Fuzzy logic controller with fuzzylab python library and the robot operating system for autonomous mobile robot navigation

4Citations
Citations of this article
15Readers
Mendeley users who have this article in their library.

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 make a desired behavior in the environment. The actions are defined by a system that processes the obtained information. This system 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 rule‐base 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.

Cite

CITATION STYLE

APA

Avelar, E., Castillo, O., & Soria, J. (2020). Fuzzy logic controller with fuzzylab python library and the robot operating system for autonomous mobile robot navigation. Journal of Automation, Mobile Robotics and Intelligent Systems, 14(1), 48–54. https://doi.org/10.14313/JAMRIS/1-2020/6

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free