High-precision task-space sensing and guidance for autonomous robot localization
Bibliographic record
Abstract
This paper addresses the accurate positioning (localization) of a robotic end-effector, undertaking high-precision tasks, by introducing a novel proximity sensing-based point-to-point motion guidance algorithm. The proposed task-space sensing system is only employed at the final stages of motion after the long-range positioning of the end-effector fails to move it to its desired location. Three identical sub-systems that are spatially placed are incorporated into the sensing system, each consisting of a laser emitter, a galvanometer, and a corresponding PSD (position sensitive diode) that is placed directly on the end-effector. The three-step guidance algorithm uses the laser beams and the offsets they produce along the PSDs to guide the end-effector from its actual pose (position and orientation) to its desired pose. The proposed system (sensing and guidance algorithm) was successfully tested via simulation on a three degree-of-freedom (dof) planar parallel manipulator.
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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 | 0.000 |
| 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 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".