Fuzzy logic controller for robot navigation in environment with obstacles and dead-end traps

• Main Author: Shayestegan, Mohsen
• Format: Thesis
• Language: English
• Published: 2013
• Online Access: http://psasir.upm.edu.my/id/eprint/56151/1/FK%202013%20104RR.pdf; http://psasir.upm.edu.my/id/eprint/56151/

The intelligent mobile robot should be capable enough to assimilate the information from the surrounding environment, process the obtained information, and move toward the target while it avoids the obstacles. The robot‟s motion should be based upon the motion which has been programmed by the humans. This movement should not endanger the robot itself so that the planning of the robot‟s motion provides an important aspect of the automated systems. This study aims to allow the robot to move safely without colliding with obstacles to reach a specified position in an unknown environment. To achieve the aim of the study, a fuzzy controller was proposed and employed in intelligent mobile robot navigation strategies within unknown environments. A modified virtual target method with switching command was integrated to solve the local minimum problem. Then, a fuzzy controller with fewer numbers of rules was proposed based upon the Braitenberg‟s strategy for faster navigation of mobile robot in an unknown environment. A memorizing strategy with virtual target approach was also integrated to solve the multiple dead end trap problem. These fuzzy controllers have four inputs (one target angle and three obstacle distance), two outputs (left and right speed) and less than 20 rules. For simplicity, membership functions consisting of triangular functions, S-type and Ztype are selected by trial-and-error based on experimentation. The suggested fuzzy rules control the speed of the robot according to the information about the target angle and distances from the obstacles. This combined method which uses a new kind of switching strategy significantly results in resolving the problem of poor performance to detect collision and dead end trap in local navigation. This is an advantage beyond the pure fuzzy logic controller and the switching strategy. In this study, dead cycle traps may have any type of shape such as U-shape dead ends traps,G-shape, snail shape and recursive U-shape. A virtual mobile robot, E-puck robot in WEBOTS simulator was used to evaluate the performance of the proposed method. Few features such as time travelling, distance travelling of the output responses were analyzed. By using the proposed controller, mobile robot can make logicaltr ajectories toward the target position, finds best paths out of dead cycle traps,avoids any types of obstacles in environment, and adjusts its speed efficiently to enhance its performance to obstacle avoidance. Comparisons are made between proposed fuzzy logic and Motlagh fuzzy controller [14]. Comparative results among these controllers indicate the superiority of the proposed fuzzy method with the ability to navigate safely with shorter path travelling even in dynamic environment. Finally, several trap situations designed by previous researchers were adopted to evaluate the performance of the proposed approach. The simulation results were presented to verify the effectiveness of the proposed architectures in most dead end trap environments. Generally, in the static environment, navigation time and navigation distance has been reduced about 40% and 50% by using the proposed method. In addition, the robot has moved 35% more safely in the dynamic environment.