CREST: Constraint-Release Execution for Multi-Robot Warehouse Shelf Rearrangement

2026-03-27

AI Summary

This work addresses the inefficiencies in multi-robot warehouse systems caused by strict trajectory dependencies during shelf rearrangement, which often lead to excessive robot idling and frequent shelf handovers. To overcome these limitations, the authors propose a novel execution framework that dynamically relaxes trajectory constraints at runtime, thereby transcending the static dependency assumptions inherent in conventional MAPF-DECOMP approaches. This enables more continuous shelf transportation and more effective task allocation. Experimental results across diverse warehouse layouts demonstrate that the proposed method reduces robot travel distance by up to 40.5%, makespan by up to 33.3%, and shelf handover frequency by up to 44.4% compared to baseline methods, with even greater improvements observed when accounting for the overhead associated with shelf lifting and releasing operations.

Abstract

Double-Deck Multi-Agent Pickup and Delivery (DD-MAPD) models the multi-robot shelf rearrangement problem in automated warehouses. MAPF-DECOMP is a recent framework that first computes collision-free shelf trajectories with a MAPF solver and then assigns agents to execute them. While efficient, it enforces strict trajectory dependencies, often leading to poor execution quality due to idle agents and unnecessary shelf switching. We introduce CREST, a new execution framework that achieves more continuous shelf carrying by proactively releasing trajectory constraints during execution. Experiments on diverse warehouse layouts show that CREST consistently outperforms MAPF-DECOMP, reducing metrics related to agent travel, makespan, and shelf switching by up to 40.5\%, 33.3\%, and 44.4\%, respectively, with even greater benefits under lift/place overhead. These results underscore the importance of execution-aware constraint release for scalable warehouse rearrangement. Code and data are available at https://github.com/ChristinaTan0704/CREST.

Problem

• multi-robot
• warehouse rearrangement
• trajectory dependencies
• shelf switching
• execution efficiency

Innovation

• constraint release
• multi-robot execution
• shelf rearrangement
• warehouse automation
• execution-aware planning