d_1-Optimal Motion for a Rod (Extended Abstract)
Bibliographic record
Abstract
) Tetsuo Asano 1 , David Kirkpatrick 2 , and Chee K. Yap 3 1 Osaka Electro-Communication University, Japan, 2 University of British Columbia, Canada, 3 Courant Institute, New York University, USA December 5, 1994 Abstract We study optimal motion for a rod in the plane amidst polygonal obstacles. The optimality criterion is based on minimizing the orbit length of a fixed but arbitrary point (called the focus) on the rod. Our surprising result is that this problem is NP-hard if when focus is in the relative interior of the rod whereas it is solvable in polynomial time if the focus is an endpoint of the rod. Other results include a local characterization of d1-optimal motion and an approximation algorithm. 1 Introduction Although feasibility motion planning is very well studied, little is known about optimal motion planning except for the case where the robot body is a disc. In this paper we are interested in studying optimal motion for a rod (a directed line segment). Of c...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".