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This paper presents a multistage, real-time optimization algorithm to perform visual searches. A cost function relates the success of the visual search at any given pose in the workspace. This function is measurable at every camera pose, but it is not necessarily known as a function of changing pose, and its gradient with respect to the workspace or joint space coordinates is not known. In the first...
This paper presents a novel approach to improve the global performance of extremum seeking control to optimize static target functions. This algorithm adopts the traditional extremum seeking control to find local extrema, and a direct search algorithm to search for the global extremum. The two methods are employed in an iterative switching manner. Theoretical analysis shows that under the proposed...
This paper presents a novel approach to increasing the information content in sensor measurements, with special applications in images or video. The entropy of a signal gives a measurement of the information content. In the case of images, entropy is low when large parts of an image are uniformly colored or shaded. This can occur due to poor camera settings, poor lighting conditions, or the camera...
This paper presents a sensor fusion implementation to improve the accuracy of robot localization by combining multiple visual odometry approaches with wheel and IMU odometry. Discrete and continuous Homography Matrices are used to recover robot pose and velocity from image sequences of tracked feature points. The camera's limited field of view is addressed by chaining vision-based motion estimates...
This paper presents a novel approach to increase the amount of visual stimuli in sensor measurements using saliency maps. A saliency map is a combination of normalized feature maps in different channels (i.e. color, intensity) to represent the relative strength of visual stimuli in an image. The total saliency is higher when the camera is looking at a scene with more interesting things in the field...
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