Add Figure 6 embodiment experiments and S9-S10 records
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- README.md +28 -2
- checkpoints/figure6/cassie/connectome/seed_10871/final.pt +3 -0
- checkpoints/figure6/cassie/connectome/seed_10872/final.pt +3 -0
- checkpoints/figure6/cassie/connectome/seed_10873/final.pt +3 -0
- checkpoints/figure6/cassie/connectome/seed_10874/final.pt +3 -0
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- checkpoints/figure6/cassie/connectome/seed_871/final.pt +3 -0
- checkpoints/figure6/cassie/connectome/seed_872/final.pt +3 -0
- checkpoints/figure6/cassie/connectome/seed_873/final.pt +3 -0
- checkpoints/figure6/cassie/connectome/seed_874/final.pt +3 -0
- checkpoints/figure6/cassie/connectome/seed_875/final.pt +3 -0
- checkpoints/figure6/cassie/connectome/seed_876/final.pt +3 -0
- checkpoints/figure6/cassie/mlp/seed_10871/final.pt +3 -0
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- checkpoints/figure6/cassie/mlp/seed_20871/final.pt +3 -0
- checkpoints/figure6/cassie/mlp/seed_20872/final.pt +3 -0
- checkpoints/figure6/cassie/mlp/seed_20873/final.pt +3 -0
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- checkpoints/figure6/cassie/mlp/seed_871/final.pt +3 -0
- checkpoints/figure6/cassie/mlp/seed_872/final.pt +3 -0
- checkpoints/figure6/cassie/mlp/seed_873/final.pt +3 -0
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- checkpoints/figure6/cassie/mlp/seed_876/final.pt +3 -0
- checkpoints/figure6/go1/connectome/seed_10841/final.pt +3 -0
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README.md
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@@ -28,13 +28,39 @@ Code: [FlyControl](https://github.com/THU-NeuroML/FlyControl/tree/1a49c33bf1e6ea
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| S5 | BANC descending and motor readouts | 6 seeds per readout; initial and final states |
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| S6 | BANC regional recovery | 3 seeds per readout |
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| S8 | Ant Large Maze trajectories, speed and route complexity | Seven controller families; 20 seeds each |
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The seven Ant maze controller families are Adult connectome, MLP, GRU, LSTM, Transformer, Reservoir and Reservoir+RO. The Ant flat-ground MLP uses two 1,378-unit ReLU hidden layers.
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The repository contains
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`model_index.json` identifies each checkpoint by figure, experiment, controller, seed, configuration and SHA-256. Figure 5 entries are also listed in `figure5/model_index.json`.
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## Download and load
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| S5 | BANC descending and motor readouts | 6 seeds per readout; initial and final states |
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| S6 | BANC regional recovery | 3 seeds per readout |
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| S8 | Ant Large Maze trajectories, speed and route complexity | Seven controller families; 20 seeds each |
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| Figure 6a–e | Cassie balance; Tripod, Go1 and Hexapod walking | Connectome and MLP; 20 seeds per body and family |
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| Figure 6f | Cassie standing and lateral-motion stability | Connectome and MLP; 20 seeds each |
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| Figure 6g | Go1 tilt, pace and heading stability | Connectome and MLP; 20 seeds each |
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| S9 | Tripod direction and path stability | The Figure 6 Tripod policies |
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| S10 | Hexapod path and lateral-corridor stability | The Figure 6 Hexapod policies |
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The seven Ant maze controller families are Adult connectome, MLP, GRU, LSTM, Transformer, Reservoir and Reservoir+RO. The Ant flat-ground MLP uses two 1,378-unit ReLU hidden layers.
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The repository contains 846 checkpoint files: 810 final policies and 36 initial states. Figure 5 contributes 40 flat-ground policies and 420 maze policies. Checkpoints contain actor and critic weights and the saved components used by each policy, as listed in the model index.
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`model_index.json` identifies each checkpoint by figure, experiment, controller, seed, configuration and SHA-256. Figure 5 entries are also listed in `figure5/model_index.json`. Figure 5 model IDs follow `figure5/<flat|umaze|medium|large>/<method>/seed_<0–19>/final`.
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## Figure 6, S9 and S10
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Figure 6 contributes 160 final policies: Connectome and MLP controllers for Cassie, Tripod, Go1 and Hexapod, with 20 training seeds per body and controller. S9 and S10 use the same Tripod and Hexapod policies.
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| Body | Experiment | Training steps | Evaluation command (m/s) |
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|---|---|---:|---:|
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| Cassie | Biped balance | 524,288 | 0.0 |
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| Tripod | Radial tripod walking | 131,072 | 0.1 |
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| Go1 | Quadruped walking | 524,288 | 0.8 |
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| Hexapod | Hexapod walking with an analytic CPG | 131,072 | 0.5 |
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`figure6/model_index.json` maps each policy to its figure, body, controller, seed, configuration and checksum. The shared connectome is stored once in `figure6/graph.npz`. Figure 6 policies consume the features produced by their body interface; their PPO configuration uses `normalize_observation: false`.
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```bash
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python /path/to/model-snapshot/load_embodiment_policy.py \
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--model-id figure6/cassie/connectome/seed_871/final \
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--code-dir /path/to/FlyControl
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```
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The helper restores the policy and runs three numerical forward steps. `load_policy.py` also accepts Figure 6 model IDs. Use the corresponding FlyControl body interface to construct observations and apply motor actions. Evaluation conditions and reset seeds are stored in each index entry. File and loading checks are recorded in `figure6/validation.json`.
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## Download and load
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