| --- |
| license: apache-2.0 |
| tags: [robotics, lerobot, real-robot] |
| --- |
| |
| # shell_game — delta EEF, per-frame subtask |
| |
| Cups hide a red block, the cups are shuffled by hand, and the arm lifts the cup the block ended |
| under. 45 episodes, 18,442 frames. |
| |
| Delta EEF, 10-dim. Six sentences, assigned per frame: |
| |
| ``` |
| observe 6,051 frames |
| uncover the left cup 2,203 |
| uncover the middle cup 1,517 |
| uncover the right cup 1,848 |
| move the red cube into the basket 6,823 |
| ``` |
| |
| Labels are derived from state, never from the video: the gripper separates cup (closure |
| 0.120-0.200) from cube (0.440-0.460) with no overlap and exactly two grasps in 45 of 45 |
| episodes, and the cup is read off cartesian y, which is 3-modal. They agree with the human |
| collection sheet on 44 of 45; the one disagreement is an episode where the operator lifted the |
| wrong cup. |
| |
| Which cup to uncover cannot be derived from the current frame — the shuffle has already |
| happened and every cup looks alike. That is the point of the task, and it is why a planner |
| trained on this needs memory rather than perception. |
| |
| Converted from the recorder's DROID-schema `teleoperation.h5`, one episode per directory, with |
| the videos re-encoded all-intra. The raw h5 is the source of record and lives at |
| `ghkim-rlwrld/shell_game`; anything that needs a different action representation or a fresh label |
| pass has to go back to it, not to this tree. |
|
|
| Cameras are three stereo pairs and only the left eye is shipped here, which is what a policy |
| reading three streams actually loads: |
|
|
| ``` |
| 11845904 wrist looks down over the gripper |
| 37149196 cam_ext_left external, to the robot's left |
| 34022131 cam_ext_right external, to the robot's right |
| ``` |
|
|
| Control rate is 9.2 Hz measured. The mp4 containers say 10 fps and are wrong. |
|
|
| ### Naming |
|
|
| `<task>_<action space>_<language>`. An earlier set of names took the action space from one |
| dataset and the language from another, so they could not be compared side by side. |
|
|
| | | action | language | |
| |---|---|---| |
| | `shell_game_joint_global` | 7 joints + gripper (8) | one sentence per episode | |
| | `shell_game_eef_global` | delta EEF, xyz + rot6d + gripper (10) | one sentence per episode | |
| | `shell_game_eef_subtask` | delta EEF (10) | per-frame subtask | |
| | `solve_equation_eef_subtask` | delta EEF (10) | per-frame subtask | |
|
|
| ### Why rot6d and not rpy |
|
|
| This recorder's roll sits at +-pi and flips sign 269 times across the 45 shell_game episodes. |
| Regressing the raw angle puts a 2*pi step in the target at every flip. Unwrapping and moving to |
| the first two columns of the rotation matrix leaves 0 discontinuities and takes the roll channel |
| from std 3.08 to 0.039. The delta mask is `(9, -1)`: position and rotation relative to the |
| current state, gripper absolute. |
| |
| A runtime that wants 7-dim xyz+rpy can recover it exactly — Gram-Schmidt the two 3-vectors, take |
| the third by cross product, then `as_euler("xyz")`, verified to 4.44e-16 over 41 episodes. Doing |
| that at inference is safe; training on rpy is not, for the reason above. |
|
|
