Path planning algorithm of mobile robot based on combination of fuzzy inference and reinforcement learning

Rongxia Zhang; Shuliang Wei; Yuantao Li; Jixiang Zhang; Changxu Wu; Zengshun Zhao

doi:10.1117/12.2639717

19 October 2022 Path planning algorithm of mobile robot based on combination of fuzzy inference and reinforcement learning

Rongxia Zhang, Shuliang Wei, Yuantao Li, Jixiang Zhang, Changxu Wu, Zengshun Zhao

Author Affiliations +

Proceedings Volume 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering; 122943V (2022) https://doi.org/10.1117/12.2639717
Event: 7th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2022), 2022, Xishuangbanna, China

Abstract

This paper combines fuzzy inference algorithm with the simulated annealing modified Q (λ) learning algorithm to solve the problem of robot who avoids obstacles in unknown environments. The system learns autonomously by itself without supervision or any prior training data. One of the popular methods for path planning algorithm is improved simulated annealing Q (λ)-learning. The fuzzy logic control is utilized to solve the generalization of continuous space. The combination of the two algorithms can solve the generalization of the continuous state space. Another advantage is that it can reach the balance of the exploration and utilization of the action strategy. The Simulation results exhibit the effectiveness of the proposed method compared with the original method.

Citation Download Citation

Rongxia Zhang, Shuliang Wei, Yuantao Li, Jixiang Zhang, Changxu Wu, and Zengshun Zhao "Path planning algorithm of mobile robot based on combination of fuzzy inference and reinforcement learning", Proc. SPIE 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, 122943V (19 October 2022); https://doi.org/10.1117/12.2639717

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