FALCON-S: Fixed-wing ground-effect Aerodynamics Simulator and Flight Control Learning Suite
cs.RO, cs.LG, cs.SY, eess.SY
Submitted: 2026-09-05
Updated: 2026-09-05
Comments: Index Terms: Robot Learning, Flight Control, Reinforcement Learning, Autonomous Navigation, Control and Dynamics, Modeling and Simulation, Wind In Ground Vehicles
License: http://creativecommons.org/licenses/by/4.0/
The gist: We present a modular, high-fidelity simulation framework for the development and benchmarking of flight control strategies in fixed-wing aerial robots operating near the ground.
Terminology
Abstract
We present a modular, high-fidelity simulation framework for the development and benchmarking of flight control strategies in fixed-wing aerial robots operating near the ground. Unlike existing simulators that rely on simplified or hover-oriented dynamics, our framework models full 6DoF rigid-body physics, semi-empirical ground-effect aerodynamics, actuator dynamics, sensor noise, and environmental disturbances. This physical realism, combined with modular component design, enables systematic analysis of low-altitude flight behavior under realistic conditions. The simulator supports both CPU and GPU backends via Torch and NVIDIA Warp, enabling high-throughput parallel execution suitable for large-scale reinforcement learning training and optimal control rollouts. A unified interface accommodates a range of controllers (both RL and optical control algorithms) across tasks such as altitude regulation and trajectory tracking. Cross-validation with X-Plane and JSBSim is also supported to facilitate engineering integration and visual fidelity.
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