Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 148-153).

Actualmente, muchos investigadores están desarrollando robots capaces de desplazarse por el interior de espacios confinados, como por ejemplo los In-pipe robots, capaces de trasladarse por el interior de ductos. Existen siete tipos de robots consolidados en esta área: Pig, Wheel, Caterpillar, Wall-press, Walking, Inch worm y Screw [1]. Usualmente un sistema de ductos está compuesto por complejos obstaculos que dificultan la navegación como variaciones de diámetros, codos y uniones tipo T. Estas últimas presentan un particular desafío dado que ningún sistema robótico ha demostrado la capacidad de sobrepasarlas cuando se presentan en ciertas posiciones. El objetivo de este trabajo es diseñar y construir un prototipo de una nueva categoría de robot de inspección de ductos consistente en un Robot Deformable Octaédrico con una estructura compuesta principalmente por actuadores lineales. Al ser un octaedro, todos los lados del robot son triangulares, que al estar compuestos por actuadores lineales, pueden deformarse. De esta forma el robot puede adaptarse a los distintos escenarios, en particular a los complejos componentes de una red de tuberías, en un rango mayor de diámetros interiores. Esta estructura se puede adaptar y navegar por espacios confinados inaccesibles para la mayoría de los sistemas robóticos existentes. Tiene 6 puntos de apoyo que ejercen presión en la superficie interna del ducto, los cuales pueden funcionar de forma independiente como dos triángulos inscritos en la superficie cerrada. Cada triángulo permite mantener estable al robot al interior del espacio cerrado sin necesidad de que el otro ejerza presión alguna. Para el desarrollo de este robot, se trabajó inicialmente con ODE (Open Dynamic Engine), una librería de software para simular la dinámica de cuerpos rígidos articulados, que permitió probar el diseño básico del robot. El robot se simuló en los distintos escenarios posibles y se estudió su estructura deformable. Inicialmente se construyó un prototipo hidráulico para estudiar el comportamiento cinemático de la estructura. Se finalizó con otro prototipo, con actuadores lineales eléctricos diseñados exclusivamente para el uso en robots deformables, con el cual se probaron las deformaciones principales necesarias para producir los movimientos básicos que permiten navegar por una red de tuberías. Con el software existente, el prototipo eléctrico puede navegar en tuberías cuyo diámetro interior va desde 35 a 48 cm, a una velocidad en línea recta de 0.5 cm/seg utilizando movimiento peristáltico. La capacidad mecánica permite aumentar el diámetro máximo a 67 cm y se estima que su velocidad seria de 1 cm/seg. Gracias a su geometría octaédrica, el prototipo es capaz de avanzar hacia cualquier dirección en forma análoga, permitiendo así superar una unión tipo T con salida superior.

The purpose of this research was to determine potential job functions in the food systems industry for implementation with robots. The research objectives included (1) to isolate job functions in food systems that should be implemented with robots, (2) to identify job functions that robot manufacturers believe robots are technologically capable of performing in the food industry, (3) to compare job functions that are most desired by food systems with those that are technologically possible from robot manufacturers and (4) to identify characteristics of professionals who are evaluating job functions for robots in food systems. Data collection was accomplished through the use of a survey questionnaire. The survey, consisting of two parts, was mailed nationwide to target populations in the food industry and robot manufacturing. Part one of the survey consisted of sixty-four job functions categorized into the major categories of receiving and storage, sanitation, food production, food service, food distribution, related job functions, education and entertainment. Part two of the survey consisted of ten demographic data questions, involving age, job title, work experience, educational background, sex and computer usage. The sample population to receive the survey was divided into three groups. These were (1) foodservice industries, including hospitals, universities and primary/secondary schools, (2) food processors and (3) robot manufacturers. Management personnel in foodservice and food processing were asked to provide an assessment of job functions feasible for robotics implementation. Robot manufacturers received questionnaires to provide an assessment of robot capabilities with regard to food industry needs. Each population group was stratified, based on a predetermined cut-off point, to include only large volume producers. Individual participants in each population group were selected through a systematic sample with a random start. Of six hundred sixty-seven surveys mailed, forty-one percent provided valid responses and were analyzed using frequencies and chi square test of significance. Using a seventy-five percent or greater yes response rate and significance greater than .05, sixteen of the sixty-four job functions were identified for further analysis with the demographic data. This identification process was used to determine job functions which the food industry and robot manufacturers did not disagree on feasibility for robotics implementation. Looking at seventy-five percent or greater no responses where significance is greater than .05, only five of the sixty-four job functions were identified as not feasible for robots at this time. Analysis of demographic data with the sixteen identified job functions resulted in no significant difference in responses in relation to age, years of work experience, sex, computer usage or level of education. There were several conclusions to be drawn from this research. First, the overall positive response to robots in the food industry suggest further research with actual robotics implementation would be indicated. It appears that robots aas reprogrammable, multifunctional manipulators are not currently in use in the food industry. Second, persons in the food industry need education on robots and robotics applications in the form of workshops, continuing education and academia for students. Robot manufacturers need to be educated, through publications and personal contact, in all areas of the food industry to enable the development of applications to occur. Third, further research is needed to determine appropriate job skills and training needed for food industry employees replaced by robots. / Graduation date: 1984

