English

SkyRover: A Modular Simulator for Cross-Domain Pathfinding

Robotics 2025-02-14 v1 Artificial Intelligence Machine Learning Multiagent Systems

Abstract

Unmanned Aerial Vehicles (UAVs) and Automated Guided Vehicles (AGVs) increasingly collaborate in logistics, surveillance, inspection tasks and etc. However, existing simulators often focus on a single domain, limiting cross-domain study. This paper presents the SkyRover, a modular simulator for UAV-AGV multi-agent pathfinding (MAPF). SkyRover supports realistic agent dynamics, configurable 3D environments, and convenient APIs for external solvers and learning methods. By unifying ground and aerial operations, it facilitates cross-domain algorithm design, testing, and benchmarking. Experiments highlight SkyRover's capacity for efficient pathfinding and high-fidelity simulations in UAV-AGV coordination. Project is available at https://sites.google.com/view/mapf3d/home.

Keywords

Cite

@article{arxiv.2502.08969,
  title  = {SkyRover: A Modular Simulator for Cross-Domain Pathfinding},
  author = {Wenhui Ma and Wenhao Li and Bo Jin and Changhong Lu and Xiangfeng Wang},
  journal= {arXiv preprint arXiv:2502.08969},
  year   = {2025}
}

Comments

9 pages

R2 v1 2026-06-28T21:42:34.956Z