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Article type: Research Article
Authors: Sun, Qing* | Guo, Shuai | Zhang, Leigang
Affiliations: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China
Correspondence: [*] Corresponding author: Qing Sun, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, China. E-mail: qingsun93@163.com.
Abstract: BACKGROUND: The definition of rehabilitation training trajectory is of great significance during rehabilitation training, and the dexterity of human-robot interaction motion provides a basis for selecting the trajectory of interaction motion. OBJECTIVE: Aimed at the kinematic dexterity of human-robot interaction, a velocity manipulability ellipsoid intersection volume (VMEIV) index is proposed for analysis, and the dexterity distribution cloud map is obtained with the human-robot cooperation space. METHOD: Firstly, the motion constraint equation of human-robot interaction is established, and the Jacobian matrix is obtained based on the speed of connecting rod. Then, the Monte Carlo method and the cell body segmentation method are used to obtain the collaborative space of human-robot interaction, and the VMEIV of human-robot interaction is solved in the cooperation space. Finally, taking the upper limb rehabilitation robot as the research object, the dexterity analysis of human-robot interaction is carried out by using the index of the approximate volume of the VMEIV. RESULTS: The results of the simulation and experiment have a certain consistency, which indicates that the VMEIV index is effective as an index of human-robot interaction kinematic dexterity. CONCLUSIONS: The VMEIV index can measure the kinematic dexterity of human-robot interaction, and provide a reference for the training trajectory selection of rehabilitation robot.
Keywords: Rehabilitation robot, cooperation space, human-robot interaction, dexterity, velocity manipulability ellipsoid intersection volume
DOI: 10.3233/THC-202633
Journal: Technology and Health Care, vol. 29, no. 5, pp. 1029-1045, 2021
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