A hybrid algorithm for self location

Niniejszy artykuł prezentuje podejście hybrydowe do samolokalizacji w oparciu o zintegrowany system zbierania danych. Obie funkcje topologiczna i metryczna zostały zrealizowane z użyciem dalmierza ultradźwiękowego. Do przetestowania poprawności działania opracowanej metody wykorzystano robot Lego Mindstorms NXT. Zaprezentowane rozwiązanie przyśpiesza pracę pojazdu, skracając czas rozpoznawania napotkanych obiektów orientacyjnych. Minimalizowany jest błąd odometryczny. Bardzo istotnym elementem pracy jest identyfikacja obiektów, ich orientacji i budowanie modelu mapy o względnym stopniu zaufania. Przeprowadzone badania wykazały wysoką dokładność zaprezentowanej metody samolokalizacji.Application of two independent systems is a classical approach when realizing topological-metric localization algorithms [1, 2, 3]. In this issue a hybrid localization method with an integrated data collecting is proposed. Both functions, topological and metric, are based on a sonar. Multi-reflections are one of the biggest problems by the sonar systems [7, 8]. However, there are many examples of using sonars in the Simultaneous Localization and Mapping (SLAM) [4, 9]. The presented method (Section 2) consists of four phases: 1) data collec-tion and filtering (Figs. 1 and 2), 2) object classification (Fig. 3), 3) building map with a confidence coefficient (Fig. 4), 4) local and global map (Fig. 5) comparison and end decision. Many authors use a grid map for the topological localization [5, 6]. Here a model matching attempt is performed. The concept of the confidence coefficient map is very important in this work. Section 3 describes an experiment whose workspace is shown in Fig. 6. The results (Section 4) are presented in Table 1: 77% of the tests were successful , 14% gave fault results, while in 9% – no solution was found. In spite of the restrictions of the used robot, the project seems very perspective

Lego Mindstorms NXT based quasi-autonomous vehicle

W artykule przedstawiono metodę sterowania pojazdem, która jest analogiczna do wydawania poleceń człowiekowi, czyli operuje na abstrakcyjnych pojęciach. Zbadane zostało na ile możliwa jest budowa takiego systemu korzystając z powszechnie dostępnego sprzętu - zestawu Lego Mindstorms NXT. Główne zadania wykonywane przez robota, to budowanie mapy, osiągnięcie pozycji wskazanej przez operatora oraz wykrywanie i rozpoznawanie prostych obiektów. Badania eksperymentalne wykazały, że zastosowany algorytm rozpoznawaniu obiektów, uzyskał wysoką trafność.The presented research evaluates how suitable the Lego Mindstorms NXT sets are for implementing real time algorithms in mobile devices. Therefore, a vehicle control method, based on an abstract commands list, was developed. The main tasks executed by the vehicle are: mapping, reaching a location determined by the operator and recognizing a primitive object. The interface of the project is shown in Fig. 1. It allows the user/operator to observe the map, the parameters of the objects and to send commands from the dynamic generated command list. The implemented mapping and object detection algorithms are shown in Fig. 2. The vehicle construction (Fig. 3) is based on the classical model of 2 steered and one balancing wheel. Tab.1 presents the following test results: the achieved position accuracy, object recognition precision and the time of task completion. The odometry [2, 3] of the construction is not good enough. Navigation could be improved by adding some more precise sensors [4], [5]. The efficiency of the object detection algorithm reaches 75%, which is relatively suitable for the vehicle tasks. The test experience shows that the Lego NXT set is not an easy platform to create a general purpose vehicle, because of the many sensor and motor problems. However, the general positive results speak for its partial suitability by experimental verification of different modern attempts requiring vehicles, avoiding great hardware costs

