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.

翻译：持续无间断的探索在搜救和精准农业等场景中至关重要，这些场景需要持续存在以检测大面积区域的事件。遍历搜索已在这些场景中推导出连续轨迹，从而使机器人在信息密度高的区域花费更多时间。然而，现有的遍历搜索文献未考虑机器人的能量约束，限制了机器人能够探索的时长。事实上，如果机器人由电池供电，单次充电后物理上无法实现持续探索。本文应对这一挑战，将遍历搜索方法与能量感知覆盖相结合。我们权衡电池使用与覆盖质量，通过至少一个智能体维持无间断探索。我们的方法为未来荷电状态估计推导出一个抽象电池模型，并将经典遍历搜索扩展为电池约束下的遍历搜索。仿真和真实世界实验的经验数据证明了我们能量感知遍历搜索的有效性，该搜索能够确保持续探索并保证空间覆盖。