Sun Qing, Guo Shuai, Zhang Leigang
Technol Health Care. 2021;29(5):1029-1045. doi: 10.3233/THC-202633.
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.
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.
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.
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.
The VMEIV index can measure the kinematic dexterity of human-robot interaction, and provide a reference for the training trajectory selection of rehabilitation robot.
康复训练轨迹的定义在康复训练过程中具有重要意义，人机交互运动的灵活性为交互运动轨迹的选择提供了依据。
针对人机交互的运动灵活性，提出速度可操作度椭球交集体积（VMEIV）指标进行分析，并结合人机协作空间得到灵活性分布云图。
首先建立人机交互的运动约束方程，基于连杆速度得到雅可比矩阵。然后利用蒙特卡洛法和单元体分割法获得人机交互的协作空间，并在协作空间中求解人机交互的VMEIV。最后以上肢康复机器人为研究对象，利用VMEIV近似体积指标进行人机交互灵活性分析。
仿真和实验结果具有一定的一致性，表明VMEIV指标作为人机交互运动灵活性指标是有效的。
VMEIV指标能够衡量人机交互的运动灵活性，为康复机器人训练轨迹的选择提供参考。
