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arXiv Machine Learning By Matteo El Hariry, Pedro Lima, Andrej Orsula, Matthieu Geist, Miguel Olivares-Mendez

FALCON-S: Fixed-wing ground-effect Aerodynamics Simulator and Flight Control Learning Suite

Read the original on arXiv Machine Learning →

FALCON‑S is a modular, high‑fidelity simulator designed for fixed‑wing aerial robots operating near the ground. It models full 6DoF rigid‑body physics, semi‑empirical ground‑effect aerodynamics, actuator dynamics, sensor noise, and environmental disturbances, and supports both CPU and GPU backends via Torch and NVIDIA Warp for large‑scale reinforcement learning and optimal control. The framework offers a unified interface for various controllers, including RL and optical control algorithms, and allows cross‑validation with X‑Plane and JSBSim for engineering integration and visual fidelity.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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