This article proposes a problem statement and its solution for finding a point equidistant from objects in three-dimensional space. The article considers an approach to determining the possible trajectory of a given object in an assumed threedimensional space R³, in which there are static 3D objects that impede the movement of the given object. A computer vision system is used for spatial positioning. To determine the point of displacement of the object's trajectory in space, a solution to the problem of searching for optimal trajectories on planes that do not intersect or touch the boundaries is proposed. The article discusses an algorithm for solving this problem and provides examples of determining optimal trajectories in a curved surface using the method of multicriterial interpolation of curves, with a given discretization step. The generation of a data set for a curved surface (point cloud) is described. Examples of searching for the hovering point of an object in the absence of its contact with external boundaries are given. An example of searching for an equidistant point in space with simple-shaped objects is given on a test data set, and recommendations are given for their use in robotic systems.
The article proposes an approach to the determination of small-form objects against a complex background. The proposed approach uses a parallel data processing algorithm that includes the following main modules: a multi-criteria image filtering block built on an objective function that minimizes the weighted average sum of the average square of the first order finite difference, as well as the average square of the distance difference between the input implementation and the generated data; parallel separation of objects by analyzing local features, statistical analysis of histogram changes, building a mask of object detailing and frequency analysis; the formation of a feature mask and the search for similarity elements by analyzing the generated features. On the test data set, an example of determining small-sized objects on a complex background with their subsequent classification into class objects is presented. The data were obtained by a machine vision system installed on a robotic complex. Data on the required parameters of the formed machine vision systems are given, recommendations on the required parameters of the algorithms are presented.
The article proposes a fusion technique and an algorithm for combining images recorded in the IR and visible spectrum in relation to the problem of processing products by robotic complexes in dust and fog. Primary data processing is based on the use of a multi-criteria processing with complex data analysis and cross-change of the filtration coefficient for different types of data. The search for base points is based on the application of the technique of reducing the range of clusters (image simplification) and searching for transition boundaries using the approach of determining the slope of the function in local areas. As test data used to evaluate the effectiveness, pairs of test images obtained by sensors with a resolution of 1024x768 (8 bit, color image, visible range) and 640x480 (8 bit, color, IR image) are used. Images of simple shapes are used as analyzed objects.
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