13 research outputs found

    Resource optimization and dynamic state management in a collaborative virtual environment.

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    Yim-Pan Chui.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 126-132).Abstracts in English and Chinese.Abstract --- p.iiAcknowledgments --- p.vChapter 1 --- Introduction --- p.1Chapter 1.1 --- Introduction to Collaborative Virtual Environments --- p.1Chapter 1.2 --- Barriers to Resource Management and Optimization --- p.3Chapter 1.3 --- Thesis Contributions --- p.5Chapter 1.4 --- Application of this Research Work --- p.6Chapter 1.5 --- Thesis Organization --- p.6Chapter 2 --- Resource Optimization - Intelligent Server Partitioning --- p.9Chapter 2.1 --- Introduction --- p.9Chapter 2.2 --- Server Partitioning --- p.13Chapter 2.2.1 --- Related Works --- p.15Chapter 2.2.2 --- Global Optimization Approaches --- p.17Chapter 2.3 --- Hybrid Genetic Algorithm Paradigm --- p.17Chapter 2.3.1 --- Drawbacks of traditional GA --- p.18Chapter 2.3.2 --- Problem Modeling --- p.19Chapter 2.3.3 --- Discussion --- p.24Chapter 2.4 --- Results --- p.25Chapter 2.5 --- Concluding Remarks --- p.28Chapter 3 --- Dynamic State Management - Dead Reckoning of Attitude --- p.32Chapter 3.1 --- Introduction to Dynamic State Management --- p.32Chapter 3.2 --- The Dead Reckoning Approach --- p.35Chapter 3.3 --- Attitude Dead Reckoning by Quaternion --- p.37Chapter 3.3.1 --- Modeling of the Paradigm --- p.38Chapter 3.3.2 --- Prediction Step --- p.39Chapter 3.3.3 --- Convergence Step --- p.40Chapter 3.3.4 --- Overall Algorithm --- p.46Chapter 3.4 --- Results --- p.47Chapter 3.5 --- Conclusion --- p.51Chapter 4 --- Polynomial Attitude Extrapolation --- p.52Chapter 4.1 --- Introduction --- p.52Chapter 4.2 --- Related Works on Kalman Filtering --- p.53Chapter 4.3 --- Historical Propagation of Quaternion --- p.54Chapter 4.3.1 --- Cumulative Extrapolation --- p.54Chapter 4.3.2 --- Method I. Vandemonde Approach --- p.55Chapter 4.3.3 --- Method II. Lagrangian Approach --- p.58Chapter 4.4 --- History-Based Attitude Management --- p.60Chapter 4.4.1 --- Multi-order Prediction --- p.60Chapter 4.4.2 --- Adaptive Attitude Convergence --- p.63Chapter 4.4.3 --- Overall Algorithm --- p.67Chapter 4.5 --- Results --- p.69Chapter 4.6 --- Conclusion --- p.77Chapter 5 --- Forward Difference Approach on State Estimation --- p.78Chapter 5.1 --- Introduction --- p.78Chapter 5.2 --- Positional Forward Differencing --- p.79Chapter 5.3 --- Forward Difference on Quaternion Space --- p.80Chapter 5.3.1 --- Attitude Forward Differencing --- p.83Chapter 5.3.2 --- Trajectory Blending --- p.84Chapter 5.4 --- State Estimation --- p.86Chapter 5.5 --- Computational Efficiency --- p.87Chapter 5.6 --- Results --- p.88Chapter 5.7 --- Conclusion --- p.96Chapter 6 --- Predictive Multibody Kinematics --- p.98Chapter 6.1 --- Introduction --- p.98Chapter 6.2 --- Dynamic Management of Multibody System --- p.100Chapter 6.2.1 --- Multibody Representation --- p.100Chapter 6.2.2 --- Paradigm Overview --- p.101Chapter 6.3 --- Motion Estimation by Joint Extrapolation --- p.102Chapter 6.3.1 --- Individual Joint Extrapolation --- p.102Chapter 6.3.2 --- Forward Propagation of Joint State --- p.104Chapter 6.3.3 --- Pose Correction --- p.107Chapter 6.4 --- Limitations on Predictive Articulated State Management --- p.108Chapter 6.5 --- Implementation and Results --- p.109Chapter 6.6 --- Conclusion --- p.112Chapter 7 --- Complete System Architecture --- p.113Chapter 7.1 --- Server Cluster Model --- p.113Chapter 7.1.1 --- Peer-Server Systems --- p.114Chapter 7.1.2 --- Server Hierarchies --- p.114Chapter 7.2 --- Multi-Level Resource Management --- p.115Chapter 7.3 --- Aggregation of State Updates --- p.116Chapter 7.4 --- Implementation Issues --- p.117Chapter 7.4.1 --- Medical Visualization --- p.117Chapter 7.4.2 --- Virtual Walkthrough Application --- p.118Chapter 7.5 --- Conclusion --- p.119Chapter 8 --- Conclusions and Future directions --- p.121Chapter 8.1 --- Conclusion --- p.121Chapter 8.2 --- Future Research Directions --- p.122Chapter A --- Quaternion Basis --- p.124Chapter A.1 --- Basic Quaternion Mathematics --- p.124Chapter A.2 --- The Exponential and Logarithmic Maps --- p.125Bibliography --- p.12