by Lam Chin Hung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 60-64). / Abstracts in English and Chinese. / Acknowledgments --- p.ii / List of Figures --- p.v / List of Tables --- p.vii / Abstract --- p.viii / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Algorithm Outline --- p.7 / Chapter 2.1 --- Assumptions --- p.7 / Chapter 2.2 --- Robot Localization --- p.8 / Chapter 2.3 --- Algorithm Outline --- p.11 / Chapter 3 --- Global and Local Maps --- p.15 / Chapter 3.1 --- Feature Selection --- p.17 / Chapter 3.2 --- Line Correspondence --- p.18 / Chapter 3.3 --- Map Representation --- p.20 / Chapter 3.3.1 --- Global Map --- p.21 / Chapter 3.3.2 --- Local Map --- p.22 / Chapter 3.4 --- Integration of Multiple Local 2D Maps --- p.24 / Chapter 4 --- Localization Algorithm --- p.27 / Chapter 4.1 --- Robot Orientation --- p.28 / Chapter 4.2 --- Robot Position --- p.29 / Chapter 4.2.1 --- Match Function --- p.30 / Chapter 4.2.2 --- Search Algorithm --- p.31 / Chapter 4.3 --- Continuous Localization with Retroactive Pose Update --- p.32 / Chapter 5. --- Implementation and Experiments --- p.35 / Chapter 5.1 --- Computing Robot Orientation --- p.36 / Chapter 5.2 --- Robot Position by Map Registration --- p.42 / Chapter 5.2.1 --- Error Analysis --- p.47 / Chapter 5.3 --- Discussions --- p.49 / Chapter 6. --- Conclusion --- p.52 / Appendix --- p.54 / Chapter A.l --- Intrinsic and Extrinsic Parameters --- p.54 / Chapter A.2 --- Relation Between Cameras (Stereo Camera Calibration) --- p.55 / Chapter A.3 --- Wheel-Eyes Calibration --- p.56 / Chapter A.4 --- Epipolar Geometry --- p.58 / Chapter A.5 --- The Tele-operate Interface --- p.59 / References --- p.60

