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人类-外骨相互作用肖像图
Mohammad Shushtari1, Julia Foellmer2, Arash Arami3,4
1Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.
Journal of neuroengineering and rehabilitation
|September 5, 2024
概括
本研究引入了交互肖像 (IP) 来分析下肢外骨架中人机器人共同适应. IP揭示了混合扭矩控制器 (HTC) 和基于自适应模型的扭矩控制器 (AMTC) 的不同策略,改善了用户-外骨协调.
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
- 人与计算机的交互
背景情况:
- 在人机物理交互中,优化用户体验和机器人性能至关重要.
- 在可穿戴机器人中评估用户适应和共同适应,如下肢外骨架,需要先进的分析方法.
- 仅仅对肌肉活动和相互作用扭矩的传统分析可能无法完全捕捉到复杂的人机器人协同适应动态.
研究的目的:
- 引入一种新的方法,即交互肖像 (IP),用于评估下肢外骨中人机交互和共同适应.
- 为了比较混合扭矩控制器 (HTC) 和基于适应模型的新型扭矩控制器 (AMTC) 与基于时间的控制器 (TBC) 所产生的协同适应策略.
- 为了证明知识产权分析在比较和设计控制器中所具有的潜力,以便在可穿戴机器人中优化人机交互.
主要方法:
- 肌肉活动和相互作用扭矩被分析为一个二维随机变量.
- 介绍了交互肖像 (IP),可视化这个变量的分布在极坐标.
- 应用IP来比较HTC,AMTC和TBC在跑步机上以不同的速度行走时,评估正常化氧气吸收.
主要成果:
- 与TBC相比,HTC和AMTC都显著降低了用户的正常化氧气吸收,这表明用户-外骨协调得到了改善.
- 知识产权分析发现了两种不同的协同适应策略:HTC促进了对外骨的收益控制,而AMTC鼓励了使用减少交互扭矩的用户参与.
- IP阶段的演变为个人用户交互策略形成提供了洞察力.
结论:
- 互动肖像 (IP) 为理解和量化下肢外骨中人机器人共同适应提供了一种新的方法.
- 不同的控制器引发不同的协同适应策略,由于用户参与度提高,AMTC显示出对康复和步行训练应用的希望.
- 知识产权分析有可能显著推进可穿戴机器人的控制器的设计和优化.
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