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RoboDojo keyframe memory annotations
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metadata
license: apache-2.0
task_categories:
  - robotics
tags:
  - robodojo
  - annotations

RoboDojo progress annotations

Frame-level labels over the official RoboDojo episodes, for the six tasks that require remembering something seen earlier in the episode. They carry no images, states, actions or episodes; the observations and actions a policy trains on come from RoboDojo-Benchmark/Robodojo.

Published so that the training recipe behind our RoboDojo entry can be run by anyone: without these labels the keyframe-memory stage has nothing to learn from.

What is in it

600 files, <task>/trajectory_<n>/progress.json, covering all 100 episodes of each of the six tasks. Plus index.json, which maps each task directory to the official task instruction and states the schema.

field meaning
keyframes the frames at which the task made visible progress that has to be remembered
meta[].frame / meta[].box [x1, y1, x2, y2] in raw-video pixels, the object that progress was about
meta[].window [first, last] — the frames at which recording that keyframe still counts as correct
total_frames the episode's length, so a file can be checked against the episode it describes

meta[].window exists because a keyframe is a moment, not a frame: several consecutive frames show the same progress, so a selector that answers one frame early is not wrong. Training scores the answer against the whole interval rather than against a single index.

Per-task shape

task episodes keyframes each boxes each acceptance intervals each
cover_blocks 100 4 — —
imitate_sorting_sequence 100 5 5 —
match_and_pick_from_conveyor 100 1 — 1
press_by_number 100 5–21 — —
swap_T 100 1 — —
swap_blocks 100 7 — 1

Where a task has no acceptance interval, the selection answer is scored against the single annotated candidate.

swap_T and match_and_pick_from_conveyor carry one keyframe, at frame 0: what has to be remembered is the initial position and orientation of the two blocks, and the first object on the conveyor. Both are visible at the start.

Checking them against the official episodes

An annotation bound to the wrong episode would train a policy to recall the wrong frames. Each file therefore records its episode's length; the loader binds by task instruction and stops if a length disagrees.

How they were produced

For each task we decided by hand what counts as a keyframe — the moments at which the task makes the progress a policy has to remember, such as a block being covered or a button press being committed. A script then located the frames that satisfy the rule in each episode, and every file was checked by a person and corrected where the script had put a frame in the wrong place.

Using them

hf download x-square-robot/robodojo-memory-annotations --repo-type dataset \
    --local-dir <bench_root>/data/robodojo_memory_annotations

The training code that reads them is in wall-x (wall_x/data/backends/lerobot/robodojo/); see the WallX policy README in XPolicyLab for the two training stages.