Power Play Intro Video
Power Play is a challenge, that on the outside, seems simple, but is actually very more complicated. The simple mechanical objective of the game is to place cones onto a grid poles, called "junctions". These junctions have 4 heights; ground, low, medium, high. Cones can be picked up from stacks on the sides of the arena and substations manned by a human player.
There's also many other ways to earn more points, such as:
Having your alliance's cone topmost on a junction (controlled)
Making a connected line of controlled junctions from corner to corner (circuit)
At the end of autonomous, parking in a zone designated by a randomized signal cone
Locking a junction with a scoring element (capping)
As such, strategy played a huge role in this year's game
Due to the small spaces between the junctions, and the threat of penalties via knocking cones over, our robot had to be as small and maneuverable as possible.
We accomplished this by largely 3D printing our chassis and utilizing drive belts to pack the motors in.
As for cone delivery, we chose a simple but reliable (most of the time!) linear slide from GoBilda that was initially continuously strung, but switched to cascading later
The custom design philosophy extended to the claw as well, which was entirely 3D printed. Pulled shut by rubber bands and opened by two strings attached to servos, our claw was moulded and padded to lift and hold cones effectively, regardless of how they were received.
We also began using TensorFlow to read a custom signal sleeve we made for parking at the end of autonomous
One thing we did in the beginning was make a coordinate system to identify junctions to capture. The 5x5 field was thus labeled A1 through E5, from top right to bottom left.
Our primary strategy consisted of first "taking the L" as we humorously called it; capturing three key junctions in an L shape. The figure above is marked up to show the possible junctions we could take, depending on our starting position and alliance. From there, we would work our way outwards, pushing to a circuit and simultaneously defending against one
We would also meet with teams before matches to identify strengths and weaknesses, and tune/subdivide our strategy accordingly
One feature that helped us brush up on our strategy was a custom board game that simulated the actual challenge. This allowed us to discover and experiment with key strategies and techniques.
The abundance of 3D printed parts meant that many were bound to break. We minimized this by using CAD stress analysis to identify weak points and modify them to be stronger.
To aid in movement, we included small wheels connected to encoders that fed information to the control hub much more accurately than the motors' encoders. This allowed us to greatly improve the precision of our movements.
ROadrunner /Meep Meep
Roadrunner is a vector based movement library, and Meep Meep is a visualizer. Together, they allow for smooth movements of the robot in autonomous.
scored an average of 9.4 cones per match as an alliance and an average of 80.4 points per game.
15 cones per match and 136 points per game.
13.8 cones per match and 124 points per game.
20 cones per match and 169 points per match.