Design of a Dual-generated Adversarial Network for Mechanical Arm Motion Trajectory Control
In order to improve the motion accuracy of the robotic arm and improve its work efficiency, this paper designs a dual generation adversarial network for controlling the trajectory of the robotic arm. Firstly, the structure of the robotic arm is ana-lyzed, and the coordinate system of the robotic arm is established according to the structural characteristics of the robotic arm of the robotic arm. Then, the information such as position vectors and joint velocity of the mechanical arm are combined with the encoder to obtain the bidirectional generative adversarial network, and the network is designed to control the movement trajectory of the me-chanical arm. Finally, control tests are conducted on the motion trajectory of the robotic arm by using the proposed method and the disturbance observer method. The test results showed that the control accuracy of the proposed method is 40.13％ higher than that of the disturbance observer method, and the fluctuations observed during the control of the robotic arm movement using the proposed method are also smaller than the interference observer method control process. It shows that the proposed method can not only control the movement of the robotic arm more accurately, but also stabilize the control process, which helps to improve the working efficien-cy of the robotic arm.
mechanical armmotion trackdual-generated adversarial networkstrajectory control
万方数据
维普
