Intelligent Controller for Mobile Robot: Fuzzy Logic Approach

A key issue in the research of an autonomous mobile robot is the design and development of an intelligent controller which can control and enables the robot to navigate in a real world environment, avoiding structured and unstructured obstacles especially in crowded and unpredictably changing environment, whether it is in land, underground, under water, on

the air or in space. An intelligent system has the ability to act appropriately in an uncertain environment, where an appropriate action is that which increases the probability of success, and success is the achievement of behavioral sub goals that support the system's ultimate goal. This paper presents the development in the area of intelligent controller for mobile robot in various (known and unknown) environments. A successful way of structuring the navigation task deal with the issues of individual behaviour design and action coordination. The behaviours will be addressed using fuzzy logic in the present research. The inputs to the proposed fuzzy control scheme consist of a heading angle between a robot and a specified target and the distances between the robot and the obstacles to the left, front, and right to its locations, being acquired by an array of sensors. In this paper, we proposed an intelligent controller for mobile robot navigation algorithm employing fuzzy theory in a complex cluttered environment. Simulation results verified the effectiveness of the controllers. 1 Introduction Current research and development of mobile robot have attracted the attention of researchers in the areas of engineering, computer science, biology, mining and others. This is due to the high potential of mobile robots application. Autonomous mobile robots are robots which can perform desired tasks in unstructured environments without continuous human guidance (Frank and Goswami, 2004; Ibrahim and Fernandes, 2004; Kim and Cho, 2006; Waterman, 1989). Many kinds of robots are autonomous to some degree. One important area of current robotics research is to enable the robot to cope with its environment whether this is on land, underwater, in the air, underground or in space. A fully autonomous robot in the real world has the ability to: • Gain information about the environment. • Travel from one point to another point, without human navigation assistance. • Avoid situations that are harmful to people, property or itself. • Repair itself without outside assistance. A robot may also be able to learn autonomously. Autonomous learning includes the ability to: • Learn or gain new capabilities without outside assistance. • Adjust strategies based on the surroundings. • Adapt to surroundings without outside assistance. Navigation for mobile robots can be well-defined in mathematical (geometrical) terms. It also involved many distinct sensory inputs and computational processes. Elementary decisions like turn left, or turn right, or run or stop is made on the basis...

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