Fast collision avoidance for manipulator arms: a sequential search strategy
Why this work is in the frame
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Bibliographic record
Abstract
A sequential strategy is presented for planning collision-free motions for a manipulator arm. The basic idea behind the approach is to plan the motion of each link successively, starting from the base link. Suppose that the motion of links to link i (including link i) has been planned. This already determines the path of one end (the proximal end) of link i+1. The motion of link i+1 is now planned along this path by controlling the degree of freedom associated with it, which is a 2-D motion planning problem. This strategy results in one 1-D (the first link is degenerate) and (n-1) 2-D planning problems. The 2-D motion planning problem is to plan the motion of a single link as one end of this link moves along a fixed path. This problem is posed in t* theta space, where t is the parameter along the path and theta the angle to be planned. The obstacles in t* theta space are approximated by discretizing t. Fast and efficient techniques are then used to plan a path in t* theta space. Thus, the strategy leads to fast and efficient algorithms and is especially suited for highly redundant arms.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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