airshop/Lego_task_complex_largerContext

Complex Lego Task

Description

Retrain of model with larger context: Pick up small lego block (pink) using left arm and place onto 2 x 1 (white), then right arm picks up combined block, places on 2 x 2 block (blue). In this setup, blue block is closer to right robot arm and pink block is closer to left robot arm, white block in between both.

Dataset

• Repo: airshop/Lego_task_complex
• Image augmentations: Disabled.

Training

• Model / Policy Type: ACT
• Steps: 100000
• Batch size: 8
• Vision backbone: resnet18
• VAE enabled: True (latent dim: 32)
• Training time: 1 days, 14 hours, 24 minutes, 45 seconds
• Machine: Spark (NVIDIA GB10)

Inputs

4 visual streams, 1 state inputs

Results

[Insert results here]

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How to Get Started with the Model

For a complete walkthrough, see the training guide. Below is the short version on how to train and run inference/eval:

Train from scratch

lerobot-train \
  --dataset.repo_id=${HF_USER}/<dataset> \
  --policy.type=ACT \
  --output_dir=outputs/train/<desired_policy_repo_id> \
  --job_name=lerobot_training \
  --policy.device=cuda \
  --policy.repo_id=${HF_USER}/<desired_policy_repo_id>
  --wandb.enable=true

Writes checkpoints to outputs/train/<desired_policy_repo_id>/checkpoints/.

Evaluate the policy/run inference

lerobot-record \
  --robot.type=so100_follower \
  --dataset.repo_id=<hf_user>/eval_<dataset> \
  --policy.path=<hf_user>/<desired_policy_repo_id> \
  --episodes=10

Prefix the dataset repo with eval_ and supply --policy.path pointing to a local or hub checkpoint.

Model Details

This policy has been trained and pushed to the Hub using LeRobot. See the full documentation at LeRobot Docs.

• License: apache-2.0