This research is aimed at the development of a dynamic control to enhance the performance of the existing dynamic controllers for mobile robots. System dynamics of the car-like robot with non-holonomic constraints wer...
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The main ideas and objectives of High Speed systemsengineering (HSSE) are presented. HSSE is being used as integrating pedogogical and research platforms to train modern engineers and future researchers. The newly de...
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The main ideas and objectives of High Speed systemsengineering (HSSE) are presented. HSSE is being used as integrating pedogogical and research platforms to train modern engineers and future researchers. The newly developed classes and the changes made in the curriculum is enhancing interaction between faculty, graduate and undergraduate students. A study shows that HSSE has been successful in encouraging students from all undergraduate levels to participate in learning and experimenting, also are encouraged to be involved in research and graduate studies.
Object segmentation is a crucial task in image processing. A robust semi-automated object segmentation approach is introduced in this paper. The proposed approach learns segmentation from a small number of user-prepar...
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Object segmentation is a crucial task in image processing. A robust semi-automated object segmentation approach is introduced in this paper. The proposed approach learns segmentation from a small number of user-prepared (ground-truth) samples. The segmentation is performed in two main sequential stages, namely, target object localization by applying optimal mathematical morphology procedure, and segmentation, by conducting some basic image processing operations. The outstanding feature of this approach is, unlike other existent approaches, that it does not need apriori knowledge or a large number of samples to learn from. The training is performed for a group of images to segment a specific object. The performance of the approach has been examined by a comprehensive well-designed validation set. For all test images, the target object was segmented accurately and the conducted experiments clearly show that the proposed segmentation approach is highly invariant to noise, rotation, translation, overlapping, scaling, and combination of them. The architecture of the approach and employed methodologies are explained in detail. Results are provided.
Human visual system can recognize incomplete contours and objects easily. However, these kind of recognition tasks are extremely challenging in computer and robot vision. This paper demonstrates how combination of gen...
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Human visual system can recognize incomplete contours and objects easily. However, these kind of recognition tasks are extremely challenging in computer and robot vision. This paper demonstrates how combination of genetic algorithms and morphology operations can be used to generate an image processing procedure for recognition of subjective objects (e.g. incomplete objects). In order to acquire the optimal object recognition procedure, the approach receives the subjective object and the corresponding user-prepared gold sample (physical object which reflects the user's visual expectations). After carrying out the training or optimization phase, the optimal procedure is generated and ready to be applied on new subjective objects (the same object but with different incomplete parts, sizes, etc.). No dependency on domain knowledge or huge number of sample images, one time training for a group of images, and robust object recognition are the novel features of the proposed approach. The training takes place based on one gold sample. This desirable characteristic reduces the level of dependency on expert participation which is usually an obstacle for full automation in most applications. The approach architecture and the employed methodologies are explained in detail. The performance of the approach has been evaluated by several well-prepared experiments to recognize various incomplete objects.
Today's general-purpose processors are increasingly using multithreading in order to better leverage the additional on-chip real estate available with each technology generation. Simultaneous multi-threading (SMT)...
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Today's general-purpose processors are increasingly using multithreading in order to better leverage the additional on-chip real estate available with each technology generation. Simultaneous multi-threading (SMT) was originally proposed as a large dynamic superscalar processor with monolithic hardware structures shared among all threads. Inters hyper-threaded Pentium 4 processor partitions the queue structures among two threads, demonstrating more balanced performance by reducing the hoarding of structures by a single thread. IBM's Power5 processor is a 2-way chip multiprocessor (CMP) of SMT processors, each supporting 2 threads, which significantly reduces design complexity and can improve power efficiency. This paper examines processor partitioning options for larger numbers of threads on a chip. While growing transistor budgets permit four and eight-thread processors to be designed, design complexity, power dissipation, and wire scaling limitations create significant barriers to their actual realization. We explore the design choices of sharing, or of partitioning and distributing, the front end (instruction cache, instruction fetch, and dispatch), the execution units and associated state, as well as the L1 Dcache banks, in a clustered multi-threaded (CMT) processor. We show that the best performance is obtained by restricting the sharing of the L1 Dcache banks and the execution engines among threads. On the other hand, significant sharing of the front-end resources is the best approach. When compared against large monolithic SMT processors, a CMT processor provides very competitive IPC performance on average, 90-96% of that of partitioned SMT while being more scalable and much more power efficient. In a CMP organization, the gap between SMT and CMT processors shrinks further, making a CMP of CMT processors a highly viable alternative for the future
In embedded system development, multi-tasks design is often used on real-time OS or interrupt driven environment. The multi-task programming development gives many advantages for developers. However, tasks should be c...
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The notion of dynamic abstraction was recently introduced as a means of abstracting a model during the process of model checking. In this paper we show, theoretically and practically, how dynamic abstraction can be us...
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The Coordinated Hybrid Agent (CHA) framework for the control of Multi-Agent systems (MASs) has been used to model both the homogeneous and the heterogeneous multi-agent systems. In this framework, the control of the M...
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The focus of this paper is the use of structured neural networks for sensorless control of AC machines using the zero sequence carrier signal voltage. Structured neural networks allow effective compensation of saturat...
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The focus of this paper is the use of structured neural networks for sensorless control of AC machines using the zero sequence carrier signal voltage. Structured neural networks allow effective compensation of saturation-induced saliencies as well as other secondary saliencies. In comparison with classical compensation methods, such as lookup tables, this technique has advantages such as physics-based structure (and thus is potentially insightful), general scalability, reduced size and complexity, and correspondingly reduced commissioning time. When compared with traditional neural network solutions, the structured neural networks are simpler, physically insightful, less computationally intensive and easier to train. All make the proposed method an improved implementation for sensorless drives.
The number of unknown parameters in a high degree-of-freedom (DOF) robot makes traditional identification techniques difficult to implement. A non-conventional system identification method is proposed to model the Fre...
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The number of unknown parameters in a high degree-of-freedom (DOF) robot makes traditional identification techniques difficult to implement. A non-conventional system identification method is proposed to model the Freedom 6S, a force feedback hand controller with 6 DOF. Compared to industrial robots, haptic devices are back-drivable, and they are characterized by relatively large forces and low friction. Our method is used to identify parameters such as the mass, centroid, inertia and friction of the manipulator. The number of unknown parameters in the dynamic equations describing the system can be reduced by physically locking down selected joints. This reduced parameter set can then be identified by a method of nonlinear optimization, using measured data as a basis for cost-function evaluation. By an appropriate sequence of joint analysis, all the parameters can then be identified. This paper discusses the systematic locking order of joints with the objective of reducing the number of parameters requiring identification at each stage. The method is verified by comparison between simulated and measured dynamic data
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