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Synchronous localization and mapping method based on improved image matching strategy

An image and strategy technology, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve problems such as low efficiency, poor robustness, inaccurate maps, etc., and achieve the effect of improving elimination efficiency and enhancing robustness

Inactive Publication Date: 2018-08-17
BEIJING UNIV OF TECH
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AI Technical Summary

Problems solved by technology

Due to the random selection of sample data in the standard RANSAC (Random Sample Consensus) algorithm, the number of iterations will increase and the efficiency will be low in the case of fewer inliers
The original ORB (Oriented FAST and RotatedBRIEF) features are relatively aggregated, and the robustness is relatively poor during the tracking process
In addition, the built map is inaccurate due to the cumulative error of the visual odometry

Method used

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  • Synchronous localization and mapping method based on improved image matching strategy
  • Synchronous localization and mapping method based on improved image matching strategy
  • Synchronous localization and mapping method based on improved image matching strategy

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Embodiment Construction

[0061] The present invention aims at the problems of poor robustness in the original ORB feature tracking process, high number of iterations of RANSAC and accumulation of errors in the positioning process when feature matching is performed when the proportion of inliers is low, and adopts the present invention to improve ORB features and The improved RANSAC algorithm combined with the g2o optimization library completes the tasks of positioning and mapping. Whole flow chart of the present invention is referring to explanation appendix figure 1 , the specific implementation method is divided into the following steps:

[0062] Step 1, install the open source driver libfreenect2 of Kinect, and write the corresponding program to obtain the color map and depth map of the surrounding environment through Kinect.

[0063] Step 2, use the improved ORB feature to perform feature extraction on the image, see the attached figure 2 .

[0064] Step 3 is to perform feature matching on the...

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Abstract

The invention provides a synchronous localization and mapping method based on an improved image matching strategy. According to the method, Oriented FAST (Oriented Features from Accelerated Segment Test) angular point detection is performed on each area of the image by using the improved ORB feature, the descriptor of the feature point is calculated and then feature matching and screening are performed by using an improved RANSAC algorithm; finally the initial attitude of the robot is solved by using the PnP (Perspersctive-n-Point) method, an attitude graph is generated by using the obtained initial attitude, and then the attitude is updated by using the Levenberg-Marquardt method and the attitude is optimized by using the g2o (General Graphic Optimization, G2O) optimization library; and finally the optimized attitude and the corresponding frame are combined together so as to generate the point cloud map. According to the method, the mismatch eliminating efficiency can be enhanced andthe robustness of the tracking process can be improved so as to obtain the accurate map.

Description

technical field [0001] The invention relates to a method for synchronous positioning and mapping based on an improved image matching strategy, belonging to the fields of image matching and visual SLAM (Simultaneous Localization and Mapping). Background technique [0002] The simultaneous positioning and mapping of the robot is the key to realize the autonomous navigation of the robot. How the robot completes its own positioning and mapping in an unknown environment is a very challenging problem. Traditional GPS positioning is usually used in outdoor environments, and there is often a problem of positioning failure in indoor environments. With the continuous development of research in the field of computer vision, vision-based SLAM technology in indoor environments has gradually become a research hotspot. Since the camera can obtain richer environmental information, and with the launch of the relatively cheap Microsoft kinect depth camera, it has been applied to the field of...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/46
CPCG06V10/44G06F18/22
Inventor 贾松敏郑泽玲张祥银李明爱李秀智
Owner BEIJING UNIV OF TECH
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