Abstract
The convergence of low-altitude economies, embodied intelligence, and air-ground cooperative systems creates growing demand for simulation infrastructure capable of jointly modeling aerial and ground agents within a single physically coherent environment. Existing open-source platforms remain domain-segregated: driving simulators lack aerial dynamics, while multirotor simulators lack realistic ground scenes. Bridge-based co-simulation introduces synchronization overhead and cannot guarantee strict spatial-temporal consistency. We present CARLA-Air, an open-source infrastructure that unifies high-fidelity urban driving and physics-accurate multirotor flight within a single Unreal Engine process. The platform preserves both CARLA and AirSim native Python APIs and ROS 2 interfaces, enabling zero-modification code reuse. Within a shared physics tick and rendering pipeline, CARLA-Air delivers photorealistic environments with rule-compliant traffic, socially-aware pedestrians, and aerodynamically consistent UAV dynamics, synchronously capturing up to 18 sensor modalities across all platforms at each tick. The platform supports representative air-ground embodied intelligence workloads spanning cooperation, embodied navigation and vision-language action, multi-modal perception and dataset construction, and reinforcement-learning-based policy training. An extensible asset pipeline allows integration of custom robot platforms into the shared world. By inheriting AirSim's aerial capabilities -- whose upstream development has been archived -- CARLA-Air ensures this widely adopted flight stack continues to evolve within a modern infrastructure. Released with prebuilt binaries and full source: this https URL
Abstract (translated)
低空经济、具身智能与空地协同系统的融合，催生了对能够在单一物理一致环境中联合建模空中与地面智能体的仿真基础设施的日益增长需求。现有开源平台仍存在领域割裂：驾驶模拟器缺乏空中动力学，而多旋翼模拟器则缺乏真实地面场景。基于桥接的联合仿真会引入同步开销，且无法保证严格时空一致性。本文提出CARLA-Air，这是一个开源基础设施，可在单一Unreal Engine进程中统一高保真度城市驾驶与物理精确的多旋翼飞行。该平台保留了CARLA与AirSim的原生Python API及ROS 2接口，实现零修改代码复用。在共享物理 ticking 与渲染管线中，CARLA-Air提供符合交通规则的真实感环境、具备社会意识的行人模拟以及空气动力学一致的无人机动力学，每帧同步捕捉所有平台最多18种传感器模态。平台支持代表性的空地具身智能工作负载，涵盖协同、具身导航与视觉-语言动作、多模态感知与数据集构建，以及基于强化学习的策略训练。可扩展的资源管线支持将自定义机器人平台集成至共享世界。通过继承AirSim的空中能力（其上游开发已归档），CARLA-Air确保这一广泛采用的飞行栈能在现代基础设施中持续演进。发布包含预编译二进制文件及完整源代码：此https链接
URL
https://arxiv.org/abs/2603.28032
