Rozprawy doktorskie na temat „Mobile and static robots”

The aim of this project is to examine the feasibility and reliability of the use of a low cost computer vision system to track and intercept a thrown object. A stereo vision system tracks the object using color recognition and then guides a mobile wheeled robot towards an interception point in order to capture it. Two different trajectory prediction models are compared. One model fits a second degree polynomial to the collected positional measurements of the object and the other uses the Forward Euler Method to construct the objects flight path. To accurately guide the robot, the angular position of the robot must also be measured. Two different methods of measuring the angular position are presented and their respective reliability are measured. A calibrated magnetometer is used as one method while pure computer vision is implemented as the alternative method. A functional object tracking and interception system that was able to intercept the thrown object was constructed using both the polynomial fitting trajectory prediction model as well as the one based on the Forward Euler Method. The magnetometer and pure computer vision are both viable methods of determining the angular position of the robot with an error of less than 1.5°.
I detta projekt behandlas konstruktionen av och pålitligheten i en bollfånganderobot och dess bakomliggande lågbudgetkamerasystem. För att fungera i tre dimensioner används en stereokameramodul som spårar bollen med hjälp av färgigenkänning och beräknar bollbanan samt förutspår nedslaget för att ge god tid till roboten att genskjuta bollen. Två olika bollbanemodeller testas, där den ena tar hänsyn till luftmotståndet och nedslaget beräknas numeriskt och den andra anpassar en andragradspolynom till de observerade datapunkterna. För att styra roboten till den tänkta uppfångningspunkten behövs både robotens position, vilket bestäms med kameramodulen, och robotens riktning.Riktningen bestäms medbåde en magnetometer och med kameramodulen, för att undersöka vilken metod som passar bäst. Den förslagna konstruktionen för roboten och kamerasystemet kan spåra och fånga objekt med bådadera de testade modellerna för att beräkna bollbana, dock så är tillförlitligheten i den numeriska metoden betydligt känsligare för dåliga mätvärden. Det är även möjligt att använda sig av både magnetometern eller endast kameramodulen för att bestämma robotens riktning då båda ger ett fel under 1.5°.

L'objectif du travail proposé est de concevoir et commander un groupe des robots mobiles similaires et d'architecture simple appelés m-bots (mono-robots). Plusieurs m-bots ont la capacité de saisir ensemble un objet afin d'assurer sa co-manipulation et son transport quelle que soit sa forme et sa masse. Le robot résultant est appelé p-bot (poly-robot) et est capable d'effectuer des tâches de déménageur pour le transport d'objets génériques. La reconfigurabilité du p-bot par l'ajustement du nombre des m-bots utilisés permet de manipuler des objets lourds et des objets de formes quelconques (particulièrement s'ils sont plus larges qu'un seul m-bot). Sont considérés dans ce travail l'évitement d'obstacle ainsi que la stabilité du p-bot incluant la charge à transporter. Une cinématique pour un mécanisme de manipulation a été proposée et étudiée. Ce dernier assure le levage de la charge et son dépôt sur le corps des robots pour la transporter. Plusieurs variantes d'actionnement ont été étudiées : passif, avec compliance et actionné. Un algorithme de positionnement optimal des m-bots autour de l'objet à manipuler a été proposé afin d'assurer la réussite de la tâche à effectuer par les robots. Cet algorithme respecte le critère de "Force Closure Grasping" qui assure la stabilité de la charge durant la phase de manipulation. Il maintient aussi une marge de stabilité statique qui assure la stabilité de l'objet durant la phase de transport. Enfin, l'algorithme respecte le critère des zones inaccessibles qui ne peuvent pas être atteintes par les m-bots. Une loi de commande a été utilisée afin d'atteindre les positions désirées pour les m-bots et d'assurer la navigation en formation, durant la phase du transport, durant laquelle chaque robot élémentaire doit maintenir une position désirée par rapport à l'objet transporté. Des résultats de simulation pour un objet de forme quelconque, décrite par une courbe paramétrique, sont présentés. Des simulations 3D en dynamique multi-corps ainsi que des expériences menées sur les prototypes réalisés ont permis de valider nos propositions
Our goal in the proposed work is to design and control a group of similar mobile robots with a simple architecture, called m-bot. Several m-bots can grip a payload, in order to co-manipulate and transport it, whatever its shape and mass. The resulting robot is called a p-bot andis capable to solve the so-called "removal-man task" to transport a payload. Reconfiguring the p-bot by adjusting the number of m-bots allows to manipulate heavy objects and to manage objects with anyshape, particularly if they are larger than a single m-bot. Obstacle avoidance is addressed and mechanical stability of the p-bot and its payload is permanently guaranteed. A proposed kinematic architecture for a manipulation mechanism is studied. This mechanism allows to lift a payload and put it on them-bot body in order to be transported. The mobile platform has a free steering motion allowing the system maneuver in any direction. An optimal positioning of the m-bots around the payload ensures a successful task achievement without loss of stability for the overall system. The positioning algorithm respects the Force Closure Grasping (FCG) criterion which ensures the payload stability during the manipulation phase. It respects also the Static Stability Margin (SSM) criterion which guarantees the payload stability during the transport. Finally, it considers also the Restricted Areas (RA) that could not be reached by the robots to grab the payload. A predefined control law is then used to ensure the Target Reaching (TR) phase of each m-bot to its desired position around the payload and to track a Virtual Structure (VS), during the transportation phase, in which each elementary robot has to keep the desired position relative to the payload. Simulation results for an object of any shape, described by aparametric curve, are presented. Additional 3D simulation results with a multi-body dynamic software and experiments by manufactured prototypes validate our proposal

A Large Scale Robot Colony (LSRC) is a complex artifact comprising of a significant population of both mobile and static robots. LSRC research is in its literary infancy and it is therefore necessary to rely upon external fields for the appropriate framework, Multi Agent Systems (MAS) and Large Scale Systems (LSS). At the intersection of MAS, LSS and LSRC exist near identical issues, problems and solutions. If attention is paid to coherence then solution portability is possible. The issue of Self-Reliability is poorly addressed by the MAS research field. Disparity between the real world and simulation is another area of concern. Despite these deficiencies, MAS and LSS are perceived as the most appropriate frameworks. MAS research focuses on three prime areas, cognitive science, management and interaction. LSRC is focused on Self-Sustainability, Self-Management and Self-Organization. While LSS research was not primarily intended for populations of mobile robots, it does address key issues of LSRC, such as effective sustainability and management. Implementation of LSRC that is based upon the optimal solution for any one or two of the three aspects will be inferior to a coherent solution based upon all three. LSRC’s are complex organizations with significant populations of both static and mobile robots. The increase in population size and the requirement to address the issue of Self-Reliance give rise to new issues. It is no longer sufficient to speak only in terms of robot intelligence, architecture, interaction or team behaviour, even though these are still valid topics. Issues such as population sustainability and management have greater significance within LSRC. As the size of a robot populations increases, minor uneconomical decisions and actions inhibit the performance of the population. Interaction must be made economical within the context of the LSRC. Sustainability of the population becomes significant as it enables stable performance and extended operational lifespan. Management becomes significant as a mechanism to direct the population so as to achieve near optimal performance. The Self-Sustainability, Self-Management and Self-Organization of LSRC are vastly more complex than in team robotics. Performance of the overall population becomes more significant than individual or team achievement. This thesis is a presentation of the Cooperative Autonomous Robot Colony (CARC) architecture. The CARC architecture is novel in that it offers a coherent baseline solution to the issue of mobile robot Self-Reliance. This research uses decomposition as a mechanism to reduce problem complexity. Self-Reliance is decomposed into Self-Sustainability, Self-Management, and Self-Organization. A solution to the issue of Self-Reliance will comprise of conflicting sub-solutions. A product of this research is a set of guidelines that manages the conflict of sub-solutions and maintains a coherent solution. In addressing the issue of Self-Reliance, it became apparent that Economies of Scale, played an important role. The effects of Economies of Scale directed the research towards LSRC’s. LSRC’s demonstrated improved efficiency and greater capability to achieve the requirements of Self-Reliance. LSRC’s implemented with the CARC architecture would extend human capability, enabling large scale operations to be performed in an economical manner, within real world and real time environments, including those of a remote and hostile nature. The theory and architecture are supported using published literature, experiments, observations and mathematical projections. Contributions of this work are focused upon the three pillars of Self-Reliance addressed by CARC: Self-Sustainability, Self-Management and Self-Organization. The chapter on Self-Sustainability explains and justifies the relevance of this issue, what it is, why it is important and how it can be achieved. Self-Sustainability enables robots to continue to operate beyond disabling events by addressing failure and routine maintenance. Mathematical projections are used to compare populations of non-sustained and sustained robots. Computer modeling experiments are used to demonstrate the feasibility of Self-Sustainability, including extended operational life, the maintenance of optimal work flow and graceful physical degradation (GPD). A detailed explanation is presented of Sustainability Functions, Colony Sites, Static Robot Roles, Static Robot Failure Options, and Polymorphism. The chapter on Self-Management explores LSS research as a mechanism to exert influence over a LSRC. An experimental reactive management strategy is demonstrated. This strategy while limited does indicate promising potential directions for future research including the Man in the Loop (MITL) strategy highly desired by NASA JPL for off world command and control of a significant robot colony (Huntsberger, et. al., 2000). Experiments on Communication evaluate both Broadcast Conveyance (BC) and Message Passing Conveyance (MPC). These experiments demonstrate the potential of Message Passing as a low cost system for LSRC communication. Analysis of Metrics indicates that a Performance Based Feedback Method (PBFM) and a Task Achievement Method (TAM) are both necessary and sufficient to monitor a LSRC. The chapter on Self-Organization describes a number of experiments, algorithms and protocols on Reasoning Robotics, a minor variant of Reactive Robotics. Reasoning Robotics utilizes an Event Driven Architecture (EDA) rather than a Stimulus Driven Architecture (SDA) common to Reactive Robotics. Enhanced robot performance is demonstrated by a combination of EDA and environmental modification enabling stigmergy. These experiments cover Intersection Navigation with contingency for Multilane Intersections, a Radio Packet Controller (RPC) algorithm, Active and Passive Beacons including a communication protocol, mobile robot navigation using Migration Decision Functions (MDF’s), including MDF positional errors. The central issue addressed by this thesis is the production of Self-Reliance guidelines for LSRC’s. Self-Reliance is perceived as a critical issue in advancing the useful and productive applications for LSRC’s. LSRC’s are complex with many issues in related fields of MAS and LSS. Decomposition of Self-Reliance into Self-Sustainability, Self-Management and Self-Organization were used to aid in problem understanding. It was found that Self-Sustainability extends the operational life of individual robots and the LSRC. Self-Management enables the exertion of human influence over the LSRC, such that the ratio of humans to robots is reduced but not eliminated. Self-Organization achieves and enhances performance through a routine and reliable LSRC environment. The product of this research was the novel CARC architecture, which consists of a set of Self-Reliance guidelines and algorithms. The Self-Reliance guidelines manage conflict between optimal solutions and provide a framework for LSRC design. This research was supported by literature, experiments, observations and mathematical projections.

