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.
A monocular 3D localization framework using a prebuilt, georegistered triangular mesh using a two-dimensional grid indexes the mesh, and a progressive multi-scale strategy loads high-resolution blocks for ray–mesh intersection.
Yan-Xin Sun, Ming-Ming Ma, Lan-Yu Sun et al.· Electronics· 0 citations
This paper experimentally compares three SLAM systems —ORB-SLAM3, RTAB-Map and Cartographer— on RGB-D data in a short-range robotic manipulation setting. Sequences were captured with two Intel RealSense cameras, the D405 and the D435i, mounted on a UR3e robotic arm, which enables repeatable trajectories and reduces the...
Quim Serrats, Edmundo Guerra, Y. Bolea et al.· Jornadas de Automática· 0 citations
Reliable relative localization between aerial and ground robots is a key requirement for tightly coordinated heterogeneous teams. This can be difficult to do using conventional frame-based cameras and fiducial markers because they are sensitive to motion blur, lighting variations, and payload constraints. This paper pr...
Sonar was one of the first sensors with which mobile robots built maps, and in-air sonar keeps working where cameras and lidar fail, in darkness, smoke, dust and next to glass. Classical sonar SLAM, however, relied on geometric features or occupancy grids built from sparse range readings, and both struggle with the spe...
Underwater C-JEPA (cross-view, control-conditioned, context-extended, context-extended), an object-centric multi-view predictive world model for near-field heavy-load underwater ROV salvage is presented.
Yuncong Yang, Jin-Long Li, Yu-Long Xue et al.· 0 citations
The advancement of robotics has expanded applications across various sectors, increasing the need for reliable mapping and navigation in unfamiliar environments. Simultaneous Localization and Mapping (SLAM) enables mobile robots to estimate their position while constructing an environmental map, while RGB-D SLAM combin...
Fahmizal, Priyova Muhammad Rafief, Rico Agustiawan et al.· Applied Sciences· 0 citations
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