This paper considers energy-aware route planning for a battery-constrained robot operating in environments with multiple recharging depots. The robot has a battery discharge time $D$, and it should visit the recharging depots at most every $D$ time units to not run out of charge. The objective is to minimize robot's travel time while ensuring it visits all task locations in the environment. We present a $O(\log D)$ approximation algorithm for this problem. We also present heuristic improvements to the approximation algorithm and assess its performance on instances from TSPLIB, comparing it to an optimal solution obtained through Integer Linear Programming (ILP). The simulation results demonstrate that, despite a more than $20$-fold reduction in runtime, the proposed algorithm provides solutions that are, on average, within $31\%$ of the ILP solution.

翻译：本文研究了在具有多个充电站的环境中，电池受限机器人的能量感知路径规划问题。机器人的电池放电时间为$D$，为确保电量不耗尽，它必须每$D$时间单位内至少访问一次充电站。目标是最小化机器人的旅行时间，同时确保其访问环境中的所有任务位置。我们针对该问题提出了一种$O(\log D)$近似算法。此外，我们还对近似算法进行了启发式改进，并基于TSPLIB中的实例评估其性能，将其与通过整数线性规划（ILP）获得的最优解进行比较。仿真结果表明，尽管运行时间降低了20倍以上，但所提算法提供的解平均而言与ILP解的差距在31%以内。