Datasets:

skycn110
/

pico-robotics-basic

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
frame_index: int64
timestamp_ns: int64
relative_ns: int64
balance: double
K_new: list<item: list<item: double>>
  child 0, item: list<item: double>
      child 0, item: double
resolution: list<item: int64>
  child 0, item: int64
K_original: list<item: list<item: double>>
  child 0, item: list<item: double>
      child 0, item: double
D: list<item: double>
  child 0, item: double
to
{'K_original': List(List(Value('float64'))), 'K_new': List(List(Value('float64'))), 'D': List(Value('float64')), 'resolution': List(Value('int64')), 'balance': Value('float64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              frame_index: int64
              timestamp_ns: int64
              relative_ns: int64
              balance: double
              K_new: list<item: list<item: double>>
                child 0, item: list<item: double>
                    child 0, item: double
              resolution: list<item: int64>
                child 0, item: int64
              K_original: list<item: list<item: double>>
                child 0, item: list<item: double>
                    child 0, item: double
              D: list<item: double>
                child 0, item: double
              to
              {'K_original': List(List(Value('float64'))), 'K_new': List(List(Value('float64'))), 'D': List(Value('float64')), 'resolution': List(Value('int64')), 'balance': Value('float64')}
              because column names don't match

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Pico Robotics Dataset · Basic Edition

Pico + Tracker 采集的机器人学习视觉数据集 — 基础版

由 Pico VR 头显 + 自研 Tracker 硬件在真实环境中采集，涵盖去畸变双路视频、~1kHz 6DoF 头部位姿、双麦克风音频、相机标定等多模态数据。适合机器人视觉、具身智能、深度估计、SLAM 等方向的研究。

🎯 数据集总览

我们提供三个版本，从基础到完整，满足不同研究需求：

版本	内容	访问方式
Basic（本仓库）	去畸变双路视频 + 逐帧深度图 + 双路麦克风音频 + ~1kHz 6DoF 头部位姿 + 相机标定	🟢 公开
Advanced	基础版全部 + 位姿对齐立体点云(.npz) + 21 关节手部 + 世界坐标点云 + MCAP/Foxglove 可视化	🔒 申请访问
Annotated	进阶版全部 + 动作分段粗标 + segments.json 标注文件	🔒 申请访问

👉 想要进阶版或粗标版？ 点击这里填写表单，自动获取访问权限。

📁 目录结构

每个样本是一个独立目录，包含以下文件：

sample_01/
├── head_left_camera_undistorted.mp4    # 左摄像头去畸变视频
├── head_right_camera_undistorted.mp4   # 右摄像头去畸变视频
├── undistort_camera.json               # 去畸变相机内参 + 标定参数
└── video_index.json                    # 帧索引 + 时间戳 + 6DoF 位姿

📊 数据字段说明

head_left/right_camera_undistorted.mp4

格式：H.264 MP4
分辨率：双目同步
已做去畸变处理，可直接用于立体视觉算法

undistort_camera.json

{
  "intrinsics": { ... },     // 相机内参
  "distortion": { ... },     // 畸变参数（去畸变后可忽略）
  "extrinsics": { ... }      // 左右相机外参
}

video_index.json

逐帧元数据，包括：

帧号、时间戳
6DoF 头部位姿（位置 + 四元数）
帧率与时长信息

🚀 快速开始

import json
import cv2

# 读取视频
cap = cv2.VideoCapture("sample_01/head_left_camera_undistorted.mp4")

# 读取帧索引和位姿
with open("sample_01/video_index.json") as f:
    index = json.load(f)

print(f"总帧数: {len(index['frames'])}")
print(f"首帧位姿: {index['frames'][0]['pose']}")

📜 许可证

本数据集采用 CC BY 4.0 协议发布。使用时请注明：

Pico Robotics Dataset by skycn110, licensed under CC BY 4.0

📬 联系与合作

数据咨询 / 商业合作：skycn110@gmail.com
申请进阶版 / 粗标版：填写表单
Issues / Discussions：欢迎在仓库提出

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