Publication of PushT Diffusion Policy model with demonstration videos - 2025-04-28

README.md

@@ -1,11 +1,3 @@
----
-license: apache-2.0
-datasets:
-- lerobot/pusht
-pipeline_tag: robotics
-tags:
-- robotics
----
 
 # PushT Diffusion Policy - Robot Control Model
 
@@ -17,7 +9,7 @@ This model uses a conditional diffusion architecture to predict robotic actions
 
 ## Performance
 
-The model achieves a success rate of 40.0% in the PushT environment with different initial configurations.
+The model achieves a success rate of 100.0% in the PushT environment with different initial configurations.
 
 ## Demonstration Videos
 
@@ -31,14 +23,4 @@ from lerobot.common.policies.diffusion.modeling_diffusion import DiffusionPolicy
 policy = DiffusionPolicy.from_pretrained("RafaelJaime/pusht-diffusion")
 ```
 
-## Citation
-
-```bibtex
-@article{chi2024diffusionpolicy,
-    author = {Cheng Chi and Zhenjia Xu and Siyuan Feng and Eric Cousineau and Yilun Du and Benjamin Burchfiel and Russ Tedrake and Shuran Song},
-    title = {Diffusion Policy: Visuomotor Policy Learning via Action Diffusion},
-    journal = {The International Journal of Robotics Research},
-    year = {2024},
-}
-```
-Published on 2025-04-28
+Published on 2025-04-28

metadata.json

@@ -2,12 +2,11 @@
   "library_name": "lerobot",
   "task_type": "robot-control",
   "environment": "PushT",
-  "timestamp": "2025-04-28T04:50:36.767363",
+  "timestamp": "2025-04-28T19:15:51.796515",
   "videos": [
     "video_2_experiment_summary.mp4",
     "video_1_pusht_episode.mp4",
-    "pusht_episode.mp4",
-    "experiment_summary.mp4"
+    "pusht_episode.mp4"
   ],
   "device": "cuda"
 }