Map Generation and Path Planning for Autonomous Mobile Robot in Static Environments Using GA

In this paper, we present our initial idea of developing an integrated an autonomous mobile robot system that can explore an unknown environment. The proposed system consists of three components 1) a map generation 2) path planning and 3) path tracking. The proposed approach allows a mobile robot to navigate the unknown environment, avoiding obstacles and following a defined path to reach the target position without collision. Ultrasonic sensor data was collected via moving the robot along the perimeter of the environment while incrementally updating the occupancy grid using ultrasonic/laser sensor to measure the distance between the obstacles and the edge of the environment. This dataset will be converted to a map that is used by Genetic Algorithms (GAs) to create an optimal route from a pre-defined start and target points. The autonomous robot system will travel between these points by following a trajectory defined by waypoints estimated using GAs. The pure pursuit (PP) algorithm is used for trajectory following. The proposed system was tested in a real environment using LEGO robot and in simulation using GAZEBO software. The results indicate that the proposed integrated autonomous mobile robot system is promising.