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

Fuente: arXiv
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Autori principali: Zang, Chuanlong, Mannucci, Anna, Barz, Isabelle, Schillinger, Philipp, Lier, Florian, Hönig, Wolfgang
Natura: Preprint
Pubblicazione: 2026
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author Zang, Chuanlong
Mannucci, Anna
Barz, Isabelle
Schillinger, Philipp
Lier, Florian
Hönig, Wolfgang
author_facet Zang, Chuanlong
Mannucci, Anna
Barz, Isabelle
Schillinger, Philipp
Lier, Florian
Hönig, Wolfgang
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2603_10858
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle GRACE: A Unified 2D Multi-Robot Path Planning Simulator & Benchmark for Grid, Roadmap, And Continuous Environments
Zang, Chuanlong
Mannucci, Anna
Barz, Isabelle
Schillinger, Philipp
Lier, Florian
Hönig, Wolfgang
Robotics
Artificial Intelligence
Multiagent Systems
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.
title GRACE: A Unified 2D Multi-Robot Path Planning Simulator & Benchmark for Grid, Roadmap, And Continuous Environments
topic Robotics
Artificial Intelligence
Multiagent Systems
url https://arxiv.org/abs/2603.10858