Handwritten digit pattern recognition based on education robot

Niniejsza praca prezentuje zaimplementowanie systemu rozpoznającego ręcznie pisane wzorce cyfrowe z użyciem mobilnego układu edukacyjnego LEGO Mindstorms NXT. Został on wybrany ze względu na prostotę w konstrukcji i równocześnie możliwość złożonego programowania. Zbudowany w ramach projektu robot skanujący znaki pisma ręcznego spełnił założenia początkowe. Wyniki zaimplementowanego algorytmu rozpoznającego również pokryły się z oczekiwaniami - system osiągnął skuteczność na poziomie 100% w warunkach idealnych. We względnie utrudnionych warunkach skuteczność spadła do 91%.Pattern recognition can be classified depending on the data source, the way data is read, processed and on the implementation of the recognition itself [9]. This paper presents a method of pattern recognition identifying handwritten Arabic numbers. The data is collected by a Lego Mindstorms NXT 2.0 mobile robot using a color sensor. Usually, the input data are gathered by high-precision equipment [2,5], and or have an additional multi-sensor subsystem [1]. Very successive recognition approaches are based on neural networks [3, 4,6] additional supported by statistic [8]. Unfortunately, all these methods require powerful calculations. The environment data read by such a simple educational robot contains many drawbacks: noises, relative stabile confidence etc. The solution we propose solves to some extent the problem using a minimal hardware equipment (Fig. 4) and undemanding computation effort. The built recognition system is divided into two parts. The first part presents the data set collection - the hand-written digits scanning (Fig.1) and the data initial processing. The second one consists of primary and secondary classification (Figs. 2 and 3). The algorithm is based on the undirected graph model [10]. The results of the conducted experiments are very interesting (Tabs. 1 and 2). This encourages further exploration of implementation of the well-known and new recognition methods on minimal hardware

Analysis of medical images based on graph search algorithms

W artykule przedstawiono wyniki testów niekonwencjonalnego zastosowania metod do przeszukiwania grafów w celu analizy obrazów powstałych z rezonansu magnetycznego głowy. Zaprezentowano GUI do automatycznej obróbki serii obrazów. Zbudowane klasyfikatory wykazały, że metoda BFS analizy plików DICOM, po odpowiednej selekcji cech, pozwala na 100% rozpoznawanie chorych na wodogłowie i ponad 90% zdrowych, co zachęca do dalszych badań i obserwacji, np. czy osoby sklasyfikowane błędnie jako chorzy, po czasie rzeczywiście nie rozwinęli tej choroby.There are many methods for image segmentation [1, 2]: threshold, area, edge and hybrid methods. Area methods indicate groups of similar pixels form local regions [3, 4]. Edge methods detect boundaries between homogeneous segments [5, 6, 7]. In this paper we present the results of tests of unconventional implementation of graph search methods for the analysis of images generated from magnetic resonance imaging [8]. We explored the effectiveness of different approaches for dividing areas within a similar gray scale, using adapted graph search algorithms (DFS, BFS) after appropriate modification (Fig. 1). For this purpose, the Weka package (a tool for pre-processing, classification, regression, clustering and data visualization) was used [9]. A training set was generated after analyzing all the series of images from the database. First, we evaluated models created using certain algorithms and compared their efficacy (Tab. 1). This was followed by a selection of attributes (Tab. 2) and a re-evaluation of the models (Tab. 3). Comparison of the results of both evaluations showed that after selection of the relevant product attributes, you can achieve up to 100% detection of patients with hydrocephalus and over 90% proper recognition of healthy persons. This encourages further research and observation, such as whether persons wrongly classified as sick actually developed the disease in time. We designed a web application for the study, written in Windows Azure, as well as a GUI for automatic processing of a series of images (Fig. 2)

Implementation of tracking algorithm using cameras and mobile educational robot

Artykuł prezentuje algorytm śledzenia z wykorzystaniem filtru Kalmana. Do realizacji celu został wykorzystany smartfon z systemem Android i wbudowaną kamerą oraz robot z serii LEGO Mindstorms NXT. W ramach pracy został zaprojektowany i stworzony działający system śledzący obiekt. Zastosowanie filtru Kalmana w dużym stopniu poprawiło skuteczność śledzenia. Przedstawione zostały testy wraz z interpretacją ich wyników. Pokazują one skuteczność zaimplementowanych rozwiązań. Opisany został także wpływ różnych parametrów na efektywność śledzenia.Information obtained through analysis of video sequences can have many uses, for instance in different video-game controllers or intelligent mobile safety systems [1]. Thanks to the miniaturization of integrated circuits, it is possible to use these solutions in intelligent mobile vehicles [2]. In order to keep track of an object, first there has to be found its existence and location. Many methods of detection and tracking are based on the specific object characteristic [3,4]. The observation of the object contour is also very popular[5,6]. In every case, however, the disadvantages are downside costs and possibility of losing an object by sudden changes of the selected feature. This work presents the implementation of a tracking algorithm with double detection-color and shape. Both parameters were analysed with a large tolerance, which simplified the calculation engine. There was used the Kalman filter [7]. An Android Smartphone with a built-in camera and a robot of LEGO Mindstorms NXT series were applied. The paper contains a description of the structure of the system (Fig.1) and the most important implementation details associated with a specific way of detecting and tracking the object (Fig.2). The experiments carried out show the efficiency of the system (Fig. 2, ). The impact of the various parameters on the efficiency of the trace is described (Tab 1). The tests together with the interpretation of their results are presented

