From Multi-Fisheye Sensing to Panoramic Perception: A Parallax-Aware Onboard Platform for Ultra-Low-Altitude UAVs

• URL: http://arxiv.org/abs/2609.02319v2
• Date: Sat, 05 Sep 2026 14:28:53 GMT
• Title: From Multi-Fisheye Sensing to Panoramic Perception: A Parallax-Aware Onboard Platform for Ultra-Low-Altitude UAVs
• Abstract summary: Ultra-low-altitude unmanned aerial vehicles (UAVs) require surround vision near buildings, vegetation, and other obstacles.<n>We present a parallax-aware onboard platform that converts four synchronized fisheye streams into an open 1280x640rectangular panorama (ERP) interface.
• Score: 9.663036325597135
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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. Ours adds content-adaptive seam search and a validation-gated residual mesh and is evaluated under a sensor-rate deployment configuration. Evaluation uses more than 50,000 four-view groups from 18 field sequences. Relative to Fixed Depth, Ours reduces far-field P90 feature misalignment by 41.6% and achieves the lowest aggregate geometric errors across held-out sites. At a paced 20 Hz input rate, Ours sustains 19.99 frames/s at 13.29 W 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. Source code is available at https://github.com/DUNDAI1998/parallax-aware-uav-panorama.git.

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