gyroscopyГироскопия и навигацияGiroskopiya i Navigatsiya0869-70352075-0927AO «Концерн «ЦНИИ «Электроприбор»10.17285/0869-7035.2017.25.1.018-032gyroscopy-300Research ArticleСтатьиSLAM-алгоритм на основе лазерных измерений при использовании микролетательных аппаратов в помещенииIndoor Laser-Based SLAM for Micro Aerial VehiclesДоерК.DoerC.

Доер Кристофер

ШольцГ.ScholzG.

Шольц Георг

ТроммерГ. Ф.TrommerG.F.

Троммер Герт Франц

Действительный член общественного объединения «Академия навигации и управления движением».

Институт оптимизации систем, Технологический институт КарлсруэГерманияInstitute of Systems Optimization (ITE), Karlsruhe Institute of Technology (KIT), KarlsruheGermanyИнститут оптимизации систем, Технологический институт Карлсруэ.ГерманияInstitute of Systems Optimization (ITE), Karlsruhe Institute of Technology (KIT), KarlsruheGermanyИнститут оптимизации систем, Технологический институт Карлсруэ. Университет ИТМО (С.-Петербург).ГерманияInstitute of Systems Optimization, Karlsruhe Institute of Technology; National Research University of Information Technologies, Mechanics and Optics (ITMO), Saint Petersburg, RussiaGermany2017251120252511832Copyright © Доер К., Шольц Г., Троммер Г., 20252025Доер К., Шольц Г., Троммер Г.Doer C., Scholz G., Trommer G.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.gyroscopy.ru/jour/article/view/300

В статье описан двухмерный SLAM-алгоритм одновременной локализации объекта и картографирования помещения на основе лазерных измерений. Предлагаются при применении на микролетательных аппаратах (МЛА) адаптация и оптимизация алгоритма TinySLAM, используемого для наземных объектов. Оптимизация стратегии обновления карты и модели движения значительно повышает точность работы алгоритма. Проведено расширение работы алгоритма до трехмерного решения. Испытания предложенного алгоритма проведены на модельных и реальных данных. Оптимизированный SLAM-алгоритм способен составить карту целого этажа офисного здания с высокой точностью, а также может использоваться в режиме реального времени.

This article presents a laser-based 2D simultaneous localization and mapping (SLAM) algorithm for indoor environments. An adaption and optimization of a ground vehicle SLAM solution (TinySLAM) for the use with Micro Aerial Vehicles is proposed. Optimizations of the map update strategy and a motion model improves the accuracy strongly. An extension to 3D mapping is introduced. The presented algorithm is tested with simulated and real world data. The optimized SLAM solution maps a whole floor of an office building very accurately and achieves embedded real-time capability.

