Optimized Interaction Control for Robot Manipulator Interacting with Flexible Environment

In this article, a novel interactioncontrol is presented to resolve the optimized robot-environment interaction control problems subject to flexible environment with unknown dynamics parameters. A cost function measuring the trajectory tracking error as well as the noninertial interaction force is defined. A complete state-space equation considering the robot desired trajectory, object dynamics and position parameters is also presented to address the optimized robot-environment interaction control problem. The improved Q-learning method is developed as the fundamental of the proposed control to deal with the challenges brought by the unknown environment dynamics and the reference position of the robot desired trajectory. Simulation and experimental studies verify the validity of the presented method.