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Self-adaption landmark selection method facing moon navigation

An adaptive and landmark technology, applied in the field of visual navigation system, can solve the problems of poor real-time performance and poor self-adaptive ability, and achieve the effect of good real-time performance and good adaptability

Active Publication Date: 2015-12-02
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0005] In order to overcome the shortcomings of poor adaptive ability and poor real-time performance of existing landmark selection methods for lunar surface navigation, the present invention provides a self-adaptive landmark for lunar surface navigation with good adaptive ability and good real-time performance selection method

Method used

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  • Self-adaption landmark selection method facing moon navigation
  • Self-adaption landmark selection method facing moon navigation
  • Self-adaption landmark selection method facing moon navigation

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Embodiment Construction

[0033] The present invention will be further described below in conjunction with the accompanying drawings.

[0034] refer to figure 1 with figure 2 , an adaptive landmark selection method for lunar surface navigation, comprising the following steps:

[0035] 1) Use the SiftGPU algorithm to extract the sift feature points. SiftGPU is the Sift algorithm accelerated by the GPU. The details are in http: / / www.cs.unc.edu / ~ccwu / siftgpu / There is an introduction on the website. The effect is as figure 2 (a) shown.

[0036] 2) Use the K-dTree data structure and the boundary feature point removal method to down-sample the sift feature points. First, remove the feature points located within 10% of the image edge. If the number of feature points is less than 1000 at this time, do not perform K-dtree feature points are down-sampled, otherwise use this structure to delete several feature points closest to the current point (the number is obtained by dividing the total number of fea...

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Abstract

Provided is a self-adaption landmark selection method facing moon navigation. The method comprises the following steps: firstly, extraction of sift characteristic points is carried out by utilization of the SiftGPU algorithm; secondly, downsampling of characteristic points is carried out; thirdly, the characteristic points in the second step is subjected to clustering by utilization of the self-adaption DBSCAN cluster algorithm, and the process is as follows: firstly, distribution is carried out according to a shortest distance of each characteristic point, and the initialized parameter of the cluster algorithm is obtained and secondly, a non-recursive mode is employed to achieve the DBSCAN algorithm, and a plurality of candidate landmarks are obtained; fourthly, a characteristic point M in a current landmark in correct matching, Mmax with the most characteristic points in all the landmarks in matching and detected characteristic point number A are obtained through matching of two adjacent images, and the landmark with the highest score is selected as a landmark by utilization of an evaluation function. The provided method is advantaged by good self-adaption capability and good real-time.

Description

technical field [0001] The invention is used in a visual navigation system, and is especially suitable for using the landmark selection method to assist navigation when the GPS signal is weak or even non-existent. Background technique [0002] In the process of lunar navigation, due to the cumulative error of the inertial navigation system, it is necessary to correct the error by combining the method of visual navigation. During this process, the selection of a suitable landmark will help improve the accuracy of visual navigation. [0003] In the current navigation and positioning of UAVs, the position of UAVs is located by manually setting landmarks. There are also many related papers on the selection of natural landmarks. Generally, by matching the images of two adjacent frames, the designed evaluation function is used to evaluate according to the matching situation, and the appropriate landmark is selected according to the evaluation results. [0004] Defects in existi...

Claims

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Application Information

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IPC IPC(8): G01C21/24
Inventor 张剑华冯余剑谢榛任亲虎步青刘盛陈胜勇
Owner ZHEJIANG UNIV OF TECH
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