SkyRover: A Modular Simulator for Cross-Domain Pathfinding

SkyRover: A Modular Simulator for Cross-Domain Pathfinding

Wenhui Ma, Wenhao Li, Bo Jin, Changhong Lu, Xiangfeng Wang

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
Demo Track. Pages 11086-11090. https://doi.org/10.24963/ijcai.2025/1268

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. We believe the SkyRover fills a key gap in MAPF research. Project is available at https://sites.google.com/view/mapf3d/home.
Keywords:
Agent-based and Multi-agent Systems: MAS: Engineering methods, platforms, languages and tools
Planning and Scheduling: PS: Search in planning and scheduling
Planning and Scheduling: PS: Learning in planning and scheduling
Robotics: ROB: Motion and path planning