FalconWing: An Open-Source Platform for Ultra-Light Fixed-Wing Aircraft Research

• URL: http://arxiv.org/abs/2505.01383v1
• Date: Fri, 02 May 2025 16:47:05 GMT
• Title: FalconWing: An Open-Source Platform for Ultra-Light Fixed-Wing Aircraft Research
• Authors: Yan Miao, Will Shen, Hang Cui, Sayan Mitra,
• Abstract summary: FalconWing is an open-source, ultra-lightweight (150 g) fixed-wing platform for autonomy research.<n>We develop and deploy a vision-based control policy for autonomous landing using a novel real-to-sim-to-real learning approach.<n>When deployed zero-shot on the hardware platform, this policy achieves an 80% success rate in vision-based autonomous landings.
• Score: 2.823704956886882
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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