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| About site: Robotics/Research - Vision-based Robot Localization |
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| About site: http://www.ele.auckland.ac.nz/~cyue001/ |
Title: Robotics/Research - Vision-based Robot Localization Research on various statistical localization architectures, with focus on vision based systems done by David Yuen of the University of Auckland Robotics Group. Site includes description, presentations
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David Yuen's Homepage    Research Interest Contact . IntroductionI was a PhD student in the Robotics Group, which is part of theComputer System Research Cluster in the Department of Electrical and Computer Engineering. The research was supervised by Dr Bruce MacDonald and related to vision-based robot localisation. Robotic research still lacks behind the human imagination nad expectation inmany fronts. It was one of the motivations that drives me to startmy research in this field. My earlier research experience was more process engineering oriented. My master thesis was about the application model-predictive control for the fermentation process in a beer brewery. It would be nice to see whether my previous exposure can give me some interesting insights to a fairly different application domain.Now I am a research fellow in the Intelligence, Agents, Multimedia(IAM) group of University of Southampton. My research focus shiftsfrom single robot to multiple agents by applying primarily market basedcontrol methods. Please visit my new homepage at http://www.ecs.soton.ac.uk/~dy.ResearchVision-based localisation is a biologically-inspired process. In contrast to the development of robotic research in the past few decades, only a few types of nocturnal animals, such as bats, use direct range sensing as a mean to explore the environment. The heavy computation requirement involved in near real-time image processing hindered the widespread use of vision inrobotics. Due to the continuous advances in electronics, this physical barrier has largely been overcome nowadays. It is now about time for us to explore further into this fascinating area. To be more specific, statistical vision-based localisation is myresearch focus. If we want the robot to localise using naturallandmarks extracted from the scene, it will have to match theselandmarks before carrying out triangulation. Image features arenot unique in many scenes, which may be leaves on a tree or identicalchairs in a conference room. It is different to match thesesimilar objects precisely. Robust estimation methods,e.g. RANSAC, can be improved to take advantage of the extra availableinformation. Panoramic image geometry has a number ofdesirable properties, including very large field-of-view and easeprocessing, which is particularly relevant for robotics. Itsuse has been integrated to my robot localisation algorithm.Recent development in Sequential Monte Carlo (SMC)methods offers very efficient estimation to the Bayes' Theorem. Manydifferent classes of localisation problems, including absoluteposition estimation, tracking and the very difficult kidnapped robotproblem, have been solved using SMC. Possible extension tolocalisation problems, in which neither robot nor landmark positionsare known, is one of the other direction that I am researching on atthis moment. Research to extend the algorithm for localisation usingimage features is still on-going.For more details: Selected presentationsPublications Panoramic image with cylindrical projection. (epipolar lines are shown in green) SMC robot localisation simulation. The blue spots are individual "particles" whereas the current robot positiin is represented in green. Technical InterestsIn this section, I am going to put a few scripts/programs/designsthat I have worked on previously. Some are originated from myresearch, some are just my personal interest. SICK LMS-200 laser scanner Other Interests IEEE student branch Penguins!!!My Favourite Links Contact Info Postal Address: Department of Electrical and Computer Engineering School of Engineering, University of Auckland Private Bag 92019, Auckland, New Zealand. Physical Address: Room 2.308 (a.k.a. SPACE Lab), Level 3, 20 Symonds Street URL: www.ece.auckland.ac.nz/~cyue001 Email: d.yuen@auckland.ac.nz Phone: +64-9-3737599 ext 88104 Last Updated: Web Jul 6 10:59:52 NZDT 2005 |
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Research | on | various | statistical | localization | architectures, | with | focus | on | vision | based | systems | done | by | David | Yuen | of | the | University | of | Auckland | Robotics | Group. | Site | includes | description, | presentations |
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http://www.ele.auckland.ac.nz/~cyue001/
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Research on various statistical localization architectures, with focus on vision based systems done by David Yuen of the University of Auckland Robotics Group. Site includes description, presentations
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