A Large Scale Robot Colony (LSRC) is a complex artifact comprising of a significant population of both mobile and static robots. LSRC research is in its literary infancy and it is therefore necessary to rely upon external fields for the appropriate framework, Multi Agent Systems (MAS) and Large Scale Systems (LSS). At the intersection of MAS, LSS and LSRC exist near identical issues, problems and solutions. If attention is paid to coherence then solution portability is possible. The issue of Self-Reliability is poorly addressed by the MAS research field. Disparity between the real world and simulation is another area of concern. Despite these deficiencies, MAS and LSS are perceived as the most appropriate frameworks. MAS research focuses on three prime areas, cognitive science, management and interaction. LSRC is focused on Self-Sustainability, Self-Management and Self-Organization. While LSS research was not primarily intended for populations of mobile robots, it does address key issues of LSRC, such as effective sustainability and management. Implementation of LSRC that is based upon the optimal solution for any one or two of the three aspects will be inferior to a coherent solution based upon all three. LSRC’s are complex organizations with significant populations of both static and mobile robots. The increase in population size and the requirement to address the issue of Self-Reliance give rise to new issues. It is no longer sufficient to speak only in terms of robot intelligence, architecture, interaction or team behaviour, even though these are still valid topics. Issues such as population sustainability and management have greater significance within LSRC. As the size of a robot populations increases, minor uneconomical decisions and actions inhibit the performance of the population. Interaction must be made economical within the context of the LSRC. Sustainability of the population becomes significant as it enables stable performance and extended operational lifespan. Management becomes significant as a mechanism to direct the population so as to achieve near optimal performance. The Self-Sustainability, Self-Management and Self-Organization of LSRC are vastly more complex than in team robotics. Performance of the overall population becomes more significant than individual or team achievement. This thesis is a presentation of the Cooperative Autonomous Robot Colony (CARC) architecture. The CARC architecture is novel in that it offers a coherent baseline solution to the issue of mobile robot Self-Reliance. This research uses decomposition as a mechanism to reduce problem complexity. Self-Reliance is decomposed into Self-Sustainability, Self-Management, and Self-Organization. A solution to the issue of Self-Reliance will comprise of conflicting sub-solutions. A product of this research is a set of guidelines that manages the conflict of sub-solutions and maintains a coherent solution. In addressing the issue of Self-Reliance, it became apparent that Economies of Scale, played an important role. The effects of Economies of Scale directed the research towards LSRC’s. LSRC’s demonstrated improved efficiency and greater capability to achieve the requirements of Self-Reliance. LSRC’s implemented with the CARC architecture would extend human capability, enabling large scale operations to be performed in an economical manner, within real world and real time environments, including those of a remote and hostile nature. The theory and architecture are supported using published literature, experiments, observations and mathematical projections. Contributions of this work are focused upon the three pillars of Self-Reliance addressed by CARC: Self-Sustainability, Self-Management and Self-Organization. The chapter on Self-Sustainability explains and justifies the relevance of this issue, what it is, why it is important and how it can be achieved. Self-Sustainability enables robots to continue to operate beyond disabling events by addressing failure and routine maintenance. Mathematical projections are used to compare populations of non-sustained and sustained robots. Computer modeling experiments are used to demonstrate the feasibility of Self-Sustainability, including extended operational life, the maintenance of optimal work flow and graceful physical degradation (GPD). A detailed explanation is presented of Sustainability Functions, Colony Sites, Static Robot Roles, Static Robot Failure Options, and Polymorphism. The chapter on Self-Management explores LSS research as a mechanism to exert influence over a LSRC. An experimental reactive management strategy is demonstrated. This strategy while limited does indicate promising potential directions for future research including the Man in the Loop (MITL) strategy highly desired by NASA JPL for off world command and control of a significant robot colony (Huntsberger, et. al., 2000). Experiments on Communication evaluate both Broadcast Conveyance (BC) and Message Passing Conveyance (MPC). These experiments demonstrate the potential of Message Passing as a low cost system for LSRC communication. Analysis of Metrics indicates that a Performance Based Feedback Method (PBFM) and a Task Achievement Method (TAM) are both necessary and sufficient to monitor a LSRC. The chapter on Self-Organization describes a number of experiments, algorithms and protocols on Reasoning Robotics, a minor variant of Reactive Robotics. Reasoning Robotics utilizes an Event Driven Architecture (EDA) rather than a Stimulus Driven Architecture (SDA) common to Reactive Robotics. Enhanced robot performance is demonstrated by a combination of EDA and environmental modification enabling stigmergy. These experiments cover Intersection Navigation with contingency for Multilane Intersections, a Radio Packet Controller (RPC) algorithm, Active and Passive Beacons including a communication protocol, mobile robot navigation using Migration Decision Functions (MDF’s), including MDF positional errors. The central issue addressed by this thesis is the production of Self-Reliance guidelines for LSRC’s. Self-Reliance is perceived as a critical issue in advancing the useful and productive applications for LSRC’s. LSRC’s are complex with many issues in related fields of MAS and LSS. Decomposition of Self-Reliance into Self-Sustainability, Self-Management and Self-Organization were used to aid in problem understanding. It was found that Self-Sustainability extends the operational life of individual robots and the LSRC. Self-Management enables the exertion of human influence over the LSRC, such that the ratio of humans to robots is reduced but not eliminated. Self-Organization achieves and enhances performance through a routine and reliable LSRC environment. The product of this research was the novel CARC architecture, which consists of a set of Self-Reliance guidelines and algorithms. The Self-Reliance guidelines manage conflict between optimal solutions and provide a framework for LSRC design. This research was supported by literature, experiments, observations and mathematical projections.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Griffith School of Engineering
Faculty of Engineering and Information Technology
Full Text

The aim of this diploma thesis is design of docking station for an autonomous mobile robot Breach. The task of docking station is to connect this robotic device to power supply without human intervention in order to charge its batteries. The theoretical part of diploma thesis contains research study about autonomous charging of robots. After that it is assessed suitability of using different types of docking stations and it was chosen optimal solution. The practice part of diploma thesis contains design of docking mechanism, which takes account of inaccurate navigation of robot with deviation of several centimeters. One part of this design deals with connector system, which is dimensioned for long-term transmission of electric current with minimal value of 20 A. At the end of diploma thesis there was created 3D model of the complete docking station including connectors for charging in program called SolidWorks.

Planejamento de movimento tem o propósito de determinar quais movimentos o robô deve realizar para que alcance posições ou configurações desejadas no ambiente sem que ocorram colisões com obstáculos. É comum na robótica móvel simplificar o planejamento de movimento representando o robô pelas coordenadas do seu centro e desconsiderando qualquer restrição cinemática e dinâmica de movimento. Entretanto, a maioria dos robôs móveis possuem restrições cinemáticas não-holonômicas, e para algumas tarefas e robôs, é importante considerar tais restrições juntamente com o modelo dinâmico do robô na tarefa de planejamento. Assim é possível determinar um caminho que possa ser de fato seguido pelo robô. Nesse trabalho é proposto um método de planejamento cinemático-dinâmico que permite planejar trajetórias para robôs móveis usando malhas de estados. Essa abordagem considera a cinemática e a dinâmica do robô para gerar trajetórias possíveis de serem executadas e livre de colisões com obstáculos. Quando obstáculos não representados no mapa são detectados pelos sensores do robô, uma nova trajetória é gerada para desviar desses obstáculos. O planejamento de movimento utilizando malhas de estados foi associado a um algoritmo de desvio de obstáculos baseado no método da janela dinâmica (DWA). Esse método é responsável pelo controle de seguimento de trajetória, garantindo a segurança na realização da tarefa durante a navegação. As trajetórias planejadas foram executadas em duas plataformas distintas. Essas plataformas foram utilizadas em tarefas de navegação em ambientes simulados interno e externo e em ambientes reais. Para navegação em ambientes internos utilizou-se o robô móvel Pioneer 3AT e para navegação em ambientes externos utilizou-se o veículo autônomo elétrico CaRINA 1 que está sendo desenvolvido no ICMC-USP com apoio do Instituto Nacional de Ciência e Tecnologia em Sistemas Embarcados Críticos (INCT-SEC).
Motion planning aims to determine which movements the robot must accomplish to reach a desired position or configuration in the environment without the occurrence of collisions with obstacles. It is common in mobile robotics to simplify the motion planning representing the robot by the coordinates of its center of gravity and ignoring any kinematic and dynamic constraint motion. However, most mobile robots have non-holonomic kinematic constraints, and for some tasks and robots, it is important to consider these constraints together with the dynamic model of the robot in task planning. Thus it is possible to determine a path that can actually be followed by the robot. Here we propose a method for kinematic-dynamic path planning using lattice states. This approach considers the kinematic and dynamic of the robot to generate generate feasible trajectories free of collisions with obstacles. When obstacles not represented on the map are detected by the sensors of the robot, a new trajectory is generated to avoid these obstacles. The motion planning using lattice state was associated with an obstacle avoidance algorithm based on the dynamic window approach (DWA). This method is responsible for trajectory tracking to ensure safety in navigation tasks. This method was applied in two distinct platforms. These platforms were used for navigation tasks in both indoor and outdoor simulated environments, as well as, in real environments. For navigation in indoor environments we used a Pioneer 3AT robot and for outdoor navigation we used the autonomous electric vehicle CaRINA1 being developed at ICMC-USP with support National Institute of Science and Technology in Critical Embedded Systems (INCT-SEC).

