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Framework for Fast Experimental Testing of Autonomous Navigation Algorithms

Group of Automation, Robotics and Computer Vision (AUROVA), University of Alicante, San Vicente del Raspeig S/N, 03690 Alicante, Spain
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Appl. Sci. 2019, 9(10), 1997;
Received: 12 April 2019 / Revised: 9 May 2019 / Accepted: 10 May 2019 / Published: 15 May 2019
(This article belongs to the Special Issue Mobile Robots Navigation)
PDF [6650 KB, uploaded 21 May 2019]


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. View Full-Text
Keywords: autonomous navigation; mobile robots; Monte Carlo localization; SLAM; GNSS; planning; control; Kalman filter autonomous navigation; mobile robots; Monte Carlo localization; SLAM; GNSS; planning; control; Kalman filter

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Muñoz–Bañón, M.Á.; del Pino, I.; Candelas, F.A.; Torres, F. Framework for Fast Experimental Testing of Autonomous Navigation Algorithms. Appl. Sci. 2019, 9, 1997.

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