It is hypothesized that the uncertainty of the Synchrony® model from the rotation of a geometrically asymmetrical single fiducial shall be non-zero during the motion tracking. To validate this hypothesis, the uncertainty was measured for a Synchrony® model built for a respiratory motion phantom oriented at different yaw angles on a Cyberknife® treatment table. A Mini-ball Cube with three cylindrical GoldMark™ (1mmx5mm Au) numbered fiducials was placed inside a respiratory phantom and used for all tests. The fiducial with the least artifact interference was selected for the motion tracking. A 2cm periodic, longitudinal, linear motion of the Mini-ball cube was executed and tested for yaw rotational angles, 0° – 90°. The test was repeated over 3 nonconsecutive days. The uncertainty increased with the yaw angle with the most noticeable changes seen between20° and 60° yaw, where uncertainty increased from 23.5% to 57.9%. A similar test was performed using a spherical Gold Anchor™ fiducial. The uncertainties found when using the Gold Anchor™ were statistically lower than those found when using the GoldMark™ fiducial for all angles of rotation. For the first time, it is found that Synchrony® model uncertainty depends on fiducial geometry. In addition, this research has shown that tracking target rotation using a single fiducial can be accomplished with the Synchrony® model uncertainty as it is displayed on the treatment console. The results of this research could lead to decreased acute toxicity effects related to multiple fiducials. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

This thesis looks at the problem of optimally placing binary directional proximity markers to assist a robot as it navigates waypoints through an environment. A simple planar fiducial marker is developed to serve as the binary directional proximity marker. A scoring function is proposed for marker placement as well as a method for random generation of hallway maps. Several common metaheuristic algorithms are run to find optimal marker placements with respect to the scoring function for a number of randomly generated hallway maps. From these results, placements are then evaluated by physical experimentation on an iRobot Create equipped with relatively inexpensive webcams. / Graduate

Harbours play a vital role in the economies of most countries since a significant amount of international trade is conducted through them. Ships rely on harbours for the safe loading and unloading of cargo and the harbour infrastructure relies on breakwaters for protection. As a result, the design and analysis of breakwaters receives keen interest from the engineering community. Coastal engineers need an easy-to-use tool that can model the way in which waves interact with large numbers of interlocking armour units. Although the study of fluid–structure interaction generates a lot of research activity, none of the reviewed literature describes a suitable method of analysis. The goal of the research was to develop a simulation algorithm that meets all the criteria by allowing CFD software and physics middleware to work in unison. The proposed simulation algorithm used Linux “shell scripts” to coordinate the actions of commercial CFD software (Star-CCM+) and freely available physics middleware (PhysX). The CFD software modelled the two-phase fluid and provided force and moment data to the physics middleware so that the movement of the armour units could be determined. The simulation algorithm was verified numerically and experimentally. The numerical verification exercise was of limited value due to unresolved issues with the CFD software chosen for the analysis, but it was shown that PhysX responds appropriately given the correct force data as input. Experiments were conducted in a hydraulics laboratory to study the interaction of a solitary wave and cubes stacked on a platform. Fiducial markers were used to track the movement of the cubes. The phenomenon of interest was the transfer of momentum from the wave to the rigid bodies, and the results confirmed that the effect was captured adequately. The study concludes with suggestions for further study. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2014

Harbours play a vital role in the economies of most countries since a significant amount of international trade is conducted through them. Ships rely on harbours for the safe loading and unloading of cargo and the harbour infrastructure relies on breakwaters for protection. As a result, the design and analysis of breakwaters receives keen interest from the engineering community. Coastal engineers need an easy-to-use tool that can model the way in which waves interact with large numbers of interlocking armour units. Although the study of fluid–structure interaction generates a lot of research activity, none of the reviewed literature describes a suitable method of analysis. The goal of the research was to develop a simulation algorithm that meets all the criteria by allowing CFD software and physics middleware to work in unison. The proposed simulation algorithm used Linux “shell scripts” to coordinate the actions of commercial CFD software (Star-CCM+) and freely available physics middleware (PhysX). The CFD software modelled the two-phase fluid and provided force and moment data to the physics middleware so that the movement of the armour units could be determined. The simulation algorithm was verified numerically and experimentally. The numerical verification exercise was of limited value due to unresolved issues with the CFD software chosen for the analysis, but it was shown that PhysX responds appropriately given the correct force data as input. Experiments were conducted in a hydraulics laboratory to study the interaction of a solitary wave and cubes stacked on a platform. Fiducial markers were used to track the movement of the cubes. The phenomenon of interest was the transfer of momentum from the wave to the rigid bodies, and the results confirmed that the effect was captured adequately. The study concludes with suggestions for further study. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2014

