We propose a distributed control law for a heterogeneous multi-robot coverage problem, where the robots could have different energy characteristics, such as capacity and depletion rates, due to their varying sizes, speeds, capabilities, and payloads. Existing energy-aware coverage control laws consider capacity differences but assume the battery depletion rate to be the same for all robots. In realistic scenarios, however, some robots can consume energy much faster than other robots; for instance, UAVs hover at different altitudes, and these changes could be dynamically updated based on their assigned tasks. Robots' energy capacities and depletion rates need to be considered to maximize the performance of a multi-robot system. To this end, we propose a new energy-aware controller based on Lloyd's algorithm to adapt the weights of the robots based on their energy dynamics and divide the area of interest among the robots accordingly. The controller is theoretically analyzed and extensively evaluated through simulations and real-world demonstrations in multiple realistic scenarios and compared with three baseline control laws to validate its performance and efficacy.

翻译：本文针对异构多机器人覆盖问题提出了一种分布式控制律，其中机器人可能因尺寸、速度、能力和有效载荷的不同而具有不同的能量特性，如电池容量和能耗速率。现有的能量感知覆盖控制律考虑了容量差异，但假设所有机器人的电池能耗速率相同。然而在实际场景中，某些机器人的能量消耗可能远快于其他机器人；例如，无人机在不同高度悬停，这些变化可根据其分配的任务动态更新。为最大化多机器人系统的性能，必须同时考虑机器人的能量容量与能耗速率。为此，我们基于劳埃德算法提出了一种新型能量感知控制器，该控制器根据机器人的能量动态调整其权重，并据此将目标区域分配给各机器人。我们通过理论分析、多场景仿真及实物验证对该控制器进行了全面评估，并与三种基线控制律进行了性能比较，结果证实了该控制器的有效性与优越性。