Implementation of Graph Based Path Planning Algorithms on a Mobile Robot in a Confined Site

Simultaneous Localization and Mapping (SLAM) is often associated with the problems of building a map of an unknown environment using a mobile robot while having the ability to keep track of the mobile robot within the map. Path planning is described as the ability of the mobile robot to navigate...

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Main Author: TANG, HON PANN
Format: Final Year Project
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.22983 /
Published: Universiti Teknologi PETRONAS 2017
Subjects:
Online Access: http://utpedia.utp.edu.my/22983/1/Tang%20Hon%20Pann_20025_EE_FYP%202_Dissertation.pdf
http://utpedia.utp.edu.my/22983/
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Summary: Simultaneous Localization and Mapping (SLAM) is often associated with the problems of building a map of an unknown environment using a mobile robot while having the ability to keep track of the mobile robot within the map. Path planning is described as the ability of the mobile robot to navigate without collision within the generated map from the starting point to the goal point using the shortest path and this enables autonomous navigation robots to perform many useful tasks. However, a lot of studies have been conducted to investigate effective and efficient algorithms to be used for generating accurate map from an environment and navigate in the environment effectively. This project investigates the performance of three different graph based path planning algorithms used, relaxed A*, A* and Dijkstra’s algorithm in a few environments with different obstacles settings using Gazebo environment simulator and Turtlebot simulator (computer simulation) and 4WD navigation robot (real environment simulation).