Optimized Impedance Adaptation of Robot Manipulator Interacting With Unknown Environment

In this brief, impedance adaptation is investigated for robots interacting with unknown environments, subject to unknown environment dynamics and position parameters. A cost function that measures the tracking error and interaction force is defined, and a complete state-space function considering the desired trajectory, environment dynamics, and position parameters is presented. The unknown environment dynamics and the unobservable environment position lead to unknown part of the system function as well as the system states in the complete system model. To this end, the output feedback adaptive dynamic programming (OPFB ADP) method is selected to realize the optimized impedance adaptation. Moreover, when considering the environment position/trajectory, the optimal impedance solution is difficult to obtain due to the existence of the arbitrary endpoint. An adaptive dynamic programming algorithm considering the trajectory tracking problem with arbitrary endpoint is proposed to deal with the problem. The convergence speed is accelerated by adding a discount factor. The validity of the proposed method is verified through simulation and experimental studies.