In this thesis, we explore three methods for the geometrico-static modelling of continuum parallel robots. Inspired by biological trunks, tentacles and snakes, continuum robot designs can reach confined spaces, manipulate objects in complex environments and conform to curvilinear paths in space. In addition, parallel continuum manipulators have the potential to inherit some of the compactness and compliance of continuum robots while retaining some of the precision, stability and strength of rigid-links parallel robots. Subsequently, the foundation of our work is performed on slender beam by applying the Cosserat rod theory, appropriate to model continuum robots. After that, three different approaches are developed on a case study of a planar parallel continuum robot constituted of two connected flexible links. We solve the forward and inverse geometrico-static problem namely by using (a) shooting methods to obtain a numerical solution, (b) an elliptic method to find a quasi-analytical solution, and (c) the Corde model to perform further model analysis. The performances of each of the studied methods are evaluated and their limits are highlighted. This thesis is divided as follows. Chapter one gives the introduction on the field of the continuum robotics and introduce the parallel continuum robots that is studied in this work. Chapter two describe the geometrico-static problem and gives the mathematical description of this problem. Chapter three explains the numerical approach with the shooting method and chapter four introduce the quasi-analytical solution. Then, Chapter five introduce the analytic method inspired by the Corde model and chapter six gives the conclusions of this work.

After decades of unrealistic predictions and expectations, robots have finally escaped from industrial workplaces and made their way into our homes,offices, museums and other public spaces. These service robots are increasingly present in our environments and many believe that it is in the area ofservice and domestic robotics that we will see the largest growth within thenext few years. In order to realize the dream of robot assistants performing human-like tasks together with humans in a seamless fashion, we need toprovide them with the fundamental capability of understanding complex, dynamic and unstructured environments. More importantly, we need to enablethem the sharing of our understanding of space to permit natural cooper-ation. To this end, this thesis addresses the problem of building internalrepresentations of space for artificial mobile agents populated with humanspatial semantics as well as means for inferring that semantics from sensoryinformation. More specifically, an extensible approach to place classificationis introduced and used for mobile robot localization as well as categorizationand extraction of spatial semantic concepts from general place appearance andgeometry. The models can be incrementally adapted to the dynamic changesin the environment and employ efficient ways for cue integration, sensor fu-sion and confidence estimation. In addition, a system and representationalapproach to semantic mapping is presented. The system incorporates and in-tegrates semantic knowledge from multiple sources such as the geometry andgeneral appearance of places, presence of objects, topology of the environmentas well as human input. A conceptual map is designed and used for modelingand reasoning about spatial concepts and their relations to spatial entitiesand their semantic properties. Finally, the semantic mapping algorithm isbuilt into an integrated robotic system and shown to substantially enhancethe performance of the robot on the complex task of active object search. Thepresented evaluations show the effectiveness of the system and its underlyingcomponents and demonstrate applicability to real-world problems in realistichuman settings.
QC 20110527

In this thesis two methods to solve the Simultaneous Localization And Mapping problem are presented. The classical extended Kalman filter is used as a reference from where an efficient particle filter is examined, which uses deterministic samples called sigma points. Most of the effort is put on implementing these algorithms together with the Symmetries and Permutations Model, but a preliminary comparison of the methods has been done as well. Experiments show that linearization errors make the map inaccurate over long periods of time, and methods are discussed which decrease these effects.

The problem addressed in this thesis is discrimination of gases with an array of partially selective gas sensors. Metal oxide gas sensors are the most common gas sensing technology since they have, compared to other gas sensing technologies, a high sensitivity to the target compounds, a fast response time,they show a good stability of the response over time and they are commercially available. One of the most severe limitation of metal oxide gas sensors is the scarce selectivity, that means that they do not respond only to the compound for which they are optimized but also to other compounds. One way to enhance the selectivity of metal oxide gas sensors is to build an array of sensorswith different, and partially overlapping, selectivities and then analyze the response of the array with a pattern recognition algorithm. The concept of anarray of partially selective gas sensors used together with a pattern recognition algorithm is known as an electronic nose (e-nose).In this thesis the attention is focused on e-nose applications related mobile robotics. A mobile robot equipped with an e-nose can address tasks like environmental monitoring, search and rescue operations or exploration of hazardous areas. In e-noses mounted on mobile robots the sensing array is most often directly exposed to the environment without the use of a sensing chamber.This choice is often made because of constraints in weight, costs and because the dynamic response obtained by the direct interaction of the sensors with the gas plume contains valuable information. However, this setup introduces additional challenges due to the gas dispersion that characterize natural environments.Turbulent and chaotic gas dispersal causes the array of sensors to be exposed to rapid changes in concentration that cause the sensor response to behighly dynamic and to seldom reach a steady state. Therefore the discriminationof gases has to be performed on features extracted from the dynamics of the signal. The problem is further complicated by variations in temperature and humidity, physical variables to which metal oxide gas sensors are crossensitive.For these reasons the problem of discrimination of gases when an array of sensors is directly exposed to the environment is different from when the array of sensors is in a controlled chamber. This thesis is a compilation of papers whose contributions are two folded.On one side new algorithms for discrimination of gases with an array of sensors directly exposed to the environment are presented. On the other side, innovative experimental setups are proposed. These experimental setups enable the collection of high quality data that allow a better insight in the problem of discrimination of gases with mobile robots equipped with an e-nose. The algorithmic contributions start with the design and validation of a gas discrimination algorithm for gas sensors array directly exposed to the environment. The algorithmis then further developed in order to be able to run online on a robot, thereby enabling the possibility of creating an olfactory driven path-planning strategy. Additional contributions aim at maximizing the generalization capabilitiesof the gas discrimination algorithm with respect to variations in the environmental conditions. First an approach in which the odor discrimination is performed by an ensemble of linear classifiers is considered. Then a feature selection method that aims at finding a feature set that is insensitive to variations in environmental conditions is designed. Finally, a further contribution in this thesis is the design of a pattern recognition algorithm for identification of bacteria from blood vials. In this case the array of gas sensors was deployed ina controlled sensing chamber.

This work proposes a biologically inspired collective behaviour for a team of co-operating robots. Collective behaviour is achieved by controlling the local interactions among a set of identical mobile robots, each robot performing a set of simple behaviours in order to realise group goals. A modification of the subsumption architecture is proposed for implementing control of individual robots. This architecture is adopted because it is computationally inexpensive and potentially suitable for low-level reactive and reflexive behaviours. In this scenario, the individual behaviours of the robots have different aims, which may cause conflict. To address this issue, a fuzzy logic-based approach for multiple behaviour coordination within each robot is proposed. The work also focuses on the development of intelligent multi-agent robot teams capable of acting autonomously and of collaborating in a dynamic environment to achieve team objectives. A knowledge-based software architecture is proposed that enables these robots to select co-operative behaviours and to adapt their performance during the specified time of the mission. These abilities are important because of uncertainties in the environmental conditions and because of possible functional failures in some team members. Improvement in team performance is achieved by updating the control of the robots based on knowledge acquired on-line. This architecture is implemented in a simulated team of mobile robots performing a proof-of-concept collaborative task. The results show a significant improvement in overall group performance and the robot team is able to achieve adaptive cooperative control despite dynamic changes in the environment and variation in the capabilities of the team members. Finally, a task involving real mobile robots is undertaken to demonstrate a practical, though simplified, implementation of the proposed collective behaviour.

