Trajectory Tracking Control Based on Skinner´s Operant Conditioning

In order to realize the self-learning of robot trajectory tracking, this paper presents an automata model based on Skinner´s conditioning operation (SKCOA). The model consists of states set, actions set, states transition mechanism, probabilities set, orientation function, learning mechanism and entropy of operating behavior, etc. In the simulation experiment, robot learns 3 different trajectories based on SKCOA automata and test it by tracking linear and circular trajectories. The experimental results show that the robot has a certain ability to learn, and can track the trajectory well.