    Formalizing a Framework for Dynamic Hybrid Strategy Models in Distributed Interactive Applications

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    Predictive contract mechanisms such as dead reckoning are widely employed to support scalable remote entity modelling in Distributed Interactive Applications (DIAs). By employing a form of controlled inconsistency, a reduction in network traffic is achieved. Previously, we have proposed the Dynamic Hybrid Strategy Model (DHSM) as an extension to the concept of dead reckoning that adaptively selects extrapolation models based on the use of local performance criteria. In this paper, we formalize the notion of the DHSM as a generalized framework for network traffic reduction in DIAs, alongside a set of consistency metrics for use as local performance criteria

    Multistep-Ahead Neural-Network Predictors for Network Traffic Reduction in Distributed Interactive Applications

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    Predictive contract mechanisms such as dead reckoning are widely employed to support scalable remote entity modeling in distributed interactive applications (DIAs). By employing a form of controlled inconsistency, a reduction in network traffic is achieved. However, by relying on the distribution of instantaneous derivative information, dead reckoning trades remote extrapolation accuracy for low computational complexity and ease-of-implementation. In this article, we present a novel extension of dead reckoning, termed neuro-reckoning, that seeks to replace the use of instantaneous velocity information with predictive velocity information in order to improve the accuracy of entity position extrapolation at remote hosts. Under our proposed neuro-reckoning approach, each controlling host employs a bank of neural network predictors trained to estimate future changes in entity velocity up to and including some maximum prediction horizon. The effect of each estimated change in velocity on the current entity position is simulated to produce an estimate for the likely position of the entity over some short time-span. Upon detecting an error threshold violation, the controlling host transmits a predictive velocity vector that extrapolates through the estimated position, as opposed to transmitting the instantaneous velocity vector. Such an approach succeeds in reducing the spatial error associated with remote extrapolation of entity state. Consequently, a further reduction in network traffic can be achieved. Simulation results conducted using several human users in a highly interactive DIA indicate significant potential for improved scalability when compared to the use of IEEE DIS standard dead reckoning. Our proposed neuro-reckoning framework exhibits low computational resource overhead for real-time use and can be seamlessly integrated into many existing dead reckoning mechanisms

    Multistep-Ahead Neural-Network Predictors for Network Traffic Reduction in Distributed Interactive Applications

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    Predictive contract mechanisms such as dead reckoning are widely employed to support scalable remote entity modeling in distributed interactive applications (DIAs). By employing a form of controlled inconsistency, a reduction in network traffic is achieved. However, by relying on the distribution of instantaneous derivative information, dead reckoning trades remote extrapolation accuracy for low computational complexity and ease-of-implementation. In this article, we present a novel extension of dead reckoning, termed neuro-reckoning, that seeks to replace the use of instantaneous velocity information with predictive velocity information in order to improve the accuracy of entity position extrapolation at remote hosts. Under our proposed neuro-reckoning approach, each controlling host employs a bank of neural network predictors trained to estimate future changes in entity velocity up to and including some maximum prediction horizon. The effect of each estimated change in velocity on the current entity position is simulated to produce an estimate for the likely position of the entity over some short time-span. Upon detecting an error threshold violation, the controlling host transmits a predictive velocity vector that extrapolates through the estimated position, as opposed to transmitting the instantaneous velocity vector. Such an approach succeeds in reducing the spatial error associated with remote extrapolation of entity state. Consequently, a further reduction in network traffic can be achieved. Simulation results conducted using several human users in a highly interactive DIA indicate significant potential for improved scalability when compared to the use of IEEE DIS standard dead reckoning. Our proposed neuro-reckoning framework exhibits low computational resource overhead for real-time use and can be seamlessly integrated into many existing dead reckoning mechanisms

    Recent Advances in Indoor Localization Systems and Technologies

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    Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

