从多鱼眼传感到全景感知：面向超低空无人机的视差感知机载平台

中文摘要 AI 辅助

超低空无人机需要在建筑物、植被和其他障碍物附近实现环绕视觉。我们提出了一种视差感知机载平台，可将四路同步鱼眼相机流转换为开放的1280×640等距柱状投影全景（ERP）界面。特制的碳纤维机身集成了相机、NVIDIA Jetson Orin NX、飞行控制器和全球导航卫星系统（GNSS）接收器。其构建流水线会为每个重叠区域选择投影深度，并结合可控接缝和光度融合；精度配置文件添加了内容自适应接缝搜索和验证门控残差网格，而部署配置文件则保留了边缘门控的逐接缝更新，以实现传感器速率运行。评估使用了来自18个野外序列的超过50000组四路视图。与固定深度相比，精度配置文件将远场P90特征错位减少了41.6%；部署的逐接缝配置文件在保留站点中实现了最低的总几何误差。在20 Hz的回放节奏下，部署配置文件以13.29W的平均模块输入功率维持了19.99帧/秒的帧率。八区域ERP采样达到了90.8%的平均白天视觉地点识别Recall@5。这些结果共同验证了一种集成的机载全景感知架构，该架构将视差感知构建、传感器速率嵌入式执行和可重复使用的下游视觉接口统一起来，适用于超低空无人机。该项目已在该httpsURL开源。

英文摘要

We present an open panoramic aerial robot with four synchronized fisheye cameras integrated into a carbon-fiber airframe and an onboard NVIDIA Jetson Orin NX. The robot outputs calibrated raw views and an equirectangular panorama (ERP; 1280x640 in all experiments). The ERP pipeline uses overlap-specific projection radii, gated local alignment, seam control, and multi-rate state updates, and it runs onboard on the live four-camera stream during flight. The field dataset contains 18 sequences and more than 50,000 synchronized groups from seven sites. On a 60-frame far-field sample, the method reduces the median per-frame AKAZE P90 misalignment by 40.7% compared with Fixed Radius, and with fixed parameters it gives the lowest geometric errors among the tested controls at two held-out sites. Controlled replay on the same NVIDIA Jetson Orin NX measures final-ERP continuity, timing, and module-input power at a 20 Hz input rate. Compared with external stitching software given the same calibrated projection, the onboard pipeline gives final-ERP line continuity no lower than any tested method, while every external configuration measured on the module needs 5.3 to 147 times the input period and 3.8 to 106 times the energy per output. Frozen detection and place-recognition models are used to evaluate the exported images. Code, calibration, reference hardware, and data-access documentation are available in an anonymized repository at https://anonymous.4open.science/r/Open-Pano-Field-CE1F/README.md.

发表机构

• School of Automation Science and Electrical Engineering, Beihang University（北京航空航天大学自动化科学与电气工程学院）
• Tianmushan Laboratory（天目山实验室）

机构由 AI 辅助整理，请以论文原文为准。