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Ros: An Autonomous Robot Operating System For Simultaneous Localization And Mapping Using A 2D Lidar Sensor

Published in: Prospective and trends in technology and skills for sustainable social development. Leveraging emerging technologies to construct the future: Proceedings of the 19th LACCEI International Multi-Conference for Engineering, Education and Technology
Date of Conference: July 19-23, 2021
Location of Conference: Virtual
Authors: Alberto José Chinchilla Santos (Universidad Tecnológica Centroamericana, UNITEC, HN)
José Manuel Murillo Castellanos (Universidad Tecnológica Centroamericana, UNITEC, HN)
Alicia María Reyes Duke (Universidad Tecnológica Centroamericana, UNITEC, HN)
Full Paper: #520

Abstract:

Currently the need and use of autonomous robots is growing exponentially both in the industrial sector and in everyday life, due to this arises the implementation of systems that facilitate the robot to operate autonomously and, in turn, make a graphical model of the environment in which it is mobilized. SLAM systems allow the robot to be located in real time without the need for technologies such as GPS, and at the same time they create a graphic model that is very accurate to reality. There are different ways to implement a SLAM system, one of the most popular is by using LIDAR sensors that through the principle of laser triangulation generate the necessary feedback for the robot to detect surfaces, objects, obstacles and distance between them. The following research project was carried out with the aim of developing an intelligent mobile autonomous robot that allows accurate maps to reality and can be located in real time and accurately, using ROS for communication between actuators, microcontrollers and sensors. The design of the structure and its studies have been carried out with CAD software, the selection of components was made with the use of multicriteria and decision matrices, which helped to select those that best fit the project. It was proposed and demonstrated that the use of this sensor is an excellent option to implement SLAM and thus develop autonomous robots.