Datasets:
license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- robotics
- so101
- code-as-policies
- auto-collected
- cap
- 10fps
- single-arm
- dual-camera
- skill-annotations
- close-pot-lid
configs:
- config_name: default
data_files: data/*/*.parquet
SO101 CAP Close Pot Lid
This dataset contains 100 LeRobot v3.0 demonstration episodes for an SO101 follower robot. The task is: Pick up the pot lid by its handle and place it on the pot. The dataset was collected at 10 Hz and includes paired top-view and wrist-view RGB videos, robot state/action trajectories, and CAP skill annotations.
Dataset Details
| Field | Value |
|---|---|
| Repository | CoRL2026-CSI/SO101-cap_close_pot_10fps |
| LeRobot codebase version | v3.0 |
| Robot type | so101_follower |
| FPS | 10 |
| Episodes | 100 |
| Frames | 37669 |
| Tasks | 2 |
| Split | 0:100 train |
| Objects | pot and pot lid |
| Parquet files | 2 |
| Video files | 4 |
Task And Annotations
Task: Pick up the pot lid by its handle and place it on the pot.
Task indices: 0, 1
Observed subtask annotations:
- pick pot lid and place on pot
Representative skill types:
- move_initial
- move_and_open
- move
- gripper_close
- move_linear
- gripper_open
- move_and_close
- move_free
Representative skill-language annotations:
- Move to initial position
- Approach pot lid handle and open gripper
- Pick up the pot lid by its handle
- grasp pot lid
- Lift the pot lid
- Move pot lid above the pot
- Place lid on pot and seat it with a drag motion
- push lid +2cm on pot
- pull lid -0cm on pot
- release lid on pot
- Retreat from pot and close gripper
- Return to initial state
Observation And Action Space
| Feature | Shape | Names / Notes |
|---|---|---|
observation.state |
6 |
shoulder_pan.pos, shoulder_lift.pos, elbow_flex.pos, wrist_flex.pos, wrist_roll.pos, gripper.pos |
action |
6 |
shoulder_pan.pos, shoulder_lift.pos, elbow_flex.pos, wrist_flex.pos, wrist_roll.pos, gripper.pos |
observation.images.top |
480x640x3 |
RGB video, 10 fps |
observation.images.left_wrist |
480x640x3 |
RGB video, 10 fps |
Raw camera keys are observation.images.top and observation.images.left_wrist. The local SmolVLA training scripts map them to observation.images.camera2 and observation.images.camera1, respectively.
Files
meta/info.json
meta/tasks.parquet
meta/episodes/chunk-*/file-*.parquet
data/chunk-*/file-*.parquet
videos/{observation.images.top,observation.images.left_wrist}/chunk-*/file-*.mp4
The dataset uses the LeRobot v3.0 format. Episode metadata and frame-level trajectories are stored in parquet files; image observations are stored as H.264 MP4 videos referenced by the frame records.
Annotation Columns
| Column | Shape |
|---|---|
skill.natural_language |
1 |
skill.verification_question |
1 |
skill.type |
1 |
skill.progress |
1 |
skill.goal_position.joint |
6 |
skill.goal_position.robot_xyzrpy |
6 |
skill.goal_position.gripper |
1 |
subtask.natural_language |
1 |
subtask.object_name |
1 |
subtask.target_position |
3 |
Loading
from lerobot.datasets.lerobot_dataset import LeRobotDataset
dataset = LeRobotDataset("CoRL2026-CSI/SO101-cap_close_pot_10fps")
sample = dataset[0]
Intended Uses
This dataset is intended for robot imitation learning, action-chunking policy training, skill-conditioned behavior analysis, and reproducible LeRobot/SmolVLA experiments on the specified tabletop task.
Limitations
The dataset is task-specific and collected in a fixed workspace. It does not include an official validation or test split, nor does it include benchmark success-rate results. Downstream users should verify camera calibration, action normalization, and task-language assumptions before transferring policies to a different robot, workspace, or object set.