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Datasets:
sk1700
/
iros101

Tasks:
Robotics
Modalities:
Tabular
Video
Formats:
parquet
Languages:
English
Size:
10K - 100K
Tags:
robotics
dataset
lerobot
ur5e
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
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  1. README.md +43 -0
  2. data/chunk-000/episode_000000.parquet +3 -0
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README.md ADDED
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+ ---
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+ language:
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+ - en
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+ license: apache-2.0
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+ tags:
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+ - robotics
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+ - dataset
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+ - lerobot
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+ - ur5e
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+ task_categories:
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+ - robotics
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+ pretty_name: UR5e Dual RealSense Haptic Teleop Dataset (action = q[t+1] absolute, LeRobot v2.1)
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - data/*/*.parquet
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+ ---
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+
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+ # UR5e Dual RealSense Haptic Teleoperation Dataset (LeRobot v2.1)
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+
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+ - Control loop: ~500 Hz (RTDE)
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+ - Dataset sampling: fixed 30 Hz
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+
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+ Definitions:
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+ - `observation.state[t] = q_actual[t]` (UR joint positions, rad)
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+ - `action[t] = q_actual[t+1]` (next-step absolute joint positions at 30 Hz)
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+
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+ Temporal alignment:
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+ - Camera frames are stored in timestamped ring buffers (depth=8).
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+ - At each 30 Hz sample, the frame whose capture timestamp is closest to the
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+ RTDE packet timestamp is selected for both cameras independently.
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+ - This eliminates grab-latest race conditions and cross-camera temporal skew.
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+
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+ Visualizer-friendly naming:
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+ - observation.state names: ['shoulder_pan.pos', 'shoulder_lift.pos', 'elbow_flex.pos', 'wrist_1.pos', 'wrist_2.pos', 'wrist_3.pos']
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+ - action names: ['shoulder_pan.next_pos', 'shoulder_lift.next_pos', 'elbow_flex.next_pos', 'wrist_1.next_pos', 'wrist_2.next_pos', 'wrist_3.next_pos']
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+
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+ Videos:
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+ - `videos/chunk-000/observation.images.wrist/episode_XXXXXX.mp4`
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+ - `videos/chunk-000/observation.images.front/episode_XXXXXX.mp4`
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+
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+ Per-episode Parquet schema (STRICT order):
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+ `action`, `observation.state`, `timestamp`, `frame_index`, `episode_index`, `index`, `task_index`
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