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atharva-manav/
dp-clean-delta-joints

Name: dp-clean-delta-joints
Availability: InStock

bimanual-manipulation

apache-2.0

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dp-clean-delta-joints

DiffusionPolicy trained on clean bimanual robot manipulation data. Action space: delta joint angles (Δjoints(18) + grippers(2) = 20-dim). 142 episodes, 45116 frames @ 20fps. ResNet18 backbone, 2 cameras (cam_head + cam_wrist), 279M params, 100k training steps.

Training Details

Parameter	Value
Policy	DiffusionPolicy (UNet)
Vision backbone	ResNet18
Cameras	cam_head + cam_wrist (640×480)
Obs steps	2
Action horizon	16
Action steps	8
Batch size	64
Steps	100,000
Optimizer	Adam (lr=1e-4, betas=[0.95,0.999])
Scheduler	Cosine (500 warmup steps)
Noise scheduler	DDIM (100 train / 10 inference steps)
Normalization	MEAN_STD (visual), MIN_MAX (state/action)

Dataset

Split: clean_train (142 episodes, 45,116 frames @ 20 Hz)
Robot: Bimanual SO-101 (2× 7-DoF arms)
Task: Clean object manipulation

Usage

python

from lerobot.policies.diffusion.modeling_diffusion import DiffusionPolicy

policy = DiffusionPolicy.from_pretrained("atharva-manav/dp-clean-delta-joints")