Quote:
Originally Posted by yash101
http://en.wikipedia.org/wiki/A*_search_algorithm
^^ That seems like something I want in my next year program. I would like it if I could have a tablet pc for the driver station, with the robot constantly generating a map of the field. If you click on a location on the field in the tablet, the robot could automatically navigate there with a high accuracy.
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This is a cool concept, and I definitely don't want to discourage you from exploring AI to the fullest, however I want to ensure that your expectations are realistic.
First, in FRC, assuming the structure of the game does not change drastically going into next year there is no way you will know where everything on the field is, there are other robotics competitions where this is feasible, however FRC is not one of them. You can incorporate some awesome sensors into the robot and give it a ton of information, however it will never be able to process all of the info that is relevant as accurately and quickly as a human can.
Second, really think about why you would want to do this. Does it offer a competitive advantage? Do you want to do it because It will look cool? What would be cooler, a well driven robot with some automated features to assist the driver that performs very well? Or a robot that learned how to play the game its self but functions poorly compared to human operated robots built by teams with less programming expertise. Which is more inspirational to students (that is the goal in the end right?).
AI has it's place, I spent a lot of time in college studying AI and robotics. I then got out into the real world and realized that as cool as AI is it isn't usually the right solution. In order of preference for robotics typically your first question is can this be done faster, better, or safer if a human is controlling the robot. Then in order of preference we go through
1.) How do we Control the environment
2.) How do we react to the uncontrollable aspects of the environment
3.) How do we improve our reactions.
It isn't until you get to #3 that AI comes up. Even then most applications it is easier to "Teach" by giving the directions directly on how to improve, rather than letting the robot learn on its own.
I love AI and there are some great competitions out there where it is key to winning. FRC is not one of them. The top AI labs in the world could not write an FRC legal AI that could beat student drivers in any FRC game (other than perhaps 2001 (? the year where 71 grabbed both goals and then shuffled) ).
My advice would be that instead of choosing an algorithm now and looking for an application you learn all you can now. Then when the game is released you look for the tasks a computer CAN do better than a human. Some examples I can think of are Aiming a shooter (2006), adjusting height for positioning an arm (2005, 2007, 2011 and others), and automating those features. If precise positioning on the field is important then maybe that is what you need to automate, however I don't think that trying to generate a full field map is the best idea, instead let the driver handle gross movement and then allow him to automate the fine adjustment based on vision (or other) sensor feedback.