AutoCaddie

Jarett Artman □ Computer Engineering

Joshua Glaspey □ Computer Engineering

Rylan Simpson □ Computer Engineering

Louis Deal □ Electrical Engineering

Training and improving oneself when getting involved in a sport, or maintaining performance even after seasoned experience in a sport can be a rigorous or even difficult task. When training, feedback may be one of the best modes of improvement. AutoCaddie seeks to be a source of reliable feedback for golfers. Focusing on driving a golf ball downrange, AutoCaddie aims to use both pattern recognition driven by artificial intelligence (AI) and inertial measurement unit (IMU) sensor data to provide feedback recommendations on the form of the user’s golf drive. The IMU system is worn by the wearer via means such as Velcro pads, and the IMU data feeds into a wireless tranceiver device that transmits data to a receiver computer. This receiver then sends the IMU data to an artificial intelligence, and a direct-calculation program which is controlled by the artificial intelligence. The artificial intelligence uses machine learning and pattern recognition on live video footage of the user in order to develop feedback for the user. All feedback developed should be displayed for the user to observe. Ultimately, the user of AutoCaddie should be able to utilize the received feedback to improve their abilities in golf drives.

Key terms: Golf, Artificial Intelligence, Pattern Recognition, IMU, Sensor, Feedback

Senior Design 1 Initial Divide & Conquer Document

Senior Design 1 "60 Page" Midterm Draft Document

Senior Design 1 Final Documentation

Senior Design 2 8 Page Conference Paper

Senior Design 2 Final Documentation

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