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

TL;DR

AirSimAG is a high-fidelity simulation platform enabling synchronized air-ground multi-agent collaboration, supporting complex tasks like mapping and exploration, and facilitating research in heterogeneous UAV-UGV systems.

Contribution

This paper introduces AirSimAG, a novel simulation platform tailored for interactive air-ground multi-agent systems with customizable sensing and control interfaces.

Findings

Supports complex collaborative tasks like mapping and exploration

Enables synchronized multi-agent simulation with heterogeneous sensing

Demonstrates effectiveness in multi-agent coordination

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.