[faust1706]

Ok, I'm on my phone. Lets see how this goes. It's storming at work so I have time.

Machine learning for vision is rather common, but the approach you want to take isn't feasible due to your lack of training examples. The rule of thumb is that you need at least 50 training examples to start learning from. You simply won't have enough training examples to get a result worth the effort, or any noticeable result at all.

Moving on. You can use machine learning for calculating distance from characteristics in the image. You have to have training examples though. So you'd go out, record contour characteristics such as height, width, area, and center.x and .y. then you manually input distance. You do this from as many points as you possibly can bear to do. Then you run a gradient descent algorithm(regression) or apply the normal equation. You can scale your data if you don't think it's linear, such as taking the natural log of contour height. For this example, you are dealing with 6 dimensions, so it is impossible to visualise. You just have to guess what scaling is needed. Then you apply the squared error function (predicted-actual)^2, also called your resudual. You want this to be as close to zero as possible. This can also be applied to game pieces.

Another application is shooting pieces. You have a chart of inputs such as motor speed, angle, and distance, and the output is a 1 or 0: making a basket or miss. You have a 3d plot now. There exists a line, or multiple lines virtually the same, in 3d space that garuntees making all your shots (given your robot is 100% consistent).

Another type of ai is path planning. If you have a depth map of all your objects in front of you, then you can apply the a star path planning to get to a certain location on the field given you have a means of knowing where you are on the field. (Cough cough encoders on undriven wheels or a vision pose calculation)

I might have forgetten somethings. Feel free to ask questions.

Disclaimer: all these calculations can be done virtually instantly using octave or matlab. The a star is a bit more intensive. It is an iterative algorithm to my understanding.