Vision... what? how?

[adciv]

From experience, programming in Open CV means you have to handle the (in)stability issues in the program or you'll lose your vision processing. I tried Open CV this year but had some null pointer issues running some of the libraries. This occured with some particularly noisy images.

That said, there is still an advantage to running vision processing on the robot in terms of reduced bandwidth requirements and reduced lag. The question becomes, does the advantage make up for this complexity? For 2014, I'm considering purchasing a sub $400 windows tablet and installing labview on it to run video processing on. Less than one pound of weight and about 1/4" thick.

Regardless, I recomend purchasing a new laptop if you can afford it. I do not like the classmates from a cost or durability perspective. I replaced our driverstation in 2012 with an i7 laptop for about the same price as a new classmate would cost, but with about an order of magnitude more computing power.

[mrklempae]

... OpenCV is a great route if you're going to use a camera like the Kinect or Asus Xtion Pro (which allow you to measure depth). The problem with that is that it's not easy to set up. You have to rebuild the libraries from the source to get things like OpenNI support, CUDA (gpu core) support, multi core or hyperthreaded core support, and other cool stuff. I have personally been trying for the last week to successfully build it using CMake with little or no success (I'm going to try to find someone to FTP me a working build). There's quite a few options available if you're going to go with a small form-factor desktop computer on your robot.