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Unread 11-01-2016, 10:17
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Re: Two Boulder Auto

Quote:
Originally Posted by AlexanderTheOK View Post
I apologize that you found offense in my statement, however, I hope you understand that giving two factually incorrect statements in a row gives off a particularly negative impression on one's memory, so I wouldn't say my statement was particularly out of line.
Neither of my statements was factually incorrect. Please read what I wrote, and not what you think I wrote.

Quote:
Originally Posted by AlexanderTheOK View Post
I will reiterate my point once again:

In 2013, the margin of error would be defined by the construction and design of your intake, and the teams that were good enough to go for the mid-line Frisbees also had intakes that would successfully capture Frisbees over their entirety. This left such teams with enough clearance that localization via encoders and IMU would yield error that would not affect intake effectiveness.

In addition, the margin of error for getting a foul was that of your entire robot, which would be several feet, meaning if a team WAS to miss the frisbees, they would not accrue a foul. In 2016, crossing the midline in any way is a foul.
Watch the videos of 987 I posted. Their intake was located along the narrow end of their robot, meaning the margin for error was only a couple inches for acquisition. As a result, it meant they had to center their long axis of the robot exactly on the center line as they drove backwards (which is the accuracy you were questioning in your previous post), as they need their intake centered after they rotate. They then had to rotate, and drive a precise distance down the line to acquire the Frisbees, but not overshoot the required positioning to make it back to their starting location without contacting the pyramid (or other robots) in time to fire the newly acquired Frisbees. They executed multiple maneuvers within their autonomous routine that contained the same degree of precision than you're stating is impossible in this years' challenge. That is far from the only example of such precision in autonomous.
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