Target object recognition and positioning method based on color images and depth images

Abstract

The invention relates to a target object recognition and positioning method based on color images and depth images. The method is characterized by comprising the following steps that (1), a target region is confirmed by a robot by the adoption of the remote HSV color recognition, the distance between the robot and the target region is obtained according to the RGB color images and the depth images, and the robot conducts navigation and path planning and moves to the portion near the target region; (2), when the robot reaches the portion near the target region, through the SURF feature point detection, the RGB feature information of the target object is obtained, feature matching is conducted on the RGB feature information and the pre-stored RGB feature information of the target object, and if the feature of the target object accords with an existing object model, the target object is positioned; and (3), the RGB color images are collected to an imaging plane, the two-dimensional coordinates of the target object in the imaging plane are obtained, and the relative distance between the target object and a camera is obtained through the depth images, so that the three-dimensional coordinates of the target object are obtained. By the adoption of the target object recognition and positioning method, the category of the object can be judged quickly, and the three-dimensional coordinates of the object can be determined quickly.

Description

technical field [0001] The invention relates to a method for identifying and locating a target object, in particular to a method for identifying and locating a target object based on a color image and a depth image. Background technique [0002] With the improvement of people's requirements for robot functions, it has become a current development trend that mobile robots have visual functions, and work together with the robotic arm mounted on the mobile platform, "hand-eye" to complete the work. However, the traditional visual recognition positioning method uses monocular or binocular vision for positioning, which is easily affected by changes in illumination and requires a large amount of calculation. Especially for monocular vision, it is necessary to obtain three-dimensional space coordinates by comparing images taken from different angles of the same object, and the calculation is relatively complicated. Therefore, using infrared cameras and receivers to obtain object d...

AI Technical Summary

Problems solved by technology

However, when the SURF algorithm faces the occlusion of other objects around the target object, it cannot distinguish the target object well, resulting in false detection of feature points.

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