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 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).