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.topview β€” Fixed overhead. Better for unoccluded pick-place tasks.
  • observation.images.wristview β€” Egocentric wrist-mounted. Better for overlapping and cluttered scenes.

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Dataset used to train ShubhamK32/act_so101_declutter