Digits recognition using an educational robot

Artykuł przedstawia system rozpoznający liczby rzymskie przy użyciu edukacyjnego zestawu Mindstorms NXT. Algorytm OCR wybrany do rozpoznania znaków został oparty na klasyfikacji cech. Zaadaptowana wersja algorytmu Region of Interest ROI i klasyfikacja cech są głównymi atutami tej pracy. System został skutecznie przetestowany pod wieloma względami. Powstała konstrukcja umożliwiająca skanowanie kartki formatu A4, a obsługujący ją program umożliwia prawidłową interpretację zeskanowanych liczb rzymskich.Pattern recognition is always associated with powerful calculation [1, 2]. A specific branch in this area is Optical Character Recognition [3, 4, 5] where one of the most popular techniques is Feature Extraction, also known as Intelligent Character Recognition [6]. All ICR algorithms are topological [7, 8, 9]. This paper presents an implementation of Roman Number Recognition system realized on LEGO Mindstorms NXT educational robot. The main point is successful minimalistic realization of an on-board pattern recognition system. The NXT platform allows also an easy reconfiguration of the hardware and more building freedom without extra costs (Fig. 1.). An adapted version of the ROI algorithm is implemented [10]. Based on the extracted features (Fig. 2.) a classification of the roman digits is proposed (Fig. 3.). The final stage of the program includes segmentation, end result calculation and visualization of it on the robot screen. The conducted experimental tests proved a 100% efficiency for digit and number recognition having a process in optimal conditions and quite good stability for the optical noises (Fig. 4.) and color chances (Tab. 1). In spite of many drawbacks of the hardware, the implemented system seems very perspective and invokes many ideas toward pattern recognition technics

Topological-metric indoor path planning

W artykule przedstawiono eksperyment posługujący się metodą hybrydową: asocjacyjno-wizyjne podejście - adaptacja metody QualNav oraz pomiar odległości. Do praktycznej realizacji użyte robot Lego Mindstorms NXT 2.0, kamera telefonu komórkowego oraz sonar. Eksperymenty wykazały dużą skuteczność wykonanych poleceń. Scenariusz jest bardzo aktualny dla realizacji zadań autonomicznego poruszania się w dużych salach gdzie często pozycja i orientacja przedmiotów (krzesła, fotele, skrzynie itd.) nie jest stała.Quality strategies used in mobile robot navigation [4][6] can be successfully supplemented by quantity ones [2, 8]. In this paper we present a path-planning approach based on a hybrid [1][7], topological-metric strategy. It is based on topological navigation [5] adapted to enclosed spaces, expanded with sonar data-updating. The landmarks are assumed to possess properties common to those of office furniture, additionally marked with a color - a time-saving simplification (Fig. 1). Measurements of the distance have a secondary role: the distance was only measured if unambiguous identification of the registered objects was not obtained. What is significant in this approach is that parts of the landmarks have a non-steady position: instead by a fixed point, their presence is described by a zone (Fig. 2). The main task executed by a vehicle is to follow a route achieving the end position. The command structure (giving the route) is a data sequence - edges which have to be crossed over by the robot (Fig. 3). Besides odometry difficulties [3, 8], the great localization accuracy and the time impact of the scanning angle of a robot (Fig. 4) was experimentally proved. Dependencies between the precision of task-execution (accuracy of position achievement), work duration and the scan-angle used by the robot were examined and described. All final observations are presented in Tab.1. The scan-angle of about 25o was suggested based on investigations. The used scenario is very suitable for large office halls, where the position of the objects (chairs, armchairs, chests, etc.) is often not constant

