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arXiv · 2310.11805

GMC-Pos: Graph-Based Multi-Robot Coverage Positioning Method

Khattiya Pongsirijinda·Zhiqiang Cao·Muhammad Shalihan·Benny Kai Kiat Ng·Billy Pik Lik Lau·Chau Yuen·U-Xuan Tan
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Abstract

Nowadays, several real-world tasks require adequate environment coverage for maintaining communication between multiple robots, for example, target search tasks, environmental monitoring, and post-disaster rescues. In this study, we look into a situation where there are a human operator and multiple robots, and we assume that each human or robot covers a certain range of areas. We want them to maximize their area of coverage collectively. Therefore, in this paper, we propose the Graph-Based Multi-Robot Coverage Positioning Method (GMC-Pos) to find strategic positions for robots that maximize the area coverage. Our novel approach consists of two main modules: graph generation and node selection. Firstly, graph generation represents the environment using a weighted connected graph. Then, we present a novel generalized graph-based distance and utilize it together with the graph degrees to be the conditions for node selection in a recursive manner. Our method is deployed in three environments with different settings. The results show that it outperforms the benchmark method by 15.13% to 24.88% regarding the area coverage percentage.

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Khattiya Pongsirijinda, Zhiqiang Cao, Muhammad Shalihan, Benny Kai Kiat Ng, Billy Pik Lik Lau, Chau Yuen, U-Xuan Tan. 2023-10-18. GMC-Pos: Graph-Based Multi-Robot Coverage Positioning Method. https://doi.org/10.1109/robio58561.2023.10354990

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