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Muhammed Tayar
Muhammed Tayar

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Synchronizing RGB, LiDAR & ToF in one platform TEMAS– our journey from KI Palooza to Kickstarter


Last week we had the chance to showcase our prototype TEMAS at KI Palooza – an AI-focused conference in Germany.

We’re a young company working at the intersection of robotics and computer vision, and this was the first time we presented TEMAS to a larger audience.


What is TEMAS?

TEMAS is a modular 3D sensor platform that combines:

  • RGB camera
  • LiDAR
  • ToF (Time of Flight) sensor

All sensors are pre-calibrated and synchronized so developers get reliable, aligned data right out of the box.

Powered by a Raspberry Pi 5 (PoE, optional AI accelerator), TEMAS delivers:

  • Colorized 3D point clouds
  • Easy integration via Python SDK on PyPI (pip install rubu)

Why synchronization matters

Anyone who has tried to integrate multiple sensors knows:

  • Different frame rates create time misalignments
  • Calibration between depth and RGB can take weeks
  • Data streams don’t just “fit” together

This was one of our biggest challenges.

Our solution:

  • Factory pre-calibration for sensor alignment
  • Raspberry Pi 5 acting as a central sync unit
  • Unified data stream → a single, aligned point cloud

This saves labs and developers a huge amount of time.


Road to Kickstarter

After KI Palooza, we’re now officially on the Road
to Kickstarter: from Pre-Launch to Launch
.

And this is where we’d love your support:

  • Feedback on use cases where you’d see TEMAS being most useful
  • Ideas for reward tiers that would make sense for devs/researchers
  • Tips from anyone who has been through a hardware Kickstarter before

Closing thoughts

We’re excited to share more of our journey here on DEV.

As a young company, this community means a lot to us – honest feedback from developers is exactly what we need to improve TEMAS and make the launch successful.

*From KI Palooza → to Kickstarter * – thanks for being part of the journey!

(More technical deep-dives coming soon – e.g. streaming point clouds and integrating with robotics.)

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