Elucidating the underlying mechanism of the cellular physiological activities at the molecular level is currently an important research topic in life sciences. The invention of the atomic force microscopy (AFM) provid...
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Virtual and augmented reality environments have been adopted in medicine as a means to enhance the clinician's view of the anatomy and facilitate the performance of minimally invasive procedures. Their value is tr...
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The treatment of Non-Hodgkin's lymphoma (NHL) was revolutionized by the approval of rituximab in 1997. Rituximab is a CD20-directed monoclonal antibody (mAb). Despite the great success of rituximab in the treatmen...
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In following the "Signals of Opportunity" theme of the NAECON '09 Grand Challenge, we explore the use of computer-vision technique proposed in [3]. The proposed approach is not affected by the strength o...
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We are extremely pleased to present this special issue of the Journal of Control Theory and *** dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adap...
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We are extremely pleased to present this special issue of the Journal of Control Theory and *** dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain environments over *** optimizes the sensing objectives accrued over a future time interval with respect to an adaptive control law,conditioned on prior knowledge of the system,its state,and uncertainties.A numerical search over the present value of the control minimizes a Hamilton-Jacobi-Bellman (HJB) equation providing a basis for real-time,approximate optimal control.
Particle filtering methods are gradually attaining significant importance in a variety of embedded computervision applications. For example, in smart camera systems, object tracking is a very important application an...
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Particle filtering methods are gradually attaining significant importance in a variety of embedded computervision applications. For example, in smart camera systems, object tracking is a very important application and particle filter based tracking algorithms have shown promising results with robust tracking performance. However, most particle filters involve vast amount of computational complexity, thereby intensifying the challenges faced in their real-time, embedded implementation. Many of these applications share common characteristics, and the same system design can be reused by identifying and varying key system parameters and varying them appropriately. In this paper, we present a System-on-Chip (SoC) architecture involving both hardware and software components for a class of particle filters. The framework uses parameterization to enable fast and efficient reuse of the architecture with minimal re-design effort for a wide range of particle filtering applications as well as implementation platforms. Using this framework, we explore different design options for implementing three different particle filtering applications on field-programmable gate arrays (FPGAs). The first two applications involve particle filters with one-dimensional state transition models, and are used to demonstrate the key features of the framework. The main focus of this paper is on design methodology for hardware/software implementation of multi-dimensional particle filter application and we explore this in the third application which is a 3D facial pose tracking system for videos. In this multi-dimensional particle filtering application, we extend our proposed architecture with models for hardware/software co-design so that limited hardware resources can be utilized most effectively. Our experiments demonstrate that the framework is easy and intuitive to use, while providing for efficient design and implementation. We present different memory management schemes along with results on t
The development of a novel Biologically-inspired (or Biomimetic) Autonomous Underwater Vehicle (BAUV) inspired by the Pacific electric ray is addressed. The design and hardware implementation of experimental prototype...
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ISBN:
(纸本)9781424474264
The development of a novel Biologically-inspired (or Biomimetic) Autonomous Underwater Vehicle (BAUV) inspired by the Pacific electric ray is addressed. The design and hardware implementation of experimental prototypes of the "RayBot" BAUV are described. Extensive observations of live electric rays provided key biological inspirations in the development of the BAUV. As part of the effort, a six degree-of-freedom impulse-based multi-body approach for modeling and simulation of BAUVs was also developed and validated through comparison with experimental data.
Rapid progress in graphene-based applications is calling for an inexpensive technique for creating mass graphene components with specialized shapes, sizes, and edge structures. In this paper, an Atomic Force Microscop...
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In this paper a visual Simultaneous Localization and Mapping (SLAM) algorithm suitable for indoor area measurement applications is proposed. The algorithm is focused on computational effectiveness. The only sensor use...
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In this paper a visual Simultaneous Localization and Mapping (SLAM) algorithm suitable for indoor area measurement applications is proposed. The algorithm is focused on computational effectiveness. The only sensor used is a stereo camera placed onboard a moving robot. The algorithm processes the acquired images calculating the depth of the scenery, detecting occupied areas and progressively building a map of the environment. The stereo vision-based SLAM algorithm embodies a custom-tailored stereo correspondence algorithm, the robust scale and rotation invariant feature detection and matching Speeded Up Robust Features (SURF) method, a computationally effective v-disparity image calculation scheme, a novel map-merging module, as well as a sophisticated Cellular Automata (CA)-based enhancement stage. The proposed algorithm is suitable for autonomously mapping and measuring indoor areas using robots. The algorithm is presented and experimental results for self-captured image sets are provided and analyzed.
In this paper, a prediction- and cost function-based algorithm (PCB) is proposed to implement robust freeway driving in autonomous vehicles. A prediction engine is built to predict the future microscopic traffic scena...
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In this paper, a prediction- and cost function-based algorithm (PCB) is proposed to implement robust freeway driving in autonomous vehicles. A prediction engine is built to predict the future microscopic traffic scenarios. With the help of a human-understandable and representative cost function library, the predicted traffic scenarios are evaluated and the best control strategy is selected based on the lowest cost. The prediction- and cost function-based algorithm is verified using the simulator of the autonomous vehicle Boss from the DARPA Urban Challenge 2007. The results of both case tests and statistical tests using PCB show enhanced performance of the autonomous vehicle in performing distance keeping, lane selecting and merging on freeways.
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