novtexmechМехатроника, автоматизация, управлениеMekhatronika, Avtomatizatsiya, Upravlenie1684-64272619-1253Commercial Publisher «New Technologies»10.17587/mau.22.246-253novtexmech-987Research ArticleРОБОТЫ, МЕХАТРОНИКА И РОБОТОТЕХНИЧЕСКИЕ СИСТЕМЫROBOT, MECHATRONICS AND ROBOTIC SYSTEMSПоследовательное сравнение сканов для навигации мобильного робота в условиях слабоструктурированной местностиScan Matching for Navigation of a Mobile Robot in Semi-Structured Terrain ConditionsБузловН. А.BuzlovN. A.

аспирант

г. Москва 

Buzlov Nikita A., Postgraduate 

Moscow, 105005 

nikita_buzlov@outlook.comМГТУ им. Н. Э. БауманаРоссияBauman Moscow Technical UniversityRussian Federation202117052021225246253Copyright © Commercial Publisher «New Technologies», 20212021Commercial Publisher «New Technologies»Commercial Publisher «New Technologies»https://mech.novtex.ru/jour/about/submissions#copyrightNoticehttps://mech.novtex.ru/jour/article/view/987

Для обеспечения беспилотного автономного движения наземных робототехнических средств требуется точно определять положение и ориентацию робота. Настоящее исследование связано с оценкой координат с помощью сопоставления сканов лазерного сканирующего дальномера в условиях слабоструктурированной местности и отсутствия сигнала глобальной спутниковой связи. Существующие методы сопоставления сканов имеют существенные недостатки в условиях движения по слабоструктурированной местности, связанные как со временем обработки данных от лазерного сканирующего дальномера, так и с качеством получаемых результатов. Предложенный метод основан на использовании искусственного потенциального поля фиксированного размера, создаваемого для каждой точки скана. Для простоты описания весь скан предварительно помещается в карту, состоящую из ячеек. При этом описываемые силы потенциального поля могут быть представлены законами, относящимися как к физике мира, так и к теории вероятностей. В ячейках карты происходит учет взаимовлияния всех сил от каждой точки скана, и, таким образом, получается итоговое искусственное потенциальное поле скана. Положение робота оценивается по изменению числа действующих сил одного скана на точки смежного скана с учетом их направления. Оценка ориентации осуществляется на основании суммы векторных моментов сил, действующих на точки смежного скана. Такой способ позволяет быстро оценивать смещение робота между сканами вне зависимости от условий движения и характера местности. В статье приведены результаты компьютерной апробации метода на данных, полученных от 3D-лидара Velodyne HDL-32 и обозначены условия работы метода для данного лидара, а также время, затрачиваемое на расчет оценки смещения. Ввиду особенности лидара при движении робота приводится способ устранения эффекта Доплера (дисторсии) для исходного облака точек. Проведенный сравнительный анализ разработанного метода по отношению к способу комплексирования данных от колесной одометрии, блока инерциальной и спутниковой навигации, использующий расширенный фильтр Калмана (Extended Kalman Filter), показывает применимость метода для оценки положения и ориентации робота в условиях его движения по слабоструктурированной местности.

To ensure unmanned autonomous movement of ground robotic means, it is required to accurately determine the position and orientation of the robot. The present study is related to the estimation of coordinates by comparing the scans of a laser scanning rangefinder in conditions of semi-structed infrastructure and the absence of a global satellite communications signal. The existing methods of comparing scans have significant drawbacks in the conditions of movement over a semi-structured terrain, associated both with the processing time of data from the laser scanning rangefinder, and with the quality of the results obtained. The scan is preliminarily placed in a map consisting of cells. Each cell of around point scan is described by forces represented by the laws of physics or probability theory. In the cells of the map, we take into account the mutual influence of all forces from each point of the scan and thus we obtain the resulting artificial potential field of the scan. The position of the robot is estimated by the change in the number of acting forces of one scan per points of the next scan taking into account their direction. We estimate the orientation of the robot based on the sum of the vector products of the forces and distances to the given forces acting on the points of the next scan. This method allows you to calculate the displacement of the robot between scans regardless of road conditions and terrain. This article presents the results of an experimental verification of the method on a mock-up of a mobile robot equipped with a Velodyne HDL-32 LIDAR. We indicate the operating conditions of the method for a given LIDAR, as well as the time spent on calculating the bias estimate. Given the peculiarities of the LIDAR, we present a method for eliminating the Doppler Effect (distortion) for the original point cloud. A comparative analysis of the developed method for integrating wheel odometry data, inertial and satellite navigation using the Extended Kalman Filter shows the applicability of this method to assess the position and orientation of the robot in conditions of its movement over rough terrain.

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