SkyRover: A Modular Simulator for Cross-Domain Pathfinding
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 8 of its 32 references that are in the map. First posted on arXiv 13 Feb 2025.
Builds on
8 of 32 references.
References · 8
- 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,451
- 2019Multi-Agent Pathfinding: Definitions, Variants, and Benchmarkscited by 199
- 2022Robot Operating System 2: Design, Architecture, and Uses In The Wildcited by 199
- 2021Learning Selective Communication for Multi-Agent Path Findingcited by 32
- 2016Vehicle Routing Problems for Drone Deliverycited by 24
- 2021Iterative Refinement for Real-Time Multi-Robot Path Planningcited by 12
- 2022Graph-Based Multi-Robot Path Finding and Planningcited by 7
- 2024Recent Surge in Public Interest in Transportation: Sentiment Analysis of Baidu Apollo Go Using Weibo Datacited by 2
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Citing papers per year: 2026: 1.
1 paper.