This paper proposed a novel dual-threshold computation method of Canny edge detector based on gradient magnitude histogram (GMH), targeting with the adaptive acquisition of low-/high-threshold for unimodal hysteresis ...
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ISBN:
(纸本)9781479908813
This paper proposed a novel dual-threshold computation method of Canny edge detector based on gradient magnitude histogram (GMH), targeting with the adaptive acquisition of low-/high-threshold for unimodal hysteresis thresholding. With the introduction of the bowstring concept, which accurately measures the tendency of the GMH on the whole, the dual-threshold computation is implemented by adaptive-searching two tangent points with transitional characteristics. This skillful algorithm of the dual-threshold computation method is further evaluated by using the receiver operating characteristics (ROC) curve evaluation method. The detailed comparison to the Otsu's method is presented and demonstrates the reliability and robust performance of the proposed dual-threshold computation method.
This paper considers the distributed attitude tracking problem of multiple spacecraft with disturbances and unknown inertia matrices. Based on the relative attitudes and angular velocities of neighboring spacecraft, w...
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This paper considers the distributed attitude tracking problem of multiple spacecraft with disturbances and unknown inertia matrices. Based on the relative attitudes and angular velocities of neighboring spacecraft, we design a distributed robust controller to each follower to guarantee that the attitude errors between the followers and the leader converge to zero for any communication graph containing a directed spanning tree with the leader as the root. To deal with the problem of parameters uncertainties, we further propose a distributed adaptive sliding mode controller, under which the system is globally robust with respect to external disturbances and inertia matrices uncertainties.
This paper is concerned with the problem of data-driven predictive control for networked controlsystems (NCSs), which is designed by applying the subspace matrices technique, obtained directly from the input/output d...
This paper is concerned with the problem of data-driven predictive control for networked controlsystems (NCSs), which is designed by applying the subspace matrices technique, obtained directly from the input/output data transferred from networks. The networked predictive control consists of the control prediction generator and network delay compensator. The control prediction generator provides a set of future control predictions to make the closed-loop system achieve the desired control performance and the network delay compensator eliminates the effects of the network transmission delay. The effectiveness and superiority of the proposed method is demonstrated in simulation as well as experiment study.
Electro-hydraulic servo systems (EHSSs) have been widely used in industrial and military applications for their high power-to-size ratio and the ability to supply huge force. However, precise control of EHSSs cannot b...
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Electro-hydraulic servo systems (EHSSs) have been widely used in industrial and military applications for their high power-to-size ratio and the ability to supply huge force. However, precise control of EHSSs cannot be easily obtained due to their inner nonlinearity and parameter uncertainty. Variable load is another factor to decrease the tracking performance of EHSSs. Indirect adaptive robust control (IARC) was proposed to improve the tracking performance of EHSS, but due to the poor parameter adapting speed, IARC can be further improved to have better performance. Traditional projection type parameter estimation algorithm is redesigned to increase the adapting speed when parameter is changed. A fast adaptive robust control (FARC) is then proposed to speed up the parameter adapting speed, so that a better tracking performance of FARC is maintained. Simulation results show that the proposed FARC gives an improved tracking performance and a faster parameter adaptation.
The navigation precision drops rapidly when MIMU (Micro Inertial Measurement Unit) works alone. Odometer data are easy to get on land vehicle, but the performance of integration system of MIMU/odometer is not enhanced...
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ISBN:
(纸本)9781479925667
The navigation precision drops rapidly when MIMU (Micro Inertial Measurement Unit) works alone. Odometer data are easy to get on land vehicle, but the performance of integration system of MIMU/odometer is not enhanced obviously. In this work, a novel method is designed using nonholonomic constraints. When vehicle travels without slide and jump, the velocity in the plane perpendicular to forward direction is zero, as well as acceleration. Taking velocity constraint and acceleration constraint as measurement value, new measurement models are established. Integrated navigation algorithm is designed with the help of Kalman filter. With this method, the position error is 150m after 600s, and heading attitude error is 0.1°, comparing the result that the position error expands to 300m after 150s only aided by odometer.
The local invariant features SURF (Speeded Up Robust Features) is introduced into the robot visual recognition field to solve scale changes, rotation, perspective changes, changes in illumination and other problems. A...
