估计人类关节时刻统一了外骨的控制,减少了用户的努力
Dean D Molinaro1,2, Inseung Kang3, Aaron J Young1,2
1George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Science robotics
|March 20, 2024
概括
这项研究介绍了一种统一的机器人外骨控制框架,该框架使用时卷积网络 (TCN) 来适应协助增强人类移动性. 该系统显著降低了代谢成本,使先进的外骨技术更容易用于现实世界.
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
- 机器学习 机器学习
背景情况:
- 目前的机器人下肢外骨架在现实应用中面临着挑战,原因是特定环境的控制要求.
- 需要具有适应性和用户独立的控制系统来提高外骨的生存能力.
研究的目的:
- 提出一个统一的外骨控制框架,根据实时用户生物力学自主调整辅助.
- 评估时间卷积网络 (TCN) 的性能,以估计用户关节时刻.
- 评估统一控制器对用户代谢成本和生物机械力度的影响.
主要方法:
- 开发了一种统一的控制框架,用于部外骨架,使用时卷积网络 (TCN).
- 据TCN估计,即时的用户联合时刻提供了适应性协助.
- 在没有用户特定校准的情况下,在35个门诊条件中评估了系统的准确性.
- 测量了用户的新陈代谢成本和下肢积极工作在平地和倾斜行走.
主要成果:
- 在各种条件下,TCN在联合动量估计中实现了较低的平均根平均平方误差 (0.142Nm/kg).
- 统一控制器显著降低了用户在行走时的代谢成本.
- 在外骨架的帮助下,下肢积极工作显著下降.
- 该系统在不需要用户特定校准的情况下展示了有效的性能.
结论:
- 开发的统一控制框架和基于TCN的估计提供了适应性外骨架辅助的强大解决方案.
- 这项技术显著提高了用户的移动性,减少了体力劳动,弥合了实验室研究和实际应用之间的差距.
- 这些发现表明,这种方法可以使先进的外骨控制成为更广泛的用户社区的可行性.
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