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14widely used in almost all branches of robotics. The operation of the ultrasonic sensor is based on the principle of echolocation. Here's how it works: Ultrasonic Sensors generate an ultrasonic wave by means of a piezo element in the front part of the housing. The wave spreads in the atmosphere in accordance with the laws of physics. The same piezo element can detect and measure the sound reflected by an object. Therefore, it functions alternately as sender and receiver (transceiver). Microphones are known to be useful for detecting surface noise that occurs at the onset of motion and during slip. The sensor is reported to be very effective in detecting slip and surface roughness during movement. Tactile sensors based on ultrasonic approach have fast dynamic response and good force resolution [4].
Since the main trend in the development of tactile sensors is the reproduction of the tactile properties of human skin. This tendency is most satisfied by tactile devices of matrix type, since each cell of the matrix, which is a microelectronic force (or strain) sensor, provides specific information, and all together allow one to form a holistic view of the form of the object. The design and technological development of tactile sensors are developing quite actively. Robots increasingly have to interact with objects, the capture of which must mimic the human.
To date, robots can very well identify similar textures, it is not yet able to find out what a person needs. Scientists say that the technology of the touch robot can be used in prostheses or to assist companies where specialists are needed to evaluate consumer goods or even human skin.
References
1. Gritsay I., Yakubov В. Holistic design optimization in mechatronics // Технологии XXI века: проблемы и перспективы развития: сборник статей Международной научно-практической конференции. Июнь, 2017.
2. Ravinder S. Dahiya, Maurizio Valle, Giorgio Metta Tactile Sensing Arrays for Humanoid Robots // Research in Microelectronics and Electronics Conference, 2007. PRIME 2007. Ph.D.
3. Frank L. Lewis, Darren M. Dawson, Chaouki T. Abdallah Robot Manipulator Control Theory and Practice Second Edition // Resised and Expanded, 2004.
4. Gritsay I., Krasilo М. Vision of Robots: Ultrasonic Sensors // Научные исследования в области технических и технологических систем: сборник статей Международной научно-практической конференции, 2018.
CAMERAS IN ROBOTICS Gritsay I.P.1, Gurin I.V.2
'Gritsay Irina Petrovna — Senior Lecturer, SCIENTIFIC TECHNICAL TRANSLATION DEPARTMENT;
2Gurin Ilya Vasilyevich — Student, FACULTY AUTOMATION, MECHATRONICS AND ROBOTICS, DON STATE TECHNICAL UNIVERSITY, ROSTOV-ON-DON
Abstract: this article describes the device of analogue cameras and the process of image visualization. This paper describes the principles of analogue cameras and image visualization. The authors of the article consider various kinds of getting information. The special attention is given to such a visual sensor as an analogue camera. The principles of different cameras operation were described. Matrix CCD and CMOS were studied.
Keywords: analogue camera, robotics, image acquisition, image processing, CCD, CMOS, machine vision.
Every day more and more modern advanced robots are invented, «but engineers have not come to a consensus on what the vision of robots should be» [1]. In this article we discussed vision of robots and cameras. To provide robots with good interaction with the environment, new, more advanced cameras are being developed which can almost instantly read the image and transfer it to robot's processor. Cameras have been used in robotics for a long time. The earliest analogue cameras were on magnetic tape, recording analog signals on cassettes for video tapes. In 2006, digital recording became common: the tape was replaced with storage media, such as mini-HD, micro-DVD, internal flash memory and SD cards. Analogue cameras have some advantages over other sensors, they can broadcast a video signal at a great distance, easy to install on a robot, reliable, the quality of shooting does not depend on the failures in the robot processor. For example, the Mars rover Curiosity «uses three cameras: MARDI, MAHLI and MastCam» [2]. Analogue cameras also have
drawbacks, for example, they can't work in places without light or in places with low visibility, and a significant disadvantage is that for receiving a video signal that costs more than the camera itself.
The camera works with visible light or with other parts of the electromagnetic spectrum. A camera is an optical device that creates one image of an object or scene and writes it to an electronic sensor or film. The human eye works by a similar principle.
In robotics, analogue cameras are mainly used, the principle of their work is that the light flux captured by the camera lens falls on the CCD and is converted into an electrical signal transmitted through the cable to the receiving device. Unlike digital technology, the «electrical signal is not converted to a binary code»[3], but falls on the recording device in an unchanged form. This simplifies the monitoring process and eliminates the need for computer processing. It is possible to connect an analogue camera to a digital converter, which allows you to receive video from multiple cameras.
1. Image acquisition in robotics
Image acquisition is the most important part in a machine vision system. It involves capturing an image of the object to be analyzed with the help of camera. Different types of cameras can be used for image acquisition; they can include an ordinary mobile camera, a typical digital camera, or even a webcam. But cameras that are tailored specially for industrial use are also available. Depending on the sensor technology used, different cameras can be classified into two categories as follows:
• «CCD refers to a semiconductor architecture in which charge is transferred through storage areas. The CCD architecture has three basic functions: charge collection, charge transfer, and the conversion of charge into a measurable voltage. A CCD can be attached to a variety of detectors. The basic building block of the CCD is the metal-insulator-semiconductor (MIS) capacitor» [4].
