A Path Planning Method for Mobile Robots Based on Fuzzy Firefly Algorithms

Introduction: Mobile Robot is a kind of robot system consisting of sensors, remote control operators and automatic control mobile carriers. It is a product of the integrated application of integrated disciplines developed in recent years. In the research of mobile robot-related technology, navigation technology is its core, and path planning is an important link and subject of navigation research. Objective: An improved firefly algorithm is proposed for path planning of Mobile Robots in this paper. Methods: In this paper, an improved firefly algorithm is proposed. Compared with the traditional firefly algorithm, this algorithm has three main improvements: (1) using Sobol sequence to initialize population; (2) adding a dynamic disturbance coefficient to enhance the global search ability of the algorithm; (3) considering the uncertainty of search, the attraction between individuals is strong. Fuzzy control is carried out by setting the membership function. Results: The new algorithm takes advantage of the uniformity of Sobol sequence sampling and starts to optimize in a wider range, which makes the initial path of the algorithm longer, but because the new algorithm introduces the dynamic disturbance coefficient and the fuzzy control strategy, the average running time is shorter. Conclusion: In the simulation experiment of the mobile robot path planning problem, the improved firefly algorithm proposed in this paper is easier to jump out of local optimum than the traditional firefly algorithm and has a more robust search ability. Discussion: It is obvious from the graph that in 100 iterations, the FaFA algorithm takes advantage of the uniformity of Sobol sequence sampling and starts to optimize in a wider range, which makes the initial path of the algorithm longer, but because the FaFA algorithm introduces the dynamic disturbance coefficient and the fuzzy control strategy, it makes the algorithm able.