In mobile robot applications navigation systems are of great importance. Automation of mobile robots demands robust navigation systems. This thesis deals with a few solutions on how to help a mobile robot navigate in an environment. Navigation systems using retroreflective beacons and applications relying on laser range finders are two different solutions to aid a mobile robot. The first type of system provides very robust navigation, with the use of extra infrastructure in the environment. The latter has no need for any extra infrastructure as it can use the structure in the surrounding environment. Navigation using dead reckoning and GPS systems are also discussed. Furthermore, some of the mobile robot platforms available at Luleå University of Technology, and their application are presented.
Godkänd; 2007; 20071113 (ysko)
CASTT - Centre for Automotive Systems Technologies and Testing

Mestrado em Engenharia Eletrónica e Telecomunicações
Automação, na mais simples das designações, é a arte de criar vida na máquina, possibilitando certas ações sem controlo directo por parte de um utilizador. Esta área de estudo permite que certas atividades que consideramos aborrecidas ou perigosas possam ser executadas por máquinas. Nesta tese, um estudo do estado da arte no campo de robôs móveis e inteligentes foi realizado, apresentando um focus especial em algoritmos de navegação baseados em procura e amostragem. Uma simulação foi desenvolvida, na qual um modelo do robô Wiserobot foi criado, utilizado como ambiente de teste um ed cio conhecido no campo da robótica, o laboratório da Willow Garage. Nesta simulação foram realizados testes aos algoritmos explorados anteriormente, nomeadamente Dijkstra, PRM e RRT. Para testar os algoritmos por amostragem, um plug-in foi desenvolvido para utilizar a Open Motion Planning Library para avaliar resultados dos mesmos. Por fim, código foi desenvolvido, usando e tendo por base bibliotecas existentes no ROS, de modo a dar ao nosso modelo do robô capacidades de navegação no ambiente simulado, inicialmente estático seguido de testes com objectos não declarados. Os resultados dos vários planeadores foram comparados para avaliar a prestação nos casos de testes definidos, utilizando métricas escolhidas previamente.
Automation, in the simplest of designations, is the art of creating life in the machine, allowing the performance of certain actions without the need of direct control by an user. This area of study allows for certain activities that we deem as tedious or dangerous to be executed by machines. In this thesis, a study of the state of the art in the eld of mobile and autonomous robotics is made, focusing in navigation algorithms based on search and sampling. A simulation was developed, in which a model of the robot was created, to be used with an environment well know by roboticist, Willow Garage. In this simulation, tests were made to the algorithms explored earlier, namely Dijkstra, PRM and RRT. To test multiple samplebased planners, a plug-in was developed to use the Open Motion Planning Library for benchmarking purposes. Finally code is developed, based and using existing ROS packages, to give a model cargo robot navigation capabilities in a simulated indoor environment, initially static then with undeclared obstacles. The results were compared from multiple planners to evaluate the performance in the test cases de ned, using pre-established metrics.

This thesis implements solution for automatic docking for a mobile robot using visual markers. After initial survey of already implemented works, new docking solution is proposed. Feasibility of the solution is verified with tests of marker detection precision. The implementation is tested in a simulation and with a real robot. The functionality of the proposed solution is verified by long-term tests. The result of this work is robot’s ability to navigate known environment to find and dock a charging station. After charging the robot is able to safely disconnect from the station.

