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canyuchen
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embodied-science-exam-renders

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Tags:
robotics
embodied-ai
science
mujoco
blender
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
suite: string
task: string
source: string
renderer: string
rendering: string
width: int64
height: int64
fps: int64
speed: double
success_check: bool
image: string
row: string
group: string
arm: string
family: string
source_commit: string
source_label: string
instance: string
note: string
why_fewer: string
teaser: string
highlights: list<item: string>
  child 0, item: string
to
{'teaser': Value('string'), 'highlights': List(Value('string')), 'why_fewer': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              suite: string
              task: string
              source: string
              renderer: string
              rendering: string
              width: int64
              height: int64
              fps: int64
              speed: double
              success_check: bool
              image: string
              row: string
              group: string
              arm: string
              family: string
              source_commit: string
              source_label: string
              instance: string
              note: string
              why_fewer: string
              teaser: string
              highlights: list<item: string>
                child 0, item: string
              to
              {'teaser': Value('string'), 'highlights': List(Value('string')), 'why_fewer': Value('string')}
              because column names don't match

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Embodied Science Exam (ESciE): cinematic renders

Path-traced videos of ESciE v3 tasks (a robot arm doing a lab experiment end to end, measuring a physical or chemical quantity). Each video is a faithful replay of a recorded run of the task family's reference solution, re-lit and re-framed for viewing. Work in progress: tasks are added as their demonstration runs become available.

Contents

  • esci/<task>/ per task: video.mp4 (2560x1440, 30 fps, H.264 CRF 16), poster.png, meta.json. The task id is <family>_<robot>_<group>, e.g. rc_time_constant_ur5e_s1p; groups are s0 (procedure given) and s1p (goal only, paused clock).
  • esci/highlights.json: suite highlights in the exam-media format.
  • check_media_esci.txt: output of the exam-media standard v2 checker on esci/ (0 failing).

How the videos were made

  1. Run. The reference solution (oracle) on a public demonstration instance of the task, never the instance the task is scored on. meta.json names the row, group, robot and source commit only.
  2. Replay. The run's recorded commands are re-executed with the rsb package at that commit and the task image's pins (numpy 2.2.6, scipy 1.15.3, MuJoCo 3.3.7), exactly as the verifier does: verifier success and replay match (success_check: true).
  3. Poses and instruments. Body poses of every 20 ms control tick are written into Blender as keyframes; nothing is simulated in Blender. Instrument displays (a meter's LCD) and liquid levels are drawn from the run's own state at every tick.
  4. Render. Blender 4.5.14 LTS, Cycles path tracer (OptiX) on NVIDIA L40S and RTX 4090 GPUs, 64 samples adaptive (threshold 0.015), OpenImageDenoise with albedo and normal passes, AgX Medium High Contrast. Studio light; a wide 3/4 shot of the whole robot pushes in to the apparatus over the first seconds, with a slow 10 degree orbit. At high speed-ups, moving apparatus parts (a pendulum bob, a carried beaker) get whole-frame motion blur so they do not strobe; the robot stays sharp.
  5. Timing. Constant speed per task (speed in meta.json, e.g. 10x for a 6 minute experiment); first frame held 0.6 s, last 1.5 s.

Quality checks

Every video is checked frame by frame before upload: a contact sheet, whole frames at 10/50/90 %, full-resolution crops of consecutive frames wherever pixels jump and come back, and a scan for single-frame jumps across the whole video, read by a person and by an independent model reviewer.

Changelog

  • 2026-10-29 (second upload): both RC videos re-rendered. In the first upload a mounting plate under the robot base flickered (two coincident surfaces); the plate now sits just below the tabletop. The renderer also no longer reuses scene data between frames, which can swap materials for a single frame. Added pendulum_lab_g_ur5e_s0 and neutralisation_enthalpy_ur5e_s1p.
  • 2026-10-29 (first upload): rc_time_constant_ur5e_s0, rc_time_constant_ur5e_s1p.
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