An FPGA-based architecture for a latitude and longitude correction in autonomous navigation tasks

• Published in: Measurement : journal of the International Measurement Confederation Vol. 182; p. 109757
• Main Authors: Correa-Caicedo, Pedro J., Barranco-Gutiérrez, Alejandro I., Guerra-Hernandez, Erick I., Batres-Mendoza, Patricia, Padilla-Medina, Jose A., Rostro-González, Horacio
• Format: Journal Article
• Language: English
• Published: London Elsevier Ltd 01.09.2021; Elsevier Science Ltd
• Subjects: Algorithms; Autonomous navigation; Autonomous vehicles; Data Correction; Field programmable gate arrays; FPGA-based Implementation; Fuzzy logic; Fuzzy Systems; GPS; Latitude; Longitude; Parallel processing; Personal computers; Platforms; Sensor arrays; Software; Studies; GPS; Data Correction; FPGA-based Implementation; Fuzzy Systems
• ISSN: 0263-2241; 1873-412X
• DOI: 10.1016/j.measurement.2021.109757

•A fully reconfigurable and scalable FPGA-based architecture for latitude and longitude correction.•The correction is performed by a fuzzy system implemented in the FPGA.•Correction results are highly similiar as in software as in hardware.•The hardware implementation speed up in 40000x the software implementation.•This implementation is highly suitable for autonomous vehicles. The response speed of the intelligent systems embedded in an autonomous vehicle is crucial for its correct operation and reduction of the risks on the road derived from autonomous driving. For that reason, it is necessary to optimize the algorithms that process the data from the sensors; with that aim the Field-Programmable Gate Arrays (FPGAs) offer the possibility of parallelizing the tasks to be carried out by mentioned systems, accelerating their response and improving their performance. In this regard, this paper introduces a fuzzy absolute position correction system, which corrects the latitude and longitude data registered from a GPS Pmod sensor and its implementation on a FPGA to speed up the correction results. A necessary comparison of the algorithm execution time on different platforms such as: A Raspberry pi 4 model B, a personal computer (PC) with Ubuntu 18.04.4 64-bit and the FPGA model, was performed to validate the results and the effectiveness of the implementation. The correction system was validated in software and hardware on 4 different routes, each of them with a large number of samples. The results were highly similar in the three platforms; however, the FPGA-based implementation offers a speed up of 40000x compared to software-based implementations.