为多机器人长期任务设计最优充电调度方案，减少充电站占用。
The Persistent Robot Charging Problem for Long-Duration Autonomy
- 用整数线性规划建模，优化机器人初始电量分配。
- 相比传统方法，显著降低充电站资源利用率。
- 适合需要长期自主运行的多机器人系统应用。
本文提出一种新方法，旨在为n个异构机器人制定最优充电调度方案，以最小化充电资源消耗。研究构建了基于整数线性规划（ILP）的模型，用于计算各机器人最优初始充电状态（部分电量），从而实现充电站使用最少。该框架进一步推广至在充足充电站条件下最大化服务时间。通过与现有文献中的节俭定价调度算法对比，验证了所提方法的有效性，证明其在多机器人任务规划中，尤其在长时自主（LDA）场景下的潜力，可为机器人及工程系统中的资源优化提供有力工具。
原文摘要 · Abstract (English)
This paper introduces a novel formulation aimed at determining the optimal schedule for recharging a fleet of $n$ heterogeneous robots, with the primary objective of minimizing resource utilization. This study provides a foundational framework applicable to Multi-Robot Mission Planning, particularly in scenarios demanding Long-Duration Autonomy (LDA) or other contexts that necessitate periodic recharging of multiple robots. A novel Integer Linear Programming (ILP) model is proposed to calculate the optimal initial conditions (partial charge) for individual robots, leading to the minimal utilization of charging stations. This formulation was further generalized to maximize the servicing time for robots given adequate charging stations. The efficacy of the proposed formulation is evaluated through a comparative analysis, measuring its performance against the thrift price scheduling algorithm documented in the existing literature. The findings not only validate the effectiveness of the proposed approach but also underscore its potential as a valuable tool in optimizing resource allocation for a range of robotic and engineering applications.
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