Vehicle Dynamic State Estimation on ReV-StED (test)
0.02Velocity X ErrorPRML2
Evaluation Results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| PRML2Physics-based regularization=true2026.07 | 0.02 | 0.01 | 0.15 | 0.12 | 0.18 | |
| PRML2*Physics-based regularization=false2026.07 | 0.03 | 0.01 | 0.18 | 0.13 | 0.24 | |
| NN-VDMArchitecture=Neural network-based (GRU)2026.07 | 0.06 | 0.03 | 0.13 | 0.13 | 0.41 | |
| DL-AVLArchitecture=LSTM-based2026.07 | 0.07 | 0.03 | 0.16 | 0.13 | 0.46 | |
| RNN-EKFArchitecture=GRU network with attention2026.07 | 0.07 | 0.02 | 0.13 | 0.13 | 0.44 | |
| Backprop-KFArchitecture=Observation model with differentiable EKF2026.07 | 0.12 | 0.02 | 0.31 | 0.15 | 0.38 | |
| OSD-BaselineDescription=Simple classical model-based approach using Onboard Sensor Data2026.07 | 0.22 | — | — | 0.2 | 0.43 |