HapticWAM — ICRA 2027
Collection
Teacher, student, baselines, ablations and data. Paper: arxiv.org/abs/2609.23888 - code: github.com/Advanced-Robotic-Manipulation/HapticWAM • 10 items • Updated
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 80, in _split_generators
raise ValueError(
...<2 lines>...
)
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
HapticWAM — simulation episodes
HapticWAM: Distilling Imagined Touch into a World-Action Model without Inference-Time Tactile Sensing — paper arXiv:2609.23888, submitted to ICRA 2027. Code: github.com/Advanced-Robotic-Manipulation/HapticWAM · all repos: HapticWAM — ICRA 2027.
Isaac Sim episodes for HapticWAM (Haptic World-Action Model), the tactile world-action model built on Cosmos-Predict2.5-2B: a tactile-conditioned teacher whose imagined contact future is distilled into a pad-free student. Scene: UR3 CB3 + Robotiq 2F gripper with the custom tactile pads, optical table, gridded mat, packet and collection bin, with calibrated D435 geometry.
Renamed from
armteam/phantom-sim-episodeson 2026-09-19, when the project's working name PHANTOM became HapticWAM. The old id still redirects. The Python package and CLI keep the namephantom, so checkpoint names, config keys and run names are unchanged.
Layout
| Path | What |
|---|---|
sim_expert_20260912/ |
first sim-expert collection — index.jsonl, norm_stats_v6.json, raw_trials/*.tar |
sim_expert_20260914/ |
second collection, incl. the flattened tasks/ view and aside_duplicates/ |
Each raw_trials/*.tar is one trial export; _canonical_assets.tar holds the shared scene
assets. index.jsonl carries one JSON record per trial.
Part of the HapticWAM release
Ten repos on the hub, gathered in the HapticWAM — ICRA 2027 collection.
| Repo | Kind | Holds |
|---|---|---|
armteam/hapticwam-teacher |
model | the tactile-input teacher. Deployed checkpoint teacher_v6_simft/teacher_002000.pt; also holds the Cosmos prompt cache text_embeddings.pt |
armteam/hapticwam-student |
model | the distilled pad-free student, the model that runs on the rig. Deployed checkpoint hid_simft/student_001000.pt |
armteam/hapticwam-baselines |
model | the pi0.5, Diffusion Policy and X-VLA baselines at the deployed steps |
armteam/hapticwam-ablations |
model | every training arm that is not deployed, and the complete evaluation sweeps |
armteam/hapticwam-teleop-dataset |
dataset | the training corpus — 1,115 teleoperated episodes, packed per task |
armteam/hapticwam-teleop-raw |
dataset | the same teleoperation as loose, as-recorded sessions (provenance) |
armteam/hapticwam-sim-episodes ← you are here |
dataset | Isaac Sim expert episodes, used for the sim fine-tune |
armteam/hapticwam-rig-episodes |
dataset | the closed-loop rig takes the reported numbers are computed from |
armteam/hapticwam-rollouts |
dataset | policy-driven rollouts — the DAgger rounds and the deploy days |
armteam/hapticwam-results |
dataset | archived result media — videos, plots, evidence |
Code, training and deployment scripts: github.com/Advanced-Robotic-Manipulation/HapticWAM.
Schema
One directory per episode: meta.json plus one zarr group per stream, each holding a
data array (T, …) and a ts array (T,) of master-clock seconds. Every stream keeps
its own T and its own timestamps — nothing is resampled onto a common grid — so align by
nearest ts (observations) or first ts >= t (future targets).
