ACT β SO-101 Space Decluttering
ACT (Action Chunking Transformer) policy trained on the SO-101 Space Decluttering Dataset v1 for pick-and-place decluttering tasks on a 6-DoF SO-101 robotic arm. Trained using LeRobot.
Training Details
- Policy: ACT (Action Chunking Transformer)
- Steps: 100,000
- Robot: SO-101 6-DoF leader-follower
- Cameras: Dual-view β fixed top-view + wrist-mounted egocentric
- Framework: LeRobot
Dataset
Trained on ShubhamK32/so101_declutter_v1 β a multi-view teleoperation dataset with spatial distractors injected to prevent visual shortcut learning.
Usage
from lerobot.policies.act.modeling_act import ACTPolicy
policy = ACTPolicy.from_pretrained("ShubhamK32/act_so101_declutter")
Camera Views
observation.images.topviewβ Fixed overhead. Better for unoccluded pick-place tasks.observation.images.wristviewβ Egocentric wrist-mounted. Better for overlapping and cluttered scenes.
Related
- Dataset: ShubhamK32/so101_declutter_v1
- SmolVLA checkpoint: ShubhamK32/smolvla_so101_declutter
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