Chan Hung-Kwan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 100-101). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Analysis of a tracking robot system: Challenges --- p.2 / Chapter 1.2.1 --- Vision approach: Detecting a moving ob- ject from a moving background in real-time --- p.2 / Chapter 1.2.2 --- Non-vision sensor approach: The determi- nation of the angle of the target --- p.3 / Chapter 1.2.3 --- Emitter-and-receiver approach --- p.4 / Chapter 2 --- Literature Review --- p.5 / Chapter 2.1 --- People Detection --- p.5 / Chapter 2.1.1 --- Background Subtraction --- p.5 / Chapter 2.1.2 --- Optical Flow --- p.6 / Chapter 2.2 --- Target Tracking Sensors --- p.7 / Chapter 3 --- Hardware and Software Architecture --- p.8 / Chapter 3.1 --- Camera --- p.8 / Chapter 3.2 --- Software --- p.8 / Chapter 3.3 --- Hardware --- p.9 / Chapter 3.4 --- Interface --- p.12 / Chapter 3.5 --- The USB Remote Controller --- p.12 / Chapter 4 --- Vision --- p.17 / Chapter 4.1 --- Vision Challenges --- p.17 / Chapter 4.1.1 --- Detecting a moving object from a moving background --- p.17 / Chapter 4.1.2 --- High-speed in real-time --- p.19 / Chapter 4.2 --- Leg Tracking by Binary Image --- p.19 / Chapter 4.3 --- Algorithm --- p.20 / Chapter 4.4 --- Advantages --- p.22 / Chapter 4.5 --- Limitations --- p.22 / Chapter 4.6 --- "Estimation of the distance, d, by vision" --- p.23 / Chapter 4.6.1 --- A more accurate version --- p.23 / Chapter 4.6.2 --- Inaccuracies --- p.25 / Chapter 4.7 --- Future Work: Estimation of the distance by both vision sensor and ultrasonic sensor --- p.25 / Chapter 4.7.1 --- Ruler-based Sensor Fusion --- p.26 / Chapter 4.7.2 --- Learning-based Sensor Fusion --- p.27 / Chapter 5 --- Control --- p.28 / Chapter 5.1 --- Control of the Camera --- p.28 / Chapter 5.1.1 --- "Estimation of the Angle, Ψ" --- p.29 / Chapter 5.2 --- Kinematic Modeling of the Robot --- p.30 / Chapter 5.3 --- The Time Derivatives of d and Ψ --- p.36 / Chapter 5.4 --- Control of the Robot --- p.38 / Chapter 5.5 --- Steering Angle and Overshooting --- p.41 / Chapter 5.5.1 --- Steering Angle Gain --- p.41 / Chapter 5.5.2 --- Small Gain --- p.41 / Chapter 6 --- Obstacle Avoidance --- p.43 / Chapter 6.1 --- Ultrasonic sensor configurations --- p.45 / Chapter 6.2 --- Approach of Control --- p.46 / Chapter 6.3 --- Algorithm --- p.49 / Chapter 6.4 --- Robot Travelling Distance Determination --- p.50 / Chapter 6.5 --- Experimental Result 1 --- p.53 / Chapter 6.6 --- Experimental Result 2 --- p.55 / Chapter 6.7 --- New ideas on the system --- p.57 / Chapter 7 --- Tracking Sensor --- p.60 / Chapter 7.1 --- Possible Methods --- p.61 / Chapter 7.1.1 --- Magnet and Compass --- p.61 / Chapter 7.1.2 --- LED --- p.61 / Chapter 7.1.3 --- Infra-red : Door Minder --- p.62 / Chapter 7.2 --- Rangefinders --- p.64 / Chapter 7.2.1 --- Configuration --- p.65 / Chapter 7.2.2 --- Algorithm --- p.67 / Chapter 7.2.3 --- Wireless Ultrasonic Emitter-receiver Pair . --- p.68 / Chapter 7.2.4 --- Omni-directional Emitter --- p.74 / Chapter 7.2.5 --- Experiments --- p.75 / Chapter 7.2.6 --- Future Work --- p.79 / Chapter 8 --- Experiments and Performance Analysis --- p.80 / Chapter 8.1 --- Experiments --- p.80 / Chapter 8.2 --- Current Performance of the Tracking Robot --- p.85 / Chapter 8.3 --- Considerations on the System Speed and Subsys- tem Speeds --- p.85 / Chapter 8.4 --- Driving and Steering work in the same time --- p.86 / Chapter 8.5 --- Steering Motor --- p.87 / Chapter 8.5.1 --- Encoders --- p.87 / Chapter 8.6 --- Driving Motor --- p.87 / Chapter 8.6.1 --- Speed --- p.87 / Chapter 8.6.2 --- Speed Range --- p.87 / Chapter 8.7 --- Communication of the Vision Part and Control Part --- p.88 / Chapter 9 --- Conclusion --- p.92 / Chapter 9.1 --- Contributions --- p.92 / Chapter 9.2 --- Future Work --- p.93 / Chapter A --- Mobile Robot Construction --- p.97 / Bibliography --- p.101

