Energy-Aware Route Planning for a Battery-Constrained Robot with Multiple Charging Depots

TL;DR

This paper introduces an approximation algorithm for energy-aware route planning of battery-constrained robots with multiple charging depots, balancing travel time minimization and energy constraints.

Contribution

It presents a novel $O(\log D)$ approximation algorithm for the problem, along with heuristic improvements and empirical evaluation on TSPLIB instances.

Findings

Algorithm reduces runtime by over 20 times compared to ILP.

Solutions are within 31% of optimal on average.

Effective for large-scale, energy-constrained routing problems.

Abstract

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.