Hand-eye type robot movable target extracting method with low servo accuracy based on visual sensation

Abstract

The invention discloses a method for grabbing a moving target by a vision-based hand-eye type low-servo precision robot, which is performed by the following: step 10, capturing the characteristic parameter of an image of a target object, and estimating the relative position between the target object and a camera; step 20, predicating the position of the target object in the next clock cycle ; and step 30, generating a track layout for grabbing of the moving target object, so that a controller of the robot can control a robot arm to approach the target object to realize grabbing. The method can generate a layout for the grabbing track of the moving object, thereby improving grabbing precision to finally realize grabbing of the moving object, and solving the technical difficulty of breaking through low-precision robot arm based on visual servo.

Description

technical field [0001] The invention relates to the field of robot vision control, in particular to a vision-based hand-eye low-servo precision robot moving target grasping method. Background technique [0002] With the development of science and technology and the expansion of robot application fields, people have put forward higher requirements for robot technology, hoping that robots have higher intelligence and stronger environmental adaptability. Robot visual servo research is just to meet this requirement. And unfolded. Robot visual servoing first appeared in the 1980s and developed rapidly in the mid-to-late 1990s. This is because the expansion of robot application fields and the rapid advancement of computer hardware technology have greatly improved the speed of image processing and greatly reduced the cost of dedicated image processing equipment. Compared with traditional sensor-based robot control, visual servo control has obvious advantages: higher flexibility, ...

AI Technical Summary

Problems solved by technology

[0009] Therefore, the robot visual servo control method in the prior art extracts information from the measured image, estimates the relative pose between the target object and the camera from the image information, and then uses the error between it and the expected pose to give feedback to the robot. The control method is mainly suitable for robots with relatively high position accuracy. For systems with poor position control accuracy of the robot arm, the grasping accuracy is poor, overshooting occurs during the grasping process, and even the grasping fails.

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