An FPGA implementation of the SMG-SLAM algorithm

• Published in: Microprocessors and microsystems Vol. 36; no. 3; pp. 190 - 204
• Main Authors: Mingas, Grigorios, Tsardoulias, Emmanouil, Petrou, Loukas
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-05-2012
• Subjects: Co-design; Field programmable gate array; Genetic algorithm; Scan-matching; Simultaneous localization and mapping; Simultaneous localization and mapping; Co-design; Field programmable gate array; Scan-matching; Genetic algorithm
• ISSN: 0141-9331; 1872-9436
• DOI: 10.1016/j.micpro.2011.12.002

One of the main tasks of a mobile robot in an unknown environment is to build and update a map of the environment and simultaneously determine its location within this map. This problem is referred to as the simultaneous localization and mapping (SLAM) problem. The article introduces scan-matching genetic SLAM (SMG-SLAM), a novel SLAM algorithm. It is based on a genetic algorithm that uses scan-matching for gene fitness evaluation. The main scope of the article is to present a hardware implementation of SMG-SLAM using an field programmable gate array (FPGA). The architecture of the system is described and it is shown that it is up to 14.83 times faster compared to the software algorithm without significant loss in accuracy. The proposed implementation can be used as part of a larger system, providing efficient SLAM for autonomous robotic applications.