Case Study: Autonomous mobile robot exploration and navigation in unknown maze environment

Autonomous robots are becoming part of people’s daily lives in service applications such as vacuum cleaners, grass mowers, and food serving. One of the most recurrent challenges is to find a fitting path to move in an unknown environment. This student project aims to simulate this problem using the Turtlebot robot platform, inside an unknown maze. The main goal is the derivation of an autonomous exploration algorithm that allows the robot to eventually exit the maze, based on the assumption, that the robot has no preexisting knowledge about the maze. Additionally, to perceive his environment the robot only uses its integrated sensors, like LiDAR. The derived algorithms are implemented using two simulation environments, firstly a pure mathematical simulation implemented in Python and secondly as a Gazebo simulation, using ROS. In its final status, the robot can explore the maze probability-driven based on a type of occupancy grid. After finding the exit, the suboptimal path is determined using a wavefront algorithm in combination with a gradient descent method.