Numerical Analysis of 2-D Positioned, Indoor, Fuzzy-Logic, Autonomous Navigation System Based on Chromaticity and Frequency-Component Analysis of LED Light

Topics concerning autonomous navigation, especially those related to positioning systems, have recently attracted increased research attention. The commonly available global positioning system (GPS) is unable to determine the positions of vehicles in GPS-shaded regions. To address this concern, this paper presents a fuzzy-logic system capable of determining the position of a moving robot in a GPS-shaded indoor environment by analyzing the chromaticity and frequency-component ratio of LED lights installed under the ceiling. The proposed system’s performance was analyzed by performing a MATLAB simulation of an indoor environment with obstacles. During the simulation, the mobile robot utilized a fuzzy autonomous navigation system with behavioral rules to approach targets successfully in a variety of indoor environments without colliding with obstacles. The robot utilized the x and y coordinates of the fuzzy positioning system. The results obtained in this study confirm the suitability of the proposed method for use in applications involving autonomous navigation of vehicles in areas with poor GPS-signal reception, such as in tunnels.

Robot control and navigation: ARI’s autonomous system

This paper describes ARI robot, the social robot developed by PAL Robotics, highlights its autonomous navigation system framework using Visual SLAM and the potential of combining it with its interaction abilities to achieve safe and robust navigation in human-crowded environments.

Robot control and navigation: ARI’s autonomous system

This paper describes ARI robot, the social robot developed by PAL Robotics, highlights its autonomous navigation system framework using Visual SLAM and the potential of combining it with its interaction abilities to achieve safe and robust navigation in human-crowded environments.