Sequence-modification based collision-free motion planning of multiple robots workcell
Why this work is in the frame
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Bibliographic record
Abstract
This work is inspired by the problem of planning multiple robots in a shared workspace. The goal is to find out a sequence order for coordinating the paths of robots so as to avoid collisions among them and deadlocks, that is, situations where each robot is waiting for the other to proceed. We assume that the workcell is known and the paths of robots can be planned in advance and all the robots move synchronously. These assumptions are good models of many tasks. The coordination is achieved by introducing improved A* heuristic algorithm for continuous state sequence planning in high dimensional space. The proposed method consist of two steps: 1) path planning for the robots, which taking into account avoidance of collision between the robots and the environment; 2) calculating all the possible colliding state and translating the coordinating problem into scheduling the path segments. Experimental cases are shown for the proposed algorithm and for their implementations. The results of the planning method can be applied to the industrial applications.
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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