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PhysProbe Dynamics Probing Dataset

Manipulation episodes from Isaac Lab collected for probing physics understanding in video world models (V-JEPA 2, VideoMAE, DINOv2). Each episode includes dual-camera RGB (384×384), robot state, scripted/RL actions, and per-timestep physics ground truth (contact forces, object kinematics, physics randomization parameters).

Tasks

Task Episodes Policy Physics Randomization
Push 1,500 Scripted (random direction, no target — Step 0) mass, obj_friction, surface_friction
Strike 3,000 Scripted (random direction, no target — Step 0) mass, friction, surface_friction, restitution
Reach 600 Scripted None (negative control)
Drawer 2,000 RL (RSL_RL) drawer_joint_damping
PegInsert 2,500 Scripted (Factory) held_friction, fixed_friction, held_mass
NutThread 2,500 Scripted (Factory) held_friction, fixed_friction, held_mass
Total 12,100

Format

LeRobot V2 layout. Per-task:

<task>/
  data/chunk-000/episode_NNNNNN.parquet
  videos/chunk-000/observation.images.image_0/episode_NNNNNN.mp4   # table_cam
  videos/chunk-000/observation.images.image_1/episode_NNNNNN.mp4   # wrist_cam
  meta/info.json
  meta/episodes.jsonl
  meta/tasks.jsonl
  meta/stats.json
  meta/modality.json

Per-episode parquet columns:

  • observation.state (8D): 7 joint positions + 1 gripper
  • action (3–8D, task-dependent)
  • next.reward, next.done
  • physics_gt.* (task-specific — see below)
  • Frame index, timestep, episode index metadata

Physics Ground Truth (physics_gt.*)

Common across all tasks

  • ee_position (3), ee_orientation (4), ee_velocity (3), ee_angular_velocity (3) — end-effector kinematics
  • joint_pos (7), joint_vel (7) — arm joint state
  • phase (1) — task phase label (task-dependent enum; 7 = idle)

Contact fields (per task)

Push, Strike, Reach:

  • contact_flag (1), contact_force (3), contact_point (3) — aggregate ee↔object + object↔surface
  • contact_finger_l_object_flag/force, contact_finger_r_object_flag/force — per-finger ee↔object (new in 2026-04-23)
  • contact_object_surface_flag/force — object↔surface (new in 2026-04-23)

PegInsert, NutThread:

  • contact_flag (1), contact_force (3), contact_point (3) — aggregate
  • contact_finger_l_peg_flag/force, contact_finger_r_peg_flag/force (PegInsert) — finger↔peg
  • contact_finger_l_nut_flag/force, contact_finger_r_nut_flag/force (NutThread) — finger↔nut
  • contact_peg_socket_flag/force (PegInsert) — peg↔hole (reconstructed as residual from peg total contact minus finger reactions; direct pair filter unsupported in Factory direct env)
  • contact_nut_bolt_flag/force (NutThread) — nut↔bolt (direct exact-pair sensor)

Drawer:

  • handle_position (3), handle_velocity (3)
  • drawer_joint_pos (1), drawer_joint_vel (1)

Task-specific kinematics

Push/Strike/Reach (Step 0):

  • object_position (3), object_orientation (4), object_velocity (3), object_angular_velocity (3)
  • target_position (3) — placeholder [0, 0, 0] (no target in Step 0)

PegInsert/NutThread:

  • held_position (3), held_orientation (4), held_velocity (3), held_angular_velocity (3) — peg/nut kinematics
  • fixed_position (3), fixed_orientation (4) — hole/bolt pose
  • insertion_depth (1) — peg_insert only

Physics randomization parameters (per episode)

Stored in episode metadata (physics_gt.*_{static,dynamic}_friction, *_mass, etc.) — see per-task schema above for exact fields.

2026-04-23 Recollection Note

The previous version of this dataset (before 2026-04-23) had a data-collection bug: contact forces were zero-filled across all tasks because the sensor configuration did not use the proper body filters / the Factory direct env does not support get_net_contact_forces on ArticulationView. This version fixes the following:

  1. Push, Strike, Drawer, Reach: Per-pair ContactSensor with filter_prim_paths_expr on finger/object bodies → real nonzero contact forces.
  2. NutThread: Direct exact-pair sensor (contact_nut_bolt_*) → direct nut↔bolt force.
  3. PegInsert: GPU pair filtering on hole is unsupported in direct Factory env. Peg↔socket contact is reconstructed as a residual: F_peg_socket = F_peg_total - F_finger_l_peg - F_finger_r_peg (Newton's 3rd law). This is sparser and noisier than a direct sensor; finger-grip force dominates and is subtracted, so pay attention when using contact_peg_socket_* for downstream probing.
  4. Phase label: Now correctly tracks scripted policy state transitions (previously always 7/idle for RL policies).

Known caveats (unchanged from previous release)

  • Push/Strike are Step 0: no target, success=True for all, target_position=[0,0,0].
  • Drawer randomizes only drawer_joint_damping (Isaac Lab env limitation — handle friction/mass are fixed).
  • Factory tasks (PegInsert, NutThread): collection uses scripted policy; success rate is low for unguided inserts.

Collection Pipeline

  • Isaac Sim 4.5 / Isaac Lab v2.2.1
  • Scripted oracle policies + optional RL checkpoints (rl_games for Factory, rsl_rl for Drawer)
  • Dual camera rendering at 384×384, 15 fps
  • num_envs per task: 8 (Factory), 16 (others) parallel
  • Hardware: 4× NVIDIA A6000 48 GB

Collection script: Leesangoh/PhysREPA_Tasks (archive_data_collection/collect_sample_data.py).

Intended use

This dataset is designed for probing physics understanding in pretrained video encoders:

  • Linear probes from mean-pooled features onto physics_gt.* targets
  • Temporal-aligned window-level probing (per-window features → per-window targets)
  • Do NOT episode-mean aggregate features/targets for kinematic probing — that collapses temporal structure and produces misleading results.

Citation

TBD (paper in preparation).

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