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Agradecemos a compreensão. on 2017-10-31T19:32:41Z (GMT) / Submitted by LEANDRO JORGE DE OLIVEIRA LINO null (leandro@linoadvocacia.com.br) on 2017-10-31T19:55:36Z No. of bitstreams: 1 LEANDRO JORGE DE OLIVEIRA LINO final.pdf: 6431885 bytes, checksum: 0fb0c0bcbfe43eb0c1d404555b6e1d66 (MD5) / Approved for entry into archive by LUIZA DE MENEZES ROMANETTO (luizamenezes@reitoria.unesp.br) on 2017-11-08T17:55:13Z (GMT) No. of bitstreams: 1 lino_ljo_me_fran.pdf: 6431885 bytes, checksum: 0fb0c0bcbfe43eb0c1d404555b6e1d66 (MD5) / Made available in DSpace on 2017-11-08T17:55:13Z (GMT). No. of bitstreams: 1 lino_ljo_me_fran.pdf: 6431885 bytes, checksum: 0fb0c0bcbfe43eb0c1d404555b6e1d66 (MD5) Previous issue date: 2017-10-11 / De acordo com o censo realizado pelo Instituto Brasileiro de Geografia e Estatística em 2010, identificou-se que 18,8% da população nacional são pessoas com alguma espécie de deficiência visual. Ante a esse expressivo número, figura-se ser importante para o mundo jurídico a análise do conceito de pessoa com deficiência visual e suas modificações ao longo do tempo, principalmente, quando, na práxis forense e administrativa previdenciária, observa-se a segregação de pessoas detentoras de deficiência visual monocular deste conceito jurídico. Há também ainda, a interpretação de legislações vigentes, que ainda trazem um conceito superado do que se considera pessoa com deficiência. Para conceituá-la, inicialmente, se utilizou o modelo exclusivamente médico lastreado em limitações físicas; passo seguinte se adotou o modelo social, cujo enfoque era a opressão social sofrida pelas pessoas com deficiência; e, atualmente, o modelo utilizado é o biopsicossocial, analisando-se a pessoa com deficiência por intermédio de perícia médica e social, conjugando a análise dos impedimentos corpóreos de longo prazo, frente às barreiras sociais, ambientais e atitudinais existentes. Para as legislações que usam o modelo médico restritivamente, o possuidor de visão monocular não se enquadra no conceito de pessoa com deficiência. Contudo, por todos os modelos, o médico, social ou biopsicossocial, é possível se considerar a pessoa com visão monocular como pessoa com deficiência visual. Nesse contexto, e com iguais propósitos, tem-se que analisar o conceito jurídico-constitucional da pessoa com deficiência visual, para fins de reconhecimento do direito ao gozo da aposentadoria especial nesta condição, aos possuidores de visão monocular. Apesar de serem possuidores de Cegueira ou Deficiência Visual Grave ou Moderada por critérios médicos, têm sido excluídas do acesso a vários direitos, inclusive desta espécie de aposentadoria, vez que, regra geral em termos legais expressos, não são considerados pessoas com deficiência visual. O objetivo deste trabalho, portanto, é analisar a evolução desses modelos e aferir o grau de proteção social hoje conferido à pessoa com deficiência visual, em especial no caso da visão monocular, principalmente no que concernente à concessão de aposentadoria especial da pessoa com deficiência. / According to the census done by Brazilian Institute of Geography and Statistics in 2010, was identified that 18.8% of the national population are persons with, at least, one kind of visual impairment. Before this expressive number, ifigures out that, it has been important to the legal word, the concept analisys of a person with visual impairment and its modifications along the time, specially, when, in the forensic and administrative social security praxis, it is noted a segregation of detaining persons with monocular vison deficiency at this legal concept. There is even, a legislation in force version, that it is still giving a concept surpassed of what, at the beginning, was used as an exclusively backed medical model considering the person with visual impairment. To concept it, the physical limitations; the next step is adopted a social model, whose approach was based in the social oppression suffered by the persons with deficiency; and, actually, this used model is the biopsychosocial, analysing the person with this disable throughout the social and medical expertise, joining the longterm bodily impediments analisys, facing the social, environmental and existing attitudinal barriers. For the legilations that use a restrict medical model, the monocular vision possessor does not fit as a person with deficiency. However, for all the kinds of models, like medical, social or biopsychosocial, it is possible to consider a person with monocular vison as one with visual impairment. In this context, and with same purposes, there is a way to analyse the conditions of a visual impairment person and the monocular vison possessor legal-constitutional concept, to recognize the rights of a special retirement enjoyment. In spite of being Severe or Moderate Vision or Blindness possessor by medical criteria, it has been excluded of many right accesses, including this kind of retirement, once that, the general rules, in expressive legal therms, are not considered persons with visual impairment. The purpose of this research is, therefore, to analyse these models evolution and to assess the degree of social protection to a person with visual impairment nowadays, in a special case, the monocular vision one, mainly in relation to the granting of special retirement of the disabled person.

