Trajectory Planning and Tracking Control for LED Placement Spray Wax Robot

For the motion system of a LED placement spray wax robot, this paper uses shortest path planning method of optimization theory to plan the robot's motion trajectory. It uses high order polynomial to plan spray wax robot's joint movement. Guided by the determining learning theory, this paper uses radial basis function (RBF) to design an adaptive neural network controller (ANNC). It tracks and controls the motion process of robot to move along the planned trajectory. This ensures the stability and rapidity of robot movement to achieve the purpose of save time and energy. Experiment is conducted using the algorithm designed in this paper, and comparison experiment with PID algorithm is also well done. The experimental results illustrate the effectiveness of the method designed in this paper.