Vision-based positioning systems are founded primarily on a simple image processing technique of identifying various visually significant key-points in an image and relating them to a known coordinate system in a scene. Fiducial markers are used as a means of providing the scene with a number of specific key-points, or features, such that computer vision algorithms can quickly identify them within a captured image. This thesis proposes a reliable vision-based positioning system which utilizes a unique pseudo-random fiducial marker. The marker itself offers 49 distinct feature points to be used in position estimation. Detection of the designed marker occurs after an integrated process of adaptive thresholding, k-means clustering, color classification, and data verification. The ultimate goal behind such a system would be for indoor localization implementation in low cost autonomous mobile platforms.

Vision-based positioning systems are founded primarily on a simple image processing technique of identifying various visually significant key-points in an image and relating them to a known coordinate system in a scene. Fiducial markers are used as a means of providing the scene with a number of specific key-points, or features, such that computer vision algorithms can quickly identify them within a captured image. This thesis proposes a reliable vision-based positioning system which utilizes a unique pseudo-random fiducial marker. The marker itself offers 49 distinct feature points to be used in position estimation. Detection of the designed marker occurs after an integrated process of adaptive thresholding, k-means clustering, color classification, and data verification. The ultimate goal behind such a system would be for indoor localization implementation in low cost autonomous mobile platforms.

Vision-based positioning systems are founded primarily on a simple image processing technique of identifying various visually significant key-points in an image and relating them to a known coordinate system in a scene. Fiducial markers are used as a means of providing the scene with a number of specific key-points, or features, such that computer vision algorithms can quickly identify them within a captured image. This thesis proposes a reliable vision-based positioning system which utilizes a unique pseudo-random fiducial marker. The marker itself offers 49 distinct feature points to be used in position estimation. Detection of the designed marker occurs after an integrated process of adaptive thresholding, k-means clustering, color classification, and data verification. The ultimate goal behind such a system would be for indoor localization implementation in low cost autonomous mobile platforms.

