PP-ST: An Indoor Mobile Robot Path Tracking Algorithm

Aiming at the problems that Pure Pursuit algorithm is too slow to approach the target path and take shortcuts at the corners under long forward-looking distance, and large heading jitter at the corners of the target path under short forward-looking distance, this paper proposes a path tracking algorithm based on Pure Pursuit and Stanley. First, a new nearest point selection strategy is proposed according to the need of algorithm fusion. Then, new algorithm coefficients are designed in order to adapt the algorithm to indoor environment. Finally, a new fusion method is proposed to solve the above problems. In order to verify the effectiveness of the proposed algorithm, it was tested in three different paths and compared with the improved Pure Pursuit algorithm proposed by two other related researchers in 2023. The experimental results show that the proposed fusion algorithm is 62.8% faster than the improved Pure Pursuit algorithm proposed by Macenski et al. in approaching the target path in indoor environment, and the proposed fusion algorithm’s distance error is 40% less than that of the improved Pure Pursuit algorithm proposed by Macenski et al. in indoor environment; the proposed fusion algorithm’s average heading angle error at the corners of the target path is 20.3% less than that of the improved Pure Pursuit algorithm proposed by Wu, Jiangdong et al. in indoor environment, and the proposed fusion algorithm’s maximum heading angle error is 30.9% less than that of the improved Pure Pursuit algorithm proposed by Wu, Jiangdong et al. in indoor environment. Overall, the fusion algorithm is more suitable than the other two algorithms for mobile robot path tracking in indoor environments.