• «CMOS image sensors, of which today most can be referred to as CMOS Active Pixel Sensors (APS), exploit the same silicon chip technology used in microprocessor systems. The attraction is mostly due to the nature of CMOS technology in that many millions of transistors can be integrated on a single silicon circuit» [5].
2. Image processing
The acquired image needs to be further processed by using image processing tools such that the information lost during acquisition could be regained. Some of the generally used image-processing tools for machine vision applications are as follows:
• Pixel counting: Pixel counting is one of the most common image processing methods. It involves counting of the light or dark pixels that an image is formed of. It can be analyzed by histogram that shows the grayscale distribution in an image.
• Thresholding: It is the simplest process of dividing the image into segments. It is used for creating a binary image from a grayscale image so that the region of interest is separated from the background. It requires that the region of interest and the background have enough contrast.
• Image filtering: Different image filters can be applied for the image processing. Ready-made filters are available and also user-customized filters can be created. Linear filters, spatial filters, FFT are some of the filters used in image processing. The algorithms of the image processing filters are not included in this thesis. But, usually the software that is being used for machine vision has most of the common filters inbuilt.
3. Output
«Output is of immense importance in any process. Something is done to get something in return. Machine vision applications also have a final output. Generally the outputs of machine vision applications are categorized as Pass/Fail. But additional attributes for Pass/Fail outputs can also be defined, for instance number of passed/failed items, setting an alarm if the items are failed, and so on. It depends on the objective of the application. But it is always significant to define the attributes for further R&D tasks» [6].
References
1 Gritsay I., Krasilo M. Vision Of Robots: Ultrasonic Sensors // В сборнике: «Научные исследования в области технических и технологических систем». Сборник статей международной научно-практической конференции, 2018, С. 144-147.
2 Gritsay I., Degtyarev N. Space Robotics // В сборнике: Технологии XXI века: «Проблемы и перспективы развития». Сборник статей международной научно-практической конференции: в 2 ч., 2017. С. 76-79.
3 Gurin E. Bronzova Z. Increase of the computer performance by parallelization // В журнале: «Академическая публицистика», 2018. С. 6-12.
4 Holst Gerald. «CCD arrays cameras and displays. Chapter I. Introduction. Solid state detectors» // [Электронный ресурс]. Режим доступа: http://citeseerx.ist.psu.edu/ (дата обращения: 02.05.2018).
5 Waltham Nick. «CCD And CMOS Sensors. CMOS» // [Электронный ресурс]. Режим доступа: http://ankaa.unibe.ch/ (дата обращения: 07.05.2018).
6 Bikarna Pokhael. « Machine vision and object sorting. Chapter III. Machine vision process. Output» // [Электронный ресурс]. Режим доступа: https://www.theseus.fi/ (дата обращения: 07.05.2018).
WALKING ROBOTS. ZMP TECHNOLOGY Gritsay I.P.1, Krasilo M.S.2
'Gritsay Irina Petrovna — Senior Lecturer, SCIENTIFIC TECHNICAL TRANSLATION DEPARTMENT; 2Krasilo Mikhail Sergeevich — Student, FACULTY AUTOMATION, MECHATRONICS AND ROBOTICS, DON STATE TECHNICAL UNIVERSITY, ROSTOV-ON-DON
Abstract: the ability to move robots in hard and difficult conditions is a priority for many industries where robotic mechanisms are used. For example, rescuers, geologists and the military require robots that can overcome such obstacles that can't be overcome by wheeled or caterpillar vehicles. That is why scientists in many countries are developing walking, on two or more limbs, robots.
Keywords: ZMP-technology, walking robots, the projection the center of gravity, humanoid robots, difficult to pass terrain.
Many people have seen of humanoid robots, which have two arms, two legs and one head in movies and the pictures. In films, these robots move faster and more accurately than humans, but few of the audience thought that moving the robot on two "legs" is one of the most difficult tasks of robotics. But if this is such a difficult task, then why create walking robots if there are wheels and caterpillars? And the answer is simple, wheeled and caterpillar robots can't travel everywhere, for example, in mountains, in buildings, and walking robots can be useful in the analysis of blockages. Therefore, scientists began to develop walking robots. The first publications devoted to the theoretical and practical issues of creating walking robots belong to the 70s-80s of the 20th century. Moving the robot using the "legs", as already mentioned, is a difficult task of dynamics. Now in many countries there is a development of robots moving on two extremities, but these robots can't yet achieve such a stable movement, as in humans.
Also, many mechanisms are created, moving on three, four, and so forth limbs. To begin with, we list the main technological solutions for this topic that are currently in use.
1. Servo-drive + hydro mechanical drive: early technology for the construction of walking robots, implemented in a number of models of experimental robots manufactured by General Electric in the 1960 s.
2. ZMP technology: ZMP (Zero Moment Point, "zero point") is an algorithm used in robots similar to ASIMO by Honda. The on-board computer controls the robot in such a way that the sum of all external forces acting on the robot is directed toward the surface along which the robot moves.
3. Leaping robots: in the 1980s, Professor Marc Raibert of the English Leg Laboratory of the Massachusetts Institute of Technology developed a robot capable of maintaining balance by jumping using only one leg.
The movement of the robot resembles the movements of a person on the simulator pogo-stick. And now authors of the paper pay attention to ZMP-technology.
Fig. 1. Stable position of chair Fig. 2. Unstable position of chair 26
