Feature	Type	Shape
`observation.state`	STATE	(16,)
`observation.images.ceiling`	VISUAL	(3, 600, 960)
`observation.images.head_left`	VISUAL	(3, 720, 1280)
`observation.images.head_right`	VISUAL	(3, 720, 1280)
`observation.images.wrist_left`	VISUAL	(3, 600, 960)
`observation.images.wrist_right`	VISUAL	(3, 600, 960)

Feature	Type	Shape
`action`	ACTION	(16,)

Training

Policy type: ACT (Action Chunking with Transformers)
Vision backbone: ResNet-18 (ImageNet pretrained)
Chunk size / action steps: 100 / 100
VAE: enabled (latent dim 32, KL weight 10.0)
Transformer: dim_model 512, 8 heads, 4 encoder layers, 1 decoder layer

How to Use

python

from lerobot.policies.act.modeling_act import ACTPolicy

policy = ACTPolicy.from_pretrained("k1000dai/act-openarm-2-cell-pick_up_cube_mujoco")

To evaluate or fine-tune with the LeRobot CLI, pass --policy.path=k1000dai/act-openarm-2-cell-pick_up_cube_mujoco.