SLAMМЛАкарта с координатной сеткойлазерлокализация по методу Монте-Карло.SLAMMAVGrid mapLaserMonte Carlo Localization.ReferencesThrun S., Burgard S., Fox D. Probabilistic Robotics, MIT Press.Thrun S., Burgard S., Fox D. Probabilistic Robotics, MIT Press.Elizzar A., Parr R. DP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks. International Joint Conference on Artificial Intelligence (IJCAI). 2003.Elizzar A., Parr R. DP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks. International Joint Conference on Artificial Intelligence (IJCAI). 2003.Mur-Artal, Montiel R., Tard J. ORB-SLAM: A Versatile and Accurate Monocular SLAM System. IEEE Transactions on Robotics. 2015.Mur-Artal, Montiel R., Tard J. ORB-SLAM: A Versatile and Accurate Monocular SLAM System. IEEE Transactions on Robotics. 2015.Leonard J., Durrant-Whyte H. Mobile robot localization by tracking geometric beacons. IEEE Transactions on Robotics and Automation. 1991.Leonard J., Durrant-Whyte H. Mobile robot localization by tracking geometric beacons. IEEE Transactions on Robotics and Automation. 1991.Grisetti G., Kuemmerle R., Stachniss C., Burgard W. A Tutorial on Graph-Based SLAM. IEEE Intelligent Transportation Systems Magazine. 2010.Grisetti G., Kuemmerle R., Stachniss C., Burgard W. A Tutorial on Graph-Based SLAM. IEEE Intelligent Transportation Systems Magazine. 2010.Montemerlo M., Thrun S., Koller D., Wegbreit B. FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem. 18th National Conference on Artificial Intelligence (AAAI-02) Proceedings. 2002.Montemerlo M., Thrun S., Koller D., Wegbreit B. FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem. 18th National Conference on Artificial Intelligence (AAAI-02) Proceedings. 2002.Scholz G., Trommer G.F. Model Based Control of a Quadcopter with Tiltable Rotors. Gyroscopy and Navigation. 2016. Vol 7. No. 1. P. 77–81.Scholz G., Trommer G.F. Model Based Control of a Quadcopter with Tiltable Rotors. Gyroscopy and Navigation. 2016. Vol 7. No. 1. P. 77–81.Bloesch M., Weiss S., Scaramuzza D., Siegwart S. Vision based MAV navigation in unknown and unstructured environments. IEEE International Conference on Roboics and Automation (ICRA). Anchorage, USA, 2010. P. 21–28.Bloesch M., Weiss S., Scaramuzza D., Siegwart S. Vision based MAV navigation in unknown and unstructured environments. IEEE International Conference on Roboics and Automation (ICRA). Anchorage, USA, 2010. P. 21–28.Alpen M., Frick K., Horn J. A Real-Time On-Board Orthogonal SLAM for an Indoor UAV. 5th International Conference on Intelligent Robotics and Applications (ICIRA). Proceedings. Part III. 2012. P. 542–551.Alpen M., Frick K., Horn J. A Real-Time On-Board Orthogonal SLAM for an Indoor UAV. 5th International Conference on Intelligent Robotics and Applications (ICIRA). Proceedings. Part III. 2012. P. 542–551.Bachrach A., He R., Roy N. Autonomous flight in unstructured and unknown indoor environments. European Micro Air Vehicle Conference and Flight Competition (EMAV). Delft, Netherlands, 2009. P. 21–28.Bachrach A., He R., Roy N. Autonomous flight in unstructured and unknown indoor environments. European Micro Air Vehicle Conference and Flight Competition (EMAV). Delft, Netherlands, 2009. P. 21–28.Steux B., El Hamzaoui O. TinySLAM: A SLAM algorithm in less than 200 lines C-language program. 11th International Conference on Control Automation Robotics & Vision (ICARCV). 2010.Steux B., El Hamzaoui O. TinySLAM: A SLAM algorithm in less than 200 lines C-language program. 11th International Conference on Control Automation Robotics & Vision (ICARCV). 2010.Steux B., El Hamzaoui O. SLAM algorithm with parallel localization loops: TinySLAM 1.1. IEEE International Conference on Automation and Logistics (ICAL). 2011.Steux B., El Hamzaoui O. SLAM algorithm with parallel localization loops: TinySLAM 1.1. IEEE International Conference on Automation and Logistics (ICAL). 2011.Doer C., Scholz G., Trommer G.F. Grid-based Laser SLAM for Micro Aerial Vehicles. Proceedings 23rd Saint Petersburg International Conference on Integrated Navigation Systems. P. 463–467.Doer C., Scholz G., Trommer G.F. Grid-based Laser SLAM for Micro Aerial Vehicles. Proceedings 23rd Saint Petersburg International Conference on Integrated Navigation Systems. P. 463–467.Nister D., Naroditsky O., Bergen J. Visual Odometry. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2004.Nister D., Naroditsky O., Bergen J. Visual Odometry. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2004.Scanning Laser Range Finder UTM-30LX-EW Specification. Hokuyo Automatic CO. LTD, 2012.12.03.Scanning Laser Range Finder UTM-30LX-EW Specification. Hokuyo Automatic CO. LTD, 2012.12.03.

The authors declare that there are no conflicts of interest present.