Underwater environment reconstruction using stereo and inertial data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The underwater environment presents many challenges for robotic sensing including highly variable lighting, the presence of dynamic objects, and the six degree of freedom (6DOF) 3D environment. Yet in spite of these challenges the aquatic environment presents many real and practical applications for robotic sensors. A common requirement of many of these tasks is the need to construct accurate 3D representations of structures in the environment. In order to address this requirement we have developed a stereo vision-inertial sensing device that we have successfully deployed to reconstruct complex 3D structures in both the aquatic and terrestrial domains. The sensor temporally combines 3D information, obtained using stereo vision algorithms with a 3DOF inertial sensor. The resulting point cloud model is then converted to a volumetric representation and a textured polygonal mesh is extracted for later processing. Recently obtained underwater reconstructions of wrecks and coral obtained with the sensor are presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it