In recent papers, a new class of model-free (i.e., the 3-dimensional task-space model of the object is unknown) visual servoing methods was proposed that are based on the estimation of the relative camera orientation ...
ISBN:
(纸本)0780379241
In recent papers, a new class of model-free (i.e., the 3-dimensional task-space model of the object is unknown) visual servoing methods was proposed that are based on the estimation of the relative camera orientation between two views of an object. By utilizing homography-based techniques, the control problem is decoupled by separating the rotation and translation components. A single controller is used to control the rotation component, and the class members consist of various translation controllers. Each of the current class members has been proven to yield asymptotic regulation in the presence of uncertainty in the intrinsic and extrinsic calibration parameters. New control development and stability analysis techniques are crafted in this paper to develop a new translation controller that yields exponential rotation and translation regulation in the presence of uncertainty in the intrinsic and extrinsic calibration parameters. Extensions to this research can be used to yield exponential regulation by the other translation controllers in the asymptotic class presented.
In this paper, the 3-dimensional (3D) position and orientation of a camera held by the end-effector of a robot manipulator is regulated to a constant desired position and orientation despite (i) the lack of depth info...
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In this paper, the 3-dimensional (3D) position and orientation of a camera held by the end-effector of a robot manipulator is regulated to a constant desired position and orientation despite (i) the lack of depth information of the actual or desired camera position from a target, (ii) the lack of a geometric model of the target object, and (iii) uncertainty regarding both the angle and axis of rotation of the camera with respect to the robot end-effector (i.e., the orientation extrinsic camera parameters). By fusing 2D image-space and projected 3D task-space information (i.e., 2.5D visual servoing), a robust controller is developed that ensures exponential regulation of the position and orientation of the camera. The stability of the controller is proven through a Lyapunov-based analysis.
In this paper, a new continuous observer is developed to determine range information (and hence the 3-dimensional (3D) coordinates) of an object feature moving with affine motion dynamics (or the more general Riccati ...
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In this paper, a new continuous observer is developed to determine range information (and hence the 3-dimensional (3D) coordinates) of an object feature moving with affine motion dynamics (or the more general Riccati motion dynamics) with known motion parameters. The unmeasurable range information is determined from a single camera provided an observability condition is satisfied that has physical significance. To develop the observer, the perspective system is expressed in terms of the nonlinear feature dynamics. The structure of the proposed observer is inspired by recent disturbance observer results. The proposed technique facilitates a Lyapunov-based analysis that is less complex than the sliding-mode based analysis derived for recent discontinuous observer designs. The analysis demonstrates that the 3D task-space coordinates of the feature point can be asymptotically identified.
We present a combined real-time face region tracking and highly accurate face recognition technique for an intelligent surveillance system. High-resolution face images are very important to achieving accurate identifi...
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We present a combined real-time face region tracking and highly accurate face recognition technique for an intelligent surveillance system. High-resolution face images are very important to achieving accurate identification of a human face. Conventional surveillance or security systems, however, usually provide poor image quality because they use only fixed cameras to record scenes passively. We have implemented a real-time surveillance system that tracks a moving face using four pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction with the PTZ. Color information in the ROI is updated to extract features for optimal tracking and zooming. FaceIt/sup /spl reg//, which is one of the most popular face recognition software packages, is evaluated and then used to recognize the faces from the video signal. Experimentation with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.
Fuzzy Cognitive Maps (FCM) is a soft computing, modeling methodology for complex systems, which is originated from the combination of fuzzy logic and neural networks. Many different learning algorithms have been sugge...
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Most of the technological systems are characterized by complexity, coupled relationships with feedback and a demanding procedure to develop their models. This paper presents the Soft Computing technique of Fuzzy Cogni...
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An observer based control strategy is proposed for a flexible Cartesian (SCARA) Robot which is modeled as a flexible cantilever beam with a translational base support. A piezoelectric (PZT) patch actuator is bonded on...
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Autonomous mobile robots need to use spatial information about the environment in order to effectively plan and execute navigation tasks. The information can be represented at different levels of abstraction, ranging ...
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Most fuzzy modeling algorithms rely either on simplistic (grid type) or off-line (trial-and-error type) structure identification methods. The proposed neurofuzzy modeling architecture, NeuroFAST, is an on-line, struct...
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作者:
Abd-Almageed, WaelSmith, ChristopherRobotics
Artificial Intelligence and Vision Laboratory Electrical and Computer Engineering Department University of New Mexico United States
In this paper, a new technique for object classification from silhouettes is presented. Hidden Markov Models are used as a classification mechanism. Through a set of experiments, we show the validity of our approach a...
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ISBN:
(纸本)1889335185
In this paper, a new technique for object classification from silhouettes is presented. Hidden Markov Models are used as a classification mechanism. Through a set of experiments, we show the validity of our approach and show its invariance under severe rotation conditions. Also, a comparison with other techniques that use Hidden Markov Models for object classification from silhouettes is presented.
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