Line-of-Sight Based 3D Localization of Parallel Kinematic Mechanisms
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Autonomous robots (manipulators or vehicles) may accumulate significant errors during their long-range motion to a desired position and orientation (pose). These errors, however, can be compensated for by subsequent local, short-range corrective actions to within random noise levels of the system. This paper presents a generic localization method for high-precision parallel kinematic mechanisms (PKMs) in order to allow them to accurately achieve their desired poses. The proposed method employs a novel non-contact spatial sensing technique combined with an iterative posecorrection procedure. The proposed sensing technique is based on the use of multiple spatial lines-of- sights (LOSs) emanating from a single source and ‘hitting’ a planar position sensitive detector (PSD) placed on the PKM’s platform. Using the positional feedback provided by the PSD, the instantaneous actual pose of the platform is accurately estimated. A pose-correction method is subsequently invoked to iteratively guide the platform to its desired location within noise levels. Extensive simulations were carried out to illustrate the effectiveness of the proposed localization method for a spatial PKM being developed in our laboratory.
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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 it