Datasets:
Complete verified EEF companion release with explicit action semantics and reader
Browse files- .gitattributes +1 -0
- README.md +62 -0
- dataset_info.json +10 -1
- eef/episodes.jsonl +3 -0
- eef/info.json +27 -0
- eef/models.json +868 -0
- eef/reader.py +99 -0
- eef/shards.jsonl +268 -0
- eef/statistics.json +1034 -0
.gitattributes
CHANGED
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@@ -59,3 +59,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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*.webm filter=lfs diff=lfs merge=lfs -text
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metadata/episode_outcomes.jsonl filter=lfs diff=lfs merge=lfs -text
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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*.webm filter=lfs diff=lfs merge=lfs -text
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metadata/episode_outcomes.jsonl filter=lfs diff=lfs merge=lfs -text
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+
eef/episodes.jsonl filter=lfs diff=lfs merge=lfs -text
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README.md
CHANGED
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@@ -137,6 +137,68 @@ The archive members contain the exported video and state/action bytes. Episode m
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reduced to public data fields. `dataset_info.json` summarizes the release and `shards.jsonl`
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lists archive sizes, episode counts, and SHA-256 checksums.
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## Source and license
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Upstream sources are [X-Humanoid/RoboMIND2.0-Agilex](https://modelscope.cn/datasets/X-Humanoid/RoboMIND2.0-Agilex),
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reduced to public data fields. `dataset_info.json` summarizes the release and `shards.jsonl`
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lists archive sizes, episode counts, and SHA-256 checksums.
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+
## EEF action/state companions
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The optional `eef/` companion release covers every episode in this processed subset,
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using the same stable `episode_id` and exactly the same retained video frames. The
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original joint binaries and videos remain available. Companion TARs contain
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`<episode_id>.npz` arrays and `<episode_id>.json` frame/pose provenance.
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`state_pose` is `[T, 2, 7]` float32: XYZ in metres followed by quaternion **xyzw**,
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left arm then right arm. `command_pose` uses the same layout; when a recorded command
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stream exactly copies the state, the array is stored once and the metadata declares
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the alias. Gripper arrays use **0 = closed, 1 = open**. Boolean pose and gripper masks
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must be respected. `source_frame_index` preserves the video-to-source row mapping.
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Select action semantics explicitly in `eef/reader.py`:
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- `action_mode="command"`: the corresponding recorded-command pose, with no added
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timestep shift. Copied source pose commands are excluded from supervision by default.
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- `action_mode="next_state"`: the achieved state at the next retained frame, including
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gripper state. This is a derived target, not an original controller command. The
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final target is masked; do not shift it again in another loader.
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All RoboMIND EEF states and commands are calculated separately from the published
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puppet and master joint rows. Franka uses `panda_link0` to `panda_link8`; UR5e uses
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the manufacturer's nominal UR5e DH base to `tool0`; AgileX uses the dataset authors'
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`aloha_new.urdf`, verified byte-identical to the manufacturer model, from each
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`fl_base_link`/`fr_base_link` to `fl_link6`/`fr_link6`. The two arms' local base frames
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are distinct; no missing common-base or camera calibration is fabricated.
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The earlier UR5e rotation encoding discrepancy is avoided by reconstructing poses
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from the corresponding joints after diagnosis. The twelve command-review episodes
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listed above have command supervision masked out. These are nominal-model poses,
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not factory-calibrated measurements or a certificate of camera reprojection accuracy.
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Invalid AgileX native EEF fields are not used as ground truth or fitted calibration.
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The reader emits `[T, 80]` state/action arrays and masks by default, with the left
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20-D schema arm in dimensions `0:10` and the right arm in `34:44`; the unused slots
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are masked. Set `unify_action=False` for `[T, 20]`: each arm is XYZ + the first two
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rotation-matrix columns (6D rotation) + gripper. Poses use the frames named in each
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episode, not camera coordinates or a universal fingertip TCP.
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From a downloaded dataset root, join an existing episode's metadata to its companion:
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```python
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from eef.reader import load_index, load_indexed_episode
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eef_index = load_index("eef/episodes.jsonl")
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targets = load_indexed_episode(
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".", eef_index[metadata["episode_id"]], action_mode="command"
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)
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# targets["state"], targets["action"], targets["state_mask"], targets["action_mask"]
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```
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`eef/episodes.jsonl` supplies direct TAR offsets. `eef/shards.jsonl` supplies file
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sizes and SHA-256 checksums; `eef/info.json` records full coverage and verification.
