This paper presents new global visual features: random distribution of limited set of pixels luminance. Our approach aims to improve the real-time performance of visual servoing applications. In fact, using these new ...
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ISBN:
(纸本)9789898565211
This paper presents new global visual features: random distribution of limited set of pixels luminance. Our approach aims to improve the real-time performance of visual servoing applications. In fact, using these new features, we reduce the computation time of the visual servoing scheme. Our method is based on a random process which ensures efficient and fast convergence of the robot. The use of our new features removes the matching and tracking process. Experimental results are presented to validate our approach.
In this work, we use the approach based on observers such as the neural observer in order to introduce the diagnosis of nonlinear systems. There are different techniques for training the neural networks. Among these t...
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This paper describes a Predictive control method used for track following control in hard disc drives (HDD). While reading/writing data, the head must be positioned on the target data track quickly and precisely, and ...
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This paper describes a Predictive control method used for track following control in hard disc drives (HDD). While reading/writing data, the head must be positioned on the target data track quickly and precisely, and with the predictive control, we have achieved good tracking with the suppression of vibrations from high-order resonance modes. Simulation results show the effectiveness of the proposed approach and the servo system with predictive control presents good performances.
The objective of our system is to detect vehicles from aerial sequences. Theses sequences are taken from a camera mounted on UAV which flies over roads and highways. Our approach is to firstly compensate the motion in...
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ISBN:
(纸本)9789898565211
The objective of our system is to detect vehicles from aerial sequences. Theses sequences are taken from a camera mounted on UAV which flies over roads and highways. Our approach is to firstly compensate the motion introduced by the dynamic behaviour of the camera. This leads us to a problem of image registration. The moving regions (vehicles) are after that extracted using residual motion. The aim of this paper is to present a combined method for features matching and outliers rejection to increase the accuracy of the registration phase. We use first, the SIFT descriptors and then outliers are rejected using geometric constraints. This leads to a better registration and a minimum of false alarms in the detection phase.
In this paper we present a system that aims at detecting and tracking moving objects from aerial video streams. These sequences are obtained from a camera mounted on an aerial vehicle which flies over roads and highwa...
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The ultrasonic sensor is the most replied sensor in mobile robot to get environmental information and avoid obstacles. In fact, this type of sensors offers satisfactory results with affordable cost. However, one senso...
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The ultrasonic sensor is the most replied sensor in mobile robot to get environmental information and avoid obstacles. In fact, this type of sensors offers satisfactory results with affordable cost. However, one sensor is insufficient for a better perception of the environment. In this paper we opt for the conception of an ultrasonic sensor network to extract as much information as possible for measuring the distance between the robot and the obstacle. The algorithm for distance calculation is based on the measurement of the time of flight for the ultrasonic wave. The experimental results show a good performance of the conceived system for the distinction between different shapes of obstacles.
In this paper we present an overview of recent robust approaches which aim 2D visual servoing systems. Since Visual servoing has been considered as a very effective technique for positioning and tracking functionaliti...
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In this paper we present an overview of recent robust approaches which aim 2D visual servoing systems. Since Visual servoing has been considered as a very effective technique for positioning and tracking functionalities, its main goal was to find good selections of visual data in order to be injected in a closed-loop. To guarantee the visual servoing robustness, it is important to alter many techniques like extraction, matching, tracking and path planning. The robustness depends on the error minimization which means the ability to resist severe outliers and to analyze confidence in each feature. Thereby, we can accomplish a better control and an accurate robotic task.
In this work, we use the approach based on observers such as the neural observer in order to introduce the diagnosis of nonlinear systems. There are different techniques for training the neural networks. Among these t...
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In this work, we use the approach based on observers such as the neural observer in order to introduce the diagnosis of nonlinear systems. There are different techniques for training the neural networks. Among these techniques, we quote the backpropagation technique, the backpropagation technique with momentum and the hybrid one which is a mixture between the backpropagation technique and the sliding variable structure. The robustness of this kind of training for neural observer is tested through a physical example. The obtained results show that the third type of training is better than using a classic kind of training especially concerning the rapidity of convergence.
In this paper, the Bouc-Wen model widely used in describing hysteretic systems is applied to piezoelectric actuator (PEA) modelling and real-coded adaptive genetic algorithm (GA) is adopted to identify the model param...
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ISBN:
(纸本)9787900769428
In this paper, the Bouc-Wen model widely used in describing hysteretic systems is applied to piezoelectric actuator (PEA) modelling and real-coded adaptive genetic algorithm (GA) is adopted to identify the model parameters simultaneously. By dynamically adjusting the crossover probability and mutation probability, adaptive genetic algorithm improves the performance of local convergence and premature convergence and enhances search speed and precision of the simple genetic algorithm. Then some experiments are conducted to verify the efficiency of the identification method with satisfactory parameter identification results.
Face recognition is one of the most efficient applications of computer authentication and pattern recognition. Therefore it attracts significant attention of researchers. In the past decades, many feature extraction a...
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Face recognition is one of the most efficient applications of computer authentication and pattern recognition. Therefore it attracts significant attention of researchers. In the past decades, many feature extraction algorithms have been proposed. In this paper Gabor features and Zernike moment were used to extract features from human face images for recognition application. This paper is a study for new constructive training algorithm for Multi Layer Perceptron (MLP) which is applied to face recognition application. An incremental training procedure was employed where the training patterns are learned incrementally. This algorithm started with a single training pattern and a single hidden-layer using one neuron. During neural network training, the hidden neuron is increased when the Mean Square Error (MSE) of the Training Data (TD) is not reduced or the algorithm gets stuck in a local minimum. Input patterns are trained incrementally (one by one) until all patterns of TD are selected and trained. Face recognition system structure based on a MLP neural network was constructed and was tested for face recognition. The proposed approach was tested on the UMIST database. Experimental results indicate that we can obtain an optimal architecture of neural network classifier (with the least possible number of hidden neuron) using our present constructive algorithm, and prove the effectiveness of the proposed method compared to the MLP architecture with back-propagation algorithm.
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