title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° ÑÐ¸ÑÑÐµÐ¼Ñ ÑÑÐµÑÐµÐ¾Ð·ÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐ¾Ð±Ð¾ÑÐ°-Ð¼Ð°Ð½Ð¸Ð¿ÑÐ»ÑÑÐ¾ÑÐ°
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: The development of a stereo vision system for the robotic arm
Creators: name: ÐÑÑÐ°ÐµÐ²Ð°, ÐÐ½ÐµÐ»Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð·ÑÐµÐ½Ð¸Ðµ
ÑÑÐµÑÐµÐ¾Ð·ÑÐµÐ½Ð¸Ðµ
ÑÐ²ÐµÑÑÐ¾ÑÐ½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
computer vision
stereovision
convolutional neural network

description: ÐÐ°ÐºÐ°Ð»Ð°Ð²ÑÑÐºÐ°Ñ Ð´Ð¸Ð¿Ð»Ð¾Ð¼Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ñ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð½Ð° Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¸. ÐÑÐ¸Ð²ÐµÐ´ÐµÐ½ Ð¾Ð±Ð·Ð¾Ñ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ñ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð½Ð° Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¸, Ð² ÑÐ°ÑÑÐ½Ð¾ÑÑÐ¸ ÐºÐ°ÑÑ Ð³Ð»ÑÐ±Ð¸Ð½, Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÐºÐ¾ÑÐ¾ÑÐ¾Ð³Ð¾ Ð´Ð°Ð½Ð¾ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ð½ÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð². Ð Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ñ Ð¼ÐµÑÐ¾Ð´Ñ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ ÐºÐ°ÑÑ Ð³Ð»ÑÐ±Ð¸Ð½ Ð¸ Ð¸Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð´Ð»Ñ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ ÑÐ¾Ð±Ð¾ÑÐ¾Ð¼-Ð¼Ð°Ð½Ð¸Ð¿ÑÐ»ÑÑÐ¾ÑÐ¾Ð¼ Ñ Ð¾Ð³ÑÐ°Ð½Ð¸ÑÐµÐ½Ð¸ÐµÐ¼ Ð½Ð° Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ðµ ÑÐ¾Ð»ÑÐºÐ¾ Ð¾Ð´Ð½Ð¾Ð¹ ÐºÐ°Ð¼ÐµÑÑ. ÐÑÐ»Ð¸ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ñ ÑÐµÐ¾ÑÐµÑÐ¸ÑÐµÑÐºÐ¸Ðµ Ð¾ÑÐ½Ð¾Ð²Ñ Ð¸ Ð°ÑÐ¿ÐµÐºÑÑ, Ð½ÐµÐ¾Ð±ÑÐ¾Ð´Ð¸Ð¼ÑÐµ Ð´Ð»Ñ Ð¸Ñ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ. ÐÑÐ»Ð¾ Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð¾ 2 Ð¼ÐµÑÐ¾Ð´Ð° Ð´Ð»Ñ ÐºÐ¾Ð½ÑÑÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÐºÐ°ÑÑ Ð³Ð»ÑÐ±Ð¸Ð½. ÐÐµÑÐ²ÑÐ¹ Ð¾ÑÐ½Ð¾Ð²ÑÐ²Ð°ÐµÑÑÑ Ð½Ð° Ð¼ÐµÑÐ¾Ð´Ð°Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ: Ð±ÑÐ»Ð° ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð° Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð°Ñ ÑÐµÑÑ Ð´Ð»Ñ Ð¾ÑÐµÐ½ÐºÐ¸ Ð³Ð»ÑÐ±Ð¸Ð½Ñ Ð¿Ð¾ Ð¾Ð´Ð½Ð¾Ð¼Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ. ÐÑÐ¾ÑÐ¾Ð¹ Ð¼ÐµÑÐ¾Ð´ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÐµÑ ÑÑÑÐ¾Ð¸ÑÑ ÐºÐ°ÑÑÑ Ð³Ð»ÑÐ±Ð¸Ð½Ñ Ð¸Ð· ÑÑÐµÑÐµÐ¾Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ, Ð¿Ð¾ÑÐ»ÐµÐ´Ð½ÐµÐµ Ð¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÐµÐ»Ñ Ð¿Ð¾Ð»ÑÑÐ°ÐµÑ Ð¿ÑÐ¸ Ð¿Ð¾Ð¼Ð¾ÑÐ¸ ÑÑÐµÑÐµÐ¾ÑÑÑÐ°Ð½Ð¾Ð²ÐºÐ¸. ÐÐ°Ð½Ð½ÑÐ¹ Ð¼ÐµÑÐ¾Ð´ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÐµÑ ÑÐ°ÐºÐ¶Ðµ ÑÑÑÐ¾Ð¸ÑÑ ÐºÐ°ÑÑÑ Ð³Ð»ÑÐ±Ð¸Ð½Ñ Ð¿Ð¾ Ð¾Ð´Ð½Ð¾Ð¹ ÐºÐ°Ð¼ÐµÑÐµ. Ð ÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð½Ð¾Ðµ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ðµ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ðµ Ð±ÑÐ»Ð¾ Ð¿ÑÐ¾ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¾ Ð¸ Ð¸Ð½ÑÐµÐ³ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¾ Ð² Ð¼Ð¾Ð´ÐµÐ»Ñ ÑÐ¾Ð±Ð¾ÑÐ°-Ð¼Ð°Ð½Ð¸Ð¿ÑÐ»ÑÑÐ¾ÑÐ° Ð¸ Ð±ÑÐ» Ð²ÑÐ±ÑÐ°Ð½ Ð½Ð°Ð¸Ð±Ð¾Ð»ÐµÐµ Ð¾Ð¿ÑÐ¸Ð¼Ð°Ð»ÑÐ½ÑÐ¹ Ð¼ÐµÑÐ¾Ð´.
description: Bachelor's thesis is devoted to the study of methods for determining objects in the image. A review of existing methods for determining objects in an image, in particular, depth maps, is given, on the basis of which the comparison of the considered methods is given. In this paper, methods for constructing depth maps and their use for controlling a robotic arm with a restriction on the use of only one camera are considered. The theoretical foundations and aspects necessary for their construction were also considered. Two methods have been proposed for constructing depth maps. The first one is based on machine learning methods: the neural network was implemented to estimate depth from a single image. The second method allows you to build depth maps from a stereo image, the latter is obtained by the user using a stereo setup. This method also allows to build depth maps for one camera. The implemented software was tested and integrated into the model of the robotic arm and the most optimal method was chosen.