Problem
Research questions and friction points this paper is trying to address.
Multi-Agent Pickup and Delivery
Constrained Warehouses
Haven Selection
Dynamic Haven Selection for Multi-Agent Pickup and Delivery in Constrained Warehouses
🤖 AI Summary
为解决多机器人在受限仓库中执行取送任务时的避让问题，提出A-sharp方法，通过动态调整等待位置来优化路径规划。
📝 Abstract
Space-efficient warehouse layouts often contain single-agent-width aisles and dead-end workstations where robots have few places to wait without blocking others. In Multi-Agent Pickup and Delivery (MAPD) on such constrained layouts, robots must accept online pickup-delivery tasks while preserving protected waiting locations called Havens. The Safe HAven Retreat Planner (SHARP) introduced a mechanism that extends each committed task path with a validated retreat to the agent's dedicated initial Haven, but fixed-Haven commitments can send agents toward distant Havens after deliveries. We present A-sharp (Adaptive SHARP), which changes an agent's retreat target at task assignment time. A naive switch can cause two agents to rely on the same waiting location or let another committed path pass through a location that is still occupied or reserved. A-sharp prevents these failures with an availability test for candidate Havens and a pending-release rule that keeps the previous Haven protected until the agent departs. Under explicit Haven-structure and Safe Interval Path Planning (SIPP) assumptions, we prove invariant preservation and finite-release completeness: every task in any finite release sequence is delivered in finite time. Across 72,000 runs on 14,400 paired map-agent-count-rate-seed cases over four maps, both SHARP and A-sharp complete their respective 14,400 runs. For makespan (final delivery time), a prespecified paired comparison with Holm correction over all 138 configurations with more Havens than agents finds A-sharp significantly better in 107 configurations and never significantly worse than SHARP; on the tested tree map, the median reduction is 16.7%.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Dynamic Haven Selection
Multi-Agent Pickup and Delivery
Safe Interval Path Planning
Availability Test
Pending-Release Rule
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