Open Access

ARTICLE

Intermediary RRT*-PSO: A Multi-Directional Hybrid Fast Convergence Sampling-Based Path Planning Algorithm

Loc Q. Huynh¹, Ly V. Tran¹, Phuc N. K. Phan¹, Zhiqiu Yu², Son V. T. Dao^1,2,*

1 School of Industrial Engineering and Management, International University, Vietnam National University HCMC, Ho Chi Minh City, 700000, Vietnam
2 Department of Industrial Management, National Taiwan University of Science and Technology, Taipei City, 106335, Taiwan

* Corresponding Authors: Son V. T. Dao. Email: ,

Computers, Materials & Continua 2023, 76(2), 2281-2300. https://doi.org/10.32604/cmc.2023.034872

Received 30 July 2022; Accepted 06 January 2023; Issue published 30 August 2023

Abstract

Path planning is a prevalent process that helps mobile robots find the most efficient pathway from the starting position to the goal position to avoid collisions with obstacles. In this paper, we propose a novel path planning algorithm–Intermediary RRT*-PSO-by utilizing the exploring speed advantages of Rapidly exploring Random Trees and using its solution to feed to a metaheuristic-based optimizer, Particle swarm optimization (PSO), for fine-tuning and enhancement. In Phase 1, the start and goal trees are initialized at the starting and goal positions, respectively, and the intermediary tree is initialized at a random unexplored region of the search space. The trees were grown until one met the other and then merged and re-initialized in other unexplored regions. If the start and goal trees merge, the first solution is found and passed through a minimization process to reduce unnecessary nodes. Phase 2 begins by feeding the minimized solution from Phase 1 as the global best particle of PSO to optimize the path. After simulating two special benchmark configurations and six practice configurations with special cases, the results of the study concluded that the proposed method is capable of handling small to large, simple to complex continuous environments, whereas it was very tedious for the previous method to achieve.

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Keywords

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