Adaptive impedance control with trajectory adaptation for minimizing interaction force

Jing Luo, Chenguang Yang, E. Burdet, Yanan Li
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引用次数: 4

Abstract

In human-robot collaborative transportation and sawing tasks, the human operator physically interacts with the robot and directs the robot’s movement by applying an interaction force. The robot needs to update its control strategy to adapt to the interaction with the human and to minimize the interaction force. To this end, we propose an integrated algorithm of robot’s trajectory adaptation and adaptive impedance control to minimize the interaction force in physical humanrobot interaction (pHRI) and to guarantee the performance of the collaboration tasks. We firstly utilize the information of the interaction force to regulate the robot’s reference trajectory. Then, an adaptive impedance controller is developed to ensure automatic adaptation of the robot’s impedance parameters. While one can reduce the interaction force by using either trajectory adaptation or adaptive impedance control, we investigate the task performance when combining both. Experimental results on a planar robotic platform verify the effectiveness of the proposed method.
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基于轨迹自适应的自适应阻抗控制
在人机协作运输和锯切任务中,人类操作员与机器人进行物理交互,并通过施加相互作用力来指导机器人的运动。机器人需要更新其控制策略以适应与人的交互,并使交互力最小化。为此,我们提出了一种机器人轨迹自适应和自适应阻抗控制的集成算法,以最小化人机物理交互(pHRI)中的相互作用力,保证协作任务的执行。首先利用相互作用力的信息来调节机器人的参考轨迹。然后,设计了自适应阻抗控制器,实现了机器人阻抗参数的自动自适应。虽然可以通过轨迹自适应或自适应阻抗控制来减小相互作用力,但我们研究了两者结合时的任务性能。在平面机器人平台上的实验结果验证了该方法的有效性。
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