Made available in DSpace on 2014-12-17T14:54:56Z (GMT). No. of bitstreams: 1 AndreMS_TESE_1-100.pdf: 5113772 bytes, checksum: 19386f80f787c926c4fb29b85bac4ecf (MD5) Previous issue date: 2011-02-11 / The goal of this work is to propose a SLAM (Simultaneous Localization and Mapping) solution based on Extended Kalman Filter (EKF) in order to make possible a robot navigates along the environment using information from odometry and pre-existing lines on the floor. Initially, a segmentation step is necessary to classify parts of the image in floor or non floor . Then the image processing identifies floor lines and the parameters of these lines are mapped to world using a homography matrix. Finally, the identified lines are used in SLAM as landmarks in order to build a feature map. In parallel, using the corrected robot pose, the uncertainty about the pose and also the part non floor of the image, it is possible to build an occupancy grid map and generate a metric map with the obstacle s description. A greater autonomy for the robot is attained by using the two types of obtained map (the metric map and the features map). Thus, it is possible to run path planning tasks in parallel with localization and mapping. Practical results are presented to validate the proposal / O objetivo desta tese ? apresentar uma t?cnica de SLAM (Localiza??o e Mapeamento Simult?neos) adequada para ambientes planos com linhas presentes no ch?o, de modo a permitir que o rob? navegue no ambiente fundindo informa??es de odometria e de vis?o monocular. Inicialmente, ? feita uma etapa de segmenta??o para classificar as partes da imagem em ch?o e n?o-ch?o . Em seguida, o processadomento de imagem identifica linhas na parte ch?o e os par?metros dessas linhas s?o mapeados para o mundo, usando uma matriz de homografia. Finalmente, as linhas identificadas s?o usadas como marcos no SLAM, para construir um mapa de caracter?sticas. Em paralelo, a pose corrigida do rob?, a incerteza em rela??o ? pose e a parte n?och?o da imagem s?o usadas para construir uma grade de ocupa??o, gerando um mapa m?trico com descri??o dos obst?culos. A utiliza??o simult?nea dos dois tipos de mapa obtidos (m?trico em grade e de caracter?sticas) d? maior autonomia ao rob?, permitindo acrescentar tarefas de planejamento em simult?neo com a localiza??o e mapeamento. Resultados pr?ticos s?o apresentados para validar a proposta

I nuläget finns det begränsat med forskning hur det går för de personer som opererar bort ett öga. Detta kan medföra att ögonsjuksköterskan ger otillräcklig information till patient och anhöriga i samband med att det är aktuellt att bära protes. Därför var det av intresse att undersöka den synrelaterade livskvaliteten hos personer som genomgått en ögonamputation. Syftet var att belysa synrelaterad livskvalitet hos personer som genomgått en ögonamputation och har en ögonprotes. Studien är en tvärsnittsstudie med deskriptiv design. Datainsamlingen omfattade frågeformuläret NEI-VFQ-25 med tilläggsfrågor, där deltagarna var vuxna personer som genomgått en ögonamputation de senaste fem åren. Resultatet visade att deltagarna hade lägre synrelaterad livskvalitet än personer i kontrollgruppen från H70-studien 2014/2015 med och utan påverkan på synförmågan. Mest besvär hade deltagarna med sidoseende och aktiviteter både på nära och långt håll. Resultatet av studien kan ge ögonsjuksköterskan fördjupad kunskap som kan användas i personcentrerad vård som stöd för att uppmuntra personen som genomgått en ögon amputation och att på bästa sätt hantera sin nya livssituation. Forskning omfattande synrelaterad livskvalitet hos samtliga vuxna personer i Sverige som genomgått en ögonamputation och har ögonprotes vore av intresse, eftersom resultatet baseras på en grupp patienter vid en ögonklinik. / At the moment there is little research about the outcome of people who have had an eye surgically removed. This may result in an ophthalmic nurse giving insufficient information to patients and relatives. Therefore, it would be interesting