University of Illinois Urbana-Champaign

Usage of computer vision and machine learning to solve 3D mazes

Kamalnath, Vishnu Nath

Content Files
Vishnu Nath_Kamalnath.pdf

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https://hdl.handle.net/2142/45440

Description

Title
Usage of computer vision and machine learning to solve 3D mazes
Author(s)
Kamalnath, Vishnu Nath
Issue Date
2013-08-22T16:40:13Z
Director of Research (if dissertation) or Advisor (if thesis)
  • Smaragdis, Paris
  • Levinson, Stephen E.
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2013-08-22T16:40:13Z
Keyword(s)
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • iCub
  • Computer Vision
  • Computer Science
  • Pattern Recognition
  • learning
  • q-learning
Abstract
This thesis deals with incorporating artificial intelligence into a humanoid robot by making a cognitive model of the learning process. The goal is to “teach” a specialized humanoid robot, the iCub robot, to solve any puzzle, wherein a ball of a given color would be placed at the ‘start’ position of the maze, and the robot would navigate the ball through obstacles and get the ball to the ‘finish’ position. The robot would be able to move the ball through the maze by physically tilting the base of the puzzle with its hand. In the process, the robot would utilize the most efficient way possible. If no possible path exists, the robot would not begin to solve the maze. The first approach was to test the feasibility of the project and an open loop offline-learning algorithm was used to test if the robot could physically solve a given maze. Once this proved successful, the robot was then given multiple mazes that were labeled with the best path, so that it would be able to pick up on the ideal policy on its own, as a result of supervised learning. Once sufficient training was provided, the robot was tested on multiple patterns of mazes that were not seen beforehand by the robot. The robot correctly solved all test mazes that were given to it, giving it a final accuracy rate of 100%.
Graduation Semester
2013-08
Permalink
http://hdl.handle.net/2142/45440
Copyright and License Information
Copyright 2013 Vishnu Nath Kamalnath

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