wty-yy/go2_rl_gym_data

Go2 RL GYM Data

Checkpoint files for go2_rl_gym.

📦 Files

The table below mirrors the evaluation table in the main repository README. Link points to the corresponding Hugging Face file or folder page.

Model	Score	Tracking	Safety	Quality	Level	Link
go2_moe_cts (Ours)	0.6713	0.6669	0.7857	0.7392	7.85	go2_moe_cts_137000_0.6713
go2_ac_moe_cts	0.6509	0.6442	0.7644	0.7149	7.52	go2_ac_moe_cts_115k_0.6509.pt
go2_mcp_cts	0.6399	0.6355	0.7542	0.7058	7.41	go2_mcp_cts_91k_0.6399
go2_moe_ng_cts	0.6519	0.6447	0.7639	0.7186	7.56	go2_moe_ng_cts_79k_0.6519
CTS vanilla	0.5786	0.5755	0.7066	0.6624	6.83	go2_cts_vanilla2_103.5k_0.5786
HIM	0.5379	0.5453	0.6476	0.6050	6.19	go2_him_21k_0.5379.pt
DreamWaQ	0.5054	0.5105	0.6149	0.5730	5.74	go2_dwaq_119.5k_0.5054.pt

Additional self-collision-enabled result:

Model	Score	Download
go2_moe_cts_high_slope_thre	0.6715	go2_moe_cts_high_slope_thre_164k_0.6715_20260419

🚀 Usage

File types:

• policy.pt: TorchScript policy for Sim2Sim deployment.
• policy.onnx: ONNX policy for C++ / Sim2Real deployment.
• policy.pkl: raw policy weights.
• model_*.pt: full training checkpoint.
• single *.pt files at repository root: standalone checkpoint files kept as released.

Example paths:

# Sim2Sim policy
./go2_moe_cts_137000_0.6713/policy.pt

# ONNX deployment policy
./go2_moe_cts_137000_0.6713/policy.onnx

# Full training checkpoint
./go2_moe_cts_self_103.5k_0.6669/model_103500.pt

For training, evaluation, export, and deployment commands, see the main repository go2_rl_gym README.

🔎 Details

• Most directory entries contain exported policies.
• go2_moe_cts_high_slope_thre_164k_0.6715_20260419 contains both exported policies and the full model_164000.pt.
• go2_moe_cts_self_103.5k_0.6669 contains exported policies and model_103500.pt.
• On the Hugging Face web page, folder entries should use tree/main/... URLs for navigation.

📄 Citation

If you find our work helpful, please cite:

@article{wu2026robogauge,
      title={Toward Reliable Sim-to-Real Predictability for MoE-based Robust Quadrupedal Locomotion}, 
      author={Tianyang Wu and Hanwei Guo and Yuhang Wang and Junshu Yang and Xinyang Sui and Jiayi Xie and Xingyu Chen and Zeyang Liu and Xuguang Lan},
      year={2026},
      journal={arXiv preprint arXiv:2602.00678},
      url={https://arxiv.org/abs/2602.00678}, 
}