to investigate the vision related quality of life in relation to the eyesight of persons who have undergone an eye amputation. The purpose was to illustrate the vision related quality of life of people who have been subject to an eye amputation and have an eye prothesis. The study is a cross-sectional study with a descriptive design. The data collection was conducted using the questionnaire NEI-VFQ-25 together with supplementary questions which was sent to adults who have undergone an eye amputation in the last five years. The results showed that eye amputees had lower vision-related quality of life than participants in a control group from the H70 study 2014/2015 with and without visual symptoms. The biggest inconvenience for the participants was peripheral vision and both near activities and distance activities. The results of the study can provide the ophthalmic nurse with a deeper knowledge to be used working with personcentered care and provide thourough information to support persons how has went through an eye amputation to manage their new life situation. Further research on eye amputees vision-related quality of life nationally is needed because the result is based on a limited study group.

Orientador: Juliana Presotto Pereira Netto / Resumo: De acordo com o censo realizado pelo Instituto Brasileiro de Geografia e Estatística em 2010, identificou-se que 18,8% da população nacional são pessoas com alguma espécie de deficiência visual. Ante a esse expressivo número, figura-se ser importante para o mundo jurídico a análise do conceito de pessoa com deficiência visual e suas modificações ao longo do tempo, principalmente, quando, na práxis forense e administrativa previdenciária, observa-se a segregação de pessoas detentoras de deficiência visual monocular deste conceito jurídico. Há também ainda, a interpretação de legislações vigentes, que ainda trazem um conceito superado do que se considera pessoa com deficiência. Para conceituá-la, inicialmente, se utilizou o modelo exclusivamente médico lastreado em limitações físicas; passo seguinte se adotou o modelo social, cujo enfoque era a opressão social sofrida pelas pessoas com deficiência; e, atualmente, o modelo utilizado é o biopsicossocial, analisando-se a pessoa com deficiência por intermédio de perícia médica e social, conjugando a análise dos impedimentos corpóreos de longo prazo, frente às barreiras sociais, ambientais e atitudinais existentes. Para as legislações que usam o modelo médico restritivamente, o possuidor de visão monocular não se enquadra no conceito de pessoa com deficiência. Contudo, por todos os modelos, o médico, social ou biopsicossocial, é possível se considerar a pessoa com visão monocular como pessoa com deficiência visual. Nesse contexto, e... (Resumo completo, clicar acesso eletrônico abaixo) / Mestre

Tracking a moving object and reconstructing its trajectory can be done with a stereo camera system, since the two cameras enable depth vision. However, such a system would not work if one of the cameras fails to detect the object. If that happens, it would be beneficial if the system could still use the functioning camera to make an approximate trajectory reconstruction. In this study, I have investigated how past observations from a stereo system can be used to recreate trajectories when video from only one of the cameras is available. Several approaches have been implemented and tested, with varying results. The best method was found to be a nearest neighbors-search optimized by a Kalman filter. On a test set with 10000 golf shots, the algorithm was able to create estimations which on average differed around 3.5 meters from the correct trajectory, with better results for trajec-tories originating close to the camera. / Att spåra ett objekt i rörelse och rekonstruera dess bana kan göras med ett stereokamerasystem, eftersom de två kamerorna möjliggör djupseende. Ett sådant system skulle dock inte fungera om en av kamerorna misslyckas med att detektera objektet. Om det händer skulle