Coarse Global Visual Localization of a Mobile Robot

Localization, which is the ability of a mobile robot to estimate its position within its environment, is a key capability for autonomous operation of any mobile robot. This thesis presents a system for indoor coarse and global localization of a mobile robot based on visual information. The system is based on image matching and uses SIFT features as natural landmarks. Features extracted from training images arestored in a database for use in localization later. During localization an image of the scene is captured using the on-board camera of the robot, features are extracted from the image and the best match is searched from the database. Feature matching is done using the k-d tree algorithm. Experimental results showed that localization accuracy increases with the number of training features used in the training database, while, on the other hand, increasing number of features tended to have a negative impact on the computational time. For some parts of the environment the error rate was relatively high due to a strong correlation of features taken from those places across the environment.

Mobile robot localization using sonar ranging and wlan intensity maps

 Main goal of this thesis was to implement a localization system which uses sonars and WLAN intensity maps to localize an indoor mobile robot. A probabilistic localization method, Monte Carlo Localization is used in localization. Also the theory behind probabilistic localization is explained. Two main problems in mobile robotics, path tracking and global localization, are solved in this thesis. Implemented system can achieve acceptable performance in path tracking. Global localization using WLAN received signal strength information is shown to provide good results, which can be used to localize the robot accurately, but also some bad results, which are no use when trying to localize the robot to the correct place. Main goal of solving ambiguity in office like environment is achieved in many test cases.

Multi-sensor Simultaneous Localization and Mapping

Simultaneous localization and mapping(SLAM) is a very important problem in mobile robotics. Many solutions have been proposed by different scientists during the last two decades, nevertheless few studies have considered the use of multiple sensors simultane¬ously. The solution is on combining several data sources with the aid of an Extended Kalman Filter (EKF). Two approaches are proposed. The first one is to use the ordinary EKF SLAM algorithm for each data source separately in parallel and then at the end of each step, fuse the results into one solution. Another proposed approach is the use of multiple data sources simultaneously in a single filter. The comparison of the computational com¬plexity of the two methods is also presented. The first method is almost four times faster than the second one.

Of pearls and pigs : a conceptual-semantic Tiernet approach to formal representation of structure and variation of phraseological units

"Helmiä sioille", pärlor för svin, säger man på finska om någonting bra och fint som tas emot av en mottagare som inte vill eller har ingen förmåga att förstå, uppskatta eller utnyttja hela den potential som finns hos det mottagna föremålet, är ointresserad av den eller gillar den inte. För sådana relativt stabila flerordiga uttryck, som är lagrade i språkbrukarnas minnen och som demonstrerar olika slags oregelbundna drag i sin struktur använder man inom lingvistiken bl.a. termerna "idiom" eller "fraseologiska enheter". Som en oregelbundenhet kan man t.ex. beskriva det faktum att betydelsen hos uttrycket inte är densamma som man skulle komma till ifall man betraktade det som en vanlig regelbunden fras. En annan oregelbundenhet, som idiomforskare har observerat, ligger i den begränsade förmågan att varieras i form och betydelse, som många idiom har jämfört med regelbundna fraser. Därför talas det ofta om "grundform" och "grundbetydelse" hos idiom och variationen avses som avvikelse från dessa. Men när man tittar på ett stort antal förekomstexempel av idiom i språkbruk, märker man att många av dem tillåter variation, t.o.m. i sådan utsträckning att gränserna mellan en variant och en "grundform" suddas ut, och istället för ett idiom råkar vi plötsligt på en "familj" av flera besläktade uttryck. Allt detta väcker frågan om hur dessa uttryck egentligen ska vara representerade i språket. I avhandlingen utförs en kritisk granskning av olika tidigare tillvägagångssätt att beskriva fraseologiska enheter i syfte att klargöra vilka svårigheter deras struktur och variation erbjuder för den lingvistiska teorin. Samtidigt presenteras ett alternativt sätt att beskriva dessa uttryck. En systematisk och formell modell som utvecklas i denna avhandling integrerar en beskrivning av idiom på många olika språkliga nivåer och skildrar deras variation i form av ett nätverk och som ett resultat av samspel mellan idiomets struktur och kontexter där det förekommer, samt av interaktion med andra fasta uttryck. Modellen bygger på en fördjupande, språkbrukbaserad analys av det finska idiomet "X HEITTÄÄ HELMIÄ SIOILLE" (X kastar pärlor för svin).

