多机器人环境下移动充电器路径规划与充电调度
Mobile Recharger Path Planning and Recharge Scheduling in a Multi-Robot Environment
摘要：
在许多多机器人应用中，移动工作机器人通常通过遵循预先计算的轨迹来重复地执行某些任务。由于这些机器人是电池供电的，它们需要定期充电。我们设想在未来，一些移动充电机器人将被用来提供充电的能量不足的工人机器人，以保持系统的整体效率优化。在这个设置中，我们需要找到的时刻和地点的工作机器人和充电机器人的会议最佳。我们提出了一种基于可满足性模理论（SMT）的方法，该方法以足够长的有限长度时间窗口（超循环）中的约束形式捕获机器人的活动，其重复提供其永久行为。我们的SMT编码确保了对于所选长度的超循环，工人机器人由于电荷约束的总等待时间在一定条件下最小化，并且在条件不成立时接近最优。此外，充电机器人遵循最节能的轨迹。我们通过将其与基于SMT的方法的另一种变体进行比较来显示我们的方法的有效性，该方法不可扩展，但提供了全局最佳解决方案，并且具有贪心算法。
英文摘要：
In many multi-robot applications, mobile worker robots are often engaged in performing some tasks repetitively by following pre-computed trajectories. As these robots are battery-powered, they need to get recharged at regular intervals. We envision that in the future, a few mobile recharger robots will be employed to supply charge to the energy-deficient worker robots recurrently, to keep the overall efficiency of the system optimized.In this setup, we need to find the time instants and locations for the meeting of the worker robots and recharger robots optimally. We present a Satisfiability Modulo Theory (SMT)-based approach that captures the activities of the robots in the form of constraints in a sufficiently long finite-length time window (hypercycle) whose repetitions provide their perpetual behavior. Our SMT encoding ensures that for a chosen length of the hypercycle, the total waiting time of the worker robots due to charge constraints is minimized under certain condition, and close to optimal when the condition does not hold. Moreover, the recharger robots follow the most energy-efficient trajectories. We show the efficacy of our approach by comparing it with another variant of the SMT-based method which is not scalable but provides an optimal solution globally, and with a greedy algorithm.
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