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Information 2019, 10(3), 99; https://doi.org/10.3390/info10030099

A Heuristic Elastic Particle Swarm Optimization Algorithm for Robot Path Planning

1
Department of Security, Zhejiang Police Vocational Academy, Hangzhou 310018, China
2
Department of Computer, Zhejiang Sci-Tech University, Hangzhou 310018, China
*
Author to whom correspondence should be addressed.
Received: 29 December 2018 / Revised: 22 February 2019 / Accepted: 26 February 2019 / Published: 6 March 2019
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Abstract

Path planning, as the core of navigation control for mobile robots, has become the focus of research in the field of mobile robots. Various path planning algorithms have been recently proposed. In this paper, in view of the advantages and disadvantages of different path planning algorithms, a heuristic elastic particle swarm algorithm is proposed. Using the path planned by the A* algorithm in a large-scale grid for global guidance, the elastic particle swarm optimization algorithm uses a shrinking operation to determine the globally optimal path formed by locally optimal nodes so that the particles can converge to it rapidly. Furthermore, in the iterative process, the diversity of the particles is ensured by a rebound operation. Computer simulation and real experimental results show that the proposed algorithm not only overcomes the shortcomings of the A* algorithm, which cannot yield the shortest path, but also avoids the problem of failure to converge to the globally optimal path, owing to a lack of heuristic information. Additionally, the proposed algorithm maintains the simplicity and high efficiency of both the algorithms. View Full-Text
Keywords: path planning; PSO algorithm; A* algorithm; elastic strategy path planning; PSO algorithm; A* algorithm; elastic strategy
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Wang, H.; Zhou, Z. A Heuristic Elastic Particle Swarm Optimization Algorithm for Robot Path Planning. Information 2019, 10, 99.

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