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A hybrid human motion prediction approach for human-robot collaboration
conference contribution
posted on 2023-06-09, 18:35 authored by Yanan Li, Chenguang YangPrediction of human motion is useful for a robot to collaborate with a human partner. In this paper, we propose a hybrid approach for the robot to predict the human partner’s motion by using proprioceptive and haptic information. First, a computational model is established to describe the change of the human partner’s motion, which is fitted by using the historical human motion data. The output of this model is used as the robot’s reference position in an impedance control model. Then, this reference position is modified by minimizing the interaction force between the human and robot, which indicates the discrepancy between the predicted motion and real one. The combination of the prediction using a computational model and modification using the haptic feedback enables the robot to actively collaborate with the human partner. Simulation results show that the proposed hybrid approach outperforms impedance control, model-based prediction only and haptic feedback only.
History
Publication status
- Published
File Version
- Accepted version
Journal
Proceedings of the 19th Annual UK Workshop on Computational IntelligencePublisher
SpringerExternal DOI
Volume
1043Event name
The 19th Annual UK Workshop on Computational Intelligence (UKCI 2019)Event location
Portsmouth, UKEvent type
conferenceEvent date
4 - 6 September, 2019ISBN
9783030299330Series
Advances in Intelligent Systems and ComputingDepartment affiliated with
- Engineering and Design Publications
Full text available
- No
Peer reviewed?
- Yes