Quote:
Originally Posted by meatmanek
Our team uses an 'abstraction layer' which consists of a bunch of global variables and two functions: abstractIn() and abstractOut().
The global variables are things like driveLeft, driveRight, joyL, joyR, etc.
Our abstraction code takes renaming it one step farther. Rather than using the 0-255 scale where 127 means stop, we shift it down 128 (signed char, rather than unsigned), and we also invert motors where it makes sense. (one side of the drivetrain, any appendages where the motor is 'backwards')
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We've done this for several years. We have one set of functions that maps user inputs into various abstract state variables (speed and heading, for example, arm angle, etc), and a second set of functions that maps these state variables into pwms and relay settings. This is nice, since it means that the autonomous modes are programmed the same way.
I also got the students to use a rigorously defined finite state machine for the autonomous mode this year, and it really paid off. We gained a lot of autonomous functionality without a lot of extra effort, and it's a lot more debuggable.
Otherwise, the other neat innovation was using large numbers of infrared sensors to do a lot of our work (especially in autonomous). They also give us a "virtual bumper" that can keep us from hitting things we don't want to.