Document Piper-H hardware and add CC BY 4.0 license

README.md

@@ -1,194 +1,65 @@
 ---
-task_categories:
-- robotics
+license: cc-by-4.0
 tags:
 - LeRobot
 - piper
+- piper-h
 - pick-and-place
 - imitation-learning
 - real-robot
 - realsense
+task_categories:
+- robotics
 configs:
 - config_name: default
   data_files: data/*/*.parquet
 ---
 
-This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
+# Piper-H Pick-and-Place XY Random 50
 
+This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
 
 <a class="flex" href="https://huggingface.co/spaces/lerobot/visualize_dataset?path=Smokepord/piper_pick_place_xy_random_50_v1">
 <img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl.svg"/>
 <img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl-dark.svg"/>
 </a>
 
-
 ## Dataset Description
 
-This dataset contains 50 successful real-robot demonstrations of an AgileX Piper arm picking up a blue 3D-printed container twist-lock part and placing it inside a black container.
+This dataset contains 50 successful real-robot demonstrations collected with an AgileX Piper-H robotic arm. The task is to pick up a blue 3D-printed container twist-lock part and place it inside a black container.
 
-The dataset contains 18,884 frames at 20 Hz, synchronized wrist and fixed-view RGB observations from two Intel RealSense D435i cameras (640 x 480, AV1), and 7-dimensional robot state/action vectors ordered as six joint positions followed by gripper position. Actions are absolute position targets in the same normalized coordinate system as the state.
+- **Homepage:** Not applicable.
+- **Paper:** Not applicable.
+- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
 
-The object was randomly translated within a small planar XY region. Object height and orientation, container pose, cameras, lighting, and the wider workspace arrangement remained effectively fixed. The dataset therefore supports an in-region imitation-learning baseline and should not be interpreted as covering changes in height, orientation, lighting, camera pose, container geometry, or larger workspace regions.
+## Dataset Structure
 
-An ACT policy selected at checkpoint 25,000 achieved 16 successes in 20 real-robot trials (80%; approximate 95% Wilson interval: 58.4%-91.9%). Evaluation used four in-region object start positions with five trials per position; each position produced four successes and one failure. Failure stages and trial durations were not separately recorded.
+- 50 episodes and 18,884 frames at 20 Hz
+- Two synchronized RGB observations from wrist-mounted and fixed Intel RealSense D435i cameras
+- 640 x 480 AV1 video without audio
+- 7-dimensional state and action vectors ordered as six joint positions followed by gripper position
+- Absolute position actions expressed in the same normalized coordinate system as the state
 
+The `piper_follower` value in [`meta/info.json`](meta/info.json) is the LeRobot plugin robot type. The physical robot used to collect the dataset was an AgileX Piper-H.
 
-- **Homepage:** [More Information Needed]
-- **Paper:** [More Information Needed]
-- **License:** [More Information Needed]
+## Collection Scope
 
-## Dataset Structure
+The object was randomly translated within a small planar XY region. Object height and orientation, container pose, cameras, lighting, and the wider workspace arrangement remained effectively fixed.
 
-[meta/info.json](meta/info.json):
-```json
-{
-    "codebase_version": "v3.0",
-    "fps": 20,
-    "features": {
-        "action": {
-            "dtype": "float32",
-            "names": [
-                "joint1.pos",
-                "joint2.pos",
-                "joint3.pos",
-                "joint4.pos",
-                "joint5.pos",
-                "joint6.pos",
-                "gripper.pos"
-            ],
-            "shape": [
-                7
-            ]
-        },
-        "observation.state": {
-            "dtype": "float32",
-            "names": [
-                "joint1.pos",
-                "joint2.pos",
-                "joint3.pos",
-                "joint4.pos",
-                "joint5.pos",
-                "joint6.pos",
-                "gripper.pos"
-            ],
-            "shape": [
-                7
-            ]
-        },
-        "observation.images.wrist": {
-            "dtype": "video",
-            "shape": [
-                480,
-                640,
-                3
-            ],
-            "names": [
-                "height",
-                "width",
-                "channels"
-            ],
-            "info": {
-                "is_depth_map": false,
-                "video.height": 480,
-                "video.width": 640,
-                "video.codec": "av1",
-                "video.pix_fmt": "yuv420p",
-                "video.fps": 20,
-                "video.channels": 3,
-                "has_audio": false,
-                "video.g": 2,
-                "video.crf": 30,
-                "video.preset": 12,
-                "video.fast_decode": 0,
-                "video.video_backend": "pyav",
-                "video.extra_options": {}
-            }
-        },
-        "observation.images.fixed": {
-            "dtype": "video",
-            "shape": [
-                480,
-                640,
-                3
-            ],
-            "names": [
-                "height",
-                "width",
-                "channels"
-            ],
-            "info": {
-                "is_depth_map": false,
-                "video.height": 480,
-                "video.width": 640,
-                "video.codec": "av1",
-                "video.pix_fmt": "yuv420p",
-                "video.fps": 20,
-                "video.channels": 3,
-                "has_audio": false,
-                "video.g": 2,
-                "video.crf": 30,
-                "video.preset": 12,
-                "video.fast_decode": 0,
-                "video.video_backend": "pyav",
-                "video.extra_options": {}
-            }
-        },
-        "timestamp": {
-            "dtype": "float32",
-            "shape": [
-                1
-            ],
-            "names": null
-        },
-        "frame_index": {
-            "dtype": "int64",
-            "shape": [
-                1
-            ],
-            "names": null
-        },
-        "episode_index": {
-            "dtype": "int64",
-            "shape": [
-                1
-            ],
-            "names": null
-        },
-        "index": {
-            "dtype": "int64",
-            "shape": [
-                1
-            ],
-            "names": null
-        },
-        "task_index": {
-            "dtype": "int64",
-            "shape": [
-                1
-            ],
-            "names": null
-        }
-    },
-    "total_episodes": 50,
-    "total_frames": 18884,
-    "total_tasks": 1,
-    "chunks_size": 1000,
-    "data_files_size_in_mb": 100,
-    "video_files_size_in_mb": 200,
-    "data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
-    "video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
-    "robot_type": "piper_follower",
-    "splits": {
-        "train": "0:50"
-    }
-}
-```
+This dataset supports an in-region imitation-learning baseline. It should not be interpreted as covering changes in object height or orientation, lighting, camera pose, container geometry, or larger workspace regions.
 
+## ACT Baseline
 
-## Citation
+An ACT policy selected at checkpoint 25,000 achieved 16 successes in 20 real-robot trials (80%; approximate 95% Wilson interval: 58.4%-91.9%). Evaluation used four in-region object start positions with five trials per position; each position produced four successes and one failure. Failure stages and trial durations were not separately recorded.
 
-**BibTeX:**
+## Citation
 
 ```bibtex
-[More Information Needed]
-```
+@misc{smokepord_piper_pick_place_xy_random_50_v1,
+  author       = {Smokepord},
+  title        = {Piper-H Pick-and-Place XY Random 50 Dataset},
+  year         = {2026},
+  publisher    = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/datasets/Smokepord/piper_pick_place_xy_random_50_v1}}
+}
+```