In this paper, a human motion intention estimation-based decentralized robust interaction control method of modular robot manipulators (MRMs) is proposed under the situation of physical human–robot interaction (pHRI). Different from traditional interaction control scheme that depends on the biological signal and centralized control method, the decentralized robust interaction control is implemented that using only position measurements of each joint module in this investigation. Based on the harmonic drive compliance model, a novel torque-sensorless human motion intention estimation method is developed, which utilizes only the information of local dynamic position measurements. On this basis, the decentralized robust interaction control scheme is presented to achieve high performance of position tracking and ensure the security of interaction to create the ’safety’ interaction environment. The uniformly ultimately bounded (UUB) of the tracking error is proved by the Lyapunov theory. Finally, pHRI experiments confirm the effectiveness and advancement of the proposed method.

在本文中，在物理人机交互（pHRI）的情况下，提出了一种基于人体运动意图估计的模块化机器人机械臂（MRM）分散鲁棒交互控制方法。与依赖生物信号和集中控制方法的传统交互控制方案不同，本研究仅使用每个关节模块的位置测量来实现分散鲁棒交互控制。基于谐波驱动顺应性模型，开发了一种新的无扭矩传感器人体运动意图估计方法，该方法仅利用局部动态位置测量信息。以这个为基础，提出分散鲁棒交互控制方案，实现高性能的位置跟踪，保证交互的安全性，营造“安全”的交互环境。Lyapunov理论证明了跟踪误差的统一最终有界（UUB）。最后，pHRI 实验证实了所提出方法的有效性和先进性。