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`eef/models.json` documents frames, kinematics and limitations. `eef/statistics.json`
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contains separate state, command and next-state statistics from the **training split
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only**; stored poses are unnormalized. Keep rotation-6D coordinates unnormalized.
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The portable reader matches the OpenWAM pose layout; integrating these companions
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with a training pipeline's video/window reader is still required. The original
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OpenWAM LeRobot reader does not directly consume these WebDataset companions.
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## Source and license
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Upstream sources are [X-Humanoid/RoboMIND2.0-Agilex](https://modelscope.cn/datasets/X-Humanoid/RoboMIND2.0-Agilex),
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dataset_info.json
CHANGED
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@@ -47,5 +47,14 @@
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"hours": 33.24141068607515
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}
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],
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-
"format": "WebDataset tar shards; one .mp4, .bin and .json per episode"
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}
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"hours": 33.24141068607515
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}
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],
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"format": "WebDataset tar shards; one .mp4, .bin and .json per episode",
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"eef": {
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"info": "eef/info.json",
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"episodes": 134537,
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"frames": 42559113,
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"bytes": 4257792000,
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"index": "eef/episodes.jsonl",
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"reader": "eef/reader.py",
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"verified": true
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}
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}
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eef/episodes.jsonl
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:b4bc2cfa6adc63ab6e7aec753182145308c3927651ffee2430c29a3436f10865
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size 35413669
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eef/info.json
ADDED
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@@ -0,0 +1,27 @@
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{
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"schema_version": 1,
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"episodes": 134537,
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"frames": 42559113,
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"shards": 268,
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"bytes": 4257792000,
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"counts": {
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"episodes": 134537,
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"frames": 42559113,
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"copied_command_episodes": 0,
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"unresolved_sparse_command_episodes": 0,
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"command_review_episodes": 12,
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"state_invalid_arm_frames": 0,
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"command_invalid_arm_frames": 3654
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},
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"coverage_complete": true,
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"all_shards_checksum_verified": true,
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"all_frames_pose_schema_verified": true,
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"data_index": "eef/episodes.jsonl",
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"shard_manifest": "eef/shards.jsonl",
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"statistics": "eef/statistics.json",
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"reader": "eef/reader.py",
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"pose_format": "float32 XYZ metres + xyzw quaternion, [frames,2,7]",
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"actions": "Recorded-command poses remain separate from explicitly derived next-state targets. Select action_mode in the reader.",
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"camera_reprojection_validation": "Not certified across the dataset. RoboMIND poses are nominal-model FK, with explicit per-arm base and terminal-arm frame names.",
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"models": "eef/models.json"
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}
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eef/models.json
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|
|
| 1 |
+
{
|
| 2 |
+
"schema_version": 1,
|
| 3 |
+
"position_units": "metres",
|
| 4 |
+
"quaternion_order": "xyzw",
|
| 5 |
+
"endpoint_contract": "Rigid terminal-arm attachment independent of finger articulation; no universal gripper-centre TCP",
|
| 6 |
+
"per_episode_frame_names": "base_frames and endpoints in each companion JSON",
|
| 7 |
+
"camera_geometry": "Existing per-view camera metadata remains separate. Reprojection is not certified across all episodes.",
|
| 8 |
+
"Franka": {
|
| 9 |
+
"base_frames": [
|
| 10 |
+
"left:panda_link0",
|
| 11 |
+
"right:panda_link0"
|
| 12 |
+
],
|
| 13 |
+
"endpoints": [
|
| 14 |
+
"left:panda_link8",
|
| 15 |
+
"right:panda_link8"
|
| 16 |
+
],
|
| 17 |
+
"source": "https://github.com/Open-X-Humanoid/RoboMIND-dataset-utils/blob/77d7b311cbf2f16624c941f46b2a75042858ff06/eepose/urdf/franka/panda.urdf",
|
| 18 |
+
"sample_comparison_to_recorded_state": {
|
| 19 |
+
"position_rms_m": 0.0004936879709087665,
|
| 20 |
+
"rotation_rms_rad": 0.0009590865981782139,
|
| 21 |
+
"pose_probes": 8192
|
| 22 |
+
},
|
| 23 |
+
"chains": [
|
| 24 |
+
{
|
| 25 |
+
"base": "panda_link0",
|
| 26 |
+
"tip": "panda_link8",
|
| 27 |
+
"joint_names": [
|
| 28 |
+
"panda_joint1",
|
| 29 |
+
"panda_joint2",
|
| 30 |
+
"panda_joint3",
|
| 31 |
+
"panda_joint4",
|
| 32 |
+
"panda_joint5",
|
| 33 |
+
"panda_joint6",
|
| 34 |
+
"panda_joint7"
|
| 35 |
+
],
|
| 36 |
+
"transforms": [
|
| 37 |
+
{
|
| 38 |
+
"origin": [
|
| 39 |
+
[
|
| 40 |
+
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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],
|
| 45 |
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[
|
| 46 |
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|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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],
|
| 51 |
+
[
|
| 52 |
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|
| 53 |
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|
| 54 |
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|
| 55 |
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|
| 56 |
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],
|
| 57 |
+
[
|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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],
|
| 64 |
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"axis": [
|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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],
|
| 69 |
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"joint_index": 0,
|
| 70 |
+
"type": "revolute"
