The Laser Line Object Detection Method in an Anti-Collision System for Powered Wheelchair
Bibliographic record
Abstract
The residents in long term care facilities with cognitive impairment and mobility disability need an anti-collision system on their powered wheelchairs to prevent them from causing other seniors to fall. Because of the severe consequence of falling, the detection method of the anti-collision system must be very reliable. However, many object detection techniques tend to miss targets that are unfavourably oriented or have certain surface properties. This research evaluated an uncommon method: laser line object detection (LLOD). The LLOD system projects an invisible infrared laser line onto the ground, and reads the resulting image via a camera. By analyzing the laser line in the image, the system can identify whether objects are in the target area. A pilot LLOD system was designed and installed on a powered wheelchair. The results of the evaluation experiments showed that the LLOD system can detect almost all obstacles with different orientations and materials, and produced a high detection rate on favourable flooring surfaces.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".