SkyRover: A Modular Simulator for Cross-Domain Pathfinding

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Unmanned Aerial Vehicles (UAVs) and Automated Guided Vehicles (AGVs) increasingly collaborate in logistics, surveillance, inspection tasks, 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. The project is available at https://sites.google.com/view/mapf3d/home.

Original languageEnglish
Title of host publicationProceedings of the 34th International Joint Conference on Artificial Intelligence, IJCAI 2025
EditorsJames Kwok
PublisherInternational Joint Conferences on Artificial Intelligence
Pages11086-11090
Number of pages5
ISBN (Electronic)9781956792065
DOIs
StatePublished - 2025
Event34th Internationa Joint Conference on Artificial Intelligence, IJCAI 2025 - Montreal, Canada
Duration: 16 Aug 202522 Aug 2025

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Conference

Conference34th Internationa Joint Conference on Artificial Intelligence, IJCAI 2025
Country/TerritoryCanada
CityMontreal
Period16/08/2522/08/25

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