Bump to v1.1.0: 16000 episodes / 3,728,773 frames; note ep_15999 duplicate of ep_12000

croissant.json

@@ -51,11 +51,11 @@
   "@type": "sc:Dataset",
   "name": "RoboPro",
   "alternateName": "roboreal_all_80tasks",
-  "description": "RoboPro is an 80-task bimanual manipulation dataset collected on a dual-arm Aloha-Agilex platform. It contains 15,999 expert demonstration episodes (3.73M frames at 50 Hz) recorded from three RGB cameras (top + two wrist) and synchronised 14-DoF joint commands. Each task includes a clean variant and a cluttered-scene variant with distractor objects. The dataset is released in LeRobot v2.1 format (Parquet for proprioception, MP4/H.264 for video) and is the training corpus used for the RoboPro behavior models.",
+  "description": "RoboPro is an 80-task bimanual manipulation dataset collected on a dual-arm Aloha-Agilex platform. It contains 16,000 expert demonstration episodes (~3.73M frames at 50 Hz) recorded from three RGB cameras (top + two wrist) and synchronised 14-DoF joint commands. Each task includes a clean variant and ten cluttered-scene variants (d6-d15) with progressively added distractor objects. The dataset is released in LeRobot v2.1 format (Parquet for proprioception, MP4/H.264 for video) and is the training corpus used for the RoboPro behavior models.",
   "conformsTo": "http://mlcommons.org/croissant/1.0",
   "license": "https://creativecommons.org/licenses/by/4.0/",
   "url": "https://huggingface.co/datasets/Hoshipu/RoboPro",
-  "version": "1.0.0",
+  "version": "1.1.0",
   "datePublished": "2026-05-01",
   "creator": {
     "@type": "Person",
@@ -90,7 +90,8 @@
   "rai:dataLimitations": [
     "All demonstrations were recorded on a single Aloha-Agilex hardware unit in a fixed laboratory environment; lighting, camera intrinsics, and table geometry do not vary across episodes.",
     "Tasks are limited to short-horizon (<10 s) tabletop manipulation; no long-horizon, navigation, or contact-rich tasks (e.g., insertion, peg-in-hole) are included.",
-    "Object instances are drawn from a fixed inventory of household and office props; the dataset does not span an open-vocabulary distribution of real-world clutter."
+    "Object instances are drawn from a fixed inventory of household and office props; the dataset does not span an open-vocabulary distribution of real-world clutter.",
+    "One source HDF5 (study/empty_box/clean/episode80.hdf5) was unrecoverable at conversion time, so episode 15999 in the released LeRobot dataset is a byte-for-byte duplicate of an existing empty_box/clean episode (global episode_index 12000) to maintain a 16,000-episode count. Users training on the dataset should be aware that one demonstration is repeated."
   ],
   "rai:hasSyntheticData": false,
   "rai:dataBiases": [
@@ -231,7 +232,7 @@
       "@type": "cr:RecordSet",
       "@id": "frames",
       "name": "frames",
-      "description": "Per-frame proprioception. One row per 50 Hz timestep across all 15,999 episodes (3,728,445 rows total).",
+      "description": "Per-frame proprioception. One row per 50 Hz timestep across all 16,000 episodes (3,728,773 rows total).",
       "field": [
         {
           "@type": "cr:Field",
@@ -299,7 +300,7 @@
           "@type": "cr:Field",
           "@id": "frames/episode_index",
           "name": "episode_index",
-          "description": "Global 0-based episode index (0..15998).",
+          "description": "Global 0-based episode index (0..15999).",
           "dataType": "sc:Integer",
           "source": {
             "fileSet": {