Constrained Optimal Planning to Minimize Battery Degradation of Autonomous Mobile Robots

TL;DR

This paper introduces an optimization framework for autonomous mobile robots that minimizes battery degradation through advanced planning, balancing task efficiency and battery health using linear approximation techniques.

Contribution

It presents a novel linearized optimization approach for joint path planning and battery degradation minimization in AMRs.

Findings

Effective reduction in battery aging demonstrated in case study

Optimized path planning maintains task completion

Linear approximation improves computational efficiency

Abstract

This paper proposes an optimization framework that addresses both cycling degradation and calendar aging of batteries for autonomous mobile robot (AMR) to minimize battery degradation while ensuring task completion. A rectangle method of piecewise linear approximation is employed to linearize the bilinear optimization problem. We conduct a case study to validate the efficiency of the proposed framework in achieving an optimal path planning for AMRs while reducing battery aging.