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XYZPIT/260826_pick_up_the_bread_bag

Pick Up the Bread Bag Dataset Description This dataset contains teleoperated bread-bag pickup demonstrations collected using the Galaxea R1 Lite robot. In each episode, the robot picks up a bread bag from a conveyor-belt setup. The dataset is stored in the LeRobot dataset format and contains synchronized multi-view RGB videos, robot observations, and action commands. The dataset contains a single task instruction: pick up the bread bag Dataset Summary… See the full description on the dataset page: https://huggingface.co/datasets/XYZPIT/260826_pick_up_the_bread_bag.

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Dataset Card

Pick Up the Bread Bag

Dataset Description

This dataset contains teleoperated bread-bag pickup demonstrations collected using the Galaxea R1 Lite robot.

In each episode, the robot picks up a bread bag from a conveyor-belt setup. The dataset is stored in the LeRobot dataset format and contains synchronized multi-view RGB videos, robot observations, and action commands.

The dataset contains a single task instruction:

pick up the bread bag

Dataset Summary

ItemValue
RobotGalaxea R1 Lite
Collection methodTeleoperation
Number of episodes100
Number of frames57,272
Number of videos400
Number of task instructions1
Frames per second31 FPS

Task Distribution

Task instructionEpisodes
pick up the bread bag100
Total100

Camera Observations

Each episode contains four synchronized RGB camera streams.

FeatureCamera viewResolution
observation.images.head_rgbLeft head camera1280 × 720
observation.images.head_right_rgbRight head camera1280 × 720
observation.images.left_wrist_rgbLeft wrist camera640 × 360
observation.images.right_wrist_rgbRight wrist camera640 × 360

The videos are encoded using AV1 at 31 FPS.

Robot Observations

The dataset includes robot proprioceptive observations such as:

  • —Left and right arm joint positions
  • —Left and right arm joint velocities
  • —Left and right gripper states
  • —Left and right end-effector poses
  • —Chassis state
  • —Torso state
  • —Chassis and torso velocities
  • —IMU measurements

Actions

The action features include:

  • —Left and right arm joint targets
  • —Left and right gripper targets
  • —Chassis velocity commands
  • —Torso velocity commands

Intended Use

This dataset is intended for research on robot imitation learning and vision-based manipulation, particularly for learning bread-bag pickup behavior in a conveyor-belt environment.

Limitations

  • —The demonstrations were collected using a single Galaxea R1 Lite robot.
  • —The data were collected in a single workspace and conveyor-belt configuration.
  • —The dataset contains only one task instruction.
  • —The dataset has limited variation in objects and environmental conditions.
  • —Performance learned from this dataset may not directly generalize to different objects, conveyor configurations, lighting conditions, backgrounds, or robot embodiments.