Autonomous underwater vehicles (AUVs) assisting human divers must continuously track not only the diver's 3D position but also their full-body orientation. However, vision-based perception is unreliable underwater, and forward-looking sonar -- despite being widely used -- discards the elevation information needed for o...
Eugene Park, Jiwon Lee, Seyoung Kan et al.· 0 citations
Safe underwater exploration requires a robot to understand where surrounding structures are located and which regions are available for motion. Existing vision-based underwater exploration systems commonly obtain this information indirectly by estimating monocular depth, unprojecting the geometry into 3D space, and acc...
T. Dong, Zhen-Qi Wu, Sahasra Kondapalli et al.· 0 citations
Amonocular underwater occupancy model AquaBEV is introduced, a monocular underwater occupancy model that predicts local BEV occupancy from a single RGB image, using paired 3D imaging sonar as geometric supervision during training.
T. Dong, Sheng-Ji Jin, Chen Chen et al.· 1 citation
Robust perception is essential for the deployment of autonomous underwater robots. However, optical cameras become unreliable under poor illumination and backscatter. Forward looking (2D) acoustic sensors remain effective under these conditions, but they measure range and bearing while leaving elevation unresolved, cre...
T. Dong, Zhen-Qiu Wu, Aditya Penumarti et al.· 2 citations
Sonars generate a significant amount of noise. With the advent of new technology capable of producing full 3D point clouds, the noise is amplified in sparse point clouds, making it challenging to recognize features for navigation, recognition, or reconstruction. To address this challenge, we propose using two different...
Aditya Penumarti, Khanh Dong, Zi-Hao Zhang et al.· 2 citations
A Post Fusion Stabilizer (PFS), a lightweight module that operates on intermediate BEV representations of existing detectors and produces a refined feature map for the original detection head that preserves performance while improving robustness under diverse camera and LiDAR corruptions.
T. Dong, Devangi Thakkar, Arman Sargolzaei et al.· arXiv.org· 5 citations
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