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ABSTRACT: A nonlinear model and control of a small-scale helicopter near hovering are investigated. Aiming at the characteristics of the model helicopter, the stabilizer bar dynamics is studied, and the tail rotor with the electronic gyro is discussed in detail. In addition, the main rotor inflow dynamics is modeled basing on the three-state nonlinear Pitt/Peters model. Then, a simplified nonlinear model is proposed for system identification and controller design. It is proved that the attitude-heave subsystem can be linearized by the dynamic feedback linearization technique. So, we conclude that the full nonlinear model can also be feedback linearized.
Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on; 01/2010
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ABSTRACT: In this paper we propose a new method of detecting moving objects from a moving camera based on SIFT(The Scale Invariant Feature Transform) features matching and dynamic background modeling. Firstly, feature points are extracted by SIFT algorithm to compute the affine transformation parameters of camera motion, and guided by RANSAC to remove the outliers. We adopt background subtraction approach to detect moving objects, with shadow and ghost removing. The robustness of SIFT Features matching and the validity of picking out outliers by a RANSAC algorithm make the parameters of affine transform model to be computed accurately, and by the background subtraction approach with dynamically-updated background model, foreground objects can be detected perfectly. Experimental results demonstrate that our algorithm can detect moving objects accurately, and keep the integrity of foreground objects, comparing with optical flow method.
Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on; 01/2010
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ABSTRACT: The problem of multi-robot cooperative localization based on relative bearings is researched in this paper. Relative bearings of different robots are fused with motions to improve the localization accuracy of robots. We analyse the situations about relative positions of the robots and their motion trajectories. Some relative positions and motion trajectories of the robots easily lead to not-converged localization results. We present an improved method to overcome the fault. The robust and practicability of localization are greatly increased. Simulation results prove the method is effective in dealing with the cooperative localization problem.
Robotics and Biomimetics, 2008. ROBIO 2008. IEEE International Conference on; 03/2009
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ABSTRACT: This paper copes with the problem of identifying the attitude dynamics of a small scale helicopter using the frequency sweep technology based on the flight data collected near the hovering condition. The frequency domain responses of a helicopter in the lateral, longitudinal and yaw channels are analysed by the partial coherence method, and the transfer functions are obtained by the weighted fitting method. The proposed method can identify the attitude dynamics including the actuator dynamics using the flight data only without carrying out any additional ground experiments. The models identified are verified by comparing model outputs with the experimental data on a small scale helicopter in our lab. We also carried out experiments on the attitude control of the helicopter to further validate the identified models.
Robotics and Biomimetics, 2008. ROBIO 2008. IEEE International Conference on; 03/2009
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2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 11-15, 2009, St. Louis, MO, USA; 01/2009
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ABSTRACT: This paper presents a fully distributed algorithm for target tracking using a mobile sensor network. It tries to maintain the target being visible to the mobile network all the time while consuming as little motion energy as possible. Meanwhile the network connectivity is maintained. At every time, only the nodes around the target are activated while other nodes keep idle. Certain functions are defined to quantify the main aspects in the tracking such as the target escaping probability and the network connectivity status. They transform the tracking into a multi-objective optimization problem. To solve this global problem, a local motion strategy is proposed. Simulation results show that our algorithm yields good performance.
Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on; 10/2008
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ABSTRACT: Guarantied connectivity and coverage is the goal of redeployment in wireless sensor network, which is constrained by limited sensor resources and limited sensor transmission capability. To solve fragmentation in sparse networks, a DFS_LF (Depth-First-Search_ Leader-Follower) algorithm is applied. By searching the nearest sensor node to a virtual collective object as a leader node a tracking chain can be formed by using of Leader-Follower method. To coverage holes in dense networks, an algorithm based on RHR_C (Right-Hand-Rule_Centroid) is adopted. RHR is used to find triangle-shaped communication holes (the relationship between the communication hole and sensing coverage ratio can be identified theoretically), and then Centroid method is used to fill those holes. Simulation results proved the validity of presented algorithms.
Information and Automation, 2008. ICIA 2008. International Conference on; 07/2008
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ABSTRACT: This paper addresses the problem of tracking a dynamic target using a mobile sensor network. The algorithm aims to move as few nodes as possible to maintain the dynamic target within the coverage of the network all the time. First we define the tracking uncertainty concept and obtain its derivative with the target dynamics. Then a potential function is set up to represent the network connectivity. The nodes which detect the target broadcast the target state information. A local control strategy is proposed for the node motion to minimize the tracking uncertainty under the connectivity constraint. Simulation has been conducted to demonstrate the performance of the algorithm in different situations.