det vara fördelaktigt om systemet ändå kunde använda den fungerande kameran för att göra en approximativ rekonstruktion av banan. I den här studien har jag undersökt hur tidigare observationer från ett stereosystem kan användas för att rekonstruera banor när video från enbart en av kamerorna är tillgänglig. Ett flertal metoder har implementerats och testats, med varierande resultat. Den bästa metoden visade sig vara en närmaste-grannar-sökning optimerad med ett Kalman-filter. På en testmängd bestående av 10000 golfslag kunde algoritmen skapa uppskattningar som i genomsnitt skiljde sig 3.5 meter från den korrekta banan, med bättre resultat för banor som startat nära kameran.

Indiana University-Purdue University Indianapolis (IUPUI) / Simultaneous localization and mapping (SLAM) is a general device localization technique that uses realtime sensor measurements to develop a virtualization of the sensor's environment while also using this growing virtualization to determine the position and orientation of the sensor. This is useful for augmented reality (AR), in which a user looks through a head-mounted display (HMD) or viewfinder to see virtual components integrated into the real world. Visual SLAM (i.e., SLAM in which the sensor is an optical camera) is used in AR to determine the exact device/headset movement so that the virtual components can be accurately redrawn to the screen, matching the perceived motion of the world around the user as the user moves the device/headset. However, many potential AR applications may need access to more than device localization data in order to be useful; they may need to leverage environment data as well. Additionally, most SLAM solutions make the naive assumption that the environment surrounding the system is completely static (non-moving). Given these circumstances, it is clear that AR may benefit substantially from utilizing a SLAM solution that detects objects that move in the scene and ultimately provides localization data for each of these objects. This problem is known as the dynamic SLAM problem. Current attempts to address the dynamic SLAM problem often use machine learning to develop models that identify the parts of the camera image that belong to one of many classes of potentially-moving objects. The limitation with these approaches is that it is impractical to train models to identify every possible object that moves; additionally, some potentially-moving objects may be static in the scene, which these approaches often do not account for. Some other attempts to address the dynamic SLAM problem also localize the moving objects they detect, but these systems almost always rely on depth sensors or stereo camera configurations, which have significant limitations in real-world use cases. This dissertation presents a novel approach for registering and localizing unknown moving objects in the context of markerless, monocular, keyframe-based SLAM with no required prior information about object structure, appearance, or existence. This work also details a novel deep learning solution for determining SLAM map initialization suitability in structure-from-motion-based initialization approaches. This dissertation goes on to validate these approaches by implementing them in a markerless, monocular SLAM system called LUMO-SLAM, which is built from the ground up to demonstrate this approach to unknown moving object registration and localization. Results are collected for the LUMO-SLAM system, which address the accuracy of its camera localization estimates, the accuracy of its moving object localization estimates, and the consistency with which it registers moving objects in the scene. These results show that this solution to the dynamic SLAM problem, though it does not act as a practical solution for all use cases, has an ability to accurately register and localize unknown moving objects in such a way that makes it useful for some applications of AR without thwarting the system's ability to also perform accurate camera localization.

