Onion Tau LiDAR Camera

An easy-to-use LiDAR camera that acts like a webcam for real-time 3D depth data

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The Onion Tau Camera is a 3D depth camera. Think of it like a regular webcam, except that it produces 3D depth data instead of color frames. It’s USB-based and plug-and-play, requiring no additional computation to produce depth data, so plug it into your computer with a USB cable, it will power on and start sending depth frames to your computer.

The Tau is an affordable next step beyond single-point depth or one-dimensional scanner solutions, and serves as a great starting point for 3D depth sensing. In fact, the Tau strikes a great balance between affordability and functionality when compared to other offerings in the 3D depth mapping space.

The Tau Camera outputs a real-time 160x60 point-cloud of depth data as well as a greyscale image of the scene. The range for depth sensing is 0.1 m to 7 m. The depth data from the point cloud can be visualized in 3D for use by humans, or it can be fed into an algorithm or other system.

On the software side, it will come bundled with a web-based application to visualize the camera output in real-time on a computer. A Python library will also be available, providing an easy-to-use API that’s compatible with OpenCV and can be used to configure the camera, capture output, and create applications using the depth data from the camera. The computer-side software will be open source.


  • Depth Technology: LiDAR Time of Flight
  • Depth Stream Output Resolution: 160 x 60
  • Depth Stream Output Frame Rate: 30 fps
  • Minimum Depth Distance: 0.1 meters
  • Maximum Range: 7 meters
  • Depth Field of View (FOV): 51° x 20° (subject to change based on final lens selection)
  • Connector: USB-C
  • Tau Camera: 4 mounting holes

These are early prototypes of the Onion Tau Camera. The final design will likely change before the first production run.

Use Cases

  • Primary use case:
    • Use the bundled viewer to see the depth data rendered on your computer
      • Explore 3D depth mapping and it's possibilities
  • Secondary use case:
    • Use the Python API to build your own applications
      • Compatible with OpenCV
    • Use cases this enables:
      • Environment mapping (like SLAM)
      • Augmented Reality
      • Computer vision applications
        • Person counting/presence detection
        • Object detection
        • Robotics
        • Automation

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