|
| 71 |
+
},
|
| 72 |
+
{
|
| 73 |
+
"origin": [
|
| 74 |
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[
|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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[
|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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| 100 |
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|
| 101 |
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|
| 102 |
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|
| 103 |
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],
|
| 104 |
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"joint_index": 1,
|
| 105 |
+
"type": "revolute"
|
| 106 |
+
},
|
| 107 |
+
{
|
| 108 |
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"origin": [
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| 109 |
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| 110 |
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|
| 111 |
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|
| 112 |
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| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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|
| 117 |
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|
| 118 |
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|
| 119 |
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|
| 120 |
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|
| 121 |
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| 122 |
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|
| 123 |
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|
| 124 |
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|
| 125 |
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| 126 |
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| 127 |
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| 128 |
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| 129 |
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|
| 132 |
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|
| 133 |
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|
| 134 |
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| 135 |
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| 136 |
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|
| 137 |
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|
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|
| 139 |
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"joint_index": 2,
|
| 140 |
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|
| 141 |
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|
| 142 |
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{
|
| 143 |
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| 144 |
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| 145 |
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|
| 148 |
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|
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|
| 150 |
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| 151 |
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|
| 152 |
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|
| 153 |
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|
| 154 |
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|
| 155 |
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| 156 |
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| 157 |
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|
| 158 |
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|
| 159 |
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|
| 160 |
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| 161 |
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| 162 |
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[
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| 163 |
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| 164 |
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| 165 |
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| 166 |
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|
| 167 |
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|
| 168 |
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|
| 169 |
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| 170 |
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|
| 171 |
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|
| 172 |
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|
| 173 |
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],
|
| 174 |
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"joint_index": 3,
|
| 175 |
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"type": "revolute"
|
| 176 |
+
},
|
| 177 |
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{
|
| 178 |
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| 179 |
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| 180 |
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| 183 |
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|
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|
| 185 |
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| 186 |
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|
| 187 |
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|
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|
| 189 |
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|
| 190 |
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|
| 191 |
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[
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| 192 |
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|
| 193 |
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|
| 194 |
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|
| 195 |
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|
| 197 |
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[
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|
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|
| 203 |
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|
| 204 |
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| 205 |
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|
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|
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],
|
| 209 |
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"joint_index": 4,
|
| 210 |
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"type": "revolute"
|
| 211 |
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},
|
| 212 |
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{
|
| 213 |
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| 214 |
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|
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"fr_joint5",
|
| 650 |
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"fr_joint6"
|
| 651 |
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],
|
| 652 |
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"transforms": [
|
| 653 |
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{
|
| 654 |
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|
| 655 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
| 667 |
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[
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|
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|
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|
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|
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],
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|
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|
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|
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| 681 |
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|
| 682 |
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|
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|
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|
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"joint_index": 0,
|