Les petit drones à voilure fixe rendent services aux secteurs de la recherche, de l'armée et de l'industrie, mais souffrent toujours de portée et de charge utile limitées. Le vol thermique permet de réduire la consommation d'énergie. Cependant,sans télédétection d'ascendances, un drone ne peut bénéficier d'une ascendance qu'en la rencontrant par hasard. Dans cette thèse, un nouveau cadre pour le vol à voile longue distance autonome est élaboré, permettant à un drone planeur de localiser visuellement des ascendances sous-cumulus et d’en récolter l'énergie de manière efficace. S'appuyant sur le filtre de Kalman non parfumé, une méthode de vision monoculaire est établie pour l'estimation des paramètres d’ascendances. Sa capacité de fournir des estimations convergentes et cohérentes est évaluée par des simulations Monte Carlo. Les incertitudes de modèle, le bruit de traitement de l'image et les trajectoires de l'observateur peuvent dégrader ces estimés. Par conséquent, un deuxième axe de cette thèse est la conception d'un planificateur de trajectoire robuste basé sur des cartes d'ascendances. Le planificateur fait le compromis entre le temps de vol et le risque d’un atterrissage forcé dans les champs tout en tenant compte des incertitudes d'estimation dans le processus de prise de décision. Il est illustré que la charge de calcul du planificateur de trajectoire proposé est réalisable sur une plate-forme informatique peu coûteuse. Les algorithmes proposés d’estimation ainsi que de planification sont évalués conjointement dans un simulateur de vol à 6 axes, mettant en évidence des améliorations significatives par rapport aux vols à voile longue distance autonomes actuels. / Small fixed-wing Unmanned Aerial Vehicles (UAVs) provide utility to research, military, and industrial sectors at comparablyreasonable cost, but still suffer from both limited operational ranges and payload capacities. Thermal soaring flight for UAVsoffers a significant potential to reduce the energy consumption. However, without remote sensing of updrafts, a glider UAVcan only benefit from an updraft when encountering it by chance. In this thesis, a new framework for autonomous cross-country soaring is elaborated, enabling a glider UAV to visually localize sub-cumulus thermal updrafts and to efficiently gain energy from them.Relying on the Unscented Kalman Filter, a monocular vision-based method is established, for remotely estimatingsub-cumulus updraft parameters. Its capability of providing convergent and consistent state estimates is assessed relyingon Monte Carlo Simulations. Model uncertainties, image processing noise, and poor observer trajectories can degrade theestimated updraft parameters. Therefore, a second focus of this thesis is the design of a robust probabilistic path plannerfor map-based autonomous cross-country soaring. The proposed path planner balances between the flight time and theoutlanding risk by taking into account the estimation uncertainties in the decision making process. The suggested updraftestimation and path planning algorithms are jointly assessed in a 6 Degrees Of Freedom simulator, highlighting significantperformance improvements with respect to state of the art approaches in autonomous cross-country soaring while it is alsoshown that the path planner is implementable on a low-cost computer platform.

