Six-freedom-degree locating method and system used in process of grabbing objects by industrial robot

Abstract

The invention discloses a six-freedom-degree locating method and system used in the process of grabbing objects by an industrial robot. According to the scheme, natural features and local feature points on the surfaces of the objects to be grabbed can be extracted from images, and then recognizing and locating can be carried out through the features. According to the method, next appropriate movement of a robot can be calculated according to joint angles of the robot and a kinematic model and can be executed by the robot. Finally, according to the movement process of the robot and the recognition results of two times, 3D coordinates of vertex points on the surfaces of the objects can be calculated, a corresponding coordinate system of the objects can be established, six-freedom-degree poses of the objects can be obtained, and therefore the corresponding objects can be accurately grabbed.

Description

technical field [0001] The invention relates to the technical field of object perception of a robot system, in particular to a method and system for locating an object with six degrees of freedom during the grasping process of an industrial robot. Background technique [0002] For robots to grasp objects in real environments, a suitable vision system is crucial. In an environment where the object information is unknown in advance, the vision system must not only recognize the object, but also must give a sufficiently accurate pose of the object in the robot base coordinate system. Considering a rigid 3D object model, the object pose is 6 degrees of freedom information composed of the object's position and attitude. [0003] According to the visual features used, vision-based object localization methods are mainly divided into artificial marker-based and natural feature-based methods. The method based on artificial marking needs to paste artificial patterns on the object fo...

AI Technical Summary

Problems solved by technology

Stereo vision equipment is expensive, large in size and quality, and is not suitable for use in some occasions

However, the existing monocular vision-based object positioning methods only start from images of the moving process or use known coordinate information, resulting in an overly complex calculation process or requiring additional work to obtain prior knowledge of the object.

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