OASIS: Real-Time Opti-Acoustic Sensing for Intervention Systems in Unstructured Environments
High resolution underwater 3D scene reconstruction is crucial for various applications, including construction, infrastructure maintenance, monitoring, exploration, and scientific investigation. Prior work has leveraged the complementary sensing modalities of imaging sonars and optical cameras for opti-acoustic 3D scene reconstruction, demonstrating improved results over methods which rely solely on either sensor. However, while most existing approaches focus on offline reconstruction, real-time spatial awareness is essential for both autonomous and piloted underwater vehicle operations. This paper presents OASIS, an opti-acoustic fusion method that integrates data from optical images with voxel carving techniques to achieve real-time 3D reconstruction unstructured underwater workspaces. Our approach utilizes an "eye-in-hand" configuration, which leverages the dexterity of robotic manipulator arms to capture multiple workspace views across a short baseline. We validate OASIS through tank-based experiments and present qualitative and quantitative results that highlight its utility for underwater manipulation tasks.
Code (0)
등록된 구현이 없습니다.
Tasks
3D ReconstructionSimilar Papers 제목 키워드 기반
OASIS: Automated Assessment of Urban Pedestrian Paths at Scale
The inspection of the Public Right of Way (PROW) for accessibility barriers is necessary for monitoring and maintaining the built environment for communities' walkability, rollability, safety, active transportation, and …
OASIS: Harnessing Diffusion Adversarial Network for Ocean Salinity Imputation using Sparse Drifter Trajectories
Ocean salinity plays a vital role in circulation, climate, and marine ecosystems, yet its measurement is often sparse, irregular, and noisy, especially in drifter-based datasets. Traditional approaches, such as remote se…
oASIS: Adaptive Column Sampling for Kernel Matrix Approximation
Kernel matrices (e.g. Gram or similarity matrices) are essential for many state-of-the-art approaches to classification, clustering, and dimensionality reduction. For large datasets, the cost of forming and factoring suc…
ClusteringDimensionality ReductionGeneral ClassificationBenchmarking Machine Learning Methods for Distributed Acoustic Sensing
Distributed acoustic sensing (DAS) technology represents an innovative fiber-optic-based sensing methodology that enables real-time acoustic signal monitoring through the detection of minute perturbations along optical f…
BenchmarkingData Augmentationenergy managementCross-Modal Virtual Sensing for Combustion Instability Monitoring
In many cyber-physical systems, imaging can be an important but expensive or 'difficult to deploy' sensing modality. One such example is detecting combustion instability using flame images, where deep learning frameworks…
DecoderTime SeriesTime Series Analysis