A Full Freedom Pose Measurement Method of Industrial Robot Based on Reinforcement Learning Algorithm

In order to improve the efficiency of robot operation in the field of industrial automation, a full freedom pose measurement method of industrial robot based on reinforcement learning algorithm is proposed. According to the characteristics of two-wheel independent driving industrial robot, the attitude of the robot in three kinds of moving modes in unconstrained space is calculated. The algorithm for measuring the full degree of freedom of industrial robot is given by the multi-agent method of population particle optimization combined with the reinforcement learning algorithm (PSO-QL). The experimental results show that the proposed method has the advantages of low accuracy, high measurement efficiency, high success rate of grabbing and avoiding obstacles and good application effect.