Publication Date
12-1-2016
Document Type
Dissertation/Thesis
First Advisor
Coller, Brianno D.
Degree Name
B.S. (Bachelor of Science)
Legacy Department
Department of Mechanical Engineering
Abstract
In the United States, there is a lack of young adults interested in studying Science, Technology, Engineering, and Math (STEM). One way to help spark interest in STEM is a classroom aid that demonstrates how STEM can be fun and how it is used to push the limits of modern technology. BikeBot was designed for just this purpose. BikeBot is a robotic bicycle that utilizes an algorithm called Q-learning. Q-Learning is a type of reinforcement machine learning program, a basic form of artificial intelligence, that will allow BikeBot to balance without any explicit controls. The algorithm was tested and proven to work through a computer simulation of BikeBot’s dynamics. Our results show that BikeBot learned to balance upright while moving forward at a constant velocity in 50,000 iterations or 16 minutes and 40 seconds of real time learning.
Recommended Citation
Kutz, April L.; Brennan, Kristen A.; Dixon, Jeremy; and Bogdonas, Nathan, "BikeBot: A Study in Reinforcement Learning" (2016). Honors Capstones. 232.
https://huskiecommons.lib.niu.edu/studentengagement-honorscapstones/232
Final Presentation.pdf
Extent
42 pages
Language
eng
Publisher
Northern Illinois University
Rights Statement
In Copyright
Rights Statement 2
NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.
Alt Title
BikeBot
Media Type
Text