| 686 |
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|
| 687 |
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},
|
| 688 |
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{
|
| 689 |
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|
| 690 |
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|
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|
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|
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|
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| 696 |
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[
|
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|
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1.349240164039145e-11,
|
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|
| 700 |
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[
|
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|
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|
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|
| 706 |
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0.0
|
| 707 |
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|
| 708 |
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[
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| 709 |
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1.0
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]
|
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],
|
| 715 |
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"axis": [
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| 716 |
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| 717 |
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|
| 718 |
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1.0
|
| 719 |
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],
|
| 720 |
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"joint_index": 1,
|
| 721 |
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"type": "revolute"
|
| 722 |
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},
|
| 723 |
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{
|
| 724 |
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"origin": [
|
| 725 |
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[
|
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|
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|
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|
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|
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[
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|
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],
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[
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|
| 739 |
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|
| 740 |
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1.0,
|
| 741 |
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0.0
|
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],
|
| 743 |
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[
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|
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0.0,
|
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1.0
|
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]
|
| 749 |
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],
|
| 750 |
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"axis": [
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0.0,
|
| 752 |
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0.0,
|
| 753 |
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1.0
|
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],
|
| 755 |
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"joint_index": 2,
|
| 756 |
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"type": "revolute"
|
| 757 |
+
},
|
| 758 |
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{
|
| 759 |
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"origin": [
|
| 760 |
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[
|
| 761 |
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0.18708737400939277,
|
| 762 |
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3.6083483395121796e-06,
|
| 763 |
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-0.9823432773085228,
|
| 764 |
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-0.24221
|
| 765 |
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],
|
| 766 |
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[
|
| 767 |
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0.9823432773151499,
|
| 768 |
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-6.872102970567617e-07,
|
| 769 |
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0.18708737400813064,
|
| 770 |
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0.068514
|
| 771 |
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],
|
| 772 |
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[
|
| 773 |
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0.0,
|
| 774 |
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-0.9999999999932536,
|
| 775 |
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-3.673205103360555e-06,
|
| 776 |
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0.0
|
| 777 |
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],
|
| 778 |
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[
|
| 779 |
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0.0,
|
| 780 |
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0.0,
|
| 781 |
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0.0,
|
| 782 |
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1.0
|
| 783 |
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]
|
| 784 |
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],
|
| 785 |
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"axis": [
|
| 786 |
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0.0,
|
| 787 |
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0.0,
|
| 788 |
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1.0
|
| 789 |
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],
|
| 790 |
+
"joint_index": 3,
|
| 791 |
+
"type": "revolute"
|
| 792 |
+
},
|
| 793 |
+
{
|
| 794 |
+
"origin": [
|
| 795 |
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[
|
| 796 |
+
0.9999999999999999,
|
| 797 |
+
0.0,
|
| 798 |
+
0.0,
|
| 799 |
+
0.0
|
| 800 |
+
],
|
| 801 |
+
[
|
| 802 |
+
0.0,
|
| 803 |
+
-3.673205103305044e-06,
|
| 804 |
+
-0.9999999999932537,
|
| 805 |
+
0.0
|
| 806 |
+
],
|
| 807 |
+
[
|
| 808 |
+
0.0,
|
| 809 |
+
0.9999999999932537,
|
| 810 |
+
-3.673205103305044e-06,
|
| 811 |
+
0.0
|
| 812 |
+
],
|
| 813 |
+
[
|
| 814 |
+
0.0,
|
| 815 |
+
0.0,
|
| 816 |
+
0.0,
|
| 817 |
+
1.0
|
| 818 |
+
]
|
| 819 |
+
],
|
| 820 |
+
"axis": [
|
| 821 |
+
0.0,
|
| 822 |
+
0.0,
|
| 823 |
+
1.0
|
| 824 |
+
],
|
| 825 |
+
"joint_index": 4,
|
| 826 |
+
"type": "revolute"
|
| 827 |
+
},
|
| 828 |
+
{
|
| 829 |
+
"origin": [
|
| 830 |
+
[
|
| 831 |
+
-3.6732051033327995e-06,
|
| 832 |
+
0.9999999999865075,
|
| 833 |
+
3.6732051032495328e-06,
|
| 834 |
+
0.0
|
| 835 |
+
],
|
| 836 |
+
[
|
| 837 |
+
5.551115123125783e-17,
|
| 838 |
+
-3.6732051033327995e-06,
|
| 839 |
+
0.9999999999932536,
|
| 840 |
+
0.091
|
| 841 |
+
],
|
| 842 |
+
[
|
| 843 |
+
0.9999999999932536,
|
| 844 |
+
3.6732051032495328e-06,
|
| 845 |
+
1.349240164039145e-11,
|
| 846 |
+
0.0014165
|
| 847 |
+
],
|
| 848 |
+
[
|
| 849 |
+
0.0,
|
| 850 |
+
0.0,
|
| 851 |
+
0.0,
|
| 852 |
+
1.0
|
| 853 |
+
]
|
| 854 |
+
],
|
| 855 |
+
"axis": [
|
| 856 |
+
0.0,
|
| 857 |
+
0.0,
|
| 858 |
+
1.0
|
| 859 |
+
],
|
| 860 |
+
"joint_index": 5,
|
| 861 |
+
"type": "revolute"
|
| 862 |
+
}
|
| 863 |
+
]
|
| 864 |
+
}
|
| 865 |
+
],
|
| 866 |
+
"urdf_sha256": "d4a115493af6a67ef969cfb8686b54f2970225b617ec6dd99cf682c0c4c7b6e9"
|
| 867 |
+
}
|
| 868 |
+
}
|
eef/reader.py
ADDED
|
@@ -0,0 +1,99 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""Read an EEF companion and construct explicitly selected OpenWAM-style targets.
