RobotisAI/evButtonPush-260423-01-hdf5

evButtonPush — 260423-01 (v02)

한국어

ROBOTIS OMY 6-DoF 팔이 NVIDIA Isaac Sim / Isaac Lab 환경에서 엘리베이터 호출버튼을 누르는 시뮬레이션 데모셋 (v02). 스크립트된 IK teacher로 자동 수집됨.

이전 collection (거리 기반 v01) 은 RobotisAI/evButtonPush-260422-01-hdf5 에서 받을 수 있습니다 (baseline / ablation 용).

v02 특성 (권장)

• 45 demos, seed 0~`44`, 전부 pressed=True
• 약 35초/ep, ~1050 프레임 @ 30fps
• 성공 판정: 물리 접촉 힘 ≥ 0.5 N (PhysX tip_contact sensor)
• 엘베 문 FSM: state 0 (대기) → 1 (눌림, LED on) → 2 (문 여는 중) → 3 (완전 개방)
• 평균 접촉 힘 피크: 60~80 N
• Press 목표 Z offset: button_base 기준 +0.11 m 고정
• call_button_lit LED 관찰 포함
• Teacher CLI:

  --approach-steps 100   --press-steps 400
  --stall-steps 20       --hold-steps 30
  --return-steps 300     --home-idle-steps 150
  --press-depth 0.035    --contact-force-threshold 0.5
  

Task

• Task ID (Isaac Lab): RobotisLab-CallButton-Right-OMY-v0
• 로봇: ROBOTIS OMY (6축 팔 + 2지 그리퍼)
• Pedestal 높이: 0.908 m, 그리퍼 항상 닫힘 (stiffness 2×10⁶, effort 5000)
• 엘리베이터 USD: 100종 variants 중 seed별 random_choice (elevator_setup_new)
• 로봇 초기 자세 랜덤 (seed별):
  • 버튼까지 거리(standoff): 0.55 ~ 0.65 m
  • 좌우 lateral: −0.05 ~ 0.05 m
  • yaw: 0°

카메라

3대 모두 RGB, 1920 × 1200, Pinhole:

• 수평 aperture 20.955 mm
• 수직 aperture 13.097 mm (16:10 비율로 자동 계산)
• clipping (0.01, 100) m

이름	prim_path	기준 Frame	위치 (m)	Quat (w, x, y, z)	FOV (H / V / D)	focal
cam_wrist	Robot/OMY/link6/cam_wrist	link6 (팔과 함께 이동)	(0.000, −0.080, 0.070)	(0.0018, −0.0018, 0.7071, 0.7071)	83.21° / 58.06° / 92.64°	11.8 mm
cam_top	Robot/OMY/world/cam_top	로봇 base	(0.000233, 0.1499, 0.43953)	(0.5144, 0.4146, −0.5064, −0.5542)	92.67° / 66.44° / 102.03°	10.0 mm
cam_belly	Robot/OMY/world/cam_belly	로봇 base	(0.08705, 0.1499, 0.1075)	(−0.4901, −0.5097, 0.5097, 0.4901)	92.67° / 66.44° / 102.03°	10.0 mm

OMY USD 내부의 world prim은 시뮬레이션 월드가 아니라 **로봇 base (link0)**를 가리킴.

world_pose(cam_top)   = robot.root_pose_w ⊙ offset_cam_top
world_pose(cam_wrist) = robot.root_pose_w ⊙ FK(link0→link6) ⊙ offset_cam_wrist

HDF5 내부 구조 (episode 당)

data/demo_0/
├── actions              (T, 7)    float32   arm 6 + gripper 1
├── processed_actions    (T, 10)   float32   전체 joint target
├── obs/
│   ├── cam_wrist        (T, 1200, 1920, 3)   uint8
│   ├── cam_top          (T, 1200, 1920, 3)   uint8
│   ├── cam_belly        (T, 1200, 1920, 3)   uint8
│   ├── joint_pos                (T, 10)     float32
│   ├── joint_vel                (T, 10)     float32
│   ├── call_button_pos          (T, 3)      float32   버튼 world 좌표
│   ├── rel_ee_call_button_distance (T, 3)   float32   tip-button 벡터
│   └── call_button_lit          (T, 1)      bool      ⭐ LED on/off
├── states/articulation/robot/...
├── states/rigid_object/pedestal/...
└── initial_state/...

파일 구성

• demo_XX.hdf5 - episode 하나당 파일 하나
• demo_XX.log - teacher stdout ([SETUP], [PHASE], [PRESSED], [RESULT] 마커)
• summary.log - demo당 한 줄 요약

추천 사용 방법

Imitation learning (ACT, Diffusion Policy, BC) 학습 시 qpos_dim = 8:

qpos   = concat(joint_pos[:6], gripper_closed_flag, call_button_lit)  # 8
action = [arm_delta[:6], gripper_cmd]                                 # 7
images = {cam_wrist, cam_top, cam_belly}                              # 1920×1200 (필요시 resize)

일반적으로 학습 파이프라인에서는 240×320으로 resize해서 씁니다. 원본은 1920×1200으로 보존.

