Navigation cartographic methods development for monitoring robotic complexes positioning in surrounding space

Machine-building Engineering and Machine Science

Robots, mechatronics and robotic systems


Аuthors

Lupanchuk V. Y.

Ministry of Defense of the Russian Federation, Moscow, Russia

e-mail: raketofflu@mail.ru

Abstract

The purpose of the study of this scientific article is accuracy improving of monitoring robotic complexes positioning in surrounding space while performing various types of motion.

The subject of the study are methods for joint navigational information processing obtained by on cartographic and instrumental data.

The article analyzes the approach and problems of high-precision positioning of unmanned aerial vehicles and ground-based robotic complexes in the surrounding space.

The initial data of the study are based on formation of local areas of the Earth surface employing cartographic data and instrumental measurements. The article presents the main stages of the methodology for the map high-precision local areas formation by mathematical processing of redundant navigation parameters at the base points.

The methodological approach differs from the known ones by the presence of correlations between the map errors and allows the accuracy increase of navigation parameters determination over the entire area of the local section by 1 m, and by 3 to 5 m at base points.

The studies can find application in various fields:

— when solving problems of high-precision positioning of air and ground robotic complexes in the surrounding space;

— when solving the problems of ensuring and developing the Earth Deformation Control Service within the framework of the Federal System of Seismological Observations, particularly in the highlands of the country;

— rapid creation of a multi-information cartographic basis of various scales with account for correlation dependence of navigation and geophysical information.

Keywords:

unmanned aerial vehicle, ground robotic complex, local area of the Earth surface, cartographic data, instrumental data, error map information correlation, reference marker area

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