3 - Le projet VAHM (Véhicule Autonome pour Handicapés Moteur): la localisation
Bibliographic record
Abstract
This paper describes an autonomous powered wheelchair localization method in the VAHM (Autonomous Vehicle for People with Motor Disabilities) project framework. This project aims at releasing people with heavy motor disabilities from driving wheelchair constraints by bring possibility of autonomous displacements. The wheelchair autonomy requires the achievement of localization procedure which uses the ultrasonic sensors and is split into two functions according to the state of the wheelchair: when stopped or in movement. When stopped the position of the wheelchair is searched by matching of occupancy grids. The global grid describes the environment and the local grid, built from ultrasonic data, represents the free space around the wheelchair. During the movement the ultrasonic measures are used to refine the position of the wheelchair estimated with the odometry. The tests achieved in real conditions show that the two approaches are appropriate for our application. But in dynamic location, the accuracy of the orientation is not good enough, we then give the procedure using the vision developed to improve this accuracy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".