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Fuzzy Logic Controller with Fuzzylab Python Library and the Robot Operating System for Autonomous Robot Navigation: A Practical Approach

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Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 862))

Abstract

The navigation system of a robot requires sensors to perceive its environment to get a representation. Based on this perception and the state of the robot, it needs to take an action to made a desired behavior in the environment. The actions are defined by a system that processes the obtained information and which can be based on decision rules defined by an expert or obtained by a training or optimization process. Fuzzy logic controllers are based on fuzzy logic on which degrees of truth are used on system variables and has a rulebase that stores the knowledge about the operation of the system. In this paper a fuzzy logic controller is made with the Python fuzzylab library which is based on the Octave Fuzzy Logic Toolkit, and with the Robot Operating System (ROS) for autonomous navigation of the TurtleBot3 robot on a simulated and a real environment using a LIDAR sensor to get the distance of the objects around the robot.

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Correspondence to Oscar Castillo .

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Avelar, E., Castillo, O., Soria, J. (2020). Fuzzy Logic Controller with Fuzzylab Python Library and the Robot Operating System for Autonomous Robot Navigation: A Practical Approach. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications. Studies in Computational Intelligence, vol 862. Springer, Cham. https://doi.org/10.1007/978-3-030-35445-9_27

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