Date of birth:
24/08/1990

Place of birth:
Donetsk

Schools:
1997–2003 School №115;
2003–2005 School №31;
2005–2007 Lyceum "Naukova zirka Donbasu".

Universities:
2007–2011 Donetsk State University of Management;
2012–2013 Donetsk National Technical University.

Average score:
3.8

Languages:
Russian language – fluent;
Ukrainian language – high;
English – intermediate.

Personal Achievements:
3rd place (rookie) on Capoeira – First Ukrainian championship, Kramatorsk, 15–16 September 2007.

Hobbies and Interests:
Games – mostly strategy, different genres bestsellers; books – scientific, technical; music – mostly electronic, combining electronics with some classic tools; design and development of various digital and digital-to-analog devices; party roller sports.

Personal Qualities:
Kindness, creativity, focus on results.

Professional and computer skills:
• Operating systems: Windows 98, XP, 7, 8; Android 2.2 and above;
• Programming Languages: Assembler, C;
• Development Environment: CodeVisionAVR, AVR Studio;
• Simulation: Labview, Multisim, Proteus;
• Graphic programs: Adobe (Photoshop, Audition, After Effects), 3D Studio Max;
• Other programs: MS Office.

Additional courses, internships, grants:
None.

Plans for the future:
Self-study and improvement of knowledge in the field of digital and digital-to-analog electronics.

Contact information:
E-mail: cooold@meta.ua
Skype: C0oo1D

Summary on the theme of master's work

Introduction

At the moment, there are many different tools for physical movement of an object. If you take a person as an object, then the list starts with bicycles, rollers, motorcycles, cars, and ends with airplanes, helicopters, manned space vehicles. If you take as an object, such as a photo or video camera, any other small goods – the list is reasonable to start with a radio-controlled land and air models. But, as a rule, these models are not provided with the autopilot systems, and autopilot, in fact, not dynamic.

Autopilot – a device or software and hardware that lead vehicle at a certain given trajectory [1]. This definition provides a static trajectory. It can still be used at high altitudes, but what about low or ground movements? Here static path will not help, because the situation is constantly changing. Today was a plain – tomorrow metropolis, today was not here post – tomorrow he is. Everything is changing, and technology of autopilot somewhat outdated.

In this case, cannot do without a system that would detect obstacles in its path and changed the trajectory to ask only the final coordinates, and the whole moving process was dynamic and rational. To this end, anyway, will be required array of various sensors, as obstacles come in various types, and not all of the sensors will be able to fix them.

There are several basic methods for the detection of obstacles:

• LED;
• Laser;
• Ultrasonic;
• Radio-wave;
• Vision Systems.

All methods except the last act on the basis of location (fig. 1), they have a different source and the receiver.

Figure 1 – Principle of locator action

LED and laser ranging techniques differ in that the laser diode has a higher accuracy than the LED, but is effective at long range because beam width is extremely small. The LED on the contrary, is effective at close range, and due to the fact that the beam is much wider – the accuracy is not great. The similarity of the methods is that the operating principle is the same. The transmitter emits a stream of light particles, some of them are randomly scattered by the medium, but the best part is, if it reaches an opaque body within range – back to the receiver. Next, measure response time – the time at which the signal path from the transmitter overcomes the receiver in the presence of an opaque body within range of the rangefinder. LED and laser diode can operate in one of three ranges of electromagnetic radiation – the infrared, visible and ultraviolet.

Ultrasonic and radio-wave methods differ from each other more than LED and laser, if radio-wave is a subspecies of electromagnetic radiation, ultrasonic uses sound vibration to determine the physical location of the object. In aviation radio-wave method is used, and some living organisms use an ultrasonic method.

Technical sight differs from all the above methods. Its implementation requires a video camera and a software or hardware image processing unit. It simulates human vision that is behind them their advantages and disadvantages.

Use of the system is the high speed, the possibility of a 24-hour operation and accuracy of the repeated measurements. It is also an advantage to the human vision is the lack of fatigue, illness or inattention. However, people have subtle perception within a short period, and greater flexibility in the classification and adaptation to search for other problems [2].

The use of computer vision in the obstacle detection is very difficult, because group objects as obstacles on someone principle is almost impossible, though it depends on the situation. The most commonly used example of a vision recognition system constraints, a method of binarization. This method is to convert the image to grayscale in binary (black and white pixels) with further processing. But this is only one possible method of mapping the obstacles, also must be applied the segmentation method (used to search for and/or parts counting), the method of measurement (measurement of the size of objects in inches or millimeters), and the method of edge detection.

To study and implementation examples of different recognition systems, there are various competitions, such as RoboCup, Egghead-Bot, Robofest, VEX Robotics and others [3].

At this point, the issues of recognition of obstacles in the context of the autopilot are paying too little attention, although the direction is very promising for automated movement of air and ground objects of various sizes and purposes.

At the time of writing this essay master's work is not complete. Final completion is scheduled for December 2013. Full text of the work and materials on the topic can be obtained from the author or his manager after that date.

Sources

1. Alexandrov V.G. Reference to Aircraft Equipment (Avionics). – М., 1978,-398p.
2. Davies E. R. Machine Vision: Theory, Algorithms, Practicalities. – M., 2004,-934p.
3. Portal devoted to robots and robotics [electronic resource]. – Access mode: http://myrobot.ru/