Flapping-wing aerial vehicles (FWAVs) demonstrate remarkable agility but face substantial autonomy challenges due to their high sensitivity to aerodynamic disturbances and limited sensor payload capacity. Current simulation platforms typically rely on oversimplified laminar flow assumptions and idealized sensor models, failing to capture the complex turbulence patterns and perceptual limitations encountered in real-world operation. This simulation-to-reality discrepancy significantly impedes the development of robust autonomy systems for FWAVs. We introduce FWAV-Sim, a high-fidelity Unity-based simulation framework that integrates: (1) a composite aerodynamic model combining quasi-steady blade-element theory with bluff-body drag effects, (2) spatiotemporally correlated turbulence generation through fractal noise synthesis, and (3) realistic sensor simulation including noisy IMU measurements, LiDAR point clouds, and RGB camera feeds. Our platform enables scalable generation of synchronized datasets containing ground-truth vehicle states, aerodynamic forces, turbulent wind fields, and multi-modal sensor streams. Experimental validation demonstrates that autonomy pipelines (including both controllers and perception systems) developed in FWAV-Sim exhibit significantly improved simulation capability, thereby advancing the outstanding performance in simulation-based development for flapping-wing aerial systems.

翻译：扑翼飞行器（FWAVs）展现出卓越的机动性，但由于其对气动扰动的高度敏感性和有限的传感器载荷能力，面临着巨大的自主性挑战。当前的仿真平台通常依赖过度简化的层流假设和理想化传感器模型，未能捕捉真实运行中遇到的复杂湍流模式和感知限制。这种仿真与现实的差异严重阻碍了FWAVs鲁棒自主系统的发展。我们提出FWAV-Sim，一个基于Unity的高保真仿真框架，集成以下模块：（1）结合准稳态叶素理论与钝体阻力效应的复合气动模型，（2）通过分形噪声合成生成的时空相关湍流场，以及（3）包含噪声IMU测量、激光雷达点云和RGB相机图像的逼真传感器仿真。该平台能够规模化生成包含飞行器真实状态、气动力、湍流风场和多模态传感器数据流的同步数据集。实验验证表明，在FWAV-Sim中开发的自主流水线（包括控制器和感知系统）展现出显著提升的仿真能力，从而推进了基于仿真的扑翼飞行系统卓越性能发展。