Indoor Mapping Using Sonar Sensor and Otsu Method

In this paper we present an indoor mapping algorithm based on sonar sensor. The overall object detection and mapping experiment is based on small scale local spatial information which has been accomplished in a 2D geometrical map. Considering all drawbacks and pluses of ultrasonic sensors, we present an innovative mapping approach, applying the Otsu’s method and Hit-or-Miss for sonar-data processing. The collected data are treated as a gray-scale picture. For its binarization, we applied the well-known for vision-based systems threshold calculation. Then also the morphology effect, what rises additionally the mapping accuracy, as is shown at the end of the paper. The robot is based on the education construction set LEGO Mindstorms EV3 intelligent brick on ev3dev - a Debian Linux-based operating system and Python 2.0 have been used for programming. The results are evaluated and compared with the real space

A remote controlled system based on education robots

Artykuł przedstawia badania efektywności zarządzania układami mobilnymi przez Internet oraz testowanie skuteczności algorytmu śledzenia robota sterowanego zdalnie. Eksperymenty zostały przeprowadzone na zrealizowanym do tego celu systemie - serwis internetowy oferujący przeprowadzanie gry pomiędzy dwoma, zdalnie sterowanymi robotami. Do wykonania powyższych założeń wykorzystany został statystyczny algorytm śledzenia punktu oparty o rozszerzony filtr Kalmana. Przeprowadzono szereg testów.The paper presents an analysis of the effectiveness of mobile system management via the Internet [1] and testing of the effectiveness of the tracking algorithm robot controlled remotely [2, 3]. A object tracking algorithm based on the Extended Kalman Filter is implemented into a game for two robots (Fig. 1). The project proves the efficiency of the robot control and the EKF accuracy by observing and analyzing the work of the internet service, which allows two remote-controlled robots to take a part in the game [8]. Similar examples are in medicine [5] as well as international research and education [6]. All of them use advanced robotics technologies [4, 7, 9]. The robot used in the experiments is an educational robot Mindstorms NXT and in this paper we prove that it also gives many possibilities to achieve interesting results in robot remote-control and human-robot interaction (Fig. 2). In the case of tests for the reaction time of the robot on request, one can draw positive conclusions. In situations where no response is required from the server, the response time of the systems to commands from the remote computers is instant. The effectiveness of the tracking algorithm for the remote-controlled robot was tested by conducting a series of tests. They showed a proportional dependency between the velocity of the robots and the coordinate errors (Figs. 3 and 4). A possible direction of development of the system may be the use of more advanced Internet technologies, which could accelerate communication between a client and a server

The monitoring system of human posture during seating

W artykule opisano system monitorujący prawidłowość postawy człowieka podczas siedzenia. System ten zbudowany został z użyciem platformy RaspberryPi 3b, gumowej maty oraz autorskiego oprogramowania na komputer PC. Pozwala on na informowanie w czasie rzeczywistym osoby monitorowanej o pojawieniu się niesymetrii jej siedzenia na krześle. Zaproponowany przez autorów system pozwala na identyfikację stopnia niepoprawności siedzenia podczas pracy i daje możliwość korekcji postawy, co pozwala na pozytywne oddziaływanie na zdrowie i efektywność pracy osób obsługujących monitory ekranowe. Obsługa systemu odbywa się poprzez interfejs graficzny. Dane pochodzące z monitorowania postawy osoby siedzącej są gromadzone i mogą być podstawą do przeprowadzania badań statystycznych poświęconym np. prawidłowości postawy podczas pracy pracowników biurowych.The mail goal of this paper is to present a computer system that would monitor a sitting position and inform the user if it is incorrect. As additional functionality we ensure reminding the user about breaks from sitting and check whether this break is actually executed. This topic was chosen because in last century average amount of sitting increased dramatically. Prolonged sitting has negative effects on human health both physically and mentally. That is way it is important to create systems like this one which are trying to eliminate those effects. If no eliminate then at least minimize them. The presented system includes Raspberry Pi 3B, Tact Switch buttons, prototype board, cables and rubber mat. The software was written in Kotlin and Python, involving frameworks Spring and TornadoFX. The issue contains a short literature review of negative effects of prolonged sitting and presents selected solutions dealing with the same problem. In section four we present the architecture of our proposition, explaining the most important details also about the functionality of the system. The last section summaries the project and draws number of further development