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μBotics Scouting App.
Image 1) The "Team Search Engine" tab allows the user to enter any team at the event, and displays valuable information such as pit organization, autonomous notes scored, teleoperated notes scored, number of notes shuttled, qualitative comments from the scouts, and an image of what the robot looks like in the event we needed fix issues with the robot.
The Context.
Enter the FIRST Robotics Competition (FRC), a thriving community of over 86,700 students and 3,500 teams who design, program, and compete with one another through an annually released game concept.
The Problem.
After completing qual matches to earn RP--points awarded for fulfilling in-game quests--the top 8 teams must partake in Alliance Selection, where alliances of 3 teams are chosen to compete in playoffs. But the question stands: who to pick?
The Solution.
Scouting--the process of capturing a robot's statistical metrics such as cycle count, break down rate, etc.--is the answer to the question. By developing a software front-end in FlutterFlow and a back-end with Google Sheets, I was able to transfer data by dynamically generating 2 dimensional barcodes without the need of a stable internet connection--an obstacle posed by the competition environment.
The Outcome.
After training over 20 team members how to scout, our strategy subteam was able to leverage the data we collected for match plans, which greatly contributed to our success winning the 2024 Orange County Regional and becoming 2024 Daly Division (World) Finalists.
Image 2) The "Global View" tab displays major statistics for all teams at the event, including number of game pieces scored, incap rate, and number of notes shuttled.
Image 3) The "Automated Picklist" tab calculates weighted sums using the noise data collected by the scouts to dynamically generate a picklist without any manual input.
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