3D hand-eye calibration method and device for mobile robot

Abstract

The invention provides a 3D hand-eye calibration method and device for a mobile robot. The method comprises the following steps: S1, calibrating the view finding range of a camera to cover all degrees of freedom of the mobile robot; S2, recording point cloud data of a calibration ball held by the mobile robot in a camera coordinate system and a robot pose corresponding to the calibration ball in a current robot coordinate system to form n groups of point cloud data; S3, extracting the point cloud of the spherical surface of the calibration ball, and determining the coordinate value of the center point of the calibration ball in the camera coordinate system in each group of point cloud data by adopting a least square fitting algorithm; S4, solving offset and a hand-eye calibration matrix according to a first algorithm according to the pose of the robot and the coordinates of the center point of the corresponding calibration ball; and S5, converting the hand-eye calibration matrix into an Euler angle form, and taking a hand-eye calibration matrix result as an initial value of nonlinear optimization; and respectively calculating a hand-eye calibration matrix and a difference value between the offset and the truth value according to a second algorithm, and correcting the hand-eye calibration matrix according to the difference value. Therefore, the adaptation requirement for the degree of freedom of the robot is lowered, and the universality is improved.

Description

technical field [0001] The invention relates to the technical field of machine vision, in particular to a 3D hand-eye marking method and device applicable to at least one degree of freedom movement. Background technique [0002] As robot technology continues to penetrate into industrial and life scenarios, the production and use technologies of various single robots such as robotic arms, AGV cars, and ARMs are becoming more and more mature to meet the needs of different scenarios. As an actuator, these single robots can well replace people to complete some high-risk, repetitive and intensive work such as container transportation, logistics sorting and mechanical assembly. But robots, as terminal effectors, often do not have the ability to perceive. The 3D camera can obtain the three-dimensional information of the object, and has the ability to perceive the spatial position and posture of the object. In most work scenarios, robots often need 3D vision to provide guidance an...

AI Technical Summary

Problems solved by technology

[0005] However, this prior art is mainly applied to six-degree-of-freedom manipulators, so the robot needs to perform spatial rotation and translation in a specific way.

Although the calibration process is fully automatic, it requires the robot to have the ability to rotate in three degrees of freedom in space.

However, mobile robots such as AGVs and ARMs only have the ability to rotate with one degree of freedom in space, so the existing technology cannot be applied

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