Dotación de la capacidad de localización y mapeo simultáneo indoor a un robot móvil terrestre usando sensores IMU y LIDAR sobre el Framework ROS

Mobile robotics offers a great opportunity to develop applications in various areas of life everyday However, to be useful in most applications, you must have a map of the environment on which to plan collision-free trajectories. This map allows not only move in the surrounding space but identify th...

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Autores:
Quinche Guerra, José Daniel
Tipo de recurso:
Fecha de publicación:
2018
Institución:
Escuela Colombiana de Ingeniería Julio Garavito
Repositorio:
Repositorio Institucional ECI
Idioma:
spa
OAI Identifier:
oai:repositorio.escuelaing.edu.co:001/943
Acceso en línea:
https://catalogo.escuelaing.edu.co/cgi-bin/koha/opac-detail.pl?biblionumber=21798
https://repositorio.escuelaing.edu.co/handle/001/943
Palabra clave:
Localización y mapeo simultáneos
Robotica móvil
Plataforma movil
Simultaneous location and mapping
Mobile robotics
Mobile platform
Rights
openAccess
License
Derechos Reservados - Escuela Colombiana de Ingeniería Julio Garavito
Description
Summary:Mobile robotics offers a great opportunity to develop applications in various areas of life everyday However, to be useful in most applications, you must have a map of the environment on which to plan collision-free trajectories. This map allows not only move in the surrounding space but identify the position of the robot based on the characteristics of the environment. In recent years a great variety of algorithms have been created for the realization of the SLAM with the intention to give the ability to position a robot in an unknown environment while navigating in it, resulting in techniques with very good results and with a low computational cost that allow to be implemented in embedded systems such as reduced-board computers. In this work we made use of the techniques of creating maps by probabilistic methods that they are a great contribution to the solution of the SLAM problem and how was the creation of the mobile platform through the integration of hardware and software components in particular through the use of the ROS framework. Even when it was not possible to integrate the inertial measurement unit or a WEB camera for the development of odometry, other alternatives were explored that allowed the implementation and execution of the experiments with the Gmapping and HectorSLAM methods covering the scope proposed for the work.