Ce travail porte, de façon théorétique et pratique, sur les sujets plus pertinents autour des drones en navigation autonome et semi-autonome. Conformément à la nature multidisciplinaire des problèmes étudies, une grande diversité des techniques et théories ont été couverts dans les domaines de la robotique, l’automatique, l’informatique, la vision par ordinateur et les systèmes embarques, parmi outres.Dans le cadre de cette thèse, deux plates-formes expérimentales ont été développées afin de valider la théorie proposée pour la navigation autonome d’un drone. Le premier prototype, développé au laboratoire, est un quadrirotor spécialement conçu pour les applications extérieures. La deuxième plate-forme est composée d’un quadrirotor à bas coût du type AR.Drone fabrique par Parrot. Le véhicule est connecté sans fil à une station au sol équipé d’un système d’exploitation pour robots (ROS) et dédié à tester, d’une façon facile, rapide et sécurisé, les algorithmes de vision et les stratégies de commande proposés. Les premiers travaux développés ont été basés sur la fusion de donnés pour estimer la position du drone en utilisant des capteurs inertiels et le GPS. Deux stratégies ont été étudiées et appliquées, le Filtre de Kalman Etendu (EKF) et le filtre à Particules (PF). Les deux approches prennent en compte les mesures bruitées de la position de l’UAV, de sa vitesse et de son orientation. On a réalisé une validation numérique pour tester la performance des algorithmes. Une tâche dans le cahier de cette thèse a été de concevoir d’algorithmes de commande pour le suivi de trajectoires ou bien pour la télé-opération. Pour ce faire, on a proposé une loi de commande basée sur l’approche de Mode Glissants à deuxième ordre. Cette technique de commande permet de suivre au quadrirotor de trajectoires désirées et de réaliser l’évitement des collisions frontales si nécessaire. Etant donné que la plate-forme A.R.Drone est équipée d’un auto-pilote d’attitude, nous avons utilisé les angles désirés de roulis et de tangage comme entrées de commande. L’algorithme de commande proposé donne de la robustesse au système en boucle fermée. De plus, une nouvelle technique de vision monoculaire par ordinateur a été utilisée pour la localisation d’un drone. Les informations visuelles sont fusionnées avec les mesures inertielles du drone pour avoir une bonne estimation de sa position. Cette technique utilise l’algorithme PTAM (localisation parallèle et mapping), qui s’agit d’obtenir un nuage de points caractéristiques dans l’image par rapport à une scène qui servira comme repère. Cet algorithme n’utilise pas de cibles, de marqueurs ou de scènes bien définies. La contribution dans cette méthodologie a été de pouvoir utiliser le nuage de points disperse pour détecter possibles obstacles en face du véhicule. Avec cette information nous avons proposé un algorithme de commande pour réaliser l’évitement d’obstacles. Cette loi de commande utilise les champs de potentiel pour calculer une force de répulsion qui sera appliquée au drone. Des expériences en temps réel ont montré la bonne performance du système proposé. Les résultats antérieurs ont motivé la conception et développement d’un drone capable de réaliser en sécurité l’interaction avec les hommes et les suivre de façon autonome. Un classificateur en cascade du type Haar a été utilisé pour détecter le visage d’une personne. Une fois le visage est détecté, on utilise un filtre de Kalman (KF) pour améliorer la détection et un algorithme pour estimer la position relative du visage. Pour réguler la position du drone et la maintenir à une distance désirée du visage, on a utilisé une loi de commande linéaire. / The present document addresses, theoretically and experimentally, the most relevant topics for Unmanned Aerial Vehicles (UAVs) in autonomous and semi-autonomous navigation. According with the multidisciplinary nature of the studied problems, a wide range of techniques and theories are covered in the fields of robotics, automatic control, computer science, computer vision and embedded systems, among others. As part of this thesis, two different experimental platforms were developed in order to explore and evaluate various theories and techniques of interest for autonomous navigation. The first prototype is a quadrotor specially designed for outdoor applications and was fully developed in our lab. The second testbed is composed by a non expensive commercial quadrotor kind AR. Drone, wireless connected to a ground station equipped with the Robot Operating System (ROS), and specially intended to test computer vision algorithms and automatic control strategies in an easy, fast and safe way. In addition, this work provides a study of data fusion techniques looking to enhance the UAVs pose estimation provided by commonly used sensors. Two strategies are evaluated in particular, an Extended Kalman Filter (EKF) and a Particle Filter (PF). Both estimators are adapted for the system under consideration, taking into account noisy measurements of the UAV position, velocity and orientation. Simulations show the performance of the developed algorithms while adding noise from real GPS (Global Positioning System) measurements. Safe and accurate navigation for either autonomous trajectory tracking or haptic teleoperation of quadrotors is presented as well. A second order Sliding Mode (2-SM) control algorithm is used to track trajectories