An electromyogram based force control coordinated in assistive interaction

T. Noda, J. Furukawa, T. Teramae, S. Hyon, J. Morimoto
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引用次数: 25

Abstract

This study proposes the design of electromyography (EMG)-based force feedback controller which explicitly considers human-robot interaction for the exoskeletal assistive robot. Conventional approaches have been only consider one-directional mapping from EMG to control input for assistive robot control. However, EMG and force generated by the assistive robot interfere each other, e.g., amplitude of EMG decreases if limb movements are assisted by the robot. In our proposed method, we first derive the nonlinear mapping from EMG signal to muscle force for estimating human joint torque, and convert it to assistive force using human musculoskeletal model and robot kinematic model. Additionally the feedforward interaction torque is feedback into torque controller to acquire the necessity loads. To validate the feasibility of the proposed method, assistive One-DOF system was developed as the real equipment and the simulator. We compared the proposed method with conventional approaches using both the simulated and the real One-DOF systems. As the result, we found that the proposed model was able to estimate the necessary torque adequately to achieve stable human-robot interaction.
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基于肌电图的力控制在辅助交互中的协调
针对外骨骼辅助机器人,提出了一种明确考虑人机交互的基于肌电图的力反馈控制器设计。传统的辅助机器人控制方法只考虑从肌电图到控制输入的单向映射。然而,肌电图与辅助机器人产生的力是相互干扰的,例如,当机器人辅助肢体运动时,肌电图的振幅会减小。在该方法中,我们首先导出肌电信号到肌肉力的非线性映射,用于估计人体关节扭矩,并利用人体肌肉骨骼模型和机器人运动学模型将其转换为辅助力。并将前馈相互作用转矩反馈到转矩控制器中,以获得所需的负载。为了验证该方法的可行性,开发了辅助单自由度系统作为真实设备和模拟器。在仿真和实际的单自由度系统中,将该方法与传统方法进行了比较。结果表明,所提出的模型能够充分估计所需的扭矩,以实现稳定的人机交互。
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