| --- |
| license: apache-2.0 |
| viewer: false |
| --- |
| |
| # Synthetic bimanual manipulation demonstrations |
|
|
| Bimanual demonstrations collected in simulation on **procedurally generated |
| assets**: four drawers and two test-tube racks, 1 000 episodes each. |
|
|
| - **Drawer:** the right arm opens a drawer, the left arm picks up a tomato and |
| places it inside, the right arm pushes the drawer shut. |
| - **Tube into rack:** the right arm picks up a test tube and hands it to the |
| left arm, which inserts it into a well of the rack. |
|
|
| Trajectories are synthesised by an action graph driving IK and time-optimal |
| motion planning — no teleoperation, no reinforcement learning. Every episode is |
| one the simulator scored as a success. |
|
|
| ## Contents |
|
|
| | directory | episodes | frames | size | attempts | yield | |
| |---|---|---|---|---|---| |
| | `drawer_ep0_v2/` | 1 000 | 425 000 | 17.9 GB | 1 024 | 97.5 % | |
| | `drawer_ep0/` | 1 000 | 425 000 | 17.8 GB | 1 075 | 92.6 % | |
| | `drawer_ep0_v2_var4/` | 1 000 | 425 000 | 17.4 GB | 1 374 | 72.6 % | |
| | `drawer_v2_variant/` | 1 000 | 425 000 | 18.7 GB | 1 124 | 88.9 % | |
| | `sample_loading_twin/` | 1 000 | 372 000 | 11.3 GB | 1 095 | 91.3 % | |
| | `sample_loading_var1/` | 1 000 | 372 000 | 10.5 GB | 1 148 | 87.1 % | |
|
|
| 6 000 episodes, 2.44 M frames, ~94 GB. *Yield* is episodes saved per trajectory |
| attempted, from the collection logs. |
|
|
| All six use the same settings: full domain randomisation (16 events — lighting, |
| camera intrinsics and extrinsics, materials, robot initial pose, object poses), |
| distractor objects present in every episode, each asset at its own true |
| scale, 640×480 cameras. |
|
|
| ## Format |
|
|
| LeRobot v3.0, 25 fps, 14-DoF bimanual arm. 425 frames per drawer episode, 372 |
| per rack episode. |
|
|
| | key | shape | contents | |
| |---|---|---| |
| | `observation.state` | `[14]` | joint positions | |
| | `observation.qvel` | `[14]` | joint velocities | |
| | `observation.qf` | `[14]` | joint forces — **all zero, never written by the simulator** | |
| | `action` | `[14]` | absolute joint targets | |
| | `observation.images.cam_high` | `[480, 640, 3]` | overhead camera | |
| | `observation.images.cam_left_wrist` | `[480, 640, 3]` | left wrist camera | |
| | `observation.images.cam_right_wrist` | `[480, 640, 3]` | right wrist camera | |
| | `duck_pose`, `drawer_pose` | `[4, 4]` | drawer sets: object poses; `drawer_pose` is **all zero** | |
| | `rack_pose`, `cube_pose` | `[4, 4]` | rack sets: rack and tube poses | |
|
|
| Joint order is `[left_arm(6), left_gripper(1), right_arm(6), right_gripper(1)]`. |
| Grippers are normalised to `[0, 1]`. |
|
|
| Videos are **concatenated per chunk**, not per episode — one mp4 per camera holds |
| many episodes. Episode boundaries live in `meta/episodes/` |
| (`from_timestamp` / `to_timestamp` for video, `dataset_from_index` / |
| `dataset_to_index` for the parquet). This is normal for LeRobot v3.0. |
|
|
| ## Usage |
|
|
| ```bash |
| hf download <this-repo> --repo-type dataset \ |
| --include "drawer_ep0_v2/*" --local-dir ./data |
| ``` |
|
|
| ACT and Diffusion Policy read v3.0 directly; PI0 / PI0.5 need a v2.1 conversion |
| first. Training needs nothing but this data — the reference policy adapters read |
| images, joint state and joint targets, never a URDF or a scene config. Simulation |
| assets are published under `assets/` for anyone who wants to *evaluate* a policy |
| in these scenes. |
|
|
| **Merging these files needs a patch.** Stock LeRobot dataset merging fails on |
| them: the 4×4 pose features come back from HuggingFace `datasets` as an |
| extension arrays that `pd.concat` cannot hash. Sanitise such columns to nested |
| lists at every read / write / concat boundary first. |
|
|
| ## The assets |
|
|
| | asset | handle | bar (L × H) | hook gap | tray W | travel | cabinet H | |
| |---|---|---|---|---|---|---| |
| | `drawer_ep0_v2` | protruding bar | 130 × 16 mm | 3.1 mm | 195 mm | 180 mm | 90 mm | |
| | `drawer_ep0` | protruding bar | 130 × 14 mm | 2.0 mm | 195 mm | 245 mm | 90 mm | |
| | `drawer_ep0_v2_var4` | protruding bar | 169 × 16 mm | 3.1 mm | 195 mm | 170 mm | 67 mm | |
| | `drawer_v2_variant` | protruding bar | 208 × 20 mm | 2.1 mm | 312 mm | 125 mm | 130 mm | |
|
|
| "Bar H" includes the end caps; the bar itself is 7–9 mm thick on all four. |
|
|
| Everything downstream of the mesh is derived rather than hand-tuned: the grasp |
| point, the collision decomposition, the cabinet's placement, the pull distance, |
