GMC-Pos: グラフベースのマルチロボットカバレッジ配置手法
GMC-Pos: Graph-Based Multi-Robot Coverage Positioning Method
人間と複数ロボットが協調して環境をカバーするため、環境を重み付きグラフで表現し、グラフ距離と次数に基づいてロボットの戦略的な配置を決定する手法を提案。
著者: Khattiya Pongsirijinda, Zhiqiang Cao, Muhammad Shalihan, Benny Kai Kiat Ng, Billy Pik Lik Lau, Chau Yuen, U-Xuan Tan
分類: cs.RO
原文アブストラクト
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.
