Colour-Gradient Redundancy for Real-time Spatial Pose Tracking in Autonomous Robot Navigation
Bibliographic record
Abstract
Mobile-robot interception or rendezvous with a maneuvering target requires the target’s pose to be tracked. This paper presents a novel 6 degree-of-freedom pose tracking algorithm. This algorithm incorporates an initial-pose estimation scheme to initiate tracking, operates in real-time, and, is robust to large motions. Initial-pose estimation is performed using the on-screen position and size of the target to extract 3D position, and, Principal Component Analysis (PCA) to extract orientation. Real-time operation is achieved by using GPU-based filters and a novel data-reduction algorithm. This data reduction algorithm exploits an important property of colour images, namely, that the gradients of all colour channels are generally aligned. A processing rate of approximately 60 to 85 fps was obtained. Multi-scale optical-flow has been adapted for use in the tracker, to increase robustness to larger motions.
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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 | 0.000 | 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 | 0.001 |
| 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 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".