Processing Vision Code on Laptop
 

We have heard just some ideas that vision code could theoretically be processed on a laptop on the robot. After using some of the vision examples implemented in the framework we realized how much of a processor intensive task it is. How would be go about processing code on an on board computer?

Re: Processing Vision Code on Laptop
 

The Rectangular Target VI has code for My Computer target and the cRIO target. One is a PC, the other is on the robot. This will let you compare the results and performance.

I would encourage you to think about the rates you need from the camera and how it will be used before jumping to the laptop. But if you decide to use a laptop, you have two choices. You can use the dashboard program running on you driver station to do the processing and send data back to the robot using UDP or a similar mechanism. Or you can strap a laptop to the robot. That robot still needs to communicate to the cRIO, likely using UDP. The difference is that one is wifi connected and the other uses a cable.

Greg McKaskle

Re: Processing Vision Code on Laptop
 

Take a look at the White Paper that FIRST released this season. I believe it is on First Forge.... It gives step by step instructions on how to the the vision processing.

http://firstforge.wpi.edu/sf/go/doc1302?nav=1

Re: Processing Vision Code on Laptop
 

I don't know how the FRC rules will govern this, but it is still a great idea. A x86 based micro PC would be great for this. Low power consumption, low weight, and a lot of extra CPU resources. This would be good for the off-season for advanced autonomous features.

Re: Processing Vision Code on Laptop
 

We were able to process the targets at about 12Hz using a 640x480 image on the cRIO. I'm more worried about motion blur than update rate at this point. Your mileage may vary.

Re: Processing Vision Code on Laptop
 

The cRIO has quite a bit of capability. The program has to be fairly efficient, and be wasteful, but overall fairly easy to accomplish quite a bit natively. I could imagine much more advanced and parallel algorithms being developed in the off-season.