根据连续运动模式感知,适应部外骨的平面地面和楼梯
Zhaoyang Wang1, Dongfang Xu2, Shunyi Zhao1
1Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China.
Cyborg and bionic systems (Washington, D.C.)
|April 23, 2025
概括
本研究介绍了一种新的,无需学习的部外骨架控制方法,改善了对用户运动和环境的适应. 这种方法提高了辅助控制的准确性,并显示了不同用户和机动方式的概括性.
科学领域:
- 机器人技术和人机交互的人机交互
- 生物力学和辅助技术
背景情况:
- 关节外骨架提供了用户运动增强,但需要对不同用户和连续运动进行改进的自适应控制.
- 当前的控制策略通常依赖于外骨,用户和环境之间的复杂相互作用,需要更好的环境感知.
研究的目的:
- 开发和评估一种无学习环境感知方法,以增强关节外骨架的适应性控制.
- 提高外骨适应连续运动模式和不同用户步态的能力.
主要方法:
- 实施了一个非数据驱动的环境感知技术,用于关节外骨架的自适应控制.
- 在平坦的地面和楼梯上进行了适应性控制实验,对7名人体进行了实验.
主要成果:
- 在所有受试者中 (95.7%99.7%) 实现了超过95%的稳定运动模式的预测准确度.
- 在预测移动模式转换方面表现出高准确度 (87.5%100%),在完成之前检测到它们.
- 无学习方法在适应性控制性能方面表现优于基于学习的方法,并显示了用户概括性.
结论:
- 提出的无学习环境感知方法显著增强了部外骨架的适应性控制.
- 这种方法在各种移动模式和用户类型中提供了强大的性能,优于现有的数据驱动方法.
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