title: Ð£Ð¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ðµ ÑÐ¾Ð±Ð¾ÑÐ¾Ð¼ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð·ÑÐµÐ½Ð¸Ñ Ð² Ð¿ÑÐ¾Ð¼ÑÑÐ»ÐµÐ½Ð½Ð¾ÑÑÐ¸
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Robot guidance using machine vision techniques in industry
Creators: name: Ð¡Ð°Ð»Ð°Ð¼, ÐÑÑÐ°Ð¼Ð¼Ð°Ð´
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: 2020
Subjects: ÐÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
ÐÐ¸Ð½ÐµÐ¼Ð°ÑÐ¸ÐºÐ°
Ð Ð¾Ð±Ð¾ÑÑ
ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ðµ Ð²Ð¸Ð´ÐµÐ½Ð¸Ðµ
ÐºÐ°Ð½Ð°Ð»
Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
computer vision
channel
training

description: Ð ÑÑÐ¾Ð¹ Ð´Ð¸ÑÑÐµÑÑÐ°ÑÐ¸Ð¸ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½Ñ ÑÐ¸ÑÑÐµÐ¼Ñ Ð´Ð»Ñ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¾ÑÐ¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ Ð²Ð¾ÑÐ¿ÑÐ¸ÑÑÐ¸Ñ-Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð´Ð»Ñ Ð¿ÑÐ¾Ð¼ÑÑÐ»ÐµÐ½Ð½ÑÑ ÑÐ¾Ð±Ð¾ÑÐ¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÑ ÑÐ¸ÑÑÐµÐ¼ Ñ Ð²Ð¸Ð·ÑÐ°Ð»ÑÐ½ÑÐ¼ Ð²Ð²Ð¾Ð´Ð¾Ð¼. ÐÐ±ÑÑÐ¶Ð´Ð°ÐµÑÑÑ ÑÑÐ´ Ð²Ð¾Ð¿ÑÐ¾ÑÐ¾Ð², ÑÐ°ÐºÐ¸Ñ ÐºÐ°Ðº Ð°Ð²ÑÐ¾Ð½Ð¾Ð¼Ð½Ð¾Ðµ Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ðµ ÑÐ¾ Ð·ÑÐµÐ½Ð¸ÐµÐ¼, Ð¾Ð±ÑÐ°ÑÐ½Ð°Ñ ÐºÐ¸Ð½ÐµÐ¼Ð°ÑÐ¸ÐºÐ° Ð¼Ð°Ð½Ð¸Ð¿ÑÐ»ÑÑÐ¾ÑÐ° Ð¸ Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¾Ðµ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ðµ ÑÐ¸ÑÑÐµÐ¼Ð¾Ð¹. ÐÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½Ñ Ð¾Ð¿ÐµÑÐ°ÑÐ¸Ð¾Ð½Ð½ÑÐµ ÑÐ¸ÑÑÐµÐ¼Ñ, Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÑÑÑÐ¸Ðµ ÑÐµÑÐµÐ½Ð¸Ñ ÑÑÐ¸Ñ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼. ÐÐ·ÑÑÐ°ÑÑÑÑ Ð´Ð²Ð° ÑÐ°Ð·Ð½ÑÑ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð° Ðº Ð¿ÑÐµÐ´Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð¾Ð±ÑÑÐ°ÑÑÐ¸Ñ Ð´Ð°Ð½Ð½ÑÑ. ÐÐµÐ¼Ð¾Ð½ÑÑÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ (Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ñ ÑÑÐ¸ÑÐµÐ»ÐµÐ¼) Ð¸ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÑÐºÐ¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ (ÑÐ°Ð¼Ð¾ÑÑÐ¾ÑÑÐµÐ»ÑÐ½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ). ÐÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½ Ð½Ð¾Ð²ÑÐ¹ Ð¼ÐµÑÐ¾Ð´ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð¾ÑÐ²ÐµÑÐ°ÑÑÐ¸Ð¹ Ð·Ð°ÑÐ²Ð»ÐµÐ½Ð½ÑÐ¼ ÑÑÐµÐ±Ð¾Ð²Ð°Ð½Ð¸ÑÐ¼. ÐÐµÑÐ¾Ð´ qHebb Ð¾ÑÐ½Ð¾Ð²Ð°Ð½ Ð½Ð° Ð°ÑÑÐ¾ÑÐ¸Ð°ÑÐ¸Ð²Ð½Ð¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ð¸ Ð¥ÐµÐ±Ð±Ð° Ð´Ð°Ð½Ð½ÑÑ Ð² Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ð¸ ÐºÐ°Ð½Ð°Ð»Ð°. Ð¡Ð²Ð¾Ð¹ÑÑÐ²Ð° Ð¼ÐµÑÐ¾Ð´Ð° Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÑÑÑÑÑ Ð½Ð° Ð°Ð²ÑÐ¾Ð½Ð¾Ð¼Ð½Ð¾Ð¼ ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ½Ð¾Ð¼ ÑÑÐµÐ´ÑÑÐ²Ðµ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð·ÑÐµÐ½Ð¸Ñ, Ð³Ð´Ðµ ÑÐ¸ÑÑÐµÐ¼Ð° ÑÑÐ¸ÑÑÑ Ð½Ð°Ð¿ÑÑÐ¼ÑÑ ÑÐ¾Ð¾ÑÐ½Ð¾ÑÐ¸ÑÑ ÑÐ°ÑÐ°ÐºÑÐµÑÐ¸ÑÑÐ¸ÐºÐ¸ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ Ð½Ð¸Ð·ÐºÐ¾Ð³Ð¾ ÑÑÐ¾Ð²Ð½Ñ Ñ ÑÐ¿ÑÐ°Ð²Ð»ÑÑÑÐ¸Ð¼Ð¸ ÑÐ¸Ð³Ð½Ð°Ð»Ð°Ð¼Ð¸. ÐÐ¾ÑÐ»Ðµ Ð½Ð°ÑÐ°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð¿ÐµÑÐ¸Ð¾Ð´Ð° Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ ÑÐ¸ÑÑÐµÐ¼Ð° Ð¿Ð¾ÑÑÐ¾ÑÐ½Ð½Ð¾ ÑÐ°Ð±Ð¾ÑÐ°ÐµÑ Ð°Ð²ÑÐ¾Ð½Ð¾Ð¼Ð½Ð¾. ÐÑÐ¸ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð¾ÑÐµÐ½ÐºÐµ Ð¿ÑÐµÐ´Ð»Ð°Ð³Ð°ÐµÐ¼ÑÐ¹ Ð¼ÐµÑÐ¾Ð´ Ð¾Ð½Ð»Ð°Ð¹Ð½-Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ ÑÐ¾Ð¿Ð¾ÑÑÐ°Ð²Ð¸Ð¼ Ñ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐ¼Ð¸ Ð¿Ð°ÐºÐµÑÐ½ÑÐ¼Ð¸ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ.
description: This thes is presents systems for teaching perception-action mapping for Industrial robotic systems with visual input. A number of issues are discussed, such as vision autonomous driving, inverse kinematics of a robotic arm, and dynamic system control. Operating systems demonstrating solutions to these problems are presented. Two different approaches to providing training data are being explored. Demonstration training (supervised learning) and exploratory learning (self-directed learning). A new teaching method that meets the stated requirements presented. The qHebb method is based on Hebb's associative study of data in a channel view. The properties of the method are demonstrated in a vision-based autonomous vehicle, where the system learns directly to correlate low-level image characteristics with control signals. After the initial training period, the system continuously operates autonomously. When quantified, the proposed online learning method is comparable to a modern package teaching methods.