You might want to read some of the RoboCup literature - just do a Google Scholar search for "RoboCup". At this point, the wheeled-robot classes are actually pretty decent, and the
small class is very good. The RoboCup community has solved a lot of interesting problems along the way. But just to give a little perspective: their game is very simple, and the teams are groups of PhD students who have been working on the robots for several years.
When I was taking a machine learning class and we were choosing course projects, the professor suggested a simple benchmark to tell if the project was appropriate: Is the task easy for a human? If not, it's probably between hard and impossible for a computer, unless it involves huge amounts of data or extremely fast reaction times. Driving an FRC robot is hard, way harder than driving a car.
Here's an interesting place to start that's a little easier: Given a video that shows the whole field for the duration of an Aerial Assist match, calculate the score. Don't worry about penalties. Just track the robots, track the balls (there's only 2!), and keep track of the score.
Once you can do something like this, you will have solved a number of the hard vision and analysis tasks, and will be in a position to make a robot react to play the game. Also, this would be a ludicrously awesome scouting tool.
