多接触安全关键规划和适应性神经控制软外套在不同的地形
IEEE transactions on cybernetics
|March 25, 2025
概括
这项研究介绍了一种新的软外套,通过阻抗优化和自适应神经控制优先考虑安全,从而提高下肢运动辅助. 它确保在各种地形上提供安全的协助,适应人类脚关节的动态.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 生物力学 生物力学
- 控制系统 控制系统
背景情况:
- 现有的软外衣经常忽视在人类运动辅助期间的安全性.
- 下肢外套需要对各种地形和用户互动进行强有力的控制.
研究的目的:
- 引入一款新的单发动机软外套,用于下肢辅助,并集成安全约束.
- 开发一种适应性神经控制器,以在不同地形上提供安全有效的运动辅助.
主要方法:
- 阻抗优化,结合控制屏障功能,同时满足安全限制.
- 在严格的安全限制下,自适应神经控制利用集成屏障Lyapunov功能进行轨迹跟踪.
- 分析脚关节的相互作用力,以学习和适应人类关节阻抗.
主要成果:
- 该系统通过自适应学习人类脚关节阻抗,确保参考轨迹符合安全要求.
- 实验结果显示平面,草和石表面的平均跟踪误差很低 (0.0062-0.0063rad).
- 柔软的外衣表现出有效地适应不同地形,同时保持用户的安全.
结论:
- 拟议的软外套设计有效地平衡了运动辅助与关键的安全考虑.
- 控制屏障功能和自适应神经控制的集成为安全的可穿戴机器人系统提供了强大的解决方案.
- 这项技术代表着可穿戴机器人技术的重大进步,以提高移动性和安全性.
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