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• CS
• Smart Remote-Control Vehicle

Project Description

To better understand the fundamentals of machine learning, the Aerospace Corp has tasked our team with applying machine learning principles and techniques to develop a model capable of reaching an objective or completing a task. The only underlying constraint was that we do so with a small ground vehicle affectionately named ARIA (A Rather Intelligent Automobile). The ARIA system includes the following features in its design and implementation:

• ARIA can gather information about its surroundings through various sensors attached to the vehicle.
• ARIA can transmit the gathered information to a connected desktop application for further processing.
• ARIA can receive commands from the desktop application at any point in its cycle.
• ARIA will be able to move autonomously with the help of machine learning and an archive of data points

Upon completion of the project, we hope that ARIA will give The Aerospace Corporation a better understanding of what machine learning is, how it can be utilized, and what it can accomplish.

Meeting time: Fridays 1:30-2:30.

Blake Patton - Team Leader, blakepatton13@gmail.com
William Garcia - Documentation Lead, memo05@ymail.com
Karina Martinez - Customer Liaison, Documentation Co-Lead, karinalmartinez93@gmail.com
Calvin Pham - QA Lead/Debugger, calvinthepham@gmail.com
Robin Chan - Software Lead, chryselephant29@outlook.com
Kabir Nagrecha - Machine Learning Consultant, kabir.nagrecha@gmail.com