In this paper, a novel method for robotic belt gri nding based on support vector machine and particle swarm optimization algorithm is presented. Firstly, the dynamic model of the robotic belt grinding process is ...
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ISBN:
(纸本)9781424472796
In this paper, a novel method for robotic belt gri nding based on support vector machine and particle swarm optimization algorithm is presented. Firstly, the dynamic model of the robotic belt grinding process is built using support vector machine method. This is the basis of our work because the dynamic model shows the relation between the removal and control parameters (contact force and robot's speed) of robot. Secondly, the method of reverse solution of the dynamic model is introduced. According to this method, control parameters of robot can be accurately calculated by the given value of removal. Finally, the PSO algorithm is introduced to get smooth and stable trajectories of the control parameters, because the trajectory jitter of the control parameters has a great influence on the grinding accuracy. The experiment results show that the novel method for robotic belt grinding performs well in the control of the robot parameters and the grinding accuracy is improved.
In this paper, a novel approach for person-independent head pose estimation in gray-level images is presented. There are two steps of the proposed method. In order to preserve similar patterns of faces under various p...
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In this paper, a novel approach for person-independent head pose estimation in gray-level images is presented. There are two steps of the proposed method. In order to preserve similar patterns of faces under various poses, a novel multi-view face detector using tree-structured cascaded-Adaboost classifiers is applied. Furthermore, based on the cropped face images, randomized regression trees are learned and applied to estimate head pose precisely. Experiments show that our method achieves better pose estimation results in both horizontal and vertical orientations in comparison with the reported result with skin color information.
Immune clone selection algorithm (ICSA) and the multi-user detection based on ICSA are studied. Similar to evolutionary algorithms, ICSA is an efficient tool in searching for the global optimum based on the representa...
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robotic belt grinding system has good prospect to release hand-grinder from their dirty and noisy working environment. However, as a kind of non-rigid processing system, it is a challenge to model its processes precis...
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ISBN:
(纸本)9781424457014
robotic belt grinding system has good prospect to release hand-grinder from their dirty and noisy working environment. However, as a kind of non-rigid processing system, it is a challenge to model its processes precisely for free-form surface because its performance is unstable due to a variety of factors, such as belt wear and belt replacement. In order to adapt to the variability, an adaptive modeling approach based on echo state network (ESN) is presented, whose major idea is to exhaust information from new data by using sliding window technique to select training samples. With machine learning paradigm this approach is more flexible than traditional ones which often base on formula and experimental curves. Experimental results of grinding turbine blades demonstrate this approach is workable and effective.
We address the problem of prototype design for open set face recognition (OSFR) using single sample image. Normalized Correlation (NC), also known as Cosine Distance, offers many benefits in accuracy and robustness co...
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ISBN:
(纸本)9781424475421
We address the problem of prototype design for open set face recognition (OSFR) using single sample image. Normalized Correlation (NC), also known as Cosine Distance, offers many benefits in accuracy and robustness compared to other distance measurement in OSFR problem. Inspired by classical Learning Vector Quantization (LVQ), a novel discriminative learning method is proposed to design a discriminative prototype used by NC classifier. Specifically, we develop an objective function that fixes the NC score between the prototype and within-class sample at a high level and minimizes the similarity between the prototype and between-class samples. Several experiments conducted on benchmark databases demonstrate the superior performance of the prototype designed compared to the original one.
This paper describes an approach for extracting words, textlines and text blocks by analyzing the spatial configuration of connected domain and word contour rectangles on a given document image. The basic idea is that...
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This paper describes an approach for extracting words, textlines and text blocks by analyzing the spatial configuration of connected domain and word contour rectangles on a given document image. The basic idea is that connected components of black pixels and contours can be used as computational units in document image analysis. In this paper, we try to find a spatial feature and overlapped relationships for every contour rectangle, and we call this feature rectangle “Standard Rectangle”(SR). Then we calculate the split line of every textline according to a series of operations of SRs, and separate the word contour rectangles to different lines. In the next step we estimate that if the adjacent textlines is overlapped. If it is, we calculate the overlap distance and move the word contour rectangles according to it. Our experiment show the approach does good work on both overlapped textlines and detached textlines.
A nonlinear output feedback controller is developed for an Underactuated manipulator in this paper. The PPR planar Underactuated manipulator consists of two active joints and one passive joint. The dynamic constraint ...
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A nonlinear output feedback controller is developed for an Underactuated manipulator in this paper. The PPR planar Underactuated manipulator consists of two active joints and one passive joint. The dynamic constraint on the free link is 2nd-order non-holonomic. Firstly, the motion equations are transformed into a special form using some global coordinate and input transformations. Secondly, a time-varying feedback controller is developed using Lyapunov's direct method and an extension of the current popular backstepping technique. The control method is able to force the end-effector of a three DOF planar underactuated manipulator to globally asymptotically track a reference trajectory. And the stability of the control method is proved. Simulation results are provided to demonstrate the effectiveness of the proposed control laws.
In this paper, a novel method for robotic belt grinding based on support vector machine and particle swarm optimization algorithm is presented. Firstly, the dynamic model of the robotic belt grinding process is built ...
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ISBN:
(纸本)9781424493197
In this paper, a novel method for robotic belt grinding based on support vector machine and particle swarm optimization algorithm is presented. Firstly, the dynamic model of the robotic belt grinding process is built using support vector machine method. This is the basis of our work because the dynamic model shows the relation between the removal and control parameters (contact force and robot's speed) of robot. Secondly, the method of reverse solution of the dynamic model is introduced. According to this method, control parameters of robot can be accurately calculated by the given value of removal. Thirdly, the standard PSO algorithm is introduced to get smooth and stable trajectories of the control parameters, because the trajectory jitter of the control parameters has a great influence on the grinding accuracy. Finally, a variation on the traditional PSO algorithm is presented, which is called the cooperative particle swarm optimizer, or CPSO, employing cooperative behavior to significantly improve the performance of the original algorithm. The experiment results show that the novel method for robotic belt grinding performs well in the control of the robot parameters and the grinding accuracy and efficiency is improved.
The sampling storage method which used in the current data stream could not respond data tendency effectively. For the problem, this paper presents a new processing method based on curve fitting. A weighted least...
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The sampling storage method which used in the current data stream could not respond data tendency effectively. For the problem, this paper presents a new processing method based on curve fitting. A weighted least square principle is used to fit the cached stream data and better model description is obtained. Then the fitting results are analyzed by clustering algorithm, which serves as a classifier for polynomial fitting parameters According to the clustering result, the appropriate window size will be given to fit the periodic stream data. Comparing the function solutions with the actual data, the different methods are adopted to store data according to the comparison result. The experimental results indicate that the proposed method has better fitting accuracy and compression ratio, could meet the requirement of data stream processing. And the data tendency could be responded effectively by the fitting results.
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