Framework for Fast Experimental Testing of Autonomous Navigation Algorithms
AbstractResearch 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.
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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.
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.Chicago/Turabian Style
Muñoz–Bañón, Miguel Á.; del Pino, Iván ; Candelas, Francisco A.; Torres, Fernando. 2019. "Framework for Fast Experimental Testing of Autonomous Navigation Algorithms." Appl. Sci. 9, no. 10: 1997.
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