Multi-agent trajectory planning on 10 agent scenario (ground truth goals)
2.31Trajectory Success RatePSN-Partial
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| PSN-PartialParameter=|U^i| = 22025.04 | 2.31 | 2.4994 | 0.9884 | 0.4982 | 3 | |
| PSN-PartialParameter=m_th = 0.52025.04 | 2.21 | 2.4924 | 0.9885 | 0.5035 | 2.88 | |
| AllParameter=—2025.04 | 2.15 | 2.49 | 1 | 0.568 | 10 | |
| PSN-FullParameter=|U^i| = 22025.04 | 2.13 | 2.4738 | 0.9919 | 0.5155 | 3 | |
| PSN-FullParameter=m_th = 0.52025.04 | 1.89 | 2.4682 | 0.992 | 0.5043 | 2.75 | |
| GradientParameter=|U^i| = 22025.04 | 1.78 | 2.4486 | 0.993 | 0.4816 | 3 | |
| HessianParameter=|U^i| = 22025.04 | 1.77 | 2.456 | 0.9928 | 0.482 | 3 | |
| kNNsParameter=|U^i| = 22025.04 | 1.69 | 2.4514 | 0.9908 | 0.4801 | 3 | |
| Cost EvolutionParameter=|U^i| = 22025.04 | 1.69 | 2.4931 | 0.9775 | 0.4848 | 3 | |
| BFParameter=|U^i| = 22025.04 | 1.6 | 2.456 | 0.9923 | 0.4792 | 3 | |
| CBFParameter=|U^i| = 22025.04 | 1.55 | 2.4559 | 0.9932 | 0.4798 | 3 | |
| DistanceParameter=d_th = 1.5 m2025.04 | 1.53 | 2.4658 | 0.9931 | 0.477 | 2.29 |