Position and attitude measurement method based on time of flight (TOF) scanning-free three-dimensional imaging

Abstract

The invention discloses a position and attitude measurement method based on time of flight (TOF) scanning-free three-dimensional imaging, which is characterized by comprising the following steps of: establishing a three-dimensional coordinate information database for a target object, taking a TOF camera as an imaging and distance data acquisition device, selecting three identifiable objects in a photographed picture as mark points, acquiring coordinate information of the mark points in the database under a target body coordinate system, and establishing a vector group; obtaining a distance from an optical center to the mark points by a method for calculating a distance between two points in a non-iterative three-dimensional space through the data information acquired by the TOF camera, and calculating coordinates of the mark points under a camera coordinate system; and establishing another vector group, and calculating a rotation matrix and a translation matrix through a relationship between the two vector groups so as to acquire an attitude angle and translation quantity, namely a relative attitude of the target object. By the method, a large number of iterative algorithms are avoided, position and attitude can be quickly solved, and the requirement of position and attitude parameter determination accuracy can be met.

Description

technical field [0001] The invention is a position and attitude measurement method based on TOF scanless three-dimensional imaging, and belongs to the field of three-dimensional vision target position and attitude measurement. Background technique [0002] The measurement of object position and attitude has important application value in aerospace, automobile wheel positioning and other fields. In many application fields, the position and attitude must be measured before subsequent work can be carried out. [0003] Some existing technologies include a pose measurement method based on monocular vision and a pose measurement method based on binocular vision, as well as some improved and optimized methods on this basis. [0004] The monocular vision-based method uses several coplanar or non-coplanar feature cursor points and a single CCD camera to obtain a simplified mathematical model between the physical coordinates of the feature cursor and the image coordinates of the corre...

AI Technical Summary

Problems solved by technology

[0006] 1. The basic equation in the monocular algorithm is a quadratic nonlinear equation. There is no direct analytical solution, and a numerical solution needs to be iterated. Therefore, the convergence and speed of the iterative solution will greatly affect the real-time and accuracy of the measurement.

[0007] 2. For binocular stereo vision, due to the existence of various measurement errors, there is a certain error between the calculated value and the actual value of the spatial coordinate value of each feature point, so that the positional relationship between feature points no longer meets the constraints of the model , the rigid condition of the pose calculation cannot be guaranteed, and the error of the calculation result will be large

[0008] 3. Most of the methods are iterative solutions, and multi-value results appear, which brings difficulties in identification. The convergence and convergence speed of iterative solutions will greatly affect the measurement accuracy, and the convergence and convergence speed of the iterative process mainly depend on the iterative algorithm and Initial value selection

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