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SO-101 sim cube pick-and-place, 500 demos (binary gripper)
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---
license: apache-2.0
task_categories:
- robotics
tags:
- lerobot
- so-101
- molmoact2
- pick-and-place
---
# 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](https://huggingface.co/ataghof/molmoact2-so101nexus-lora-champion).
Full story with videos: [project page](https://ataghof.github.io/molmoact2-so101-sim/).
## 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
```python
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).