sibadiНаучный рецензируемый журнал "Вестник СибАДИ"The Russian Automobile and Highway Industry Journal2071-72962658-5626The Siberian State Automobile and Highway University10.26518/2071-7296-2022-19-6-900-914sibadi-1567Research ArticleТРАНСПОРТTRANSPORTРазработка семантической карты для беспилотного автомобиля с использованием метода одновременной локализации и картографированияDevelopment of a semantic map for an unmanned vehicle using a simultaneous localisation and mapping methodhttps://orcid.org/0000-0001-7603-3413РодионовО. А.RodionovO. A.

Родионов Олег Александрович – старший инженер отдела разработки систем распознавания лаборатории беспилотных технологий

г. Иннополис

Oleg A. Rodionov – head engineer of the Recognition Systems Development Department

Innopolis

o.rodionov@innopolis.universityhttps://orcid.org/0000-0003-3874-0883РашидБ.RasheedB.

Бадер Рашид – руководитель отдела разработки систем распознавания лаборатории беспилотных технологий

г. Иннополис

Bader Rasheed – head of the Recognition Systems Development Department

Innopolis

b.rasheed@innopolis.universityЛаборатория беспилотных технологий университета ИннополисРоссияInnopolis University Unmanned Technology LaboratoryRussian Federation202207012023196900914Copyright © Родионов О.А., Рашид Б., 20232023Родионов О.А., Рашид Б.Rodionov O.A., Rasheed B.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://vestnik.sibadi.org/jour/article/view/1567Введение

Введение. Сфера беспилотных технологий стремительно развивается, и в ней проводится множество исследований по применению на практике алгоритмов искусственного интеллекта для решения комплексных задач на дороге. Сложности в восприятии машиной окружающего мира привели к появлению специальных карт высокого разрешения (High definition maps). Эти карты используются для упрощения и улучшения качества и надежности работы других подсистем из стека беспилотных технологий, таких как модули локализации, навигации и планирования. В современной литературе встречаются в основном работы по применению таких карт, а процесс разработки карты остается за рамками рассмотрения.

Цель работы

Цель работы. Создать методологию проектирования семантических карт для беспилотного транспорта с подробным описанием каждого из этапов разработки.

Материалы и методы

Материалы и методы. В данной статье описывается методология создания HD-карт, включающая в себя этапы сбора данных по методологии SLAM (Simultaneous localization and mapping), их дальнейшую обработку и разработку семантики дорожной сети. Описываемый алгоритм применяется на практике на примере разработки семантической карты района г. Иннополиса с применением SLAM подхода, использующего лидарную инерциальную одометрию – LIO-SAM (LIDAR inertial odometry via smoothing and mapping).

Результаты

Результаты. Сформированы основные этапы методологии создания HD-карт для беспилотного транспорта. Авторы реализовали предложенную концепцию на практике и подробно описали процесс создания семантической карты для г. Иннополиса.

Обсуждение и заключение

Обсуждение и заключение. Предложенная методология может быть использована для любого типа беспилотной техники (наземная, летная, водная) и для разных дорожных условий (город, бездорожье) в зависимости от информации, которую должна предоставлять карта для реализации поставленных для беспилотника целей и задач.

Introduction

Introduction: The field of unmanned technologies is rapidly developing and a lot of research is being conducted on the practical application of artificial intelligence algorithms to solve complex problems on the road. The difficulties in the perception of the surrounding world by the machine led to the appearance of special High definition maps. These maps are used to simplify and improve the quality and reliability of other subsystems from the stack of autonomous technologies, such as localization, prediction, navigation and planning modules. In modern literature, there are mainly works on the practical application of such maps, and the process of developing a map remains outside the scope of consideration.

The aim of the work is to create a methodology for designing semantic maps for autonomous vehicles with a detailed description of each of the development stages.

Materials and methods

Materials and methods: The article describes the methodology for creation of HD maps, which includes the stages of data collection using SLAM (Simultaneous localization and mapping) approach, its further processing and the development of the semantics of the road network. The described algorithm is applied in practice to develop the semantic map of Innopolis city area using SLAM approach with LIDAR inertial odometry via smoothing and mapping (LIO-SAM).

Results

Results: The main stages of the methodology for creating HD maps for autonomous vehicles have been proposed and investigated. Authors implemented the proposed concept in practice and described in detail the process of creating a semantic map for the Innopolis city area.

Conclusions

Conclusions: The proposed methodology can be used for any type of autonomous robots (ground vehicles, unmanned aerial vehicle, water transport) and can be implemented in different road conditions (city, off-road), depending on the information the map should provide for the implementation of the goals and objectives set for the autonomous vehicle.

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