{
  "fetched_at": "2026-10-19T09:41:00Z",
  "source_url": "https://www.kaggle.com/competitions/2022-sdc-localization-competition-i/data",
  "pages": [
    {
      "name": "data-description",
      "content": "# Dataset Description\n\nWe only provide the sample submission for you to understand the format you need to follow. To get the rosbag and other data, please download them from the slide.\n\nFor this case, you need to submit your result with (1 data field + 201 frames) rows data.\n\n## File descriptions\n*   sampleSubmission.csv - a sample submission file in the correct format\n\n\n## Data fields\n*  **id** - the id of the LiDAR scan sequence\n*  **x**  - translation transformation\n*  **y**  - translation transformation\n*  **z** - translation transformation\n*  **yaw** - rotation transformation\n*  **pitch** - rotation transformation\n*  **roll** - rotation transformation\n",
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    {
      "name": "Description",
      "content": "#SDC Localization Competition I\n\nThis is the Localization competition I for the Self-Driving Cars in NYCU. To get more information, please reference the competition slide we provide.\n\nFor this competition, please submit your result of the sdc_localization_1.bag",
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    {
      "name": "Evaluation",
      "content": "We use Root Mean Square Error (RMSE) as metric to evaluate your localiztion result.\n\n## Submission Format\n```\nid, x, y, z, yaw, pitch, row\n1,0,0,1,0,0,1\n2, ...\n.\n.\n.\n```\n",
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    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
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}