Role Dynamic Assignment of Human–Robot Collaboration Based on Target Prediction and Fuzzy Inference

Wang, Chengyun; Zhao, Jingjin

doi:10.1109/tii.2023.3266378

Cited by 1 publication

(2 citation statements)

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“…1. A three-module framework (HMRDA) of human-robot cooperative motion target prediction module, role dynamic assignment module, and robot motion planning module was designed, and a dynamic role assignment method based on goal prediction and fuzzy reasoning was proposed [18]. According to motion information and prediction information, the robot can adjust its role in human-robot cooperative motion to change the motion trajectory.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Role Dynamic Allocation of Human-Robot Cooperation Based on Reinforcement Learning in an Installation of Curtain Wall

Liu,

Wang,

Zhao

et al. 2024

Computer Modeling in Engineering &Amp; Sciences

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A real-time adaptive roles allocation method based on reinforcement learning is proposed to improve humanrobot cooperation performance for a curtain wall installation task. This method breaks the traditional idea that the robot is regarded as the follower or only adjusts the leader and the follower in cooperation. In this paper, a self-learning method is proposed which can dynamically adapt and continuously adjust the initiative weight of the robot according to the change of the task. Firstly, the physical human-robot cooperation model, including the role factor is built. Then, a reinforcement learning model that can adjust the role factor in real time is established, and a reward and action model is designed. The role factor can be adjusted continuously according to the comprehensive performance of the human-robot interaction force and the robot's Jerk during the repeated installation. Finally, the roles adjustment rule established above continuously improves the comprehensive performance. Experiments of the dynamic roles allocation and the effect of the performance weighting coefficient on the result have been verified. The results show that the proposed method can realize the role adaptation and achieve the dual optimization goal of reducing the sum of the cooperator force and the robot's Jerk.

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Section: Introductionmentioning

confidence: 99%

“…In addition, the premise of changing the role is that the robot can accurately recognize human intention. Compared with the dynamic adjustment of role, the article's authors [18] have contributed more to the recognition of robot intention.…”

Section: Introductionmentioning

confidence: 99%