Research on obstacle avoidance of indoor robot based on predictive control algorithm

This paper studies a predictive control algorithm to solve the obstacle avoidance problem of robot indoors. Firstly, the Kalman filter algorithm [1–3] is used to predict the position of the obstacle, and the coordinates of the obstacle in the robot camera are obtained by the vision algorithm, which is used as the initial state vector of the Kalman filter [4]. Then, assuming that the obstacle obeys the uniform velocity model, the predicted position of the obstacle is output through the updated prediction of the Kalman filter. Secondly, the adaptive fuzzy PID algorithm [5] is used to accurately control the movement speed [6–8] of the robot when it obtains the coordinates of the obstacles, so that it can pass faster without touching the obstacles. Finally, the feasibility of the algorithm is verified by simulation experiments, and the goal of robot Safe Obstacle Avoidance in the indoor environment with obstacles is achieved.