Fleet-Level Battery-Health-Aware Scheduling for Autonomous Mobile Robots
This work addresses the problem of efficient and durable fleet management for autonomous mobile robots, though it is incremental as it extends existing degradation-aware planning to a multi-robot context.
The paper tackles the problem of scheduling autonomous mobile robot fleets while accounting for battery degradation, extending single-robot methods to a multi-robot setting by jointly optimizing task assignment, charging decisions, and charger access. The result is a hierarchical matheuristic that balances degradation across the fleet, with systematic experiments showing comparisons against three baselines.
Autonomous mobile robot fleets must coordinate task allocation and charging under limited shared resources, yet most battery aware planning methods address only a single robot. This paper extends degradation cost aware task planning to a multi robot setting by jointly optimizing task assignment, service sequencing, optional charging decisions, charging mode selection, and charger access while balancing degradation across the fleet. The formulation relies on reduced form degradation proxies grounded in the empirical battery aging literature, capturing both charging mode dependent wear and idle state of charge dependent aging; the bilinear idle aging term is linearized through a disaggregated piecewise McCormick formulation. Tight big M values derived from instance data strengthen the LP relaxation. To manage scalability, we propose a hierarchical matheuristic in which a fleet level master problem coordinates assignments, routes, and charger usage, while robot level subproblems whose integer part decomposes into trivially small independent partition selection problems compute route conditioned degradation schedules. Systematic experiments compare the proposed method against three baselines: a rule based nearest available dispatcher, an energy aware formulation that enforces battery feasibility without modeling degradation, and a charger unaware formulation that accounts for degradation but ignores shared charger capacity limits.