mlsanityData to 14 Oct 2026

GRACE: A Unified 2D Multi-Robot Path Planning Simulator & Benchmark for Grid, Roadmap, And Continuous Environments

arXiv 2603.10858 ↗First posted 11 Mar 2026cs.RO cs.AI cs.MAcited by 0

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Abstract (arXiv)

Advancing Multi-Agent Pathfinding (MAPF) and Multi-Robot Motion Planning (MRMP) requires platforms that enable transparent, reproducible comparisons across modeling choices. Existing tools either scale under simplifying assumptions (grids, homogeneous agents) or offer higher fidelity with less comparable instrumentation. We present GRACE, a unified 2D simulator+benchmark that instantiates the same task at multiple abstraction levels (grid, roadmap, continuous) via explicit, reproducible operators and a common evaluation protocol. Our empirical results on public maps and representative planners enable commensurate comparisons on a shared instance set. Furthermore, we quantify the expected representation-fidelity trade-offs (MRMP solves instances at higher fidelity but lower speed, while grid/roadmap planners scale farther). By consolidating representation, execution, and evaluation, GRACE thereby aims to make cross-representation studies more comparable and provides a means to advance multi-robot planning research and its translation to practice.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 26 of its 56 references that are in the map. First posted on arXiv 11 Mar 2026.

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26 of 56 references.

References · 26

  1. 2019Multi-Agent Pathfinding: Definitions, Variants, and Benchmarkscited by 199
  2. 2018PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learningcited by 90
  3. 2020EECBS: A Bounded-Suboptimal Search for Multi-Agent Path Findingcited by 68
  4. 2023SCRIMP: Scalable Communication for Reinforcement- and Imitation-Learning-Based Multi-Agent Pathfindingcited by 37
  5. 2020Flatland-RL : Multi-Agent Reinforcement Learning on Trainscited by 32
  6. 2021Pairwise Symmetry Reasoning for Multi-Agent Path Finding Searchcited by 21
  7. 2024POGEMA: A Benchmark Platform for Cooperative Multi-Agent Pathfindingcited by 21
  8. 2014Asymptotically Optimal Sampling-based Kinodynamic Planningcited by 17
  9. 2019Representation-Optimal Multi-Robot Motion Planning using Conflict-Based Searchcited by 16
  10. 2019dRRT*: Scalable and Informed Asymptotically-Optimal Multi-Robot Motion Planningcited by 15
  11. 2024Improving Learnt Local MAPF Policies with Heuristic Searchcited by 14
  12. 2018Experimenting with robotic intra-logistics domainscited by 12
14 more
  1. 2022Conflict-based Search for Multi-Robot Motion Planning with Kinodynamic Constraintscited by 10
  2. 2024LNS2+RL: Combining Multi-Agent Reinforcement Learning with Large Neighborhood Search in Multi-Agent Path Findingcited by 7
  3. 2022Quick Multi-Robot Motion Planning by Combining Sampling and Searchcited by 6
  4. 2023db-CBS: Discontinuity-Bounded Conflict-Based Search for Multi-Robot Kinodynamic Motion Planningcited by 5
  5. 2025Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuningcited by 5
  6. 2024Anytime Multi-Agent Path Finding using Operation Parallelism in Large Neighborhood Searchcited by 4
  7. 2024HiMAP: Learning Heuristics-Informed Policies for Large-Scale Multi-Agent Pathfindingcited by 4
  8. 2025Lightweight and Effective Preference Construction in PIBT for Large-Scale Multi-Agent Pathfindingcited by 4
  9. 2020Near-Optimal Multi-Robot Motion Planning with Finite Samplingcited by 2
  10. 2017Path Planning with Kinematic Constraints for Robot Groupscited by 1
  11. 2022Conflict-Based Search for Explainable Multi-Agent Path Findingcited by 1
  12. 2023Clique Analysis and Bypassing in Continuous-Time Conflict-Based Searchcited by 1
  13. 2025CBS with Continuous-Time Revisitcited by 1
  14. 2025SkyRover: A Modular Simulator for Cross-Domain Pathfindingcited by 1

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