Lazarus Object Trajectory Predictor
Lazarus Trajectory Predictor is a physics-informed deep sequence model engineered for real-time trajectory forecasting, aerodynamic ballistic arc extrapolation, impact estimation, and motion classification for autonomous vision systems and robotics.
Trained on Google Colab Tesla T4 GPU.
Model Details
- Architecture: Attentive Residual Conv1D-Bidirectional GRU
- History Horizon: 15 timesteps (~0.5s @ 30 FPS) of
[x, y, vx, vy, ax, ay] - Prediction Horizon: 20 future timesteps (~0.67s @ 30 FPS) of coordinates and impact landing reticle
- Physics Regimes: Parabolic Ballistics (Gravity & Drag), Rebounding Bounces, Curved Evasion, Accelerated Kinematics, Stable Drift.
- Inference Runtime: ONNX Runtime / OpenCV DNN CPU real-time (< 2ms per query).
Telemetry Performance
- Validation Loss:
0.04453 - Average Displacement Error (ADE):
0.0711(normalized viewport) - Final Displacement Error (FDE):
0.1572(normalized viewport) - Classification Accuracy:
80.0%