|
| 2 |
+
|
| 3 |
+
No temporal shift is applied to command actions. next_state is an explicitly
|
| 4 |
+
derived, one-retained-frame-ahead achieved-state target, with terminal masking.
|
| 5 |
+
"""
|
| 6 |
+
import io
|
| 7 |
+
import json
|
| 8 |
+
from pathlib import Path
|
| 9 |
+
import tarfile
|
| 10 |
+
|
| 11 |
+
import numpy as np
|
| 12 |
+
|
| 13 |
+
|
| 14 |
+
def load_index(path):
|
| 15 |
+
with open(path, encoding='utf-8') as stream:
|
| 16 |
+
return {row['episode_id']:row for row in map(json.loads,stream)}
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
def load_indexed_episode(dataset_root, record, *, action_mode, unify_action=True, allow_copied_commands=False):
|
| 20 |
+
with (Path(dataset_root)/record['shard']).open('rb') as stream:
|
| 21 |
+
stream.seek(record['json_offset']);metadata=json.loads(stream.read(record['json_bytes']))
|
| 22 |
+
stream.seek(record['npz_offset']);data=stream.read(record['npz_bytes'])
|
| 23 |
+
if metadata['episode_id']!=record['episode_id']:
|
| 24 |
+
raise ValueError('EEF episode index does not match shard contents')
|
| 25 |
+
with np.load(io.BytesIO(data),allow_pickle=False) as archive:
|
| 26 |
+
arrays={key:archive[key] for key in archive.files}
|
| 27 |
+
result=build_arrays(arrays,metadata,action_mode=action_mode,unify_action=unify_action,
|
| 28 |
+
allow_copied_commands=allow_copied_commands)
|
| 29 |
+
result['metadata']=metadata
|
| 30 |
+
return result
|
| 31 |
+
|
| 32 |
+
|
| 33 |
+
def _pose20(pose, grip, pose_valid, grip_valid):
|
| 34 |
+
q = pose[..., 3:7]
|
| 35 |
+
x, y, z, w = np.moveaxis(q, -1, 0)
|
| 36 |
+
col0 = np.stack([1-2*(y*y+z*z), 2*(x*y+z*w), 2*(x*z-y*w)], axis=-1)
|
| 37 |
+
col1 = np.stack([2*(x*y-z*w), 1-2*(x*x+z*z), 2*(y*z+x*w)], axis=-1)
|
| 38 |
+
value = np.concatenate([pose[..., :3], col0, col1, grip[..., None]], axis=-1).reshape(len(pose), 20)
|
| 39 |
+
mask = np.concatenate([np.repeat(pose_valid[..., None], 9, axis=-1), grip_valid[..., None]], axis=-1).reshape(len(pose), 20)
|
| 40 |
+
return np.where(mask, value, 0).astype(np.float32), mask
|
| 41 |
+
|
| 42 |
+
|
| 43 |
+
def build_arrays(arrays, metadata, *, action_mode, unify_action=True, allow_copied_commands=False):
|
| 44 |
+
if action_mode not in {'command', 'next_state'}:
|
| 45 |
+
raise ValueError('Explicitly choose action_mode=command or next_state')
|
| 46 |
+
state, state_mask = _pose20(arrays['state_pose'], arrays['state_gripper'],
|
| 47 |
+
arrays['state_pose_valid'], arrays['state_gripper_valid'])
|
| 48 |
+
if action_mode == 'next_state':
|
| 49 |
+
action = np.zeros_like(state); action_mask = np.zeros_like(state_mask)
|
| 50 |
+
action[:-1] = state[1:]; action_mask[:-1] = state_mask[1:]
|
| 51 |
+
else:
|
| 52 |
+
pose = arrays['command_pose'] if 'command_pose' in arrays else arrays['state_pose']
|
| 53 |
+
pose_mask = arrays['command_pose_valid'].copy()
|
| 54 |
+
if not allow_copied_commands:
|
| 55 |
+
pose_mask[:, np.asarray(metadata.get('command_pose_is_state_copy', [False, False]), dtype=bool)] = False
|
| 56 |
+
action, action_mask = _pose20(pose, arrays['command_gripper'], pose_mask, arrays['command_gripper_valid'])
|
| 57 |
+
if metadata.get('command_quality_review_required', False):
|
| 58 |
+
action_mask[:]=False;action[:]=0
|
| 59 |
+
if unify_action:
|
| 60 |
+
def scatter(value):
|
| 61 |
+
