用真人参与的仿真框架，测试助行机器人控制策略效果。
A Human-In-The-Loop Simulation Framework for Evaluating Control Strategies in Gait Assistive Robots
- 构建真人参与的仿真系统，真实模拟人机交互
- 自适应控制器比传统PID更少扭曲步态，提升稳定性
- 适合康复机器人研发者与个性化控制算法设计者
随着全球人口老龄化，有效的康复与移动辅助设备将愈发重要。步态辅助机器人是极具前景的解决方案，但为不同损伤类型设计自适应控制器仍面临重大挑战。本文提出一种专为步态辅助机器人设计的人类在环（HITL）仿真框架，应对被动支撑系统带来的独特问题。通过引入真实的物理人机交互（pHRI）模型，实现了对机器人控制策略的量化评估。结果显示，相较于传统PID控制器，速度自适应控制器在保持顺应性、减少步态畸变方面表现更优。我们还将仿真结果与真实世界数据对比，揭示了人类在适应过程中策略差异及其对步态的影响。该研究证明，HITL仿真在开发和优化个性化控制策略方面具有广泛潜力。
原文摘要 · Abstract (English)
As the global population ages, effective rehabilitation and mobility aids will become increasingly critical. Gait assistive robots are promising solutions, but designing adaptable controllers for various impairments poses a significant challenge. This paper presented a Human-In-The-Loop (HITL) simulation framework tailored specifically for gait assistive robots, addressing unique challenges posed by passive support systems. We incorporated a realistic physical human-robot interaction (pHRI) model to enable a quantitative evaluation of robot control strategies, highlighting the performance of a speed-adaptive controller compared to a conventional PID controller in maintaining compliance and reducing gait distortion. We assessed the accuracy of the simulated interactions against that of the real-world data and revealed discrepancies in the adaptation strategies taken by the human and their effect on the human's gait. This work underscored the potential of HITL simulation as a versatile tool for developing and fine-tuning personalized control policies for various users.
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