Vision measuring method for three-dimensional pose of spacing target

Abstract

The invention provides a visual measuring method for the space target three-dimensional pose of two-phase iterative solutions which are absolute oriented question solution and focus depth estimation adopted in three-dimensional pose calculation. The invention adopts a visual measurement mode which is arranging characteristic cursor point on a target to be measured, and comprises the following steps: camera calibrating, target imaging, image processing, characteristic point extracting and matching and three-dimensional pose calculating. The three-dimensional pose calculation is an iterative process, wherein, the iterative process is based on projecting line inversion and comprises two phases which are absolute oriented question solution and focus depth estimation. The three-dimensional pose calculation comprises the following steps: calculating the relative pose of a space target by adopting an absolute oriented solving analytical algorithm in the absolute oriented solution phase; and in the focus depth estimation phase, reconstructing the object space coordinates of each characteristic point by utilizing the relative pose calculated in the former phase, and updating the focus depth of each characteristic point by utilizing the projection thereof on a reverse projecting line. The three-dimensional pose calculation which adopts a sloving mode of two iteratedly carried out analyzing algorithms has the advantages that the accuracy is high; the convergence is fast; the calculation amount is small; and the applicable range is wide.

Description

(1) Technical field [0001] The invention relates to measurement technology, in particular to a visual measurement method for three-dimensional pose and posture of a space object. (2) Background technology [0002] Three-dimensional pose measurement refers to solving the relative pose relationship between two coordinate systems, including three translations and rotations around three coordinate axes. The point feature-based monocular vision pose measurement method uses a single camera to image the target, and uses the image coordinates of more than three non-collinear feature points in the target image to solve the relative position and relative attitude between the target and the camera. Due to its simple structure, Ease of implementation and other features have become one of the research hotspots in the field of visual measurement, and are widely used in non-contact measurement tasks in the fields of automobiles, robots, aircraft, and spacecraft. [0003] At present, the m...

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Problems solved by technology

However, the above-mentioned relative pose measurement algorithm based on the optimization method is a nonlinear problem in which the optimal variable space is N+6 dimensions (N is the number of point features), and the amount of calculation is large, which is difficult to meet the real-time requirements of industrial applications.

[0005] Haralick et al. proposed a pose determination algorithm that simultaneously calculates the target pose and feature point depth of field based on point features. This algorithm eliminates the nonlinearity of the pose determination problem caused by perspective projection by introducing the feature point depth of field variable, and has a global Convergence, however, the local convergence speed of the algorithm is slow

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