HIGH-PERFORMANCE MULTI-BODY COLLISION DETECTION FOR THE REAL-TIME CONTROL OF A CTS SYSTEM
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a high performance methodology for the real-time implementation of collision detection on a Captive Trajectory Simulation (CTS) system. The CTS system includes a slow-moving redundant robot manipulator operating inside a wind tunnel environment with transonic conditions. Collisions can occur between robot links or the links and other objects present in the environment. A multi-body dynamic pruning method is proposed based on joint velocity bounds, which can significantly reduce the number of required collision checks without compromising the system’s safety due to its conservative assumptions. A balance is achieved between the accuracy and the speed of computations via the convex subhull subdivision of the objects, which reduces the geometrical details to further decrease the load of computations. Combining the above two strategies results in smaller and more consistent sample times allowing the collision detection to run in real-time as an integral part of a robot with a high speed control loop.
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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 | 0.001 | 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 it