Submitted by Diego Cesar (rasecg3@gmail.com) on 2017-06-26T19:47:01Z No. of bitstreams: 1 main_compressed.pdf: 16459769 bytes, checksum: b7838aeb4e94120d45daddb2c1b3c80e (MD5) / Approved for entry into archive by Flávia Sousa (flaviabs@ufba.br) on 2017-06-28T14:27:38Z (GMT) No. of bitstreams: 1 main_compressed.pdf: 16459769 bytes, checksum: b7838aeb4e94120d45daddb2c1b3c80e (MD5) / Made available in DSpace on 2017-06-28T14:27:38Z (GMT). No. of bitstreams: 1 main_compressed.pdf: 16459769 bytes, checksum: b7838aeb4e94120d45daddb2c1b3c80e (MD5) / Underwater navigation is affected by the lack of GPS due to the attenuation of the electromagnetic signals. Thereby, underwater robots rely on dead reckoning as their main navigation systems. However, localization via dead-reckoning raises uncertainties over time. Consequently, visual and acoustic sensors have been used to increase accuracy in robotic systems navigation, specially when they move in relation to a target object. This level of precision is required, for instance, for object manipulation, inspection, monitoring and docking. This work aims to develop and assess a hybrid visual controller for an autonomous underwater vehicle (AUV) using artificial fiducial markers as reference. Artificial fiducial markers are planar targets, designed to be easily detected by computer vision systems and provide means to estimate the robot’s pose in respect to the marker. They usually have high detection rate and low false positive rate, which are desirable for visual servoing tasks. On this master thesis was evaluated, from among the most popular and open-source marker systems, one that presents the best performance in underwater environments in terms of detection rate, false positives rate, maximum distance and angle for successful detection. Afterwards, the best marker was used for visual servoing purposes in an underwater robot. The firsts experiments were performed on the Gazebo robot simulation environment and, after that, on a real prototype, the FlatFish. Tests on a saltwater tank were performed in order to assess the controller using static and adaptive gains. Finally, sea trials were performed, using the controller that best behaved on the controlled environment in order to assess its performance on a real environment. The tests have shown that the visual controller was able of station-keeping in front of an artificial fiducial marker. Additionally, it was also seen that the adaptive gain brings improvements, mainly because it smooths the robot’s motion on the beginning of the task. / Navegação submarina é afetada pela falta de GPS, devido à atenuação de ondas eletromagnéticas. Por causa disso, os robôs submarinos baseiam-se em sistemas de navegação via odometria e sensores inerciais. Contudo, a localização via esse tipo de abordagem possui uma incerteza associada que cresce com o passar do tempo. Por isso sensores visuais e acústicos são utilizados para aumentar a precisão da navegação de veículos submarinos. Nesse contexto, a utilização de um controlador visual aumenta a precisão dos sistemas robóticos quando se locomovem em relação a um objeto alvo. Esse tipo de precisão é requerida para manipulação de objetos, inspeção, monitoramento e docagem submarina. Esse trabalho tem como objetivo projetar e avaliar um controlador visual híbrido para um veículo submarino autônomo (AUV) utilizando como referência marcos visuais artificiais. Os marcos artificiais são alvos planares projetados para serem facilmente detectados por sistemas de visão computacional, sendo capazes de fornecer meios para estimação da posição do robô em relação ao marco. As suas características de alta taxa de detecção e baixa taxa de falsos positivo são desejáveis para tarefas de controle servo visual. Este trabalho analisou, portanto, dentre os marcos mais populares e de código aberto, aquele que apresenta o melhor desempenho em ambientes submarinos, em termos de taxa de detecção, número de falsos positivos, máxima distância e ângulo para detecção. Posteriormente, o marco que apresentou melhor performance foi utilizado para aplicação de controle visual em um robô submarino. Os primeiros ensaios foram realizados na plataforma de simulação robótica Gazebo e, posteriormente, em um protótipo de AUV real, o FlatFish. Testes em um tanque de água salgada foram realizados visando avaliar a solução proposta utilizando um ganho estático e um ganho adaptativo para o controlador visual. Finalmente, testes no mar foram realizados utilizando o controlador que apresentou os melhores resultados no ambiente controlado, a fim de verificar seu desempenho em um ambiente real. Os testes mostraram que o controlador visual foi capaz de manter o veículo em frente aos marcos visuais artificiais e que o ganho adaptativo trouxe vantagens, principalmente por suavizar a movimentação do robô no início da missão.

Vision-based positioning systems are founded primarily on a simple image processing technique of identifying various visually significant key-points in an image and relating them to a known coordinate system in a scene. Fiducial markers are used as a means of providing the scene with a number of specific key-points, or features, such that computer vision algorithms can quickly identify them within a captured image. This thesis proposes a reliable vision-based positioning system which utilizes a unique pseudo-random fiducial marker. The marker itself offers 49 distinct feature points to be used in position estimation. Detection of the designed marker occurs after an integrated process of adaptive thresholding, k-means clustering, color classification, and data verification. The ultimate goal behind such a system would be for indoor localization implementation in low cost autonomous mobile platforms.

Image-guided neurosurgery interventions are becoming sur- gical procedure routines. We suggest a novel method for automatic marker localization in X-ray images for Leksell SurgiPlan® which is an image-based neurosergical treat- ment planning software provided by Elekta Instrument AB. We implemented an algorithm for fiducial marker localiza- tion based on feature detection, classification and prior geo- metrical knowledge of the markers. Automatic localization ca help to decrease the human error associated with manual registration of these fiducial markers which is the current applied method for X-ray images in Leksell SurgiPlan®.