Robotics and Biomimetics, 2007. ROBIO 2007. IEEE International Conference on; 01/2008
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ABSTRACT: This paper presents an efficient target detection algorithm from a sequence of infrared images using the sequential Monte Carlo method (SMC). The algorithm employs an evolution process of the particles which correspond to the candidates of the target position and whose evolution is controlled by the weight of the target feature. Through the iterative process on the differential images, a valve of the particle set is proposed to decide if there is a target in the image, and the state of the particle set is used to position the target. The experimental results demonstrated that the algorithm can detect the target with sea-sky background effectively regardless of the existence of serious non-Gaussian noises. The experiments also showed real-time efficiency of the algorithm for target detection
Mechatronics and Automation, Proceedings of the 2006 IEEE International Conference on; 07/2006
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2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006, October 9-15, 2006, Beijing, China; 01/2006
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2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006, October 9-15, 2006, Beijing, China; 01/2006
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ABSTRACT: Traditionally, the problem of stereo matching has been addressed either by a sparse feature-based approach or a dense area-based approach. This technique still suffers from a lack in accuracy or long computation time needed to match stereo images. In this paper, we employ color segments on scan lines of stereo images as primitives for matching, and introduce the widely used fuzzy set theory to the matching processes in order to handle ambiguities in matching. During the stage of accurate pixel correspondences of matched color segments, we use the technique of dynamic time warping (DTW), which is used in speech recognition. We found that DTW works robustly and rapidly regardless of the number of points to be matched. Covering more image space than point elements and providing more information than gray level features, color segments are less sensitive to noise and photometric variations and are thus more easily matched, and can reduce the false matches. Furthermore, a post-processing step can find more matches and alleviate the influence of under-segmentation or over-segmentation. A fast median filter can be applied to the results to further remove outliers. Experiments have been performed to demonstrate the accuracy and efficiency of the algorithm.
Intelligent Robots and Systems, 2005. (IROS 2005). 2005 IEEE/RSJ International Conference on; 09/2005
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ABSTRACT: Corner detection has been shown to be extremely useful in many computer vision applications. In this paper, an improved SUSAN corner detector is proposed and its performance is compared with Harris and SUSAN corner detection. The method adopts an adaptive multi-threshold strategy based on local brightness rather than one threshold for the whole image, and divides the circular mask area of SUSAN into two or more parts. Next, the number of pixels in the part where the nucleus locates is calculated. If the number is less than half the total pixels of the circular mask, the nucleus becomes a corner candidate. The exact positions of image corners are those candidates with local minimum numbers. In order to improve the computational efficiency of the algorithm, we limit the search space for corner candidates to those pixels whose intensity gradient magnitudes by Sobel operator are higher than a threshold. Experiments have demonstrated that our corner detector is accurate and efficient.
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on; 07/2004
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ABSTRACT: This paper describes a CMPP (china mobile peer to peer) Internet distributed and adaptive system for SMS (short messaging service). It is used to provide the information for the users of the cell phones by short messages. The system for SMS is often subject to rigid restrictions of delivery, and the data stream of the system is fairly asymmetrical. Sometimes the data stream flux received by us is high, whereas sometimes low. Therefore when the data stream is very large, the data often cannot be processed by the system for SMS in real time. In order to solve the problems mentioned above efficiently, after presenting the structure of this system for SMS, we mainly introduce you two new methods, including adaptive data flow algorithm and distributed client algorithm. Finally some terse conclusions are given. Just as the experiments prove, the implemented system for SMS has some advantages in the quality, performance and adaptability of the data stream.
Robotics, Intelligent Systems and Signal Processing, 2003. Proceedings. 2003 IEEE International Conference on; 11/2003
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ABSTRACT: Stereo vision has long been one of the central research problems in computer vision, and stereo matching is the most important and difficult issue of stereovision. We propose an algorithm by fuzzy identification in fuzzy theory to cope with the uncertain and fuzzy characteristic during matching. For image pairs with dense distinct features, we adopt a feature-constrained strategy. First, we obtain a precise disparity map of edges using fuzzy logic. Next we fill in the disparity data of other points under the constraint of the acquired disparity map. For images with sparse features, we use intensity segments as elements to be matched and introduce the principle of DTW, which is applied for speech recognition, into the matching processes on the segments. Experiments with real and synthetic images have been performed to demonstrate the effectiveness of the algorithms.
Robotics, Intelligent Systems and Signal Processing, 2003. Proceedings. 2003 IEEE International Conference on; 11/2003
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ABSTRACT: This paper presents an effective algorithm for calibrating the extrinsic parameters between a camera and a laser range finder whose trace is invisible. On the basis of an analysis of three possible features, we propose to design a right-angled triangular checkerboard and to employ the invisible intersection points of the laser range finder's slice plane with the edges of the checkerboard to set up the constraints equations. The extrinsic parameters are then calibrated by minimizing the algebraic errors between the measured intersections points and their corresponding projections on the image plane of the camera. We compared our algorithm with the existing methods by both simulations and the real data of a stereo measurement system. The simulation and experimental results confirmed that the proposed algorithm can yield more accurate results.
Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on;
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ABSTRACT: To ensure safety of railway operation, it is extremely important to regularly check railway conditions such as deformation of the rails. This paper presents an on-line rail deformation monitoring system for being implement on moving train so as to timely report any deformation beyond the threshold. The system is based an effective algorithm for detecting the rail deformation using three acceleration sensors mounted on the train. The proposed method can distinguish vibrations due to track deformation from those caused by motion of the train by analysing the lateral accelerations of the train's crossbeam and the lateral acceleration of the bogie. This method is testing on the railway between Shenyang and Dalian. Through experiment of large number of collected data, the performance of the detection is applicable
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on;
