Interaction Force, Impedance and Trajectory Adaptation: By Humans, for Robots
Interaction Force, Impedance and Trajectory Adaptation: By Humans, for Robots
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DOI：
10.1007/978-3-642-28572-1_23
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
E. Burdet;Ganesh Gowrishankar;Chenguang Yang;A. Albu-Schäffer
中科院分区：
文献类型：
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作者：
E. Burdet;Ganesh Gowrishankar;Chenguang Yang;A. Albu-Schäffer
本文开发并分析了一种机器人仿生学习控制器。该控制器能同时自适应参考轨迹、阻抗和前馈力，保持系统稳定性，使系统相互作用力和性能误差加权总和最小。这个控制器的灵感来自于我们对人类运动行为的研究，特别是人类运动控制方法处理典型的工具使用不稳定情况。仿真结果表明，所设计的控制器具有良好的人体运动自适应能力。实现表明，它还可以利用关节扭矩控制机器人和可变阻抗执行器的能力，以最佳地适应与动态环境和人类的交互。
This paper develops and analyses a biomimetic learning controller for robots. This controller can simultaneously adapt reference trajectory, impedance and feedforward force to maintain stability and minimize the weighted summation of interaction force and performance errors. This controller was inspired from our studies of human motor behavior, especially the human motor control approach dealing with unstable situations typical of tool use. Simulations show that the developed controller is a good model of human motor adaptation. Implementations demonstrate that it can also utilise the capabilities of joint torque controlled robots and variable impedance actuators to optimally adapt interaction with dynamic environments and humans.