Thesis (M.S.)--University of Missouri-Columbia, 2004. / Typescript. Includes bibliographical references (leaves 110-113). Also available on the Internet.

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University of Macau / Faculty of Science and Technology. / Department of Electromechanical Engineering

Lau Ah Wai, Calvin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 108-111). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- An Overview --- p.4 / Chapter 1.1.1 --- Robot Self Location --- p.4 / Chapter 1.1.2 --- Robot Navigation --- p.10 / Chapter 1.2 --- Scope of Thesis --- p.12 / Chapter 2 --- Theory --- p.13 / Chapter 2.1 --- Coordinate Systems Transformations --- p.13 / Chapter 2.2 --- Problem Specification --- p.21 / Chapter 2.3 --- The Process of Stereo Vision --- p.22 / Chapter 2.3.1 --- Disparity and Depth --- p.22 / Chapter 2.3.2 --- Vertical Edge Detection and Extraction --- p.25 / Chapter 2.3.3 --- Line Matching Using Dynamic Programming --- p.27 / Chapter 3 --- Mobile Robot Self Location --- p.29 / Chapter 3.1 --- Physical Points by Stereo Reconstruction --- p.29 / Chapter 3.1.1 --- Physical Points Refinement --- p.32 / Chapter 3.2 --- Motion Uncertainties Modeling --- p.33 / Chapter 3.3 --- Improved Physical Point Estimations by EKF --- p.36 / Chapter 3.4 --- Matching Physical Points to Model by Geometric Hashing --- p.40 / Chapter 3.4.1 --- Similarity Invariant --- p.44 / Chapter 3.5 --- Initial Pose Estimation --- p.47 / Chapter 3.5.1 --- Initial Pose Refinement --- p.50 / Chapter 3.6 --- Self Location Using Other Camera Combinations --- p.50 / Chapter 4 --- Improvements to Self Location Using Bayesian Inference --- p.55 / Chapter 4.1 --- Statistical Characteristics of Edges --- p.57 / Chapter 4.2 --- Evidence at One Pixel --- p.60 / Chapter 4.3 --- Evidence Over All Pixels --- p.62 / Chapter 4.4 --- A Simplification Of Geometric Hashing --- p.62 / Chapter 4.4.1 --- Simplification of The Similarity Invariant --- p.63 / Chapter 4.4.2 --- Translation Invariant --- p.63 / Chapter 4.4.3 --- Simplification to The Hashing Table --- p.65 / Chapter 5 --- Robot Navigation --- p.67 / Chapter 5.1 --- Propagation of Motion Uncertainties to Estimated Pose --- p.68 / Chapter 5.2 --- Expectation Map Derived from the CAD Model --- p.70 / Chapter 6 --- Experimental Results --- p.74 / Chapter 6.1 --- Results Using Simulated Environment --- p.74 / Chapter 6.1.1 --- Results and Error Analysis --- p.75 / Chapter 6.2 --- Results Using Real Environment --- p.85 / Chapter 6.2.1 --- Camera Calibration Using Tsai's Algorithm --- p.85 / Chapter 6.2.2 --- Pose Estimation By Geometric Hashing --- p.88 / Chapter 6.2.3 --- Pose Estimation by Bayesian Inference and Geometric Hash- ing --- p.90 / Chapter 6.2.4 --- Comparison of Self Location Approaches --- p.92 / Chapter 6.2.5 --- Motion Tracking --- p.93 / Chapter 7 --- Conclusion and Discussion --- p.95 / Chapter 7.1 --- Conclusion and Discussion --- p.95 / Chapter 7.2 --- Contributions --- p.97 / Chapter 7.3 --- Subjects for Future Research --- p.98 / Chapter A --- Appendix --- p.100 / Chapter A.1 --- Extended Kalman Filter --- p.100 / Chapter A.2 --- Visualizing Uncertainty for 2D Points --- p.105

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Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (Ph.D.)--City University of Hong Kong, 2009. / "Submitted to Department of Manufacturing Engineering and Engineering Management in partial fulfillment of the requirements for the degree of Doctor of Philosophy." Includes bibliographical references.

Thesis (M. Sc.)--York University, 1997. Graduate Programme in Computer Science. / Typescript. Includes bibliographical references (leaves 107-113). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://wwwlib.umi.com/cr/yorku/fullcit?pMQ27391.

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references.

Rousing applications of robot teams abound over the past three decades, but ferocious demands for viable systems to coordinate teams of mobile robots in dynamic environments still linger on. To meet this challenge, this project proposes a performance optimisation system for mobile robots to make the team performance more reliable and efficient in dynamic environments. A wide range of applications will benefit from the system, such as logistics, military, and disaster rescue. The performance optimisation system comprises three main modules: (1) a task allocation module to assign tasks to robots, (2) a motion planning module to navigate robots, and (3) a graphical simulation module to visualise robot operations and to validate the methodologies of performance optimisation. The task allocation module features a closed-loop bid adjustment mechanism for auctioning tasks to capable robots. Unlike most traditional open-looped methods, each of the robots evaluates its own performance after completing a task as feedback correction to improve its future bid prices of similar tasks. Moreover, a series of adjustments are weighed and averaged to damp out drastic deviations due to operational uncertainties. As such, the accuracy of bid prices is improved, and tasks are more likely allocated to suitable robots that are expected to perform better by offering more reliable bids. The motion planning module is bio-inspired intelligent, characterised by detection of imminent neighbours and design flexibility of virtual forces to enhance the responsiveness of robot motions. Firstly, while similar methods unnecessarily entail each robot to consider all the neighbours, the detection of imminent neighbours instead enables each robot to mimic creatures to identify and only consider imminent neighbours which pose collision dangers. Hence, redundant computations are reduced and undesirable robot movements eliminated. Secondly, to imitate the responsive motion behaviours of creatures, a virtual force method is adopted. It composes virtual attractive forces that drive the robots towards their targets and, simultaneously, exerts virtual repulsive forces to steer the robots away from one another. To enhance the design flexibility of the virtual forces, a twosection function and, more significantly, a spline-based method are proposed. The shapes of force curves can be flexibly designed and adjusted to generate smooth forces with desirable magnitudes. Accordingly, robot motions are streamlined and likelihood of robot collisions reduced. The graphical simulation module simulates and visualises robot team operations, and validates the proposed methodologies. It effectively emulates the operational scenarios and enables engineers to tackle downstream problems earlier in the design cycle. Furthermore, time and costs of robotic system development in the simulation module are considerably cut, compared with a physical counterpart. The performance optimisation system is indeed viable in improving the operational safety and efficiency of robot teams in dynamic environments. It has substantially pushed the frontiers of this field, and may be adapted as an intelligent control software system for practical operations of physical robot teams to benefit various applications. / HKU 3 Minute Thesis Award, 1st Runner-up (2012) / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy