AirSimAG: A High-Fidelity Simulation Platform for Air-Ground Collaborative Robotics

Abstract

As spatial intelligence continues to evolve, heterogeneous multi-agent systems-particularly the collaboration between Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs), have demonstrated strong potential in complex applications such as search and rescue, urban surveillance, and environmental monitoring. However, existing simulation platforms are primarily designed for single-agent dynamics and lack dedicated frameworks for interactive air-ground collaborative simulation. In this paper, we present AirsimAG, a high-fidelity air-ground collaborative simulation platform built upon an extensively customized AirSim framework. The platform enables synchronized multi-agent simulation and supports heterogeneous sensing and control interfaces for UAV-UGV systems. To demonstrate its capabilities, we design a set of representative air-ground collaborative tasks, including mapping, planning, tracking, formation, and exploration. We further provide quantitative analyses based on these tasks to illustrate the platform effectiveness in supporting multi-agent coordination and cross-modal data consistency. The AirsimAG simulation platform is publicly available at https://github.com/BIULab-BUAA/AirSimAG.

Figures (9)

• Figure 2: Overall system architecture of AirSimAG.
• Figure 3: Different Maps
• Figure 4: Air–ground collaborative mapping. (a) Mapping scene. (b) Fused point cloud map: UAV points in blue, UGV points in green. (c) UAV and UGV trajectories during the mapping task.
• Figure 5: Air–ground collaborative planning. (a) UGV planned path from UAV’s first-person view. (b) UGV first-person view during planning. (c) Executed UGV trajectory.
• Figure 6: Air–ground collaborative tracking. (a) Tracking trajectories and map. (b) Unreal Engine scene showing the third-person view, UAV first-person view, and UGV first-person view.