An attitude detection method for double hemisphere capsule robot based on magnetic vector error calibration image
A capsule robot and error calibration technology, applied in the field of automation engineering technology, can solve the problems of easily missing lesion areas, identifying lesion area obstacles, and long detection time, so as to reduce hardware resources, avoid the interference of rotating magnetic fields, and improve utilization efficiency effect
Active Publication Date: 2021-04-20
DALIAN UNIV OF TECH
View PDF10 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0003] The working environment of the capsule robot is the human gastrointestinal tract with complex physiological structure. At present, the Pillcam series capsule robot produced by Israel Given Imaging Company and the OMOM capsule robot produced by Chongqing Jinshan Company have been put into clinical application. The position and attitude of the passive capsule robot are uncontrollable, and the detection time is up to 7-8 hours
[0004] The above-mentioned passive capsule robot has the following problems: (1) the detection time is long
It needs to move forward with the help of intestinal peristalsis, and cannot quickly reach the corresponding lesion area, and it is easy to miss the lesion area, resulting in missed detection
(2) It takes up a lot of image memory resources
However, the posture information obtained by vision is mainly the movement of the capsule robot in a narrow environment such as the intestinal tract, which are the rotation around its own axis and the displacement along the axis of the intestinal tract, respectively, and it cannot obtain the capsule robot’s position in the ample environment. More complex attitude information such as pitch angle and roll angle has certain limitations, and it also poses a great obstacle to identifying lesion areas
[0013] At present, no one has proposed to use the uniformity of the universal rotating magnetic field and the follow-up of the dual-hemispheric capsule robot in the magnetic field. Under the condition that there is no need to install any sensors or other devices in the dual-hemispheric capsule robot, the magnetic vector error model and A detection method for determining complex attitude information such as pitch angle and roll angle of a dual-hemispheric capsule robot in an ample environment using image features acquired by an embedded camera
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
specific Embodiment
[0096] (1) As shown in Figure 6(a), it is the position coordinate information of the feature points in the image of the first image of the gastrointestinal inner wall captured by the dual-hemispheric capsule robot. The ORB feature point recognition algorithm and the violent matching algorithm are used to perform two images For the matching of the above feature points, call the OpenCV function library for programming, so as to obtain the pairs of feature points that match each other in the two images. The pixel of the camera used in this example is 640*480. For the convenience of observation, it is used as the coordinate axis in the image. These feature points are selected after matching with the second image. The coordinate information of the feature points is shown in Figure 6 ( a) as shown.
[0097] (2) As shown in Figure 6(b), it is the feature point of the second image taken after the attitude adjustment of the dual hemispherical capsule robot. In this example, the attitud...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention discloses a method for detecting the attitude of a dual hemispherical capsule robot based on a magnetic vector error calibration image, which belongs to the technical field of automation engineering. This method utilizes the error distribution characteristics of the universal rotating magnetic vector in space, first determines the direction of the minimum azimuth error of the magnetic vector as the initial image calibration position of the attitude of the dual hemispheric capsule robot. Recognition and matching, combined with epipolar geometry and rotation matrix to obtain the relative attitude change before and after attitude adjustment, realizes the effective estimation of the actual attitude of the dual-hemispheric capsule robot. The present invention does not need any external hardware resources, and can realize the attitude estimation of the dual hemispheric capsule robot in the ample environment of the gastrointestinal tract only through the camera carried by the robot itself.
Description
technical field [0001] The invention belongs to the technical field of automation engineering, and relates to an initial image calibration position of a dual-hemispheric capsule robot based on the minimum error orientation determined by a space universal rotation magnetic vector error model, and after attitude adjustment and initial calibration obtained by an embedded wireless camera. The feature point recognition and matching of two image information, combined with the geometric constraints of the poles, obtains the attitude detection method of the axis orientation of the dual hemispheric capsule robot in the ample environment such as the gastrointestinal tract and colon. Background technique [0002] In the field of gastrointestinal endoscopic detection, due to the limitations of traditional endoscopic detection methods, it cannot detect areas such as the small intestine with complex physiological environments, and the detection process will bring great pain to patients, an...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More Patent Type & Authority Patents(China)
IPC IPC(8): A61B1/04A61B1/045A61B1/00A61B5/06
CPCA61B1/00158A61B1/041A61B1/045A61B5/062A61B5/065A61B5/066
Inventor 张永顺王智博赵晓东贾鹏志刘旭
Owner DALIAN UNIV OF TECH