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

arXiv cs.AI / 4/1/2026

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Key Points

The paper studies the double-deck multi-agent pickup and delivery (DD-MAPD) problem for multi-robot warehouse shelf rearrangement and frames it around collision-free planning plus execution.
It critiques the MAPF-DECOMP approach, arguing that strict trajectory dependencies can cause poor execution quality such as idle time and unnecessary shelf switching.
It introduces CREST, an execution framework that proactively releases trajectory constraints during execution to enable more continuous shelf carrying.
Experiments across diverse warehouse layouts show CREST improves execution metrics—reducing agent travel, makespan, and shelf switching by up to 40.5%, 33.3%, and 44.4%, respectively, with larger gains when lift/place overhead is higher.
The authors provide code and data publicly via the linked GitHub repository, supporting replication and further evaluation.

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.