Robot stereo visual servo system construction method

Abstract

The invention discloses a robot stereo visual servo system construction method. The method includes the following steps of: the first step, robot stereo visual servo system structure and stereo visualsystem model establishment; the second step, target detection and positioning research; the third step, moving object tracking and prediction research; the fourth step, robot stereo visual servo system parallel processing research; and the fifth step, robot real-time stereo visual servo system demonstration experiment. According to the robot stereo visual servo system construction method of the invention, the tracking and capturing of moving objects of images are researched; a stereo visual servo system is adopted to realize the collection, processing, recognition, tracking and positioning ofvideo information; and the tracking and capturing of the moving targets are realized through a position-based robot visual control method; and information transmission is realized through using a network.

Description

technical field [0001] The invention relates to a method for building a robot stereo vision servo system, belonging to the technical field of vision robots. Background technique [0002] In recent years, robot technology has become one of the representative strategic technologies in the high-tech field. It has revolutionized traditional industrial production. However, even the most intelligent robot in the world cannot adapt to changes in the external environment. The ability is also very limited, and there is still a long distance from people's expected goals, which greatly affects the popularization and use of robots. One of the important reasons is that robots lack human-like perception capabilities; Improvement, the research on intelligent robots with senses has become one of the important contents of the high-tech plans of governments; among people adding various external sensors to robots, visual sensors have become the most important due to their large amount of infor...

AI Technical Summary

Problems solved by technology

[0002] In recent years, robot technology has become one of the representative strategic technologies in the high-tech field. It has revolutionized traditional industrial production. However, even the most intelligent robot in the world cannot adapt to changes in the external environment. The ability is also very limited, and there is still a long distance from people's expected goals, which greatly affects the popularization and use of robots. One of the important reasons is that robots lack human-like perception capabilities; Improvement, the research on intelligent robots with senses has become one of the important contents of the high-tech plans of governments; among people adding various external sensors to robots, visual sensors have become the most important due to their large amount of information and wide application range. One of the robot sensors; the vision sensor provides the robot with very rich external information, and can achieve the recognition of the environment and the target without the movement of the sensor and without any contact with the object, which is difficult for other sensors. Therefore, robot vision is a main research direction of robot intelligence, and it is of great significance to study it

The task of visual servoing is to use visual information to control the attitude of the end of the robot hand relative to the target or a target feature set, so as to track or grasp the target; it uses the principle of machine vision to quickly perform Image processing, giving feedback information in the shortest possible time, constitutes the closed-loop control of the robot's position; the vision system is a complex sensory system, which contains a large amount of information, and to extract useful information from it requires complex algorithms and costly A lot of computing time; and the vision is usually realized through the camera, which will be affected by many factors during the imaging process (such as the accuracy of the camera, light intensity, transmission noise, etc.), making the visual information inevitably contain noise , which increases the difficulty of image processing; since the robot itself is a nonlinear and strongly coupled complex system, it is very difficult to realize robot visual servo control