Robot eye-on-hand system structured light plane parameter calibration device and method

Abstract

The invention discloses a robot eye-on-hand system structured light plane parameter calibration device and a method. According to the device, a camera and a laser device are installed at the tail end of a robot to form a robot eye-on-hand system, and on the premise of obtaining camera intrinsic parameters, plane parameters of structured light projected by the laser device are calibrated, and thereby structured light three-dimensional vision measurement can be achieved. The robot eye-on-hand system structured light plane parameter calibration method includes that a plane checkerboard target is placed in a calibration area, laser lights are projected on the target to form a first line structured light stripe, the robot is controlled to move in a constraint mode so as to project the laser lights to another position of the target to form a second line structured light stripe, the camera respectively acquires images of two structured light stripes at two calibration positions, the relation of three-dimensional coordinate of points on stripe straight lines under a camera coordinate system at the two calibration positions is calculated, and thereby the structured light plane parameter calibration with the structured light stripe straight lines serving as calibration elements can be achieved.

Description

technical field [0001] The invention belongs to the field of robot structured light vision measurement, in particular to a device and method for calibrating structured light plane parameters based on linear primitives in a robot hand-eye system. Background technique [0002] Structured light vision is considered to be a promising visual measurement method because of its high measurement accuracy and strong anti-interference ability. The main task of the structured light vision system is to measure the three-dimensional position of the spatial scene point. Taking the line structured light vision system as an example, it has two configuration forms in 3D vision measurement: one uses two or more cameras to collect structured light stripe images, and calculates the 3D position of the scene point through binocular vision matching; The configuration method does not need to calibrate the structured light parameters; the other uses a camera and a laser to measure the three-dimensio...

AI Technical Summary

Problems solved by technology

The above two methods realize the calibration of structured light parameters by selecting feature points on the stripes, which have the following limitations: first, the method of extracting calibration feature points can only obtain a limited number of calibration feature points; There is a certain width of the stripes. In the image processing stage, the method of extracting feature points is easy to cause measure

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