FalconWing: An Open-Source Platform for Ultra-Light Fixed-Wing Aircraft Research
Journal:
arXiv
Published Date:
May 2, 2025
Abstract
We present FalconWing -- an open-source, ultra-lightweight (150 g) fixed-wing
platform for autonomy research. The hardware platform integrates a small
camera, a standard airframe, offboard computation, and radio communication for
manual overrides. We demonstrate FalconWing's capabilities by developing and
deploying a purely vision-based control policy for autonomous landing (without
IMU or motion capture) using a novel real-to-sim-to-real learning approach. Our
learning approach: (1) constructs a photorealistic simulation environment via
3D Gaussian splatting trained on real-world images; (2) identifies nonlinear
dynamics from vision-estimated real-flight data; and (3) trains a multi-modal
Vision Transformer (ViT) policy through simulation-only imitation learning. The
ViT architecture fuses single RGB image with the history of control actions via
self-attention, preserving temporal context while maintaining real-time 20 Hz
inference. When deployed zero-shot on the hardware platform, this policy
achieves an 80% success rate in vision-based autonomous landings. Together with
the hardware specifications, we also open-source the system dynamics, the
software for photorealistic simulator and the learning approach.
