ataghof/so101nexus-cube500-binary

SO-101 sim cube pick-and-place, 500 demos (binary gripper)

500 scripted-expert demonstrations of an SO-101 arm picking up a red cube and placing it on a blue target, in a MuJoCo simulator (so101-nexus). This is the training data for the v6 LoRA champion.

Full story with videos: project page.

What's in it

• 500 episodes, randomized cube placement, recorded as a LeRobot v3 dataset with videos
• Two camera views (overhead + wrist), plus 6-dim joint state and action
• Injected noise and recovery in the executed trajectories (DART-style); clean actions recorded
• Episodes end with the cube placed on the target
• Gripper relabeled to two values, open or closed, the single biggest win in training

Load it

from lerobot.datasets.lerobot_dataset import LeRobotDataset
ds = LeRobotDataset("ataghof/so101nexus-cube500-binary")

Links

• Model trained on it: https://huggingface.co/ataghof/molmoact2-so101nexus-lora-champion
• Code + collector: https://github.com/ataghof/molmoact2-so101-sim

Built with so101-nexus (John Sutor) and LeRobot (Hugging Face).