3-D Active Sensing in Time-Critical Urban Search and Rescue Missions
Bibliographic record
Abstract
Mobile robots are currently being developed to help rescue workers in urban disaster environments to search for survivors. Our research focuses on developing robust 3-D sensors that can be used in robotic rescue missions to map these unknown cluttered environments and determine the locations of victims. This paper presents the development of a new active 3-D sensory system for robotic search and rescue in unknown cluttered urban disaster environments. The sensory system can provide high resolution 2-D and 3-D information of a cluttered scene that can be used by a robot operator for real-time viewing as well as to develop a 3-D map of the disaster scene. The main advantage of the proposed sensory system is its robustness to cluttered, and dark and dimly lit environments found in disaster areas. Experimental results are presented to verify the performance of the sensory system in obtaining 3-D sensory information of rubble piles in Urban Search and Rescue like environments as well as the potential use of the sensor for 3-D mapping applications in these unknown environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".