A new path planning method of mobile robot based on adaptive dynamic firefly algorithm

Author:

Xu Guanghui12,Zhang Ting-Wei2,Lai Qiang3ORCID,Pan Jian2,Fu Bo2,Zhao Xilin2

Affiliation:

1. Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy, and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China

2. School of Electrical and Electronics Engineering, Hubei University of Technology, Wuhan 430068, China

3. School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330013, China

Abstract

Path planning has always been a hot topic in the field of mobile robot research. At present, the mainstream issues of the mobile robot path planning are combined with the swarm intelligence algorithms. Among them, the firefly algorithm is more typical. The firefly algorithm has the advantages of simple concepts and easy implementation, but it also has the disadvantages of being easily trapped into a local optimal solution, with slow convergence speed and low accuracy. To better combine the path planning of mobile robot with firefly algorithm, this paper studies the optimization firefly algorithm for the path planning of mobile robot. By using the strategies of optimizing the adaptive parameters in the firefly algorithm, an adaptive firefly algorithm is designed to solve the problem that the firefly algorithm is easy to get into the local optimal solution and improves the performance of firefly algorithm. The optimized algorithm with high performance can improve the computing ability and reaction speed of the mobile robot in the path planning. Finally, the theoretical and experimental results have verified the effectiveness and superiority of the proposed algorithm, which can meet the requirements of the mobile robot path planning.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hubei Province

Research Fund for Doctoral Program of Hubei University of Technology

Publisher

World Scientific Pub Co Pte Lt

Subject

Condensed Matter Physics,Statistical and Nonlinear Physics

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