Robot Iterative PD Optimization Control Algorithm and Offline VR Verification - Wenping Jiang, Yijie Sun, Jin Liang, Weidong Du, Jun Min (Forest Chemicals Review, 1970)
Aiming at the problem that many industrial robot control algorithms only stay in theoretical simulation and mathematical model verification, and rarely realize verification in the actual industrial environment, in order to effectively verify the effectiveness and safety of the robot control algorithm in the actual industrial environment, this paper proposes a novel research method that combines industrial robot control algorithms with offline VR simulation verification. First, build the robot kinematics model, and design the iterative PD optimization control algorithm of the robot. According to the error between the actual trajectory and the expected trajectory, the algorithm adjusts the control amount, speed and joint angle of each joint by iteratively optimizing the PD parameters. Experiments show that after continuous iterative optimization, the error between the actual trajectory of the robot end and the expected trajectory is continuously reduced. When the number of iterations reaches 90, the error between the expected trajectory of the robot end and the actual trajectory is reduced to 0.001m. Secondly, the robot terminal trajectory obtained by the algorithm is imported into the offline VR environment of the robot, and the control algorithm is verified by spraying paint on the water pipe as an example. In the offline VR simulation process, the robot did not collide, the position was reachable, and the entire simulation was successfully completed, thus verifying the feasibility of the algorithm in the actual industrial environment.