Identification of characteristic points of the radar image on the basis of "contour" invariants comparison

The article presents the one element of the autonomous maritime positioning system which task is the identification of characteristic points generated from the radar image. The system to fix position in automatic way requires extraction of characteristic points, their identification and subsequently in the last calculation step an application of classical methods of the radar navigation. The present article illustrates the characteristic point's identification algorithm based on the invariant representation of the radar image

Use genetic algorithms to construct testing tasks for the anti - collision system of an unmanned surface vehicle

Konstrukcja niezawodnego, automatycznego systemu antykolizyjnego dla Bezzałogowego Pojazdu Nawodnego wymaga intensywnego testowania. System musi być sprawdzony w wielu rożnych sytuacjach tak, aby można było stwierdzić, że jest bezpieczny i nie doprowadzi do kolizji. Tradycyjna metoda tworzenia zadań testowych polega na wykorzystaniu do tego celu człowieka. Projektant testow, bazując na swoim doświadczeniu, konstruuje kolejne testy starając się przy tym, aby utworzony przez niego zbior zadań testowych reprezentował wszystkie możliwe sytuacje, z ktorymi pojazd może mieć do czynienia na morzu. Problem jednak polega na tym, że człowiek nie jest w stanie przewidzieć wszystkich możliwych sytuacji, co może skutkować nieodpowiednim przygotowaniem systemu antykolizyjnego do pracy a w konsekwencji kolizją. W artykule zaproponowano inny sposob konstrukcji zadań testowych. Funkcję tą ma pełnić algorytm genetyczny, ktorego zadaniem jest poszukiwanie sytuacji stanowiących trudność dla systemu.To build a reliable automatic anti-collision system for an Unmanned Surface Vehicle it is necessary to implement an intensive testing procedure. In order for the system to guarantee safety at sea it has to be verified in many different situations. The traditional method for building such test tasks uses a test designer to create tests based on his or her experience; ideally the complete test set would represent all possible situations that the vehicle may face at sea. However, the problem is that a human cannot predict all possible situations, a flaw which may result in an inappropriate preparation of the anti-collision system and, in consequence, a collision. The following paper proposes another method for constructing testing tasks, a method that utilises a genetic algorithm. The algorithm's aim is to search for situations which may be difficult for the system or situations which are completely different from the ones tested so far

A quick algorithm for planning a path for a biomimetic autonomous underwater vehicle

Autonomous underwater vehicles are vehicles that are entirely or partly independent of human decisions. In order to obtain operational independence, the vehicles have to be equipped with specialized software. The task of the software is to move the vehicle along a trajectory while avoiding collisions. In its role of avoiding obstacles, the vehicle may sometimes encounter situations in which it is very difficult to determine what the next movement should be from an ad hoc perspective. When such a situation occurs, a planning component of the vehicle software should be run with the task of charting a safe trajectory between nearby obstacles. This paper presents a new path planning algorithm for a Biomimetic Autonomous Underwater Vehicle. The main distinguishing feature of the algorithm is its high speed compared with such classic planning algorithms as A*. In addition to presenting the algorithm, this paper also summarizes preliminary experiments intended to assess the effectiveness of the proposed algorithm

Application of bearing and distance trees to the identification of landmarks on the coast

The problem of continuous position availability is one of the most important issues connected with the human activity at sea. Because the availability of satellite navigational systems can be limited in some cases, e.g. during military operations, one has to consider additional methods of acquiring information about the ship’s position. In this paper one of these methods is presented, which is based on exploiting landmarks located on a coastline. A navigational radar is used to obtain information about these points. In order to estimate the ship’s position by means of a set of landmarks, it is necessary to know their accurate locations. The paper presents a landmark identification method based on the comparison of bearing and distance trees representing pattern points generated from a chart, as well as points extracted from a radar image

Radar images compression in a project of the maritime coastal positioning system - an invariant method

The article describes one of the radar image compression methods - the "invariant" method. Furthermore, evaluation of the "invariant" method in the context of its application in the designed maritime coastal positioning system is presented. Influence of the "threshold", the median filter and FFT transform to a final form of compressed image is also considered

Tworzenie sieci neuronowych z samoorganizacją Hebba za pomocą Kodowania Asemblerowego

Assembler Encoding is a new neuro-evolutionary method. To date, it has been tested in such problems as: an optimization problem, a predator-prey problem, and in an inverted pendulum problem. In all the cases mentioned, Assembler Encoding was used to create neural networks with constant, invariable architecture. To test whether Assembler Encoding is able to form other types of neural networks, next experiments were carried out. In the experiments, the task of Assembler Encoding was to form self-organizing, dynamic neural networks. The networks were tested in the predator-prey problem. To compare Assembler Encoding with other method, in the experiments, a modified version of standard neuro-evolution was also applied. The results of the experiments are presented at the end of the paper.Kodowanie Asemblerowe jest metodą neuro-ewolucyjną, która do tej pory stosowana była wyłącznie do konstrukcji sieci neuronowych o stałej, nie zmiennej w czasie architekturze. W celu sprawdzenia skuteczności metody w tworzeniu innych typów sieci neuronowych, przeprowadzonoszereg eksperymentów. W ich trakcie zadaniem Kodowania Asemblerowego była konstrukcja rekurencyjnych oraz jednokierunkowych sieci neuronowych z samoorganizacją Hebba. Tworzone sieci wykorzystywane były do sterowania zespołem "drapieżców", których celem było pochwycenie szybko poruszającej się "ofiary" (predator-prey problem) postępującej zgodnie z pewną prostą strategią. Wyniki Kodowania Asemblerowego uzyskane w trakcie badań porównano z osiągami innej metody neuro-ewolucyjnej

The method of extraction of characteristic points from the radar image of the seashore for the needs of positioning system

The problem of continuous position availability is one of the most important issues connected with human activity on the sea. Because the availability of the electronic navigational systems can be limited in some cases (for example military operations) we should considered additional methods of gathering information about ship's position. In this paper one of these methods is presented, which is based on extraction specific features from radar images - characteristic points of the coast line