Aquesta tesi tracta el problema de l'aprenentatge automàtic d'entorns estructurats n robòtica mòbil. Particularment, l'extracció de característiques a partir dels senyals dels sensors, la construcció autònoma de mapes, i l'autolocalització de robots.
S'estudien els fonaments matemàtics necessaris per a l'extracció de característiques a partir d'imatges i registres d'un làser, els quals permeten la identificació unívoca dels elements de l'entorn. Els atributs extrets a partir del senyal d'un sol sensor poden ser insuficients quan es volen caracteritzar els elements de l'entorn de forma invariant; això es pot millorar combinant informació de múltiples fonts. Es presenta un nou algorisme per la fusió d'informació complementaria extreta de dos mòduls de visió de baix nivell.
Aquesta fusió d'informació produeix descripcions més completes dels objectes de l'entorn, els quals poden ser seguits i apresos dins el context de la robòtica mòbil. Les variacions en les condicions d'il·luminació i les oclusions fan que l'associació de dades en visió per computador sigui una tasca difícil de completar.
Tot i això, l'ús de restriccions geomètriques i fotogramètriques permeten reduir la cerca de correspondències entre imatges successives; i al centrar l'atenció en un reduït nombre de característiques, aquestes poden ser seguides en imatges successives, simplificant així el problema d'associació de dades. Es recalquen les tècniques de la geometria de múltiples vistes que són rellevants pel còmput d'una estimació inicial de la posició dels elements de l'entorn, el que permet la reconstrucció del moviment del robot entre imatges successives; situació desitjable quan no existeix odometria o quan las seves lectures són poc fiables.
Quan els elements de l'entorn s'han extret i identificat, la segona part del problema consisteix en utilitzar aquestes observacions tant per estimar la posició del robot, com per refinar l'estimació dels mateixos elements de l'entorn. El moviment del robot i les lectures dels sensors es consideren com dos processos estocàstics, i el problema es tracta des del punt de vista de la teoria d'estimació, on el soroll inherent als sensors i al moviment del robot es consideren com a seqüències aleatòries.
El principal inconvenient existent en l'ús de tècniques d'estimació pel còmput concurrent de la posició del robot i la construcció d'un mapa, és que fins ara s'ha considerat la seva aplicació únicament en entorns estàtics, i que el seu ús en situacions més realistes ofereix poca robustesa. Es proposa un conjunt de funcions per avaluar la qualitat temporal de les observacions per tal de resoldre les situacions en que les observacions dels elements de l'entorn no siguin consistents en el temps. Es mostra com la utilització d'aquestes proves de qualitat temporal conjuntament amb les proves de compatibilitat espacial milloren els resultats quan es fen servir amb un mètode d'estimació òptima de la construcció concurrent de mapes i l'autolocalització de robots.
La idea principal consisteix en emprar un històric dels errors en l'associació de les dades per calcular la possibilitat d'incórrer en nous errors d'associació; i excloure del mapa aquells elements dels quals les observacions no siguin consistents.
Es posa especial atenció en el fet que l'eliminació dels elements inconsistents del mapa no violi les propietats dels algorismes de construcció concurrent de mapes i autolocalització descrits en la literatura; és a dir, convergència assimptòtica i correlació completa.
Aquesta tesi proporciona també un profund anàlisi del model de construcció concurrent de mapes i autolocalització totalment correlat des d'un punt de vista de la teoria de control de sistemes. Partint del fet que el filtre de Kalman no és més que un estimador òptim, s'analitzen les implicacions de tenir un vector d'estats que es revisa a partir de mesures totalment correladas.
Es revela de manera teòrica i amb experiments les limitacions d'utilitzar un enfocament per la construcció concurrent de mapes i l'autolocalització a partir de mesures totalment correladas.
El fet de tenir un model parcialment observable inhibeix la reconstrucció total de l'espai d'estats, produint tant mateix una estimació de la posició dels elements de l'entorn que depèn en tot cas de les observacions inicials, i que no garanteix la convergència a una matriu de covariància definida positivament.
D'altra banda, el fet de tenir un vector d'estats parcialment controlable fa que, desprès d'un reduït nombre d'iteracions el filtre cregui tenir una estimació perfecta de l'estat dels elements de l'entorn; amb els corresponents guanys de Kalman convergint a zero. Per tant, desprès d'un reduït nombre d'iteracions del filtre, els innovacions no s'utilitzen més. Es mostra com reduir els efectes de la correlació total i de la controlabilitat parcial. A més a més, suposant que el filtre de Kalman és un observador òptim per a la reconstrucció dels estats, és pertinent construir un regulador òptim que permeti conduir el robot el més a prop possible a una trajectòria desitjada durant la construcció d'un mapa. Es mostra com la dualitat existent entre l'observabilitat i la controlabilitat es pot fer servir en el disseny d'aquest regulador òptim.
Qualsevol algorisme de construcció concurrent de mapes i autolocalització de robots mòbils que s'ha d'usar en un entorn real ha de ser capaç de relacionar les observacions i els seus corresponents elements del mapa de manera expedita. Algunes de les proves de compatibilitat de les observacions són costoses des del punt de vista de la seva complexitat computacional, i la seva aplicació s'ha de dissenyar amb especial atenció. Es comenten els costos computacionals de les diferents proves de compatibilitat entre observacions; així com altres característiques desitjables de l'estructura de dades que es fa servir per a la construcció del mapa. A més a més es proposen una sèrie de tasques que han de realitzar-se durant l'associació de dades. Començant per les proves de compatibilitat amb un model bàsic dels elements del mapa, i continuant amb la reducció de l'espai de cerca quan es generen hipòtesis d'associació, així com les proves espacial i temporal d'associació de dades.
El treball que es presenta en aquesta tesi proposa noves tècniques en àrees de l'enginyera i ciències computacionals, que van des de nous algorismes per la visió per computador, a idees novells de la construcció concurrent de mapes i l'autolocalització de robots mòbils. Les contribucions principals són la proposta d'una nova tècnica per la fusió de dades visuals; la formulació d'un nou algorisme per la construcció concurrent de mapes i l'autolocalització de robots que considera la qualitat temporal dels elements del mapa; nous resultats teòrics en el nivell de reconstrucció possible quan es construeixen mapes a partir d'observacions totalment correladas; i les tècniques necessàries per pal·liar els efectes de l'observabilitat i la controlabilitat parcials, així com els efectes de les no linealitats en la solució del problema de construcció concurrent de mapes i de l'autolocalització.
Esta tesis aborda el problema del aprendizaje automático de entornos estructurados en robótica móvil. Particularmente, la extracción de características a partir de las se nales de los censores, la construcción autónoma de mapas, y la autolocalización de robots.
Se estudian los fundamentos matemáticos necesarios para la extracción de características a partir de imágenes y registros de un láser, las cuales permiten la identificación unívoca de los elementos del entorno. Los atributos extraídos a partir de la se nal de un solo sensor pueden ser insuficientes a la hora de caracterizar los elementos del entorno de forma invariante; lo que conlleva a la combinación de información de múltiples fuentes. Se presenta un nuevo algoritmo para la fusión de información complementaria extraída de dos módulos de visión de bajo nivel. Esta fusión de información produce descripciones más completas de los objetos presentes en el entorno, los cuales pueden ser seguidos y aprendidos en el contexto de la robótica móvil.
Las variaciones en las condiciones de iluminación y las oclusiones hacen que la asociación de datos en visión por computador sea una tarea difícil de llevar a cabo. Sin embargo, el uso de restricciones geométricas y fotogramétricas permiten reducir la búsqueda de correspondencias entre imágenes; y al centrar la atención en un reducido número de características, estas pueden ser seguidas en imágenes sucesivas, simplificando así el problema de asociación de datos. Se hace hincapié en las técnicas de la geometría de múltiples vistas relevantes para el cómputo de una estimación inicial de la posición de los elementos del entorno, lo cual permite la reconstrucción del movimiento
del robot entre imágenes sucesivas; situación deseable cuando se carece de odometría o cuando sus lecturas son poco fiables.
Una vez que los elementos del entorno han sido extraídos e identificados, la segunda parte del problema consiste en usar estas observaciones tanto para estimar la posición del robot, como para refinar la estimación de los mismos elementos del entorno. El movimiento del robot y las lecturas de los sensores se consideran como dos procesos estocásticos, y el problema se aborda desde el punto de vista de la teoría de estimación, en donde el ruido inherente a los sensores y al movimiento del robot se consideran como secuencias aleatorias.
La principal desventaja existente en el uso de técnicas de estimación para el cómputo concurrente de la posición del robot y la construcción de un mapa, es que hasta ahora se ha considerado su uso en entornos estáticos únicamente, y que su aplicación en situaciones más realistas carece de robustez.
Se propone un conjunto de funciones para evaluar la calidad temporal de las observaciones con el fin de solventar aquellas situaciones en que las observaciones de los elementos del entorno no sean consistentes en el tiempo.
Se muestra como el uso de estas pruebas de calidad temporal junto con las pruebas de compatibilidad espacial existentes mejora los resultados al usar un método de estimación óptima para la construcción concurrente de mapas y la autolocalización de robots. La idea principal consiste en usar un histórico
de los errores en la asociación de datos para el cómputo de la posibilidad de incurrir en nuevos errores de asociación; y eliminar del mapa aquellos elementos cuyas observaciones no sean consistentes.
Se presta especial atención a que la eliminación de elementos inconsistentes del mapa no viole las propiedades de los algoritmos de construcción concurrente de mapas y autolocalización descritos en la literatura; es decir, convergencia asintótica y correlación completa.
Esta tesis proporciona a su vez un análisis en profundidad del modelo de construcción concurrente de mapas y autolocalización totalmente correlado desde un punto de vista de la teoría de control de sistemas. Partiendo del hecho de que el filtro de Kalman no es otra cosa que un estimador óptimo, se analizan las implicaciones de tener un vector de estados que se revisa a partir de mediciones totalmente correladas. Se revela de forma teórica y con experimentos las limitaciones de usar un enfoque para la construcción concurrente de mapas y autolocalización a partir de mediciones totalmente correladas.
El hecho de tener un modelo parcialmente observable inhibe la reconstrucción total del espacio de estados, produciendo a su vez una estimación de la posición de los elementos del entorno que dependerá en todo caso de las observaciones iniciales, y que no garantiza la convergencia a una matriz de covarianza positivamente definida. Por otro lado, el hecho de tener un vector de estados parcialmente controlable, produce después de un reducido número de iteraciones que el filtro crea tener una estimación perfecta del estado de los elementos del entorno; con sus correspondientes ganancias de Kalman convergiendo a cero. Esto es, después de un peque no número de iteraciones del filtro, las innovaciones no se usan. Se muestra como reducir los efectos de la correlación total y la controlabilidad parcial. Además, dado que el filtro de Kalman es un observador óptimo para la reconstrucción de los estados, es pertinente construir un regulador óptimo que permita conducir al robot lo más cerca posible de una trayectoria deseada durante la construcción de un mapa. Se muestra como la dualidad existente entre la observabilidad y la controlabilidad se puede emplear en el diseño de este regulador óptimo.
Cualquier algoritmo de construcción concurrente de mapas y autolocalización de robots móviles que deba funcionar en un entorno real deberá ser capaz de relacionar las observaciones y sus correspondientes elementos del mapa de manera expedita. Algunas de las pruebas de compatibilidad de las observaciones son caras desde el punto de vista de su complejidad computacional, y su aplicación debe diseñarse con riguroso cuidado. Se comentan los costes computacionales de las distintas pruebas de compatibilidad entre observaciones; así como otras características deseadas de la estructura de datos elegida para la construcción del mapa. Además, se propone una serie de tareas que debe llevarse a cabo durante la asociación de datos. Partiendo por las pruebas de compatibilidad con un modelo básico de los elementos del mapa, y continuando con la reducción del espacio de búsqueda al generar hipótesis de asociación, así como las pruebas espacial y temporal de asociación de datos.
El trabajo que se presenta en esta tesis propone nuevas técnicas en áreas de la ingeniería y las ciencias computacionales, que van desde nuevos algoritmos de visión por computador, a ideas noveles en la construcción concurrente de mapas y la autolocalización de robots móviles. Las contribuciones principales son la propuesta de una nueva técnica para la fusión de datos visuales; la formulación de un nuevo algoritmo para la construcción concurrente de mapas y autolocalización de robots que toma en cuenta la calidad temporal de los elementos del mapa; nuevos resultados teóricos en el grado de reconstrucción posible al construir mapas a partir de observaciones totalmente correladas; y las técnicas necesarias para paliar los efectos de la observabilidad y controlabilidad parciales, así como los efectos de las no linealidades en la solución del problema de construcción concurrente de mapas y autolocalización.
This thesis focuses on the various aspects of autonomous environment learning for indoor service robots. Particularly, on landmark extraction from sensor data, autonomous map building, and robot localization.
To univocally identify landmarks from sensor data, we study several landmark representations, and the mathematical foundation necessary to extract the features that build them from images and laser range data. The features extracted from just one sensor may not suce in the invariant characterization of landmarks and objects, pushing for the combination of information from multiple sources. We present a new algorithm that fuses complementary information from two low level vision modules into coherent object models that can be tracked and learned in a mobile robotics context. Illumination conditions and occlusions are the most prominent artifacts
that hinder data association in computer vision. By using photogrammetric and geometric constraints we restrict the search for landmark matches in successive images, and by locking our interest in one or a set of landmarks in the scene, we track those landmarks along successive frames, reducing considerably the data association problem. We concentrate on those tools from the geometry of multiple views that are relevant to the computation of initial landmark location estimates for coarse motion recovery; a desirable characteristic when odometry is not available or is highly unreliable.
Once landmarks are accurately extracted and identied, the second part of the problem is to use these observations for the localization of the robot, as well as the renement of the landmark location estimates. We consider robot motion and sensor observations as stochastic processes, and treat the problem from an estimation theoretic point of view, dealing with noise by using probabilistic methods.
The main drawback we encounter is that current estimation techniques have been devised for static environments, and that they lack robustness in more realistic situations. To aid in those situations in which landmark observations might not be consistent in time, we propose a new set of temporal landmark quality functions, and show how by incorporating these functions in the data association tests, the overall estimation-theoretic approach to map building and localization is improved. The basic idea consists on using the history of data association mismatches for the computation of the likelihood of future data association, together with the spatial compatibility tests already available.
Special attention is paid in that the removal of spurious landmarks from the map does not violate the basic convergence properties of the localization and map building algorithms already described in the literature; namely, asymptotic convergence and full correlation.
The thesis also gives an in depth analysis of the fully correlated model to localization and map building from a control systems theory point of view. Considering the fact that the Kalman .lter is nothing else but an optimal observer, we analyze the implications of having a state vector that is being revised by fully correlated noise measurements. We end up revealing
theoretically and with experiments the strong limitations of using a fully correlated noise driven estimation theoretic approach to map building and localization in relation to the total number of landmarks used.
Partial observability hinders full reconstructibility of the state space, making the .nal map estimate dependant on the initial observations, and does not guarantee convergence to a positive de nite covariance matrix. Partial controllability on the other hand, makes the .lter beleive after a number of iterations, that it has accurate estimates of the landmark states, with their corresponding Kalman gains converging to zero. That is, after a few steps, innovations are useless. We show how to palliate the e.ects of full correlation
and partial controllability. Furthermore, given that the Kalman .lter is an optimal observer for the reconstruction of fully correlated states; it seems pertinent to build an optimal regulator in order to keep the robot as close as possible to a desired motion path when building a map. We show also how the duality between observability and controllability can be exploited in designing such an optimal regulator.
Any map building and localization algorithm for mobile robotics that is to work in real time must be able to relate observations and model matches in an expeditious way. Some of the landmark compatibility tests are computationally expensive, and their application has to be carefully designed. We touch upon the time complexity issues of the various landmark compatibility tests used, and also on the desirable properties of our chosen map data structure.
Furthermore, we propose a series of tasks that must be handled when dealing with landmark data association. From model compatibility tests, to search space reduction and hypothesis formation, to the actual association of observations and models.
The work presented in this thesis spans several areas of engineering and computer science, from new computer vision algorithms, to novel ideas in mobile robot localization and map building. The key contributions are the proposal of a new technique to fuse visual data; the formulation of new algorithms to concurrent localization and map building that take into account temporal landmark quality; new theoretical results on the degree of reconstruction possible when building maps from fully correlated observations; and the necessary techniques to palliate partial observability, partial controllability, and the nonlinear e.ects when solving the simultaneous localization and map building problem.

