Mobile Recharger Path Planning and Recharge Scheduling in a Multi-Robot Environment
This addresses the challenge of maintaining efficiency in battery-powered multi-robot systems, but it is incremental as it builds on existing SMT-based approaches with specific optimizations.
The paper tackles the problem of planning paths and scheduling recharges for mobile recharger robots to supply energy to worker robots in a multi-robot environment, resulting in minimized total waiting time for worker robots and energy-efficient trajectories for rechargers, with comparisons showing efficacy against other methods.
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.