Autonomous 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 coverage 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 by integrating ergodic search methods with energy-aware coverage. We trade off battery usage and coverage quality, maintaining uninterrupted exploration of a given space 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 and uninterrupted exploration and guarantees spatial coverage.

翻译：自主不间断探索在诸如搜索救援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范围区域内的突发状况。遍历搜索已能在上述场景中生成连续覆盖轨迹，使机器人在信息密度高的区域停留更长时间。然而，现有遍历搜索研究未考虑机器人的能量约束，限制了其持续探索的时间。事实上，若机器人采用电池供电，单次充电后无法实现物理层面的连续探索。本文通过将遍历搜索方法与能量感知覆盖策略相融合，解决了这一难题。我们在电池使用效率与覆盖质量之间进行权衡，确保至少有一个智能体能够维持对指定空间的不间断探索。该方法构建了用于未来荷电状态估计的抽象电池模型，并将经典遍历搜索扩展为电池约束下的遍历搜索。仿真与真实世界实验数据表明，我们的能量感知遍历搜索方法能有效保障连续不间断探索，并确保空间覆盖的完整性。