mlsanityData to 7 Oct 2026

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

arXiv 2603.28803 ↗First posted 27 Mar 2026cs.RO cs.AI cs.MAcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 15 of its 28 references that are in the map. First posted on arXiv 27 Mar 2026.

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References · 15

  1. 2019Multi-Agent Pathfinding: Definitions, Variants, and Benchmarkscited by 197
  2. 2018Searching with Consistent Prioritization for Multi-Agent Path Findingcited by 80
  3. 2020EECBS: A Bounded-Suboptimal Search for Multi-Agent Path Findingcited by 67
  4. 2017Lifelong Multi-Agent Path Finding for Online Pickup and Delivery Taskscited by 62
  5. 2021Pairwise Symmetry Reasoning for Multi-Agent Path Finding Searchcited by 21
  6. 2016Multi-Agent Path Finding with Delay Probabilitiescited by 17
  7. 2023Improving LaCAM for Scalable Eventually Optimal Multi-Agent Pathfindingcited by 17
  8. 2025Fabrica: Dual-Arm Assembly of General Multi-Part Objects via Integrated Planning and Learningcited by 8
  9. 2020A Feedback Scheme to Reorder a Multi-Agent Execution Schedule by Persistently Optimizing a Switchable Action Dependency Graphcited by 6
  10. 2023Bidirectional Temporal Plan Graph: Enabling Switchable Passing Orders for More Efficient Multi-Agent Path Finding Plan Executioncited by 6
  11. 2024Speedup Techniques for Switchable Temporal Plan Graph Optimizationcited by 6
  12. 2023Double-Deck Multi-Agent Pickup and Delivery: Multi-Robot Rearrangement in Large-Scale Warehousescited by 5
3 more
  1. 2024Large-Scale Multirobot Coverage Path Planning on Grids With Path Deconflictioncited by 5
  2. 2025APEX-MR: Multi-Robot Asynchronous Planning and Execution for Cooperative Assemblycited by 5
  3. 2024MARPF: Multi-Agent and Multi-Rack Path Findingcited by 2

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