we propose a hybrid framework using visual and force sensing for human-robot co-carrying tasks. Visual sensing is utilized to obtain human motion and an observer is designed for estimating control input of human, which generates robot's desired motion toward human's intended motion. An adaptive impedance-based control strategy is proposed for trajectory tracking with neural networks used to compensate for uncertainties in robot's dynamics. Motion synchronization is achieved and this approach yields a stable and efficient interaction behavior between human and robot, decreases human control effort and avoids interference to human during the interaction. The proposed framework is validated by a co-carrying task in simulations and experiments.
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