Robust localization is a prerequisite for mobile robot autonomy. In many situations the GPS signal is not available and thus an additional localization system is required. A simple approach is to apply localization based on dead reckoning by use of wheel encoders but it results in large estimation errors. With exteroceptive sensors such as a laser range finder natural landmarks in the environment of the robot can be extracted from raw range data. Landmarks are extracted with the Hough transform and a recursive line segment algorithm. By applying data association and Kalman filtering along with process models the landmarks can be used in combination with wheel encoders for estimating the global position of the robot. If several robots can cooperate better position estimates are to be expected because robots can be seen as mobile landmarks and one robot can supervise the movement of another. The centralized Kalman filter presented in this master thesis systematically treats robots and extracted landmarks such that benefits from several robots are utilized. Experiments in different indoor environments with two different robots show that long distances can be traveled while the positional uncertainty is kept low. The benefit from cooperating robots in the sense of reduced positional uncertainty is also shown in an experiment.

Except for localization algorithms a typical autonomous robot task in the form of change detection is solved. The change detection method, which requires robust localization, is aimed to be used for surveillance. The implemented algorithm accounts for measurement- and positional uncertainty when determining whether something in the environment has changed. Consecutive true changes as well as sporadic false changes are detected in an illustrative experiment.

In recent years robots have dramatically improved in functionality, but as a result their designs have also become more complicated. The increase in the complexity of the tasks and the design of the robot result in a challenging and time-consuming robot development process. Sophisticated simulation models, expensive hardware setup, and careful human supervisions are necessary to provide a safe and close-to-real world testbed that helps to draw insights to the actual operation. However, the considerable cost and time for creating well-designed tests and for meeting safety requirements present a barrier to rapid development of complex robot systems. This thesis analyses the robot development process and identifies areas for improvement. Based on the requirements analysis, it proposes that, by applying the concept of Mixed Reality (MR) to robot simulation, it is possible to create a realistic, synthetic environment that enables robot developers to experiment freely and safely. The new simulation approach, named MR simulation, offers the flexibility of creating simulation environments composed of real and virtual objects that seamlessly interact with one another. This enables robot developers to mix virtual objects into the real experimental setup for cost and safety reasons. A generic MR framework is proposed that provides the basis for creating MR simulations. The most novel element of the framework is a behaviour based interaction scheme that formalises interactions between real and virtual objects. To validate the framework, a general purpose MR robot simulator is implemented, and it is accompanied by MR interfaces designed to provide users intuitive views of MR simulations. Notably, markerless Augmented Reality (AR) techniques are integrated for real time visualisation. Through three case study evaluations, the use of MR simulations has been demonstrated to produce results that reliably represent the real world. The thesis provides an insight to how MR simulations can help to minimise resource requirements in an industrial application, and enable efficient testing of a prototype aerial robot system. Findings from an initial user study indicate positive acceptance to the technology, while an observational user study identifies a strong contribution of MR simulation to the later stages of robot development.

This thesis project is about the search and secure problem for mobile robots. The search and secure problem refers to the problem where possible moving intruders have to be detected in a given area with obstacles that are represented as polygons. The solution to this problem is given by deploying robots in a proper way so that no intruder can remain undetected or sneak back to a secured area. An intruder is considered detected when he/she is in the field of view of the robots’ on-board cameras. As a first step, in the algorithm that solves the search and secure problem, the area is divided into triangles. The resulting triangles are then merged in order to form convex polygons. The next step is to abstract the actual regions into a topological graph where each polygon is represented by its centroid and the neighboring polygons are connected by edges. At this point, blocking robots are used to break the loops in the graph and prevent the intruders from escaping from the searchers. Then the number of the searchers is determined and their paths are created. Two solutions are proposed, one that requires more searchers but less time and one that requires the minimum number of searchers but more time. The last step is to create the trajectories that the robots have to follow. The functionality and the efficiency of the algorithm is verified through simulations and the results are visualized using Matlab and the AURES simulator and controller. The demonstration that was held at SAAB facilities in Linköping is also described.

We present two different methods based on visual odometry for pose estimation (x, y, Ө) of a robot. The methods proposed are: one appearance based method that computes similarity measures between consecutive images, and one method that computes visual flow of particular features, i.e. spotlights on ceiling. Both techniques are used to correct the pose (x, y, Ө) of the robot, measuring heading change between consecutive images. A simple Kalman filter, extended Kalman filter and simple averaging filter are used to fuse the estimated heading from visual odometry methods with odometry data from wheel encoders. Both techniques are evaluated on three different datasets of images obtained from a warehouse and the results showed that both methods are able to minimize the drift in heading compare to using wheel odometry only.

This thesis presents a possible inexpensive and simple solution for humanitarian demining in developing countries. It consists of a group of mobile robots that can advance and interact collaboratively with each other in a mine field. A base station controls the group and can map their position with the aid of a long range positioning system, thus, identify the landmine position when one is detected by a robot. A short range positioning system is used within the group to measure the distance separating them from one another and the geometry of the formation. A prototype battery powered mobile robot platform has been developed and tested. Electronic hardware and software was designed and built to allow for low level control of the movements of the vehicle and for wireless communications with a base station. The base station exercises high level control over the mobile robot. A positioning system consisting of a long and a short range positioning system has been designed. The short range positioning system, which uses sonic waves within the audible frequency range, has been implemented and tested. Operating within the audible frequency range reduces the sensory system cost and results in an omni-directional range measuring system. The system provides sub-wavelength precision with an absolute error less than 2 cm for distances from 1 m to 4 m at a 5 KHz frequency.

Depuis la fin des années 1980, le développement de véhicules autonomes, capables de rouler sans l'intervention d'un être humain, est un champ de recherche très actif dans la plupart des grands pays industrialisés. La diminution du nombre d'accidents, des temps de trajet plus courts, une meilleure efficacité énergétique et des besoins en infrastructure plus limités, sont autant d'effets socio-économiques espérés de leur déploiement. Des formes de coopération inter-véhicules et entre les véhicules et l'infrastructure routière sont nécessaires au fonctionnement sûr et efficace du système de transport dans sa globalité. Cette thèse s'intéresse à une forme de coopération particulière en étudiant la coordination de robots mobiles aux intersections. La majorité des systèmes de coordination existants planifie une trajectoire que les robots doivent exécuter afin d'assurer l'absence de collision. C'est une approche classique de la planification, qui est alors considérée comme un mécanisme de génération de l'action. Dans cette thèse, seules les priorités entre les véhicules sont planifiées, c'est-à-dire l'ordre relatif de passage des véhicules dans l'intersection, ce qui est bien plus faible car un grand nombre de trajectoires respectent les même priorités. Les priorités sont alors simplement utilisées comme une ressource de coordination pour guider les robots dans l'intersection. Une fois les priorités affectées, les robots suivent une loi de contrôle qui s'assure qu'elles soient bien respectées. Il en découle un système de coordination robuste, capable de gérer toute une classe d'événements imprévisibles de façon réactive, ce qui est particulièrement adapté pour une application à la coordination de véhicules autonomes aux intersections où voitures, transports en commun et piétons partagent la route
Since the end of the 1980's, the development of self-driven autonomous vehicles is an intensive research area in most major industrial countries. Positive socio-economic potential impacts include a decrease of crashes, a reduction of travel times, energy efficiency improvements, and a reduced need of costly physical infrastructure. Some form of vehicle-to-vehicle and/or vehicle-to-infrastructure cooperation is required to ensure a safe and efficient global transportation system. This thesis deals with a particular form of cooperation by studying the problem of coordinating multiple mobile robots at an intersection area. Most of coordination systems proposed in previous work consist of planning a trajectory and to control the robots along the planned trajectory: that is the plan-as-program paradigm where planning is considered as a generative mechanism of action. The approach of the thesis is to plan priorities – the relative order of robots to go through the intersection – which is much weaker as many trajectories respect the same priorities. Then, priorities are merely used as a coordination resource to guide robots through the intersection. Once priorities are assigned, robots are controlled through a control law preserving the assigned priorities. It results in a more robust coordination system – able to handle a large class of unexpected events in a reactive manner – particularly well adapted for an application to the coordination of autonomous vehicles at intersections where cars, public transport and pedestrians share the road

Thèse (M. Ing.)--École de technologie supérieure, Montréal, 2005.
"Thesis presented to École de technologie supérieure as a partial requirement to obtain a masters in electrical engineering". Bibliogr.: f. [140]-142. Également disponible en version électronique.

Ageing infrastructure worldwide requires periodic inspection, often in-situ, in order to ensure continued safe and economic operations as well as adherence to stringent quality and performance requirements. In service automated Nondestructive Evaluation, where feasible, is highly attractive, and potentially allows inspection of operational plant. The use of such technology is very attractive in terms of safety, cost and the potential for minimal disruption to the inspection site especially if plant operations can remain online. Automated Nondestructive Evaluation in the form of remotely operated robotic vehicles is an active area of research. Knowledge of position relative to a frame of reference is a key aspect for a robotic Nondestructive Evaluation system in order to associate sensor measurements with locations on the structure being investigated. This thesis investigates relative and absolute positioning techniques for a single robot. The accuracy and repeatability of a photogra mmetry system is characterised over a large volume using a high accuracy metrology instrument. It was found that the photogrammtery system was most accurate in the centre of the volume and least accurate at the edges. This photogrammetry system is then used to evaluate the performance of algorithms developed in subsequent research. An image based positioning system is implemented which extracts motion information from a camera carried onboard a robot. The system is evaluated on surfaces typically found in industrial environments. Ultrasonic ranging techniques are investigated for robot positioning. In particular a low cost, modular, ultrasonic positioning system is characterised and calibrated. Bayesian filtering in the form of an Extended Kalman and Particle Filter are implemented to fuse noisy optical encoders estimates available at 100 Hz and the ultrasonic positioning measurements available at 3 Hz. The extended Kalman Filter, at lower computational cost, was found to produce the lowest error.