while avoiding frontal collisions in autonomous flight. The time-scale separation of the translational and rotational dynamics allows us to design position controllers by giving desired references in the roll and pitch angles, which is suitable for quadrotors equipped with an internal attitude controller. The 2-SM control allows adding robustness to the closed-loop system. A Lyapunov based analysis probes the system stability. Vision algorithms are employed to estimate the pose of the vehicle using only a monocular SLAM (Simultaneous Localization and Mapping) fused with inertial measurements. Distance to potential obstacles is detected and computed using the sparse depth map from the vision algorithm. For teleoperation tests, a haptic device is employed to feedback information to the pilot about possible collisions, by exerting opposite forces. The proposed strategies are successfully tested in real-time experiments, using a low-cost commercial quadrotor. Also, conception and development of a Micro Aerial Vehicle (MAV) able to safely interact with human users by following them autonomously, is achieved in the present work. Once a face is detected by means of a Haar cascade classifier, it is tracked applying a Kalman Filter (KF), and an estimation of the relative position with respect to the face is obtained at a high rate. A linear Proportional Derivative (PD) controller regulates the UAV’s position in order to keep a constant distance to the face, employing as well the extra available information from the embedded UAV’s sensors. Several experiments were carried out through different conditions, showing good performance even under disadvantageous scenarios like outdoor flight, being robust against illumination changes, wind perturbations, image noise and the presence of several faces on the same image. Finally, this thesis deals with the problem of implementing a safe and fast transportation system using an UAV kind quadrotor with a cable suspended load. The objective consists in transporting the load from one place to another, in a fast way and with minimum swing in the cable.

No description available.

<p>Simultaneous localization and mapping (SLAM) is a general device localization technique that uses realtime sensor measurements to develop a virtualization of the sensor's environment while also using this growing virtualization to determine the position and orientation of the sensor. This is useful for augmented reality (AR), in which a user looks through a head-mounted display (HMD) or viewfinder to see virtual components integrated into the real world. Visual SLAM (i.e., SLAM in which the sensor is an optical camera) is used in AR to determine the exact device/headset movement so that the virtual components can be accurately redrawn to the screen, matching the perceived motion of the world around the user as the user moves the device/headset. However, many potential AR applications may need access to more than device localization data in order to be useful; they may need to leverage environment data as well. Additionally, most SLAM solutions make the naive assumption that the environment surrounding the system is completely static (non-moving). Given these circumstances, it is clear that AR may benefit substantially from utilizing a SLAM solution that detects objects that move in the scene and ultimately provides localization data for each of these objects. This problem is known as the dynamic SLAM problem. Current attempts to address the dynamic SLAM problem often use machine learning to develop models that identify the parts of the camera image that belong to one of many classes of potentially-moving objects. The limitation with these approaches is that it is impractical to train models to identify every possible object that moves; additionally, some potentially-moving objects may be static in the scene, which these approaches often do not account for. Some other attempts to address the dynamic SLAM problem also localize the moving objects they detect, but these systems almost always rely on depth sensors or stereo camera configurations, which have significant limitations in real-world use cases. This dissertation presents a novel approach for registering and localizing unknown moving objects in the context of markerless, monocular, keyframe-based SLAM with no required prior information about object structure, appearance, or existence. This work also details a novel deep learning solution for determining SLAM map initialization suitability in structure-from-motion-based initialization approaches. This dissertation goes on to validate these approaches by implementing them in a markerless, monocular SLAM system called LUMO-SLAM, which is built from the ground up to demonstrate this approach to unknown moving object registration and localization. Results are collected for the LUMO-SLAM system, which address the accuracy of its camera localization estimates, the accuracy of its moving object localization estimates, and the consistency with which it registers moving objects in the scene. These results show that this solution to the dynamic SLAM problem, though it does not act as a practical solution for all use cases, has an ability to accurately register and localize unknown moving objects in such a way that makes it useful for some applications of AR without thwarting the system's ability to also perform accurate camera localization.</p>