Atanas Dimitrov

Computer system for navigating a mobile robot

In this paper a fuzzy and communication system for managing and controlling the basic movements of a mobile robot is proposed. Several ultrasound and infrared sensors are installed on the robot and the collected data is operated with the means of fuzzy logic and thus decisions for the robot route are made. This intelligent system is created to navigate the mobile robot indoors in an unknown environment. The application areas of the robot are for embedded and mobile device, guiding of visual impaired people, mobile vehicle in technological lines, etc.∗

Complex SAR signal modeling and image reconstruction

The work addresses the Synthetic Aperture Radar (SAR) geometry, signal model and imaging process. Mathematical description of the observed surface is presented. A waveform with linear frequency modulation (LFM) reflected by the surface is used to produce a two-dimensional (2-D) SAR signal model presented as a sum of Hadamard products of two-and four-dimensional matrices (arrays) with a specially defined rectangular function. It is proven that the SAR signal formation and image reconstruction can be interpreted as direct and inverse projection operations. Based on linearization of the inverse projection, two-dimensional inverse Fourier transform is applied to obtain a complex image known as a Single Look Complex (SLC) image, which can be used for interferogram generation. To verify the proposed SAR kinematics and geometry, surface geometry, signal models and image reconstruction algorithms a numerical experiment is carried out.

Kalman tracking filter in 3-D space

In this work a Kalman filter for tracking Unmanned Aerial Vehicle (UAV) moving near the base lane of a bistatic radar system and illuminated by GPS signals in three-dimensional (3-D) space is suggested. Continuous-time and discrete-time state equations are derived to define a linear time-invariant model. Model matrices describing the behavior of the object, state vectors, measurement vectors and vector noise process with its statistical characteristic are defined. Structures of the discrete state transition matrix of the dynamic model and covariance noise matrix are given. Linear time-invariant model matrices are derived. State model matrices with constant entries, measurement model matrix, state transition matrix of the dynamic model, covariance noise state matrix and covariance matrix of the measurements, are defined. Recurrent Kalman equations are described. To verify a 3-D Kalman tracking a numerical experiment is performed.

Ultrasonic Positioning System Implementation and Dynamic 3D Visualization

Abstract The paper contributes to the design and implementation of the ultrasonic positioning system based on new multifunctional hardware components, newly released. A moving object coordinates’ determination is described analytically and a matrix equation in respect to unknown coordinates with coefficients, measurement distances, is derived. Stages of data packet processing are formulated, and a pseudo pyramid of measurement distances is built. HX7TR multifunctional ultrasonic devises, transceivers, are used to implement the positioning system. A C# program source code for coordinate determination and 3D visualization is created. The algorithm for moving object coordinate computation, and its program realization as well as HX7TR ultrasonic devises can be used in development of indoor ultrasonic positioning systems embedded in IoT and robotics applications.

Ultrasonic sensor explorer

Ultrasonic Sensor Explorer (USE) is a cheap mobile robot for mapping. Instead of expensive laser sensor, it uses cheap ultrasonic sensor HC-SR04 with range up to 4 meters. The chassis of the robot is made of ABS plastic material and it is 3D printed from a model called Mini-Me on RepRap Prusa Iteration 3 3D printer. The hardware is based on ROMEO BLE mainboard. The Software consists of two parts: firmware and application. The firmware part is an Arduino source code project, written in C++ programming language, which is deployed on the robot. The application part is Windows IoT source code, written in C# programming language, which can be run on PC, tablet, phone or ARM device. The suggested robot has been tested in the university lab environment. The presented concept proves it has a potential for SLAM.