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A PSO-Inspired Multi-Robot Map Exploration Algorithm Using Frontier-Based Strategy
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Author(s): Yi Zhou (University of Technology of Troyes, France & Shanghai Jiao Tong University, China), Kai Xiao (Shanghai Jiao Tong University, China), Yiheng Wang (Shanghai Jiao Tong University, China), Alei Liang (Shanghai Jiao Tong University, China)and Aboul Ella Hassanien (Cairo University, Egypt)
Copyright: 2019
Pages: 14
Source title:
Rapid Automation: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-8060-7.ch017
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Abstract
Map exploration is a fundamental problem in mobile robots. This paper presents a distributed algorithm that coordinates a team of autonomous mobile robots to explore an unknown environment. The proposed strategy is based on frontiers which are the regions on the boundary between open and unexplored space. With this strategy, robots are guided to move constantly to the nearest frontier to reduce the size of unknown region. Based on the Particle Swarm Optimization (PSO) model incorporated in the algorithm, robots are navigated towards remote frontier after exploring the local area. The exploration completes when there is no frontier cell in the environment. The experiments implemented on both simulated and real robot scenarios show that the proposed algorithm is capable of completing the exploration task. Compared to the conventional method of randomly selecting frontier, the proposed algorithm proves its efficiency by the decreased 60% exploration time at least. Additional experimental results show the decreased coverage time when the number of robots increases, which further suggests the validity, efficiency and scalability.
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