Motion Planning of Multiple Agents in Virtual Environments on Parallel Architectures
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Bibliographic record
Abstract
We proposed in a previous paper (2006) a hybrid two-layered approach for motion planning of multiple agents in static virtual environments, consisting of open spaces connected by multiple narrow passages. The discrete generalized Voronoi diagram (GVD) of the environment is used to identify narrow passages, and plan the global path of each agent independently of other agents' global paths. As each agent moves along its global path, the agent's path is locally modified using the hybrid technique of combining steering behaviors with Coordination Graphs (CG), where coordination graphs are used for deadlock avoidance in the narrow passages. The planner in the previous paper was single threaded, and it was able to plan the motions of 30 agents moving around in a simple virtual environment with 3 narrow passages. If more agents are moving in a more complex virtual environment (i.e., with more narrow passages), we may not be able to construct and process all the coordination graphs in real-time. In this paper, we parallelize the single threaded planner in a supervisor-worker paradigm with Unix processes who communicate with each other using System V interprocess communication (IPC) mechanism. We show that significant, scalable speedups are obtained by constructing and processing coordination graphs in parallel on a symmetric multiprocessing (SMP) system.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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