Артем Филатов


Закончил в 2014 году Санкт-Петербургский электротехнический Университет со степенью бакалавра. Получил степень магистра в 2016 году в том же университете.

Основные научные интересы: информатика, С++, алгоритмическая математика.



  • Kirill Krinkin, Anton Filatov, Artyom Filatov, A. Huletski, D. Kartashov

    One of the key issues that prevents creation of a truly autonomous mobile robot is the simultaneous localization and mapping (SLAM) problem. A solution is supposed to estimate a robot pose and to build a map of an unknown environment simultaneously. Despite existence of different algorithms that try to solve the problem, the universal one has not been proposed yet. A laser rangefinder is a widespread sensor for mobile platforms and it was decided to evaluate actual 2D laser scan based SLAM algorithms on real world indoor environments. The following algorithms were considered: Google Cartographer, GMapping, tinySLAM. According to their evaluation, Cartographer and GMapping are more accurate than tinySLAM and Cartographer is the most robust of the algorithms.

    Proceedings of the 22st Conference of Open Innovations Association FRUCT, Май 2018
  • K. Krinkin, An. Filatov, Ar. Filatov, O. Kurishev, A.Lyanguzov

    DDS (data distribution service) is a middleware protocol and API standard for data transferring using a publisher-subscriber model from the Object Management Group (OMG). There exist various open source and commercial implementations of DDS standard that provides API and services for data distribution. Every developer claims that his implementation fits standard and provides the best possible parameters for data transferring. Three different implementations of DDS are compared to determine their usability and performance characteristics. This paper presents a testing framework that allows to evaluate different implementations in the same experiments and moreover to include another DDS.

    Proceedings of the 22st Conference of Open Innovations Association FRUCT, Май 2018
  • An. Filatov, Ar. Filatov, K. Krinkin, B. Chen, D. Molodan

    SLAM (Simultaneous Localization and mapping) is one of the most challenging problems for mobile platforms and there is a huge amount of modern SLAM algorithms. The choice of the algorithm that might be used in every particular problem requires prior knowledge about advantages and disadvantages of each algorithm. This paper presents the approach for comparison of SLAM algorithms that allows to find the most accurate one. The accent of research is made on 2D SLAM algorithms and the focus of analysis is 2D map that is built after algorithm performance. Three metrics for evaluation of maps are presented in this paper

    Август 2017
  • K. Krinkin, An. Filatov, Ar. Filatov, A. Huletski D. Kartashov
    Proceedings 19th Conference of Open Innovations Association FRUCT — Finland, University of Jyväskylä, 9-11 Nov 2016, Pp 99-105, Ноябрь 2016
  • A. Kolpakov, An. Filatov, Ar. Filatov
    Izvestiya SPbGETU «LETI», Июнь 2016
  • A. Kolpakov, Ar. Filatov, An. Filatov
    Izvestiya SPbGETU «LETI», Апрель 2016