Cette thèse présente un nouveau concept de robots parallèles à câble mobile (RPCM) comme un nouveau système robotique. RPCM est composé d'un robot parallèle à câble (RPC) classique monté sur plusieurs bases mobiles. Les RPCMs combinent l'autonomie des robots mobiles avec les avantages des RPCs, à savoir un grand espace de travail, un rapport charge utile/poids élevé, une faible inertie de l'effecteur final, une capacité de déploiement et une reconfigurabilité. De plus, les RPCMs présentent une nouvelle innovation technique qui pourrait contribuer à apporter plus de flexibilité et de polyvalence par rapport aux solutions robotiques industrielles existantes. Deux prototypes de RPCMs appelés FASTKIT et MoPICK ont été développés au cours de cette thèse. FASTKIT est composé de deux bases mobiles portant une plate-forme mobile à six degrés de liberté, tirée par huit câbles, dans le but de fournir une solution robotique économique et polyvalente pour la logistique. MoPICK est composé d'une plate-forme mobile à trois degrés de liberté tirée par quatre câbles montés sur quatre bases mobiles. Les applications ciblées de MoPICK sont des tâches mobiles dans un environnement contraint, par exemple un atelier ou des opérations logistiques dans un entrepôt. Les contributions de cette thèse sont les suivantes. Tout d'abord, toutes les conditions nécessaires à l'atteinte de l'équilibre statique d'un RPCM sont étudiées. Ces conditions sont utilisées pour développer un algorithme de distribution de tension pour le contrôle en temps réel des câbles RPCM. Les conditions d'équilibre sont également utilisées pour étudier l'espace de travail clé en main des RPCMs. Ensuite, les performances cinématiques et les capacités de torsion des RPCMs sont étudiées. Enfin, la dernière partie de la thèse présente des stratégies de planification de trajectoires multiples pour les RPCMs afin de reconfigurer l'architecture géométrique du RPC pour réaliser la tâche souhaitée
This thesis presents a novel concept of Mobile Cable - Driven Parallel Robots (MCDPRs) as a new robotic system. MCDPR is composed of a classical C able - D riven P a rallel R obot (CDPR) mounted on multiple mobile bases. MCDPRs combines the autonomy of mobile robots with the advantages of CDPRs, namely, large workspace, high payload - to - weight ratio, low end - effector inertia, deployability and reconfigurability. Moreover , MCDPRs presents a new technical innovation that could help to bring more flexibility and versatility with respect to existing industrial robotic solutions. Two MCDPRs prototypes named FASTKIT and MoPICK have been developed during the course of this the sis. FASTKIT is composed of two mobile bases carrying a six degrees - of - freedom moving - platform, pulled by eight cables , with a goal to provide a low cost and versatile robotic solution for logistics. MoPICK is composed of a three degrees - of - freedom movi ng - platform pulled by four cables mounted on four mobile bases. The targeted applications of MoPICK are mobile tasks in a constrained environment, for example, a workshop or logistic operations in a warehouse. The contributions of this thesis are as follow s. Firstly, all the necessary conditions are studied that required to achieve the static equilibrium of a MCDPR . These conditions are used to develop a Tension Distribution Algorithm for the real time control of the MCDRP cables. The equilibrium conditions are also used to investigate the Wrench - Feasible - Workspace of MCDPRs. Afterwards, the kinematic performance and twist capabilities of the MCDPRs are investigated. Finally, the last part of the thesis presents multiple path planning strategies for MCDPRs i n order to reconfigure the CDPR’s geometric architecture for performing the desired task

This thesis describes the implementation of a hierarchical robot simulation environment which supports the design of robots with vision and mobility. A seeing robot model applies a classification expert system for visual identification of laboratory objects. The visual data acquisition algorithm used by the robot vision system has been developed to exploit multiple viewing distances and perspectives. Several different simulations have been run testing the visual logic in a laboratory environment. Much work remains to integrate the vision system with the rest of the robot system.

Cette thèse contribue à l'analyse des raideurs statique et dynamique des robots parallèles à câbles dans un objectif d'amélioration de la précision de positionnement statique et de la précision de suivi de trajectoire. Les modélisations statique et dynamique proposées des câbles considèrent l'effet du poids du câble sur son profil et l'effet de masse du câble sur la dynamique de ce dernier. Sur la base du modèle statique de câble proposé, l'erreur de pose statique au niveau de l'organe terminal du robot est définie et sa variation en fonction de la charge externe appliquée est utilisée pour évaluer la raideur statique globale de la structure. Un nouveau modèle dynamique vibratoire de robots à câbles est proposé en considérant le couplage de la dynamique des câbles avec les vibrations de l'organe terminal. Des validations expérimentales sont réalisées sur des prototypes de robots à câbles. Une série d'expériences de statique, d'analyses modales, d'analyses en régime libre et de suivi de trajectoire sont réalisées. Les modèles statiques et dynamiques proposés sont confirmés. Les dynamiques des câbles et du robot ainsi que leur couplage sont discutées montrant la pertinence des modèles développés pour l’amélioration des performances des robots à câbles en termes de design et le contrôle. Outre l'analyse des raideurs statique et dynamique, les modèles proposés sont appliqués dans l'amélioration du calcul de la distribution des efforts dans les câbles des robots redondants. Une nouvelle méthode de calcul de la distribution des efforts dans les câbles basée sur la détermination de la limite inférieure des forces dans les câbles est présentée. La prise en compte de la dépendance à la position dans l'espace de travail permet de limiter les efforts dans les câbles et ainsi d'améliorer l'efficience des robots d'un point de vue énergétique
This thesis contributes to the analysis of the static and dynamic stiffness of cable-driven parallel robots (CDPRs) aiming to improve the static positioning accuracy and the trajectory tracking accuracy. The proposed static and dynamic cable modeling considers the effect of cable weight on the cable profile and the effect of cable mass on the cable dynamics. Based on the static cable model, the static pose error of the end-effector is defined and the variation of the end-effector pose error with the external load is used to evaluate the static stiffness of CDPRs. A new dynamic model of CDPRs is proposed with considering the coupling of the cable dynamics and the end-effector vibrations. Experimental validations are carried out on CDPR prototypes. Static experiments, modal experiments, free vibration experiments and trajectory experiments are performed. The proposed static and dynamic models are verified. Cable dynamics, robot dynamics and their coupling are discussed. Results show the relevance of the proposed models on improving the performances of CDPRs in terms of design and control. Besides stiffness analysis, the proposed models are applied on the force distribution of redundant actuated CDPRs. A new method on the calculation of the cable forces is proposed, where the determination of the lower-boundary of the cable forces is presented. The consideration of the pose-dependence of the lower force boundary can minimize the cable forces and improve the energy efficiency of CDPRs

Thesis (Ph. D.)--University of Missouri-Columbia, 2007.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on September 19, 2007) Vita. Includes bibliographical references.

This master’s thesis describes a sensorial subsystem of a mobile robot. The thesis mentions the structure and a basis of the satellite navigation. There are also described each systems and visualization techniques as e. g. WGS 84, including also other systems for specification of more accurate position on the Earth (EGNOS, WAAS and others). This thesis describes closely also a differential GPS and the corrections. For the purposes of the thesis there has been assembled GPS software for a fundamental and a remote station. There have been chosen and used modules for receiving a GPS signal and wireless modules for their communication. There are also used outcomes from the project of the Open Street Map in the thesis. Results of this project are described in details, decoded, adjusted and converted into RNDF file. At the end of this thesis there has been composed a function of the program for portable camera which works on principle time of flight. This portable camera is dedicated to look for immediate barrier and also for 3D space view in front of the robot. This thesis also including the process how the power source has been built up for this portable scanner.

