Path planning and smoothing of mobile robot based on improved artificial fish swarm algorithm

Fei-Fei Li,Ke-Jin Jia,Yun Du

doi:10.1038/s41598-021-04506-y

Fei-Fei Li, Ke-Jin Jia + Show 1 more

Open Access

https://doi.org/10.1038/s41598-021-04506-y

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Journal: Scientific Reports	Publication Date: Jan 13, 2022
Citations: 43	License type: open-access

Affiliation: Hebei University of Science and Technology

Abstract

An algorithm that integrates the improved artificial fish swarm algorithm with continuous segmented Bézier curves is proposed, aiming at the path planning and smoothing of mobile robots. On the one hand, to overcome the low accuracy problems, more inflection points and relatively long planning paths in the traditional artificial fish swarm algorithm for path planning, feasible solutions and a range of step sizes are introduced based on Dijkstra's algorithm. To solve the problems of poor convergence and degradation that hinder the algorithm's ability to find the best in the later stage, a dynamic feedback horizon and an adaptive step size are introduced. On the other hand, to ensure that the planned paths are continuous in both orientation and curvature, the Bessel curve theory is introduced to smooth the planned paths. This is demonstrated through a simulation that shows the improved artificial fish swarm algorithm achieving 100% planning accuracy, while ensuring the shortest average path in the same grid environment. Additionally, the smoothed path is continuous in both orientation and curvature, which satisfies the kinematic characteristics of the mobile robot.

Highlights

An algorithm that integrates the improved artificial fish swarm algorithm with continuous segmented Bézier curves is proposed, aiming at the path planning and smoothing of mobile robots
A large number of algorithms have been available for path planning of mobile robots, such as the ant colony algorithm2, particle swarm algorithm3, A* algorithm4, artificial potential field algorithm5, genetic algorithm6, neural network algorithm7 and rapid exploration random tree (RRT)8
To overcome the problem that the global optimal solution and the local optimal solution interfere with each other, the feasible solution is introduced and the optimal path is found in the feasible solution, improving the planning accuracy and ensuring the shortest planning path

Summary

Introduction

An algorithm that integrates the improved artificial fish swarm algorithm with continuous segmented Bézier curves is proposed, aiming at the path planning and smoothing of mobile robots. The improved artificial fish swarm algorithm shows that the path points are (start, Pi, Pi+1, Pi+2, Pi+3, goal) and that the path points after the path passing collinear optimization are (start, Pi+1, goal) , which satisfies the conditions of continuous third order Bezier curve.

Results

Conclusion