    Maritime Augmented Reality mit a prioriWissen aus Seekarten

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    The main objective of this thesis is to provide a concept to augment mar- itime sea chart information into the camera view of the user. The benefit is the simpler navigation due to the offered 3D information and the overlay onto the real 3D environment. In the maritime context special conditions hold. The sensor technologies have to be reliable in the environment of a ship’s ferrous construction. The aug- mentation of the objects has to be very precise due to the far distances of observable objects on the sea surface. Furthermore, the approach has to be reliable due to the wide range of light conditions. For a practical solution, the system has to be mobile, light-weight and with a real-time performance. To achieve this goal, the requirements are set, the possible measurement units and the data base structure are presented. First, the requirements are analyzed and a suitable system is designed. By the combination of proper sensor techniques, the local position and orienta- tion of the user can be estimated. To verify the concept, several prototypes with exchangeable units have been evaluated. This first concept is based on a marker-based approach which leads to some drawbacks. To overcome the drawbacks, the second aspect is the improvement of the sys- tem and the analysis of markerless approaches. One possible strategy will be presented. The approach uses the statistical technique of Bayesian networks to vote for single objects in the environment. By this procedure it will be shown, that due to the a priori information the underlying sea chart system has the most benefit. The analysis of the markerless approach shows, that the sea charts structure has to be adapted to the new requirements of interactive 3D augmentation scenes. After the analysis of the chart data concept, an approach for the optimization of the charts by building up an object-to-object topology within the charts data and the Bayesian object detection approach is presented. Finally, several evaluations show the performance of the imple- mented evaluation application.Diese Arbeit stellt ein Konzept zur Verfügung, um Seekarteninformationen in eine Kamera so einzublenden, dass die Informationen lagerichtig im Sichtfeld des Benutzers erscheinen. Der Mehrwert ist eine einfachere Navigation durch die Nutzung von 3D-Symbolen in der realen Umgebung. Im maritimen Umfeld gelten besondere Anforderungen an die Aufgabenstellung. Die genutzten Sensoren müssen in der Lage sein, robuste Daten in Anwesenheit der eisenhaltigen Materialien auf dem Schiff zu liefern. Die Augmentierung muss hoch genau berechnet werden, da die beobachtbaren Objekte zum Teil sehr weit entfernt auf der Meeresoberfläche verteilt sind. Weiterhin gelten die Bedingungen einer Außenumgebung, wie variierende Wetter- und Lichtbedingungen. Um eine praktikable Anwendung gewährleisten zu können, ist ein mobiles, leicht-gewichtiges und echtzeitfähiges System zu entwickeln. In dieser Arbeit werden die Anforderungen gesetzt und Konzepte für die Hardware- und Softwarelösungen beschrieben. Im ersten Teil werden die Anforderungen analysiert und ein geeignetes Hardwaresystem entwickelt. Durch die passende Kombination von Sensortechnologien kann damit die lokale Position und Orientierung des Benutzers berechnet werden. Um das Konzept zu evaluieren sind verschiedene modulare Hardware- und Softwarekonzepte als Prototypen umgesetzt worden. Das erste Softwarekonzept befasst sich mit einem markerbasierten Erkennungsalgorithmus, der in der Evaluation einige Nachteile zeigt. Dementsprechende Verbesserungen wurden in einem zweiten Softwarekonzept durch einen markerlosen Ansatz umgesetzt. Dieser Lösungsansatz nutzt Bayes'sche Netzwerke zur Erkennung einzelner Objekte in der Umgebung. Damit kann gezeigt werden, dass mit der Hilfe von a priori Informationen die dem System zugrunde liegenden Seekarten sehr gut zu diesem Zweck genutzt werden können. Die Analyse des Systemkonzeptes zeigt des weiteren, dass die Datenstruktur der Seekarten für die Anforderungen einer interaktiven, benutzergeführten 3D- Augmentierungsszene angepasst werden müssen. Nach der ausführlichen Analyse des Seekarten-Datenkonzeptes wird ein Lösungsansatz zur Optimierung der internen Seekartenstruktur aufgezeigt. Dies wird mit der Erstellung einer Objekt-zu-Objekt-Topologie in der Datenstruktur und der Verbindung zum Bayes'schen Objekterkennungsalgorithmus umgesetzt. Anschließend zeigen Evaluationen die Fähigkeiten des endgültigen Systems

    Humanoid Robots

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    For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

    Aeronautical enginnering: A cumulative index to a continuing bibliography (supplement 312)

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    This is a cumulative index to the abstracts contained in NASA SP-7037 (301) through NASA SP-7073 (311) of Aeronautical Engineering: A Continuing Bibliography. NASA SP-7037 and its supplements have been compiled by the Center for AeroSpace Information of the National Aeronautics and Space Administration (NASA). This cumulative index includes subject, personal author, corporate source, foreign technology, contract number, report number, and accession number indexes
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