Last week I promised to prepare a series of short posts that shall provide a behind-the-scenes look into the Precismo operations. In the second episode, we’ll speak about robots. The good ones, obviously!
Autonomous robotic 3D scanning is a significantly different endeavor than just running around things with a 100$ Chinese handheld 3D scanner. The results are quite different, as you’d probably expect them to be.
How different? I’d say like… Avatar vs SpongeBob SquarePants different. Yup.
There’s actually plenty of good reasons for the utilization of robotics. It provides us with improved options for precise calibration of our sensors and hence better results. We can also run the same scanning workflow 1000 times, using different parameters, and compare results. And last but not least: Robotization enables us to scale the technology and GO BIG. Scan thousands of items per hour. Scan airplanes, possibly, one day.
The ultimate challenge during the implementation was security. Robots are usually used for pre-defined tasks that are identical each time they are performed. On the contrary, 3D scanning is totally different each time it is performed. And we have to be like 110 % percent sure that the robot does not smash everything around itself, scanned object included. Therefore we decided to write our own collision detection system and combine it with the one provided by Fanuc.
Yes, we use industrial robotics from Fanuc and we could not be happier about it. They provide us with great support, have excellent training. Thanks to standardization, we are sure that each robot we buy works identically to the one we already have, no matter where we buy.
So that’s about it. Until next time! Z.
3D scanning with Precismo is a highly accurate, yet cost-effective way for creating original 3D content for retail, entertainment, media, gaming and other similar industries of the 21st century.
We also closely collaborate with industry leaders in Czech Republic to provide quality control and non-destructive testing solutions across all relevant fields.
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