Mobile Robot Trajectory Estimation Algorithm Based on Adaptive EKF

Abstract An adaptive control system based on extended Kalman filtering is designed for internal and external interference in real-world track-tracking tasks. First, the performance state of the wheeled robot at work is analyzed, and a kinetic model is developed. Then, the extended Kalman filter is used to achieve the real-time prediction of the external environmental disturbance amount, so as to obtain the error information that needs to be improved, and its error is eliminated. Finally, Lyapunov analysis is used to derive the stability of the improved rear wheel robot system and then confirm the feasibility of the scheme. The simulation verification analysis shows that the trajectory of the wheeled robot can be stably tracked steadily, which proves the feasibility and effectiveness of the proposed algorithm.