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The local invariant features SURF (Speeded Up Robust Features) is introduced into the robot visual recognition field to solve scale changes, rotation, perspective changes, changes in illumination and other problems. A Speeded up SURF (SSURF) algorithm is proposed to meet the needs of robot visual identification. In SSURF algorithms, the main direction determination step of SURF algorithm is modified which make the search scope of the main direction becomes {-α, +α} (0 ≤ α ≤ 30°) from the original scope 360 According to compressed sensing ideas and interest points distribution histogram, the main scale search space is selected to improve the interest points searching step of SURF algorithm, so the interest points searching time-consuming is reduced. Matching the sample object and the scene using SSURF descriptor, and positioning the target position in the scene and giving ROI(region of interest). Experimental results in the autonomous mobile robot platform show that the proposed method significantly improves the speed of the robot to identify the target object, and proved robust to the scale changes, rotation, perspective changes, changes in illumination.
The local invariant feature extraction algorithm SRUF (Speeded Up Robust Features) is introduced firstly. Then the new method of finding low level visual saliency feature based on SURF is deduced. The new method pay a...
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The local invariant feature extraction algorithm SRUF (Speeded Up Robust Features) is introduced firstly. Then the new method of finding low level visual saliency feature based on SURF is deduced. The new method pay attention to Hessian matrix threshold and extract image features through changing the Hessian threshold. The number of saliency feature points change with the change of Hessian threshold. The visual saliency feature points will become sparser when Hessian threshold becomes larger. When some certain extreme thresholds which are defined as Hessian threshold Nodes are reached, the retained feature points are remarkable discriminative and stable feature points which make up the best sparse saliency features set. The feature extraction, matching and object recognition experiments of robot vision are finished to verify the new method. Experiment results show that the method is very effective.
The information fusion of vision sensor and Millimeter Wave(MMW) radar can enhance the adaptability of the Unmanned Ground Vehicle(UGV) to the complex environment. Space alignment is the basic step of information fusi...
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The information fusion of vision sensor and Millimeter Wave(MMW) radar can enhance the adaptability of the Unmanned Ground Vehicle(UGV) to the complex environment. Space alignment is the basic step of information fusion. Based on the alignment problems camera and MMW radar has existed, firstly, according to the max velocity of UGV and the different attention on the close and far object, the calibration distance is determined and divided; then, a space alignment method is presented through the corresponding space point sets in image pixel coordinate of camera and polar coordinate of MMW radar. the results are verified through the experiment and the error is also analyzed.
This paper investigates the problem of connectivity-preserving flocking of multiple autonomous agents with second-order dynamics. First, the inverse power iteration algorithm is formulated in a completely distributed ...
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ISBN:
(纸本)9781479901777
This paper investigates the problem of connectivity-preserving flocking of multiple autonomous agents with second-order dynamics. First, the inverse power iteration algorithm is formulated in a completely distributed manner to estimate the algebraic connectivity, i.e., the second smallest eigenvalue of the group Laplacian, as well as the corresponding eigenvector. Furthermore, distributed gradient-based flocking algorithms that exploit decentralized eigenvalue/eigenvector estimation are developed both to steer the agent group to the desired flocking motion and to maintain the global connectivity of the underlying network during maneuvers. Different from the common potential/tension function method which keeps certain fixed edges all the time, the algorithm proposed in this paper guarantees the global connectivity which allows any existing edge to be broken, thus gives more freedom of motions for the agents. Finally, nontrivial simulations are performed to demonstrate the correctness and effectiveness of the theoretical results.
The paper describes our preliminary investigation of haptic interaction between the human and virtual iCub robot. With haptic interaction,the user is able to have tactile sensensaiton of the robot environment,and henc...
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ISBN:
(纸本)9781479900305
The paper describes our preliminary investigation of haptic interaction between the human and virtual iCub robot. With haptic interaction,the user is able to have tactile sensensaiton of the robot environment,and hence to manipulate a robot remotely,for instance,from the user's office to perform some tasks at home,or a patient operation,realized by a surgeon several miles *** this work,haptic interaction has been implemented using a 3D joystick,Novint Falcon,to connect with a virtual robot created by the Cub Simulator,which works with YARP interface and simulates the real iCub robot developed by Italian *** this end,two approaches based on CHAI3D and MATLAB are introduced and implemented in this paper and furthermore,some ideas to improve the human-robot interaction performance have also been discussed.
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