Path planning in nonholonomic system using hybridization of voronoi and Q-learning algorithms
Dissertant
Thesis advisor
University
Philadelphia University
Faculty
Faculty of Information Technology
Department
Department of Computer Science
University Country
Jordan
Degree
Master
Degree Date
2017
English Abstract
Robot movement in an environment may collide with obstacles.
Path planning is an important part of a navigation system which is composed of four parts: presentation, localization, path planning and path execution.
The path planning part is defined as a series of movement that leads the mobile robot to move from the starting point to the target without colliding with any obstacle.
The mobile robot path planning is very important especially in the environment where it's very dangerous for humans to work in such as heavy workshops, power electric environment etc.
The aim of this study is to solve path planning problems by using the hybridization of Voronoi and Q-learning algorithms.
The Voronoi algorithm has the ability to obtain an obstacle position represented by multiple points in space.
On the other hand, Q-learning has a good performance in navigation strategy.
The simulation of the proposed work has the ability to use a different style of maps that represent the robot, the target, and the obstacle positions.
The application areas of the proposed work are considered as mechatronics engineering, industrial, and robotics.
The evaluation process is performed in two main scenarios: the first one in static environment whiles the second one in the dynamic environment.
Finally, a comparison with other related works is performed and the result of this comparisons shows that our algorithm provides better performance in terms of wasting the space and the time needed to reach the target.
Main Subjects
Information Technology and Computer Science
No. of Pages
43
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Background and related works.
Chapter Three : Proposed system methodology.
Chapter Four : Implementation.
Chapter Five : Results analysis.
Chapter Six : Conclusions and future works.
References.
American Psychological Association (APA)
Hasan, Mustafa Muhammad. (2017). Path planning in nonholonomic system using hybridization of voronoi and Q-learning algorithms. (Master's theses Theses and Dissertations Master). Philadelphia University, Jordan
https://search.emarefa.net/detail/BIM-955871
Modern Language Association (MLA)
Hasan, Mustafa Muhammad. Path planning in nonholonomic system using hybridization of voronoi and Q-learning algorithms. (Master's theses Theses and Dissertations Master). Philadelphia University. (2017).
https://search.emarefa.net/detail/BIM-955871
American Medical Association (AMA)
Hasan, Mustafa Muhammad. (2017). Path planning in nonholonomic system using hybridization of voronoi and Q-learning algorithms. (Master's theses Theses and Dissertations Master). Philadelphia University, Jordan
https://search.emarefa.net/detail/BIM-955871
Language
English
Data Type
Arab Theses
Record ID
BIM-955871
