From Multi-Fisheye Sensing to Panoramic Perception: A Parallax-Aware Onboard Platform for Ultra-Low-Altitude UAVs
Dun Dai, Ze Lu, Cheng He, Yaowen Wang, Quan Quan
Abstract
Ultra-low-altitude unmanned aerial vehicles (UAVs) require surround vision near buildings, vegetation, and other obstacles. We present a parallax-aware onboard platform that converts four synchronized fisheye streams into an open 1280x640 equirectangular panorama (ERP) interface. A purpose-built carbon-fiber airframe integrates the cameras, NVIDIA Jetson Orin NX, a flight controller, and a global navigation satellite system (GNSS) receiver. The formation pipeline selects projection depth per overlap and combines controlled seams and photometric fusion. Its accuracy profile adds content-adaptive seam search and a validation-gated residual mesh, whereas its deployed profile retains margin-gated Per-seam updates for sensor-rate operation. Evaluation uses more than 50,000 four-view groups from 18 field sequences. Relative to Fixed Depth, the accuracy profile reduces far-field P90 feature misalignment by 41.6%; the deployed Per-seam profile achieves the lowest aggregate geometric errors across held-out sites. Under a paced 20 Hz replay, the deployed profile sustains 19.99 frames/s at 13.29W mean module-input power. Eight-sector ERP sampling reaches 90.8% mean daytime visual-place-recognition Recall@5. Together, these results validate an integrated onboard panoramic-perception architecture that unifies parallax-aware formation, sensor-rate embedded execution, and reusable downstream vision interfaces for ultra-low-altitude UAVs. The project has been open-sourced at https://github.com/DUNDAI1998/parallax-aware-uav-panorama.
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