Framework for Fast Experimental Testing of Autonomous Navigation Algorithms

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Title: Framework for Fast Experimental Testing of Autonomous Navigation Algorithms
Authors: Muñoz-Bañón, Miguel Á. | del Pino, Iván | Candelas-Herías, Francisco A. | Torres, Fernando
Research Group/s: Automática, Robótica y Visión Artificial
Center, Department or Service: Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal | Universidad de Alicante. Instituto Universitario de Investigación Informática
Keywords: Autonomous navigation | Mobile robots | Monte Carlo localization | SLAM | GNSS | Planning | Control | Kalman filter
Knowledge Area: Ingeniería de Sistemas y Automática
Issue Date: 15-May-2019
Publisher: MDPI
Citation: Muñoz–Bañón MÁ, del Pino I, Candelas FA, Torres F. Framework for Fast Experimental Testing of Autonomous Navigation Algorithms. Applied Sciences. 2019; 9(10):1997. doi:10.3390/app9101997
Abstract: Research in mobile robotics requires fully operative autonomous systems to test and compare algorithms in real-world conditions. However, the implementation of such systems remains to be a highly time-consuming process. In this work, we present an robot operating system (ROS)-based navigation framework that allows the generation of new autonomous navigation applications in a fast and simple way. Our framework provides a powerful basic structure based on abstraction levels that ease the implementation of minimal solutions with all the functionalities required to implement a whole autonomous system. This approach helps to keep the focus in any sub-problem of interest (i.g. localization or control) while permitting to carry out experimental tests in the context of a complete application. To show the validity of the proposed framework we implement an autonomous navigation system for a ground robot using a localization module that fuses global navigation satellite system (GNSS) positioning and Monte Carlo localization by means of a Kalman filter. Experimental tests are performed in two different outdoor environments, over more than twenty kilometers. All the developed software is available in a GitHub repository.
Sponsor: This work has been supported by InterregV Sudoe and FEDER programs of European Commission through the COMMANDIA project SOE2/P1/F0638, and by the Spanish Government through the FPU grant FPU15/04446 and the research project RTI2018-094279-B-I00.
ISSN: 2076-3417
DOI: 10.3390/app9101997
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
Peer Review: si
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