Real‐time trajectory resolution for a two‐manipulator machining system
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Recent research has considered robotic machining as an alternative to traditional computer numerical control machining, particularly for prototyping applications. However, unlike traditional machine tools, robots are subject to relatively larger dynamic disturbances and operate closer to their torque limits. Combined with inaccurate models of the manipulators and the machining process, joint actuators can often saturate during operation. Once a joint is saturated, tool‐path tracking may not be possible and the blank and/or tool may be damaged. This paper presents a real‐time trajectory planner designed to mitigate the effect of unmodeled disturbances, thus avoiding controller saturation and potential tool/blank damage. The forces acting on the end effectors are monitored to identify the onset of a disturbance so that the system can be slowed down before saturation actually occurs. In response to disturbances, a time‐scaling method reduces the tool speed, thereby reducing the demand on the joint torques and allowing the precomputed process plan to continue. When there is sufficient torque available, the tool speed is returned to its planned magnitude. The effectiveness of the proposed time‐scaling algorithm has been demonstrated with simulations. © 2006 Wiley Periodicals, Inc.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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