Genetic Goal Oriented Path Planning Algorithm for Acute Obstacle Avoidance in Mobile Robot Navigation

摘要

Current researches in mobile robots aim to build an autonomous and intelligent system which can plan its motion in a static, dynamic and uncertain environment. In this research, Genetic Algorithm (GA) is used to assist the autonomous mobile robot to move, identify the obstacles by learning the environment and reach the desired goal. This study is focused on the development of algorithm for the acute obstacle avoidance behavior. The proposed navigation technique is capable of re-planning the new optimum collision free path in the event of mobile robot encountering any dynamic obstacles. The method is verified using MATLAB simulation and validated the algorithm using Team AmigoBotTM robot. The results obtained from simulation and experiments are discussed at the end of the paper.