| the place target and the release point all come from the geometry. The two |
| generators are published under `assets/scripts/`. |
|
|
| Three quantities were originally fixed constants copied from a reference drawer, |
| and each had to become a derived rule before the generated assets worked: |
|
|
| - **Pull distance.** A single hard-coded value for every drawer, regardless of |
| its rail travel — any drawer with less usable travel jammed against its stop. |
| - **Grasp point.** "2 mm behind the handle bar" assumes room behind the bar for |
| the fingertips. One drawer has 2.1 mm of gap; its fingertip hit the door panel, |
| the close stalled, and the bar slipped out on the pull. The rule now keeps 4 mm |
| of clearance from the panel, a property of the gripper rather than the drawer. |
| - **Release point.** The gripper opens at a node that carried literal offsets |
| `x = 0.18, z = 0.14`. Against one drawer's tray that sat 25 mm from the front |
| lip — the tomato is 50 mm across — and 17 mm above the rim, so the tomato |
| settled in or toppled out depending on the pose randomisation. Anchoring it in |
| the closed frame (`|pull| + 40 mm`, tray centre, rim + 74 mm) took that asset's |
| yield from 55 % to 89 %. |
|
|
| A fourth trap was not a constant but a decomposition setting: convex |
| decomposition thresholds are relative to the whole input mesh, so a 7 mm handle |
| bar on a 200 mm tray fell below the threshold and came back merged with its end |
| caps as a single hull up to 34 mm thick. The gripper closed on that hull and the |
| finger pads sat ~4 mm clear of the visible bar in every wrist-camera frame. |
| Decomposing the handle separately fixes it. |
|
|
| ## The racks |
|
|
| | asset | size (L × W × H) | wells | well opening | tube clearance | plates | |
| |---|---|---|---|---|---| |
| | `sample_loading_twin` | 275 × 116 × 79 mm | 5 × 12 | 18.5 mm | 1.7 mm | 3 | |
| | `sample_loading_var1` | 232 × 128 × 95 mm | 4 × 7 | 20 mm | 3.2 mm | 3 | |
|
|
| The twin was generated from a frame of a real rack; the variant is the same |
| parametric model with its dimensions and well grid changed. The tube is 16.8 mm |
| across and 195 mm long. Published under `assets/rack_twin/` and |
| `assets/rack_var1/`. |
|
|
| Three things had to be right before the insertion worked: |
|
|
| - **Three plates, not two.** A tube only stands upright when it passes through |
| two guide plates; the lean it can take is clearance / plate spacing. With a |
| single well plate it leaned 20–45° and failed the 10° fall check every time. |
| - **Aim at a well on both axes.** An even well count leaves a web, not a well, |
| on the centreline. The insertion offset is the nearest well centre along the |
| length *and* across the width. |
| - **Aim the tube, not the gripper.** After the hand-over the tube sits 1–5° off |
| the gripper's nominal axis, differently every episode, so its tip — 97 mm |
| below its centre — is up to 6 mm off. Successes had 1.2° and 3.2° in hand, |
| failures 3.5° and 4.6°. Once the hand-over is finished the tube's actual pose |
| in the gripper is read and the remaining left-arm waypoints are re-solved so |
| the tube is vertical over the well. Yield went from about 45 % to 91 % on the |
| twin and from about 73 % to 87 % on the variant. |
|
|
| ## What limits yield |
|
|
| `drawer_ep0_v2_var4` is the weakest at 72.6 %, and the cause is known but |
| unfixed: **over-travel into the hard stop**, not push-back timing. Tracing the |
| push shows it finishing with 31 of its 50 steps to spare, while peak joint travel |
| is bimodal — either ~0.130 or exactly 0.1697, its limit — and after hitting that |
| stop the drawer rebounds. Reducing the pull does not help: at pull fractions |
| 0.80 / 0.70 / 0.60 the yields are 83 % / 80 % / 15 %, since a short pull leaves |
| the tomato outside the success radius once the drawer is closed. |
|
|
| Episodes here are survivors of a success filter, not a uniform sample. |
|
|
| ## Caveats |
|
|
| - `observation.qf` (all sets) and `drawer_pose` (drawer sets) are declared in |
| the schema but are **identically zero**. The simulator never writes them. |
| - These are simulation episodes only. |
| - A fifth asset, `drawer_walnut`, is published under `assets/` but has no |
| episodes: its handle is a recessed pull whose pocket opening is 70 × 22 mm, and |
| the gripper's fingers separate up to 100 mm. No wrist orientation fits. That is |
| an end-effector mismatch, not a planning failure. |
|
|
