| Navigation in unknown, much cluttered environments is a difficult task in mobilerobotics. The robot should be capable of sensing its environment, interpreting the sensedinformation to obtain the knowledge of its position and the environment, and then planning acollision free path from an initial position to a target with avoiding obstacles, and controllingthe robot direction and velocity to reach the target.Behavioral approaches have been shown to be very successful in unknown anddynamic environments with uncertainties. The behavior control method decompose thenavigation system into special task-specific behavior modules, e.g., obstacle avoidance, goalseeking, path following, etc., which are connected directly to sensors and actuators andoperate in parallel. Simple behaviors are then combined in order to produce a complexstrategy able to pursue the strategic goals while effectively reacting to any contingencies.Therefore, this architecture can act in real-time and has good robustness. Fuzzy logicapproach is one of many common ways to design behavior control architecture since thecritical problem for a behavior design is to guarantee robust operation in the presence ofuncertainty. Fuzzy systems have the ability to treat uncertain and imprecise information usinglinguistic rules. They offer possible implementation of human knowledge and experience,and have an advantage in that they do not require a precise analytical model of both robot andenvironment.This thesis presents a design of a new fuzzy behavior control system for autonomousmobile robot navigation. It calls for a robot to be given a goal target and for the robot then toreach the goal autonomously while avoiding any static or dynamic obstacles in its path. Thisapproach is verified with simulation and real-world tests. |
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