Tot i que apareixen noves tècniques que equipen els robots amb capacitats cognitives avançades, encara s'ha dedicat poca feina a una qüestió essencial per aquestes tècniques: mètodes ràpids i robustos per a la percepció d'elements semànticament rellevants en entorns no estructurats. De fet, per un robot, ser capaç d'identificar la ubicació en que es troba i quins objectes té al voltant constitueix els fonaments sobre els quals s'aguanten la resta de processos de raonament d'alt nivell que ha de dur a terme. Amb l'objectiu de reduir una mica aquest problema, aquesta tesi se centra en els problemes de localització i reconeixement d'objectes per mitjà de tècniques de visió per computador. La primera contribució que presentem és una nova tècnica per construir signatures de llocs a partir de caracter ́ıstiques detectades en imatges panoràmiques per a ser usades com a nodes d'un mapa topològic, i un mètode de "homing" per viatjar entre els nodes del mapa. Ambdós mètodes han estat provats en diversos conjunts de proves amb resultats satisfactoris. El reconeixement d'objectes genèrics per robots mòbils és un tema d'importància cabdal de cara a afegir contingut a les representacions de l'entorn que els robots usaran en els seus processos de raonament. En conseqüència, les següents contribucions d'aquesta tesi es dirigeixen a aquest problema. Després de revisar detingudament literatura recent del camp de visió per computador, han estat seleccionats dos mètodes: el mètode de reconeixement d'objectes "SIFT" i el "Vocabulary Tree". Un cop avaluats els dos mètodes en conjunts de dades de test dif ́ıcils, centrades en els aspectes rellevants per als robots mòbils, es va concloure que, tot i que el mètode SIFT era més adeqüat per aquests, ambdós mètodes tenien propietats complementàries. Per aprofitar aquesta complementarietat, la contribució final d'aquesta tesi és un mètode d'aprenentatge per reforç per seleccionar, durant l'aplicació del procés de reconeixment d'objectes, quin dels dos mètodes és el més adequat basant-se únicament en caracter ́ıstiques de la imatge simples de calcular. Aquest mètode ha estat validat en un complex conjunt de proves de reconeixement d'objectes, fins i tot ha superat els resultats d'un expert humà en alguns casos.
Although new approaches to enable robots with advanced cognitive capabilities are being developed, still few work is being devoted to a difficult problem in which all this techniques rely: fast and robust perception methods to detect semantically relevant elements in unstructured environments. Indeed, being able to identify the robot's location and what objects lie around constitute the foundations on which almost all high-level reasoning processes conducted by a robot will build up. In order to help reduce this gap, this work addresses the problems of vision-based global localization and object recognition. The first contributions presented are a new technique to construct signatures of places to be used as nodes of a topological map from constellations of features detected in panoramic images, and a homing method to travel between such nodes that does not rely in artificial landmarks. Both methods were tested with several datasets showing very good results. General object recognition in mobile robots is of primary importance in order to enhance the representation of the environment that robots will use for their reasoning processes. Therefore, the next contributions of the thesis address this problem. After carefully reviewing recent Computer Vision literature on this topic, two state of the art object recognition methods were selected: The SIFT object Recognition method and the Vocabulary Tree method. After evaluating both methods in challenging datasets, focusing on issues relevant to mobile robotics, it was found that, although the SIFT method was more suited for mobile robotics, both had complementary properties.To take advantage of this complementarity, the final contribution of this thesis is a Reinforcement Learning method to select online which object recognition method is best for an input image based on simple to compute image features. This method has been validated in a challenging object recognition experiment, even improving the performance of a human expert in some cases.
Keywords: Mobile Robotics; Vision-based localization; Object recognition; Visual Feature Detectors; Visual Feature Descriptors; Reinforcement Learning; Visual Homing

Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2007.
Magnus Egerstedt, Committee Chair ; Patricio Vela, Committee Member ; Ayanna Howard, Committee Member ; Tucker Balch, Committee Member ; Wayne Book, Committee Member.

The major problem of robotics research today is that there is a barrier to entry into robotics research. Robot system software is complex and a researcher that wishes to concentrate on one particular problem often needs to learn about details, dependencies and intricacies of the complete system. This is because a robot system needs several different modules that need to communicate and execute in parallel.

Today there is not much controlled comparisons of algorithms and solutions for a given task, which is the standard scientific method of other sciences. There is also very little sharing between groups and projects, requiring code to be written from scratch over and over again.

This thesis proposes a general framework for robotics. By examining successful systems and architectures of past and present, yields a number of key properties. Some of these are ease of use, modularity, portability and efficiency. Even though there is much consensus on that the hybrid deliberate/reactive is the best architectural model that the community has produced so far, a framework should not stipulate a specific architecture. Instead the framework should enable the building of different architectures. Such a scheme implies that the modules are seen as common peers and not divided into clients and servers or forced into a set layering.

Using a standardized middleware such as CORBA, efficient communication can be carried out between different platforms and languages. Middleware also provides network transparency which is valuable in distributed systems. Component-based Software Engineering (CBSE) is an approach that could solve many of the aforementioned problems. It enforces modularity which helps to manage complexity. Components can be developed in isolation, since algorithms are encapsulated in components where only the interfaces need to be known by other users. A complete system can be created by assembling components from different sources.

Comparisons and sharing can greatly benefit from CBSE. A component-based framework called ORCA has been implemented with the following characteristics. All communication is carried out be either of three communication patterns, query, send and push. Communication is done using CORBA, although most of the CORBA code is hidden for the developer and can in the future be replaced by other mechanisms. Objects are transported between components in the form of the CORBA valuetype.

A component model is specified that among other things include support for a state-machine. This also handles initialization and sets up communication. Configuration is achieved by the presence of an XML-file per component. A hardware abstraction scheme is specified that basically route the communication patterns right down to the hardware level.

The framework has been verified by the implementation of a number of working systems.

Mobile robots have found numerous applications in recent years, in areas such as consumer robotics, environmental monitoring, security and transportation. For information dissemination, multi-robot cooperation or operator intervention, reliable communications are important. The combination of communication constraints with other requirements in robotics, such as navigation and obstacle avoidance is called communication-aware motion planning. To facilitate integration, communication-aware methods should fit into traditional layered architectures of motion planning. This thesis contains two main contributions, applicable to such an architecture. The first contribution is to develop strategies for exploiting multipath fading while following a reference trajectory. By deviating from the reference, a robot can stop and communicate at positions with high signal strength, trading tracking performance for link quality. We formulate this problem in three different ways: First we maximize the link quality, subject to deterministic bounds on the tracking error. We control the velocity based on the position and channel quality. Second, we consider probabilistic tracking error bounds and develop a cascaded control architecture that performs time-triggered stopping while regulating the tracking error. Third, we formulate a hybrid optimal control problem, switching between standing still to communicate and driving to improve tracking. The resulting channel quality is analyzed and we perform extensive experiments to validate the communication model and compare the proposed methods to the nominal case of driving at constant velocity. The results show good agreement with the model and improvements of over 100% in the throughput when the channel quality is low. The second contribution is to plan velocities for a group of N robots, moving along pre-determined paths through an obstacle field. Robots can only communicate if they have an unobstructed line of sight, and the problem is to maintain connectivity while traversing the paths. This is mapped to motion planning in an N-dimensional configuration space. We propose and investigate two solutions, using a rapidly exploring random tree (RRT) and an exact method inspired by cell decomposition. The RRT method scales better with the problem size than the exact method, which has a worst-case time complexity that is exponential in the number of obstacles. But the randomization in the RRT method makes it difficult to set a timeout for the solver, which runs forever if a problem instance is unsolvable. The exact method, on the other hand, detects unsolvable problem instances in finite time. The thesis demonstrates, both in theory and experiments, that mobile robots can improve communications by planning trajectories that maintain visual connectivity, or by exploiting multipath fading when there is no line of sight. The proposed methods are well suited for integration in a layered motion planning architecture.
QC 20120117

With an increasing need for greater traffic safety, there is an increasing demand for means by which solutions to the traffic safety problem can be studied. The purpose of this thesis is to investigate the feasibility of using an autonomous indoor navigation system as a component in a demonstration system for studying cooperative vehicular scenarios. Our method involves developing and evaluating such a navigation system. Our navigation system uses a pre-existing localization system based on passive RFID, odometry and a particle filter. The localization system is used to estimate the robot pose, which is used to calculate a trajectory to the goal. A control system with a feedback loop is used to control the robot actuators and to drive the robot to the goal.   The results of our evaluation tests show that the system generally fulfills the performance requirements stated for the tests. There is however some uncertainty about the consistency of its performance. Results did not indicate that this was caused by the choice of localization techniques. The conclusion is that an autonomous navigation system using the aforementioned localization techniques is plausible for use in a demonstration system. However, we suggest that the system is further tested and evaluated before it is used with applications where accuracy is prioritized.

Mobile robots, either autonomous or tele-operated have the potential of assisting humans in various situations such as during natural disasters, Urban Search and Rescue (USAR) efforts, and in Explosive Ordinance Disposal (EOD). These robots need steady wireless connectivity with their base station for control and communication. On one hand, the wireless link has to be managed to maintain a stable high quality network connection. On other hand, wireless connection should be continuously monitored to foresee network failure or inadequate link quality situations caused by entering access with low signal strength. This thesis focus on the later where we aim to address the prediction of wireless network connectivity for mobile robots. To indicate wireless connection quality, we use the Radio Signal Strength (RSS) parameter which is readily available by most wireless devices, and it has been frequently used in the literature to indicate wireless connection quality as the RSS have direct relation to the network throughput. Thus the focus of this thesis is to predict the RSS in future robot positions with reference to the current position of the robot. The solution is not straight forward because of the challenging nature of the radio signal propagation which involves complex phenomena such as path loss, shadowing and multipath fading. The RSS prediction method designed in this thesis has two stages. In the first stage, we estimate the location of radio signal source using an RSS gradient-based approach that can work in both single and multiple receivers arrangements. This information will be applied in the next prediction stage. For RSS prediction, we make use of Gaussian Process Regression (GPR) due to non-parametric nature, robustness to noise in the RSS data and changes in the environment. We validate our design with extensive experiments conducted using different types of mobile robots and wireless devices in indoor and outdoor environments, and under line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. We are able to achieve results with source localization error of up to 2 meters for indoor and 5 meters for outdoor environment. In terms of RSS prediction, we obtain the mean absolute prediction error of less than 5 dBm on average, for prediction within 5 meters in indoor environment and 20 meters in outdoor environment. The work is not only promising in terms of prediction time and accuracy but also outperform the state-of-the-art (SOTA) methods including the GPR algorithm, the Kriging interpolation method and the linear regression approaches.

Thesis (M.S.)--Missouri University of Science and Technology, 2008.
Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed April 14, 2008) Includes bibliographical references (p. 119-121).