Autonomous positioning method for robot
An autonomous positioning and robot technology, which is applied in the directions of instruments, image analysis, image enhancement, etc., can solve problems affecting the positioning accuracy of robots, and achieve the effects of improving image alignment accuracy, enhancing constraint relationships, and improving accuracy
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2021-06-01
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Abstract
Description
technical field
[0001] The invention relates to the fields of computer vision and robot technology, in particular to a method for autonomous positioning of a robot. Background technique
[0002] In the existing robot autonomous positioning method, the visual SLAM direct method adopted uses the assumption of photometric invariance. After the input image is directly converted into a grayscale image, the camera motion and point projection are simultaneously estimated according to the pixel grayscale information of the image. . However, according to the visual characteristics of the human eye, the human eye is more sensitive to color than grayscale; and the grayscale assumptions in the actual camera imaging system will be affected by the camera's automatic exposure and the specular reflection of the object surface. Therefore, using grayscale information alone may lead to failure of image alignment.
[0003] Simply put, image alignment, which aims to find the best image transfo...
Examples
Embodiment Construction
[0037] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0038] In the present embodiment, the autonomous positioning method of the robot comprises the following steps:
[0039] 1) The robot collects images of the current environment through the camera.
[0040] 2) Convert the current frame image collected by the camera and the reference image selected as the positioning reference into the HSI color space to obtain three components of H, S, and I.
[0041] 3) Extract the point P in the real environment space from the reference image j The projected point p in the reference image 1 j :
[0042]
[0043] pixel The grayscale value of The color components are represents the projected point the number of rows in the image array, represents the projected point the number of columns in the image array, projected point The image coordinates of .
[0044] In the above formula (1), K is the in...