Scholarlink

<p>Aiming at the requirements of the functional rehabilitation training for ankle injuries, a novel ankle rehabilitation robot is proposed in terms of a 2RURU-2RR parallel mechanism. It consists of two RURU-type active branches, two RR-type constraint branches, a fixed base, and a moving platform composed of a rectangular frame and an adjustable-height footrest. Degree of freedom of the mechanism is analyzed using screw theory, kinematic models are established via the modified Denavit–Hartenberg method, and reachable workspace is determined through the Monte Carlo method. Motion/force transmission performance of the robot is evaluated using the local transmission index (LTI) and global transmission index (GTI). A penalty-integrated multi-objective optimization function is established based on the workspace and the GTI, and dimensional optimization is performed using the sparrow search algorithm. Optimization results demonstrate that the reachable workspace meets rehabilitation requirements and motion transmission efficiency is enhanced. Finally, both the trajectory planning for the virtual robot and the trajectory tracking experiments with the physical prototype are conducted. Experimental results validate that the robot ensures good safety (peak angle error ratio under 3.68%) during rehabilitation training, high tracking precision (maximum tracking error below 1.28°), and reliable repeatability (maximum 95% confidence interval across multiple experiments not exceeding 0.78°).</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Kinematics, optimization and trajectory planning of a 2RURU-2RR uncoupled parallel ankle rehabilitation robot

  • 期刊论文

  • 发表日期：

    2025年9月2日

查看全文
  • Yanbin Zhang,
  • Qianchen Pang,
  • Liming Song,
  • Haoxiang Xu,
  • Junchao Zhao

摘要

Aiming at the requirements of the functional rehabilitation training for ankle injuries, a novel ankle rehabilitation robot is proposed in terms of a 2RURU-2RR parallel mechanism. It consists of two RURU-type active branches, two RR-type constraint branches, a fixed base, and a moving platform composed of a rectangular frame and an adjustable-height footrest. Degree of freedom of the mechanism is analyzed using screw theory, kinematic models are established via the modified Denavit–Hartenberg method, and reachable workspace is determined through the Monte Carlo method. Motion/force transmission performance of the robot is evaluated using the local transmission index (LTI) and global transmission index (GTI). A penalty-integrated multi-objective optimization function is established based on the workspace and the GTI, and dimensional optimization is performed using the sparrow search algorithm. Optimization results demonstrate that the reachable workspace meets rehabilitation requirements and motion transmission efficiency is enhanced. Finally, both the trajectory planning for the virtual robot and the trajectory tracking experiments with the physical prototype are conducted. Experimental results validate that the robot ensures good safety (peak angle error ratio under 3.68%) during rehabilitation training, high tracking precision (maximum tracking error below 1.28°), and reliable repeatability (maximum 95% confidence interval across multiple experiments not exceeding 0.78°).