结构参数的优化和机械性能分析的新浪冗余的驱动器康复训练机器人训练机器人训练
Junyu Wu1, He Wang2, Yubin Liu1
1State Key Laboratory of Robot Technology and Systems, Harbin Institute of Technology, Harbin 150001, China.
Biomimetics (Basel, Switzerland)
|April 25, 2025
概括
这项研究增强了用于平衡障碍康复的9DOF冗余机器人设备. 优化的结构参数和冗余性提高了新型治疗工具的灵活性和性能.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 康复工程 康复工程
- 生物力学 生物力学
背景情况:
- 机器人技术中的冗余结构增加了自由度 (DOF),灵活性和任务复杂性的能力.
- 机器人设备越来越多地用于康复,特别是对于平衡障碍患者.
研究的目的:
- 评估用于康复训练的9DOF系列并行混合冗余装置的机械性能.
- 优化机器人的结构参数,减少联合驱动力,以提高功能.
主要方法:
- 设计了一个9-DOF系列并行混合冗余机器人设备.
- 采用遗传算法 (GA) 来优化结构参数并减少联合驱动力.
- 收集定制的运动相关数据,并进行模拟实验来分析机械特性.
主要成果:
- 冗余的结构设计增强了运动灵活性,优化了负载分布,并减轻了应力度.
- 优化结构参数显著改善了机器人的整体机械性能.
- 模拟实验验证了重新设计的康复机器人的增强功能.
结论:
- 整合冗余结构和优化参数显著提高了康复机器人的机械性能.
- 这项研究为开发康复机器人的先进控制系统提供了基础.
- 优化的冗余机器人设备为平衡障碍患者提供了一种新,可靠和高效的治疗工具.
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