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English

Simulated demonstrations of a ROBOTIS OMY 6-DoF arm pressing an elevator call-button, collected in NVIDIA Isaac Sim / Isaac Lab with a scripted IK teacher. This dataset is the v02 collection — improved over v01 with physics-based success detection and elevator-door FSM.

The earlier v01 collection (distance-based teacher, baseline only) is at RobotisAI/evButtonPush-260422-01-hdf5.

v02 highlights (recommended for training)

• 45 demos, seeds 0 – 44, all pressed = True
• ~35 s per episode, ~1050 frames at 30 fps
• Success criterion: physical contact force ≥ 0.5 N (PhysX tip_contact sensor)
• Elevator door FSM progresses on press: state 0 (idle) → 1 (pressed / LED on) → 2 (door opening, progress 0→1) → 3 (open)
• Average peak gripper tip contact force: 60 – 80 N
• Press target Z offset: +0.11 m relative to button_base (fixed inside teacher).
• Includes call_button_lit LED observation.
• Teacher CLI:

  --approach-steps 100   --press-steps 400
  --stall-steps 20       --hold-steps 30
  --return-steps 300     --home-idle-steps 150
  --press-depth 0.035    --contact-force-threshold 0.5
  

Task

• Task ID (Isaac Lab): RobotisLab-CallButton-Right-OMY-v0
• Robot: ROBOTIS OMY (6-DoF arm + 2-finger gripper)
• Pedestal: 0.908 m, gripper always closed (stiffness 2 × 10⁶, effort 5000)
• Elevator USD: random choice from 100 variants (elevator_setup_new)
• Robot initial pose randomization (per-seed):
  • standoff distance to button: 0.55 ~ 0.65 m
  • lateral offset: −0.05 ~ 0.05 m
  • yaw: 0°

Cameras

All three cameras record RGB, 1920 × 1200, Pinhole:

• horizontal aperture 20.955 mm
• vertical aperture 13.097 mm (derived from 16:10 aspect)
• clipping (0.01, 100) m

Name	Prim path	Frame	Position (m)	Quat (w, x, y, z)	FOV (H / V / D)	focal
cam_wrist	Robot/OMY/link6/cam_wrist	link6 (local, moves with arm)	(0.000, −0.080, 0.070)	(0.0018, −0.0018, 0.7071, 0.7071)	83.21° / 58.06° / 92.64°	11.8 mm
cam_top	Robot/OMY/world/cam_top	robot base	(0.000233, 0.1499, 0.43953)	(0.5144, 0.4146, −0.5064, −0.5542)	92.67° / 66.44° / 102.03°	10.0 mm
cam_belly	Robot/OMY/world/cam_belly	robot base	(0.08705, 0.1499, 0.1075)	(−0.4901, −0.5097, 0.5097, 0.4901)	92.67° / 66.44° / 102.03°	10.0 mm

The world prim inside the OMY USD refers to the robot's base frame (link0), not the simulation world.

world_pose(cam_top)    = robot.root_pose_w  ⊙  offset_cam_top
world_pose(cam_wrist)  = robot.root_pose_w  ⊙  FK(link0→link6)  ⊙  offset_cam_wrist

HDF5 layout per episode

data/demo_0/
├── actions              (T, 7)    float32
├── processed_actions    (T, 10)   float32
├── obs/
│   ├── cam_wrist        (T, 1200, 1920, 3)   uint8
│   ├── cam_top          (T, 1200, 1920, 3)   uint8
│   ├── cam_belly        (T, 1200, 1920, 3)   uint8
│   ├── joint_pos                (T, 10)     float32
│   ├── joint_vel                (T, 10)     float32
│   ├── call_button_pos          (T, 3)      float32
│   ├── rel_ee_call_button_distance (T, 3)   float32
│   └── call_button_lit          (T, 1)      bool       ⭐ LED state
├── states/articulation/robot/...
├── states/rigid_object/pedestal/...
└── initial_state/...

Per-version files

• demo_XX.hdf5 — one episode per file
• demo_XX.log — scripted-teacher stdout with [SETUP], [PHASE], [PRESSED], [RESULT] markers
• summary.log — one line per demo

Suggested usage

Imitation learning (ACT, Diffusion Policy, BC) with qpos_dim = 8:

qpos = concat(joint_pos[:6], gripper_closed_flag, call_button_lit)  # 8
action = [arm_delta[:6], gripper_cmd]                                 # 7
images = {cam_wrist, cam_top, cam_belly}                              # 1920×1200 (resize as needed)

For efficiency, training pipelines commonly resize to 240 × 320 before consumption. We retain the original 1920 × 1200 to keep the data lossless.