MLeggiero/g1-gr00t-inspire-pick_and_place

G1 + Inspire — multi-task "place the <object> in the box" (GR00T N1.7 / G1_INSPIRE)

Teleoperated Unitree G1 (29-DoF) + Inspire RH56DFTP hands manipulation data, converted to the GR00T-flavored LeRobot v2.1 format for fine-tuning GR00T N1.7 as a custom NEW_EMBODIMENT (here called G1_INSPIRE).

This is the multi-task extension of MLeggiero/g1-gr00t-inspire-red-ball: identical schema, four pick-and-place tasks. The per-episode task label is derived from the capture-folder name. The red-ball portion is a superset of the original dataset (it adds a third red-ball session plus the pill / bottle / cup sessions), so the two can be used interchangeably or this one used on its own.

Summary

• Tasks (4): place the red ball in the box, place the pill in the box, place the bottle in the box, place the cup in the box

• Episodes / frames: 632 / 331,315 @ 60 fps; success flag per episode in meta/episodes.jsonl

  task_index	task	episodes	success / fail
  0	place the red ball in the box	156	142 / 14
  1	place the pill in the box	134	114 / 20
  2	place the bottle in the box	170	145 / 25
  3	place the cup in the box	172	141 / 31

• Camera: onboard Intel RealSense D435 ego-view (observation.images.ego_view, 424×240, h264)

• observation.state: 63-dim · action: 30-dim · observation.tactile: 34-dim (see index below)

Data fields & vector index

observation.state (float32[63]) — proprioception (+ pooled tactile)

idx	group	per-element (in order)	unit
0–6	left_arm	shoulder_pitch, shoulder_roll, shoulder_yaw, elbow, wrist_roll, wrist_pitch, wrist_yaw	rad (absolute joint angle)
7–13	right_arm	shoulder_pitch, shoulder_roll, shoulder_yaw, elbow, wrist_roll, wrist_pitch, wrist_yaw	rad
14–19	left_hand	pinky, ring, middle, index, thumb_pitch, thumb_yaw	rad (Inspire RH56DFTP)
20–25	right_hand	pinky, ring, middle, index, thumb_pitch, thumb_yaw	rad
26–28	waist	yaw, roll, pitch	rad
29–45	tactile_left	17 hand regions (see region list)	log1p(pooled)
46–62	tactile_right	17 hand regions	log1p(pooled)

The baseline meta/modality.json uses only 0:29 (tactile-free); the tactile meta/modality.tactile.json uses 0:63.

action (float32[30]) — GR00T prediction target

idx	group	per-element (in order)	unit
0–6	left_arm	shoulder_pitch … wrist_yaw (7)	rad
7–13	right_arm	shoulder_pitch … wrist_yaw (7)	rad
14–19	left_hand	pinky, ring, middle, index, thumb_pitch, thumb_yaw	rad
20–25	right_hand	pinky, ring, middle, index, thumb_pitch, thumb_yaw	rad
26	base_height	commanded base height	m
27	navigate_command[0] = vx	base linear velocity, local frame	m/s
28	navigate_command[1] = vy	base linear velocity, local frame	m/s
29	navigate_command[2] = yaw_rate	base yaw rate	rad/s

Arm/hand action targets are stored as absolute joint angles (radians), matching the upstream g1-gr00t-inspire-red-ball dataset byte-for-byte. Lower body: GR00T does not output leg joints — it emits a base velocity (navigate_command) + base_height, which the WBC turns into leg motion.

observation.tactile (float32[34]) — pooled tactile, also embedded in state[29:63]

Per hand, 17 regions in this order (per-region max-pool of the raw taxels, then log1p): little_tip, little_nail, little_pad, ring_tip, ring_nail, ring_pad, middle_tip, middle_nail, middle_pad, index_tip, index_nail, index_pad, thumb_tip, thumb_nail, thumb_middle, thumb_pad, palm → dims 0–16 = left hand, 17–33 = right hand.

Other parquet columns

column	dtype	meaning
timestamp	float32	seconds from episode start (frame_index / 60)
frame_index	int64	0…T−1 within the episode
episode_index	int64	0…631
index	int64	global frame index, 0…331314
task_index	int64	0…3 (see task table)
annotation.human.task_description	int64	task id → text via meta/tasks.jsonl

meta/

• info.json — schema (codebase_version v2.1, fps 60, robot_type unitree_g1, per-feature shapes/names).
• episodes.jsonl — per episode: episode_index, tasks, length, success (bool), source (original <date>_<time>/episode_NNNN session).
• tasks.jsonl — the 4 task strings.
• stats.json — per-feature mean/std/min/max/q01/q99 (GR00T normalization).
• modality.json (baseline) / modality.tactile.json (tactile) — GR00T modality slices.

Sidecars (raw, not referenced by the baseline modality config)

• tactile/episode_0000NN.npz → left, right: (T, 1062) uint16 raw taxels (0…~65535). The 1062 split into the 17 regions above with grid shapes: tip 3×3 (9), nail 12×8 (96), pad 10×8 (80) for little/ring/middle/index; thumb = tip 3×3 (9) + nail 12×8 (96) + middle 3×3 (9) + pad 12×8 (96); palm 8×14 (112). (Σ = 1062.)
• depth/episode_0000NN.npz → depth: (T, 240, 424) uint16, depth in millimeters.

Units & conventions

Arm/waist/hand angles in radians; hands are Inspire RH56DFTP DoFs mapped from raw 0–1000 registers to radians via the joint limits. base_height in meters, navigate_command in m/s & rad/s (robot-local frame). Tactile in observation.* is log1p of per-region max-pooled raw taxels; the tactile/ sidecar holds the un-pooled uint16 taxels.

Fine-tuning (GR00T N1.7)

python gr00t/experiment/launch_finetune.py \
  --base-model-path nvidia/GR00T-N1.7-3B \
  --dataset-path <this dataset> \
  --embodiment-tag NEW_EMBODIMENT \
  --modality-config-path g1_inspire_modality_config.py \
  --num-gpus 1 --global-batch-size 4

Provenance & license

Author: MLeggiero. Data collected on a Unitree G1 + Inspire RH56DFTP teleoperation rig, using the open-source collection stack from the YanjieZe repository (tooling credit only). Set the license above appropriately before making this dataset public.