An Improved Method of Particle Swarm Optimization for Path Planning of Mobile Robot. (25th May 2020)

• Record Type: Journal Article
• Authors: Li, Xun; Wu, Dandan; He, Jingjing; Bashir, Muhammad; Liping, Ma
• Other Names: García Carlos-Andrés Academic Editor.
• Is Part Of: Journal of control science and engineering. Volume 2020(2020)
• Publication Date: 2020-05-25
• Subjects: Control theory -- Periodicals; 629.831205
• DOI: 10.1155/2020/3857894
• Languages: English
• ISSNs: 1687-5249

Abstract

Abstract : The existing particle swarm optimization (PSO) algorithm has the disadvantages of application limitations and slow convergence speed when solving the problem of mobile robot path planning. This paper proposes an improved PSO integration scheme based on improved details, which integrates uniform distribution, exponential attenuation inertia weight, cubic spline interpolation function, and learning factor of enhanced control. Compared with other standard functions, our improved PSO (IPSO) can achieve better optimal results with less number of iteration steps than the different four path planning algorithms developed in the existing literature. IPSO makes the optimal path length with less than 20 iteration steps and reduces the path length and simulation time by 2.8% and 1.1 seconds, respectively.