Quote:
Originally Posted by efoote868
I used DARPA as an example early on in this thread - teams of professionals and graduate level students with near unlimited bankroll behind them, completing a task that is arguably easier/more straight forward.
It took them two years to complete the challenge.
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If you really think the DGC/DUC task is easier than FRC, I think you may be mistaken. Before I moved to California, I worked at MIT with the DGC team on their continuing autonomous land vehicle research. Unknown terrain, traffic laws, REAL safety, and IC engines are all a bit more complicated than our dinky electric drive bases and arms.
But I think anyone trying this can take some experiences away from the DGC. First of all, the teams who had the best software also had the best hardware. If your machine is not mechanically reliable or controllable, you aren't going anywhere fast. One of the biggest lessons I've learned in my years as a software guy in FIRST is that the best software fix is usually a mechanical fix.
As far as the software goes, you really need to start thinking about how to set up your machine as a series of interconnected systems. There are basically three components to an autonomous robot control system: Perception, Planning, and Control. Perception is the data you take in from the world around you (vision, distance, GPS,
and their associated post-processing). Planning is the part that understands how to interpret the world around it and make educated decisions on what to do. Control is the part that actually makes the robot do what it wants to do.
If you are familiar with the Model/View/Controller design pattern, you can loosely parallel Perception to the Model, Planning to the Controller, and Control to the View. (Where the model is what you have, the controller is what you want, and the view is what you get.)