Research on hand-eye calibration method of robot grasping system based on visual guidance

Abstract

[Objective] Designing a apace grid-based hand-eye calibration method to reduce robot positioning errors and calibration object Recognition errors in automated food production lines. [Methods] Based on the composition of the attitude matrix, the attitude and position of the end of the robot relative to the camera were obtained by translating and rotating the end of the robot, and a registration method using known corresponding point pairs was proposed to reduce the influence of the robot positioning error on the attitude solution in the translation method. Based on the space circle fitting method, a two-point vector method was proposed to solve the end position, which reduced the amount of data collection. A method of fitting the center of the sphere was proposed to compensate for the result of hand-eye calibration. [Results] The average measured error after calibration is 0.8 mm. [Conclusion] The hand-eye system based on the Eye-In-Hand type, can realize high-precision object positioning.

Keywords

• point cloud registration
• eye-in-hand
• hand-eye calibration
• positioning compensation
• robot
• food automatic production line