by Law Kwok Ho Cedric. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 106-112). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Related work --- p.4 / Chapter 1.3 --- Thesis overview --- p.5 / Chapter 2 --- Single wheel robot: Gyrover --- p.9 / Chapter 2.1 --- Background --- p.9 / Chapter 2.2 --- Robot concept --- p.11 / Chapter 2.3 --- System description --- p.14 / Chapter 2.4 --- Flywheel characteristics --- p.16 / Chapter 2.5 --- Control patterns --- p.20 / Chapter 3 --- Learning Control --- p.22 / Chapter 3.1 --- Motivation --- p.22 / Chapter 3.2 --- Cascade Neural Network with Kalman filtering --- p.24 / Chapter 3.3 --- Learning architecture --- p.27 / Chapter 3.4 --- Input space --- p.29 / Chapter 3.5 --- Model evaluation --- p.30 / Chapter 3.6 --- Training procedures --- p.35 / Chapter 4 --- Control Architecture --- p.38 / Chapter 4.1 --- Behavior-based approach --- p.38 / Chapter 4.1.1 --- Concept and applications --- p.39 / Chapter 4.1.2 --- Levels of competence --- p.44 / Chapter 4.2 --- Behavior-based control of Gyrover: architecture --- p.45 / Chapter 4.3 --- Behavior-based control of Gyrover: case studies --- p.50 / Chapter 4.3.1 --- Vertical balancing --- p.51 / Chapter 4.3.2 --- Tiltup motion --- p.52 / Chapter 4.4 --- Discussions --- p.53 / Chapter 5 --- Implement ation of Learning Control --- p.57 / Chapter 5.1 --- Validation --- p.57 / Chapter 5.1.1 --- Vertical balancing --- p.58 / Chapter 5.1.2 --- Tilt-up motion --- p.62 / Chapter 5.1.3 --- Discussions --- p.62 / Chapter 5.2 --- Implementation --- p.65 / Chapter 5.2.1 --- Vertical balanced motion --- p.65 / Chapter 5.2.2 --- Tilt-up motion --- p.68 / Chapter 5.3 --- Combined motion --- p.70 / Chapter 5.4 --- Discussions --- p.72 / Chapter 6 --- Shared Control --- p.74 / Chapter 6.1 --- Concept --- p.74 / Chapter 6.2 --- Schemes --- p.78 / Chapter 6.2.1 --- Switch mode --- p.79 / Chapter 6.2.2 --- Distributed mode --- p.79 / Chapter 6.2.3 --- Combined mode --- p.80 / Chapter 6.3 --- Shared control of Gyrover --- p.81 / Chapter 6.4 --- How to share --- p.83 / Chapter 6.5 --- Experimental study --- p.88 / Chapter 6.5.1 --- Heading control --- p.89 / Chapter 6.5.2 --- Straight path --- p.90 / Chapter 6.5.3 --- Circular path --- p.91 / Chapter 6.5.4 --- Point-to-point navigation --- p.94 / Chapter 6.6 --- Discussions --- p.95 / Chapter 7 --- Conclusion --- p.103 / Chapter 7.1 --- Contributions --- p.103 / Chapter 7.2 --- Future work --- p.104

Thèse doctorat : Informatique : Chambéry : 2003. / Thèse préparée à l'Institut national de recherche en informatique et en automatique. Thèse : 2003CHAMS027. Bibliogr.: 119 rèf.

Reproduction de : Thèse de doctorat : Robotique et intelligence artificielle : Toulouse, INPT : 2006. / Titre provenant de l'écran-titre. Bibliogr. 63 réf.

Reproduction de : Thèse de doctorat : Informatique : Grenoble INPG : 1989. / Titre provenant de l'écran-titre. Bibliogr. p. 183-196.

Thesis (Ph.D.)--University of Delaware, 2009. / Principal faculty advisor: Sunil K. Agrawal, Dept. of Mechanical Engineering. Includes bibliographical references.