Camera and robot relative pose calibration method based on pixel space optimization

Abstract

The invention discloses a camera and robot relative pose calibration method based on pixel space optimization. According to the method, a calibration board carried at the tail end of a robot is adopted for moving inside the range of the view of a fixed camera, and space motion constraint information of the calibration board is utilized for calibration to obtain the optimal relative pose relation between the camera and a robot base. Firstly, linear invariance of a rotating matrix is utilized for solving a homogeneous transformation matrix to obtain a preliminary calibration result; then, the preliminary calibration result is used as an initial optimization value for optimization of pixel space, so that a reprojection error is made to the minimum. According to the camera and robot relative pose calibration method, the iterative optimization algorithm is adopted, no precision external measurement equipment is needed, model constraints of the image pixel space are utilized, the effective optimization initial value obtaining method is combined, the calibration result with the higher precision is obtained, and the requirement of a visual servo robot for completing positioning and grabbing working in industrial application can be met.

Description

Technical field [0001] The invention belongs to the field of advanced manufacturing and automation. Specifically, it is a method for calibrating the relative pose of a camera and a robot based on pixel space optimization. Background technique [0002] With the development of industrial robots, robot / manipulator operations based on visual servoing have been applied in more and more scenarios, which is currently the core issue of "machine substitution" and industrial transformation. Industrial robots with vision systems can interact with the environment more flexibly and intelligently, replacing humans to complete more tasks, and free workers from repetitive tasks on the assembly line. The accuracy of the visual sensor and the robot's spatial pose calibration is the key to ensuring the normal operation of the hand-eye system. The calibration accuracy determines the accuracy of the positioning and grasping of the visual servo robot. [0003] The problem of solving the relative positi...

AI Technical Summary

Problems solved by technology

The previous method attributed this kind of problem to solving the homogeneous transformation equation AX=XB. The solution to this equation is generally divided into two categories: one is based on the linear invariance of the rotation matrix [1], which linearizes the equation and uses linear Least squares solution, this kind of method first solves the rotation transformation part, and then uses the result of the rotation transformation to solve the translation transformation, which will lead to error transmission, so this kind of method is sensitive to noise and the accuracy is not high, one is the method of iterative optimization [2], this kind of method depends on the selection of optimal initial value, improper selection of initial value will make the optimization result fall into local optimum, and cannot obtain satisfactory calibration accuracy

The calibration data is obtained by observing the motion of the calibration board (this motion is caused by the motion of the robot) through the camera. The image coordinates corresponding to the feature points on the calibration board are direct observation data. The above methods do not use the imaging information of the camera.

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