Quote:
Originally Posted by MatthewC529
I am not going to contribute to the reasons as to why you shouldnt do it on the scale you are seeking (Because I think the idea and concept is awesome) but I will say one thing. I have worked with AI Pathfinding algorithms to a decent extent as a Game Programmer, I was freelancing and did work in implementing specific AI Algorithms and various different Game Mechanics.
You have limited Memory on an embedded system like the RoboRIO. Of course the RoboRIO is a massive step up but I am talking about 2 GB RAM vs. 256 MB RAM. A* is in its most basic form an informed Djikstra Pathfinding algorithm. Unlike Djikstra where all moves have a Heuristic cost of 1, A* has ways of assigning a cost to each movement. Depending on your method you will usually get an O((V+E)log(V)) or even O(V^2) algorithm. Pathfinding is an expensive task and if the field was a perfect size where a resolution of 64 px by 32 px worked then you could end up with an extremely large Fringe if enough obstacles exist. In certain scenarios this could be a bit long for an Autonomous period and if proper threading isnt implemented it could cripple your Teleoperated period if you have to wait too long for the calculations to finish in a dynamically changing field of non-standard robots.
Also this could work for shooting but if the game calls for a much different scoring system then your AI and Learning may be even further crippled by complexity... Also you dont want a friendly memory error popping up and killing your robot for that round.
Its an awesome idea and you should definitely follow through but probably not immediately on a 120 lbs. robot. Experiment first with Game Algorithms and get used to implementing it in an efficient and workable way, then move to the robot where efficiency will really matter. I cant speak for how efficient you will need to be... again... Game Developer but again I really like your concept of pixels but I think you should be wary of how much time and the maintainability of your code.
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I actually wanted to treat this like a game. That is the reason why I thought of creating a field grid. Are you saying that 2GB of RAM won't be enough. The program will have access to 1GB in the worst case scenario. The data collection using OpenCV will use well under 16 MB of RAM.
If you are saying that A* is too ineficient, what do you suggest I should try instead. If anything, I could have 3 computers -- vision processor, AI, and cRIO.
Also, 64 by 32 px was just a crude example. By testing the performance of the system, I could tell whether I need to reduce the resolution or what. Otherwise, I could treat everything as either go there or not.
My buddy programmer and I would like to use an nVidia Jetson Dev board. Should we use that for AI, or vision processing? We can use an ODROID for the other task!
I have already figured out how to effectively use OpenCV and optimize it for a very high performance. I can use a configuration file to make the same setup track multiple target types, and I understand how to use OpenCV to get accurate target data even if the target is tilted!