lerobot-clone

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Adil Zouitine b72274066e feat(processors): Introduce processors for various policy types

- Added `make_processor` function to create processor instances for different policy types, including `tdmpc`, `diffusion`, `act`, `vqbet`, `pi0`, `pi0fast`, `sac`, and `reward_classifier`.
- Implemented corresponding processor files for each policy type, encapsulating normalization and unnormalization steps.
- Updated existing policies to remove direct normalization dependencies, enhancing modularity and clarity.
- Enhanced test coverage to validate the integration of new processors with existing policy configurations.

2025-08-06 17:20:41 +02:00

configuration_diffusion.py

fix(DiffusionPolicy): Fix bug where training without image features would crash with exception, fix environment state docs (#1617 )

2025-07-29 13:40:16 +02:00

modeling_diffusion.py

feat(processors): Introduce processors for various policy types

2025-08-06 17:20:41 +02:00

processor_diffusion.py

feat(processors): Introduce processors for various policy types

2025-08-06 17:20:41 +02:00

README.md

Update readme (#1570 )

2025-08-01 17:39:39 +02:00

README.md

Paper

https://diffusion-policy.cs.columbia.edu

Citation

@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},
}