out = np.zeros((len(value), 80), dtype=value.dtype)
|
| 62 |
+
out[:, :10] = value[:, :10]; out[:, 34:44] = value[:, 10:20]
|
| 63 |
+
return out
|
| 64 |
+
state, action, state_mask, action_mask = map(scatter, [state, action, state_mask, action_mask])
|
| 65 |
+
return {'state': state, 'action': action, 'state_mask': state_mask, 'action_mask': action_mask,
|
| 66 |
+
'episode_id': metadata['episode_id'], 'fps': metadata['fps'], 'action_mode': action_mode}
|
| 67 |
+
|
| 68 |
+
|
| 69 |
+
def load_episode(shard_path, episode_id, *, action_mode, unify_action=True, allow_copied_commands=False):
|
| 70 |
+
with tarfile.open(shard_path, 'r') as shard:
|
| 71 |
+
metadata = json.load(shard.extractfile(episode_id+'.json'))
|
| 72 |
+
data = shard.extractfile(episode_id+'.npz').read()
|
| 73 |
+
with np.load(io.BytesIO(data), allow_pickle=False) as archive:
|
| 74 |
+
arrays = {key: archive[key] for key in archive.files}
|
| 75 |
+
result = build_arrays(arrays, metadata, action_mode=action_mode, unify_action=unify_action,
|
| 76 |
+
allow_copied_commands=allow_copied_commands)
|
| 77 |
+
result['metadata'] = metadata
|
| 78 |
+
return result
|
| 79 |
+
|
| 80 |
+
|
| 81 |
+
def iter_episodes(shard_path, *, action_mode, unify_action=True, allow_copied_commands=False):
|
| 82 |
+
"""Stream companions without repeatedly scanning the TAR directory."""
|
| 83 |
+
with tarfile.open(shard_path, 'r|') as shard:
|
| 84 |
+
pending = {}
|
| 85 |
+
for member in shard:
|
| 86 |
+
if not member.isfile():
|
| 87 |
+
continue
|
| 88 |
+
key, suffix = member.name.rsplit('.', 1)
|
| 89 |
+
data = shard.extractfile(member).read()
|
| 90 |
+
if suffix == 'npz':
|
| 91 |
+
pending[key] = data
|
| 92 |
+
elif suffix == 'json':
|
| 93 |
+
metadata = json.loads(data)
|
| 94 |
+
with np.load(io.BytesIO(pending.pop(key)), allow_pickle=False) as archive:
|
| 95 |
+
arrays = {name: archive[name] for name in archive.files}
|
| 96 |
+
result = build_arrays(arrays, metadata, action_mode=action_mode, unify_action=unify_action,
|
| 97 |
+
allow_copied_commands=allow_copied_commands)
|
| 98 |
+
result['metadata'] = metadata
|
| 99 |
+
yield result
|
eef/shards.jsonl
ADDED
|
@@ -0,0 +1,268 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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| 1 |
+
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| 29 |
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| 31 |
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|
eef/statistics.json
ADDED
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|
| 1 |
+
{
|
| 2 |
+
"scope": "training split only; exact valid-frame moments in the 20-D layout",
|
| 3 |
+
"rotation_6d_dimensions": [
|
| 4 |
+
3,
|
| 5 |
+
4,
|
| 6 |
+
5,
|
| 7 |
+
6,
|
| 8 |
+
7,
|
| 9 |
+
8,
|
| 10 |
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13,
|
| 11 |
+
14,
|
| 12 |
+
15,
|
| 13 |
+
16,
|
| 14 |
+
17,
|
| 15 |
+
18
|
| 16 |
+
],
|
| 17 |
+
"normalization_note": "Keep rotation-6D coordinates unnormalized. Grippers already use 0=closed, 1=open. No normalization has been applied to stored poses.",
|
| 18 |
+
"robots": {
|
| 19 |
+
"AgileX": {
|
| 20 |
+
"state": {
|
| 21 |
+
"count": [
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| 22 |
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| 43 |
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