Localization, Frequency, and Functions of Filled Pauses: Five American Politicians’ Use of er and erm in the Talk Show Larry King Live

Tämän pro gradu– tutkielman tavoitteena oli testata täytettyjen taukojen (er ja erm) esiintymistiheyttä, sijaintia kieliopillisessa rakenteessa sekä funktioita Kjellmerin (2003) korpus-tutkimuksessa. Materiaalina käytin viiden yhdysvaltalaisen poliitikon puhetta keskusteluohjelmasta Larry King Live. Tutkimuksessani sovelsin Kjellmerin tutkimusmenetelmiä, joita muokkasin huomattavasti suppeampaan materiaaliini sopiviksi. Lähestymistapani oli täten induktiivinen toisin kuin testatussa tutkimuksessa. Materiaalini oli tarkoituksellisesti rajattu, sillä halusin selvittää, kuvaavatko Kjellmerin laajaan materiaaliin perustuvat tutkimustulokset myös täytettyjen taukojen käyttöä suppeammassa materiaalissa. Materiaalini (kokonaisuudessaan 101 minuuttia) transkriboin ortografisesti. Analyysissäni arvioin täytettyjen taukojen esiintymistiheyden puhujakohtaisesti ja koko ryhmälle suhteuttamalla täytettyjen taukojen lukumäärän kokonaissanamäärään. Tämän jälkeen tein perinteisen kielioppianalyysin rakenteista, joita edeltää tai joissa esiintyy täytetty tauko, ja täytettyjen taukojen sijainnin perusteella luokittelin ne sana-, lauseke-, ja lausetasolle. Lopuksi analysoin täytettyjen taukojen käyttöä soveltaen Kjellmerin ehdottamia funktioita (hesitaatio, vuorottelujäsennyksen merkitseminen, huomion herättäminen ja kontaktin luominen, korostus ja korjaus) ja niiden piirteitä omaan materiaaliini. Tutkimukseni perusteella täytetyt tauot esiintyvät tutkitun viiden poliitikon puheessa suhteellisen usein. Puhujakohtaiset eroavaisuudet olivat kuitenkin huomattavat. Kieliopillisen luokitteluni mukaan sana-, lauseke- ja lausetasot eivät täysin kuvaa täytettyjen taukojen sijoittumista, sillä täytetyt tauot edelsivät mm. määre-lauseita, jotka eivät vastaa lausetasoa englannin kielessä. Materiaalini funktioanalyysi osoitti, että täytetyt tauot yleensä vastaavat yhtä tai useampaa Kjellmerin ehdottamaa funktioita. Lisäksi tutkimukseni mukaan täytetyillä tauoilla on ainakin yksi rakenteellinen funktio. Analyysini perusteella Kjellmerin tutkimustulokset ovat siis pääosin sovellettavissa suppeampaan materiaaliin. Puutteiksi hänen tutkimuksessaan osoittautuivat funktioanalyysille tärkeän kontekstuaalisen informaation puute sekä keskittyminen täytettyihin taukoihin, jotka esiintyvät vain tietyissä kielioppirakenteissa. Yleisesti voin tutkimukseni pohjalta todeta, että täytetyt tauot ovat vielä vajaasti tunnettuja ja että kieliopillisen sijoituksen ja funktioiden lisätutkimus on tarpeellista.

Two-dimensional atom localization and Raman cooling of tripod-type atoms

Both atom localization and Raman cooling, considered in the thesis, reflect recent progress in the area of all-optical methods. We focus on twodimensional (2D) case, using a four-level tripod-type atomic scheme for atom localization within the optical half-wavelength as well as for efficient subrecoil Raman cooling. In the first part, we discuss the principles of 1D atom localization, accompanying by an example of the measurement of a spontaneously-emitted photon. Modifying this example, one archives sub-wavelength localization of a three-level -type atom, measuring the population in its upper state. We go further and obtain 2D sub-wavelength localization for a four-level tripod-type atom. The upper-state population is classified according to the spatial distribution, which in turn forms such structures as spikes, craters and waves. The second part of the thesis is devoted to Raman cooling. The cooling process is controlled by a sequence of velocity-selective transfers from one to another ground state. So far, 1D deep subrecoil cooling has been carried out with the sequence of square or Blackman pulses, applied to -type atoms. In turn, we discuss the transfer of atoms by stimulated Raman adiabatic passage (STIRAP), which provides robustness against the pulse duration if the cooling time is not in any critical role. A tripod-type atomic scheme is used for the purpose of 2D Raman cooling, allowing one to increase the efficiency and simplify the realization of the cooling.

Indoor Localization Solutions for a Marine Industry Augmented Reality Tool

In this report are described means for indoor localization in special, challenging circum-stances in marine industry. The work has been carried out in MARIN project, where a tool based on mobile augmented reality technologies for marine industry is developed. The tool can be used for various inspection and documentation tasks and it is aimed for improving the efficiency in design and construction work by offering the possibility to visualize the newest 3D-CAD model in real environment. Indoor localization is needed to support the system in initialization of the accurate camera pose calculation and auto-matically finding the right location in the 3D-CAD model. The suitability of each indoor localization method to the specific environment and circumstances is evaluated.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.