エネルギー制約下でのマルチエージェント巡回探索：バッテリーを考慮した連続探索
Energy-Aware Ergodic Search: Continuous Exploration for Multi-Agent Systems with Battery Constraints
エルゴディック探索とエネルギー管理を統合し、バッテリー残量を予測しながら複数ロボットが途切れなく探索を続ける手法を提案した。
著者: Adam Seewald, Cameron J. Lerch, Marvin Chancán, Aaron M. Dollar, Ian Abraham
分類: cs.RO
原文アブストラクト
Continuous exploration without interruption is important in scenarios such as search and rescue and precision agriculture, where consistent presence is needed to detect events over large areas. Ergodic search already derives continuous trajectories in these scenarios so that a robot spends more time in areas with high information density. However, existing literature on ergodic search does not consider the robot's energy constraints, limiting how long a robot can explore. In fact, if the robots are battery-powered, it is physically not possible to continuously explore on a single battery charge. Our paper tackles this challenge, integrating ergodic search methods with energy-aware coverage. We trade off battery usage and coverage quality, maintaining uninterrupted exploration by at least one agent. Our approach derives an abstract battery model for future state-of-charge estimation and extends canonical ergodic search to ergodic search under battery constraints. Empirical data from simulations and real-world experiments demonstrate the effectiveness of our energy-aware ergodic search, which ensures continuous exploration and guarantees spatial coverage.
