In this paper, it is shown that based on an analysis of the implemented functions of existing robot manipulators the task of automation of the safe capture of objects by a robot during the assembly process is poorly developed. In the process of analysis,there were discovered technological solutions to three main tasksfor the development of a subsystem for capturing objects by a robotic manipulator: determination of the dimensions and shape of the capturing object; determination of the distance from the robot manipulator to all the points of the capturing object, determination of the capture point of the object and clarification of the distance to the robot manipulator. It is shown that all of the above tasks are not sufficiently solved. Therefore, it was proposed to develop a methodology for creating an intelligent software and hardware subsystem for capturing an object by robot manipulator. The developed methodology consists ofsix steps: obtaininga stereo image and buildingan in-depth map; determination of the distance from the robot manipulator to all the points of the object; determination of the contour of the object; determination of the capture point of the objectand clarification of the distance to the robot manipulator; determination of the degree of capturing the object; determination of the movement of the manipulator to capture an object at the desired point. To find the capture point, it is proposed to use the contour search method on the object’s depth map, and to search for the finest part on the contour, limit it to a segment and find its middle point. To implement the algorithm for determination of the distance to the object, the degree of its capture and movement to the desired point, the dependencies of the calculations on the depth map and the physical characteristics of the manipulator are formalized. The capabilities of the StereoPi microprocessor are analyzed and its use for the hardware solution of the capture function by the robotic arm is proposed. The simulation of the intelligentsoftware and hardware subsystem for capturing an object of complex shape has been performed. Conclusions are drawn about the independence of the developed subsystem from the type of object and its viewing angle by a robot manipulator. In addition, an increase in the accuracy of capturing the object by a robot manipulator equipped with an intelligent subsystem is shown in comparison with its existing analog. Potential problems inthe implementation of the proposed methodology are highlighted.

No abstract

Разработана энергоэффективная система ультразвукового обнаружения препятствий для слепых. Показана возможность повышения эффективности системы-расширения угла обзора, снижения энергопотребления, повышения времени автономной работы от элемента питания без подзарядки, за счет использования современной элементной базы, выбора оптимальной тактовой частоты и алгоритма работы микроконтроллера. Приведены результаты разработки программной модели и кода программы работы микроконтроллера. На основе данных исследований был собран и испытан макет устройства. Наличие трех ультразвуковых датчиков позволяет расширить угол обзора и определять наличие препятствий прямо перед человеком, а также слева и справа от него. Ключевые слова: ультразвуковой датчик; микроконтроллер; звуковой излучатель; программные коды; энергопотребление.

The paper considers the possibility of solving the problem of improving the quality of technical vision using the contour method, which is used to position objects in mobile computer vision systems. The hardware part of the object positioning system includes two video cameras, a Raspberry Pi 3 microcomputer, a depth contour map screen, and a motor control unit. The codes of programs based on the OpenCV library, the algorithm of the system and examples of the implementation of the contour method are given. The algorithm of the developed positioning technique includes the selection of the contours of objects on the frames of a stereopair, removal of all open contours, calculation of the moment (center of mass) of each closed contour, determination of the displacement along the x-axis of the moments of the corresponding contours, filling each closed contour with points with a brightness inversely proportional to the displacement of the moments. The presence of two video cameras, a Raspberry Pi 3 microcomputer, a contour depth map screen provides stereoscopic and panoramic "vision", that is, the ability to determine the presence of objects and their distance, as well as to get an overall picture in the "field of view" of the system. The engine control unit allows mobile devices to avoid obstacles. Based on the analysis of the research results, it was found that the proposed system provides an increase in the quality of positioning of objects and a decrease in the required computing resource, which gives a significant decrease in power consumption and ensures the autonomy of the system.