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Driving data importer
Give it recorded GPS, camera or lidar data. Get it loaded, synced and cleaned for building driving scenarios.
Driving data importer is a free AI skill for the job "Build and ship software". Give the instructions to an AI assistant that supports the required files and tools, then review its output.
Free · No account · BSD 2 Clause licence · Made by MathWorks · Level: advanced
Made by MathWorks. See the original on GitHub; we copied it as it is, with its licence.
What it does
Recorded driving data loaded, lined up in time and cleaned, ready for building driving scenarios in MATLAB. It handles GPS, camera, lidar and tracked-object data from common sources. The skill maps raw files into the right scenario builder objects: GPS, camera, lidar, actor tracks, trajectories and lane data. It accepts datasets like KITTI, nuScenes and Waymo, ROS bags, MAT, CSV and video. It also attaches mounting position, angles and camera settings, syncs sensors with different sample rates, corrects time offsets, trims segments and sets a common time zero. It will not open the Driving Log Analyzer unless you ask or report a sync problem. It needs MATLAB with the matching toolboxes.
You give it
- Your raw recording files
- The dataset type, such as KITTI or ROS bag
- Sensor mounting details (optional)
- MATLAB with the scenario builder tools
You get
- Data wrapped into scenario builder objects
- Sensors synced to one timeline
- Time offsets corrected
- A saved dataset ready for scenario building
Use it when
- You have a KITTI or ROS bag recording and want to build a scenario from it.
- Camera and lidar timestamps do not match.
- You need to crop one segment out of a long recording.
- Your sensors use different sample rates and must share a timeline.
How to use it
- Add it to your AI once: download it and add the folder to Claude, ChatGPT or Codex as a skill.
- Ask for the job in your own words. Your AI opens the skill when it fits.
- It works best when your AI can run MATLAB with Automated Driving Toolbox.