USC VEXU 2022 Tipping Point Autonomous Skills

Here’s our ideal programming run for VEXU Tipping Point - Scoring around 460 points.

USC VEXU 2022 Tipping Point Autonomous Skills

Our robots are navigating using tracking encoder based odometry. They also each have an IMU, and encoder-based positioning for all joints and arms. The small bot uses an optical sensor to align the branches for high scoring.

Both bots were designed using Autodesk Inventor, and are constructed using mostly 3D-printed parts. They are both programmed using C++.

Small bot scores 8 high rings using its optical sensor to align the branches. It also parks with two goals using an IMU. It scores a total of 190 points.

Big bot scores up to 27 low branch rings, places 1 goal into the home zone, and parks with 4 goals, again using an IMU. It scores between 260 and 291 points, depending on how many rings it intakes.

At worlds, we ran into issues cause by differences in friction between our field and the fields at worlds. We stayed up all night, tuning and testing, we simplified our runs, cutting out an entire goal from the larger bot’s routine. Unfortunately, on our final attempt, the small bot got caught on a ring. This caused it to miss collecting the high goal, which cost us at least 70 and 140 points (depending on whether or not the bot would have been successful in parking at the end).

Our driver score was also a lot lower than we had hoped, but we did score the highest of any team in this section.

Overall, we placed 2nd in the 2022 Worlds Skills Challenge. Huge congrats to Purdue for taking 1st!

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What’s this wheel for?
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It’s a goal rush mechanism, the 15" bot also has one… Reveal video coming soon!

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