Mobile robot navigation method based on one point RANSAC and FAST algorithm

A technology of mobile robot and navigation method, which is applied in the field of positioning and navigation of mobile robot based on image matching, and can solve the problems of reducing the calculation speed of the algorithm and increasing the number of iterations of the algorithm

Active Publication Date: 2015-09-02
CHONGQING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

The literature (FAST-based improved fast corner detection algorithm, Infrared and Laser Engineering, 2009 (6): 1104-1108) uses the improved FAST algorithm to extract corner points, and removes most edge points and local non-maximum points; On the other hand, for false matching elimination, literature (STR ASDA H, MONTIEL J M M, DAVISON A J. Real-time monocular SLAM: why filter[C], Proceedings of the IEEE International Conference on robotics and automation.2010:2657-2664 .) The RANSAC algorithm is a widely used mismatch elimination algorithm, but as the number of matching points increases, the number of iterations of the algorithm will increase rapidly, which reduces the calculation speed of the algorithm

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  • Mobile robot navigation method based on one point RANSAC and FAST algorithm
  • Mobile robot navigation method based on one point RANSAC and FAST algorithm
  • Mobile robot navigation method based on one point RANSAC and FAST algorithm

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Embodiment Construction

[0022] figure 1Shown is a mobile robot navigation method flow chart based on a little RANSAC and FAST algorithm, and its specific content is as follows:

[0023] (1) Start the mobile robot control system and perform camera parameter calibration.

[0024] (2) The mobile robot explores and travels in the environment driven by the servo driver and the servo motor, and the camera continuously collects environmental image information.

[0025] (3) Extract feature points from the collected video frames. If you use the following methods to extract:

[0026] Roughly match feature points with the same name in two adjacent video frames. Extract the natural feature points of the key frame and intercept the feature fragments, select the stable point set through affine transformation, and each stable point fragment in the stable point set is obtained through affine transformation to obtain the training fragment; randomly generate random fern clusters and their judgment nodes Attribute ...

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Abstract

The invention provides a mobile robot navigation method based on one point RANSAC and FAST algorithms. The method mainly includes that a robot adopts the FAST corner extraction algorithm for collecting surround environment information through a self-equipped camera; the one point RANSAC algorithm combined with extension Kalman filtering is adopted during a matching process for error matching remove; and obtained matching points are used for three-dimensional environment reconstruction and map creation. Aiming at a problem that the number of iterations is too large in the prior art employing the RANSAC algorithm, prior information obtained in a filtering phase is utilized fully. In this way, the number of iterations of the algorithm is reduced effectively and the algorithm robustness is guaranteed at the same time, so that feature matching is implemented. Problems that a traditional mobile robot is poor in monocular vision navigation real time performance and robustness and the number of iterations of the RANSAC algorithm is too large are solved.

Description

technical field [0001] The invention belongs to the field of autonomous positioning and navigation of mobile robots, in particular to the positioning and navigation of mobile robots based on image matching. Background technique [0002] With the rapid development of computer technology and the continuous progress of society, the application of mobile robots has been continuously expanded, and the level of artificial intelligence has also been continuously improved. Compared with traditional industrial robots, mobile robots integrate more advanced technologies, and are gradually becoming a comprehensive system integrating task planning, environment creation and autonomous positioning, path planning, real-time navigation, and target recognition. sexual system. Its application fields have also gradually expanded from industry to military, medical, home services, emergency rescue, ocean development, space exploration, etc. The continuous expansion of application fields also put...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
Inventor 刘想德张毅唐贤伦罗元李彦
Owner CHONGQING UNIV OF POSTS & TELECOMM
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