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ScooterV2.0

Self-Driving Mobility Scooter

ScooterV2.0

Research Areas

  • Electronic sensors including LIDAR, Radar, Ultrasonics, and accelerometers.
  • Computer Vision
  • Machine Learning
  • Mechanical Design
BACKGROUND:

This project is about designing a self-driving mobility scooter for the elderly and the infirm.  The problem is the same as designing a self-driving car, but in miniature: smaller, slower, and cheaper.  We will attach sensors to a scooter, drive it around campus recording the sensor output and driving signals from the operator, and then teach a machine to self-drive the scooter.

GOALS:

A self-driving mobility scooter for the elderly and the infirm.

KEY ELEMENTS:

Electronic sensors, computer vision, and machine learning.

ADVISORS: Charles Boncelet (ECE) and Andy Novocin (ECE)
MAJORS, PREPARATION, INTERESTS: Looking for any students who understand (or are willing to learn) sensor electronics, mechanical design, and machine learning.