| Stream | Shape | dtype | Rate | Meaning |
|---|---|---|---|---|
tactile_{left,right}_fields_ds |
(T, 72, 96, 8) |
f16 | ~5.7 Hz | tactile field stack, channels [disp_x, disp_y, depth, shear_x, shear_y, fx, fy, fz]; depth and the distributed force fx,fy,fz are in raw SDK units (uncalibrated) |
tactile_{left,right}_keyframes |
(T, 144, 192, 8) |
f16 | ~2.5 Hz | the same 8 channels at higher spatial resolution, time-decimated |
tactile_{left,right}_infer_img |
(T, 288, 384) |
u8 | ~5.7 Hz | the SDK's gel image (getInferImg) |
tactile_{left,right}_wrench |
(T, 6) |
f32 | ~5.7 Hz | pad wrench [Fx, Fy, Fz, Mx, My, Mz], N and N·m (SI: the SDK's 1e−2 N·m torques are scaled at the driver boundary) |
tactile_{left,right}_area |
(T,) |
f32 | ~5.7 Hz | contact area, mm² |
arm_q, arm_qd |
(T, 6) |
f64 | 125 Hz | joint position (rad), joint velocity (rad/s) |
arm_tcp_pose, arm_tcp_speed |
(T, 6) |
f64 | 125 Hz | TCP pose [x, y, z, rx, ry, rz] (m + rotation vector, base frame) and twist |
arm_ft |
(T, 6) |
f64 | 125 Hz | wrist wrench, N / N·m — on this CB3 arm a current-based estimate with a large pose-dependent bias, not a real F/T sensor |
gripper |
(T, 2) |
f32 | ~95 Hz | [position, obj]: closure 0 (open) … 1 (closed), and the Robotiq gOBJ status 0..3 (2 = stopped by contact while closing, i.e. holding) |
camera_scene_color |
(T, 480, 640, 3) |
u8 | 15 Hz | scene RGB, JPEG-encoded per frame (quality 92) in a zarr VLenBytes object array; the group's attrs carry encoding, frame_shape, frame_dtype, jpeg_quality |
actions |
(T, 7) |
f32 | 10 Hz | the canonical action: Δ-EE pose step [Δx, Δy, Δz, Δrx, Δry, Δrz] (m, rotation-vector rad) + commanded gripper closure |
actions_abs |
(T, 7) |
f32 | 10 Hz | absolute command [q_target(6) rad, gripper] |
Rates are what the rig actually achieved (the tactile SDK free-runs below its 8 Hz cap);
use ts, never an assumed rate. A stream that produced no samples has no directory at all,
so check before you read: a pad-free deploy (tag padfree:on) has no tactile_* streams,
simulation exports and most deploy takes have no actions_abs (and sim adds contact_gt),
and a re-derived policy rollout adds actions_plan (the executor's pre-clamp proposal).
meta.json carries task, text, operator, tags, policy, dagger_round,
success, damage, notes, driver_modes, clock_calibration, config_hash,
hardware_shapes, deploy_overrides, status and weight. It is authoritative for
task and labels — directory names are not. status must be finalized for an episode to
be trainable; success, the deliberate_failure tag and a _fail task name each zero the
action-imitation loss.
Full schema — every field, unit, threshold, the time base and a runnable "read one
episode" snippet — is docs/dataset_schema.md in the code repository.
Packaging
- Packed, one tar per episode.
tasks/<task>/<unit>.tarandaside_duplicates/<unit>.tarare single episodes (~100–200 MB, ~429 members), members rooted at the episode directory.raw_trials/*.tarare whole campaigns / raw trial exports and_canonical_assets.tarthe shared scene assets. - Each set's
index.jsonlis a genuine unit → tar index, one JSON object per unit with the columnsset,unit,tar,bytes,members,sha256, and for episode units alsotask,success,status. samples/holds one complete episode, extracted verbatim from its tar (seesamples/README.md).- Sim-only differences: the
pads_maskedtag (no gel model — thetactile_*streams are idle rows tiled from a real episode) and the extra streamcontact_gt(T, 3)=[any pad in contact, left N, right N], from which the loader takes contact events and the gate instead.
hf download armteam/hapticwam-sim-episodes sim_expert_20260914/index.jsonl \
--repo-type dataset --local-dir . # then fetch exactly the unit's tar
# one episode, resolved to the single archive that holds it, from a code checkout
python tools/hub/fetch_episode.py --dataset sim --episode first
python tools/hub/fetch_episode.py --dataset sim --episode first --samples # the sample
Licence
Data: CC-BY-4.0. The HapticWAM code and the model weights in the repos above: Apache-2.0.
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