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
