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Indoor environment feature extraction method based on entropy and gray correlation degree

A grey correlation, indoor environment technology, applied in instruments, adaptive control, control/regulation systems, etc., can solve problems such as feature confusion

Active Publication Date: 2015-07-22
UNIV OF SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Among them, the Hough transform can effectively find feature information in a large amount of uncertain information, and is an effective method for detecting straight lines or arcs. However, the extraction of line segment features is prone to feature confusion, and it is usually necessary to cluster the data points before Extract line segment features, so it can only be used to process distance data offline

Method used

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  • Indoor environment feature extraction method based on entropy and gray correlation degree
  • Indoor environment feature extraction method based on entropy and gray correlation degree
  • Indoor environment feature extraction method based on entropy and gray correlation degree

Examples

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Embodiment

[0083] figure 1 It is a flow chart of an indoor environment feature extraction method based on entropy and gray relational degree provided by Embodiment 1 of the present invention. Such as figure 1 As shown, the method mainly includes the following steps:

[0084] Step 11. Preprocess the initial data obtained when the robot is in a static state, and then extract some straight line features from the preprocessed data based on the main direction extraction method of the gray correlation degree, and determine the endpoints of the line segment based on the most special method, so as to obtain The corresponding line segments are extracted from the above-mentioned several straight line features to form the initial line segment feature set.

[0085] Specifically, this step mainly includes: data preprocessing and initial line segment feature extraction.

[0086] 1. Data preprocessing

[0087] Data preprocessing is mainly to filter the measured values ​​generated due to the measure...

Embodiment 2

[0171] For ease of understanding, the solution of the present invention will be described below in conjunction with specific examples.

[0172] In this example, 16 sonar sensors equipped with the robot Pioneer 3-DX are used to roam in an unknown environment and collect data through the sonar sensors. Visual Studio 2008 and Matlab R2009a mixed programming are used to realize indoor environment feature extraction. The detailed scheme is the same as Similar to Embodiment 1, the workflow is as follows figure 2 As shown, the specific steps are as follows:

[0173] (1) Use the robot sonar to collect current local environmental data, separate the sonar data points with r<5000mm, and record the filtered data set as c.

[0174] (2) take score in the embodiment thres = 0.9. For data set c, use the self-organizing map to cluster to obtain data set C, and perform line segment feature extraction on each point cluster after clustering, and obtain the initial line segment feature set L o...

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Abstract

The invention discloses an indoor environment feature extraction method based on entropy and gray correlation degree. The indoor environment feature extraction method includes that related technology in an information theory is utilized to complete gradual cognition of environment through a knowledge processing method simulating human processing environment information; environment feature extraction is realized by utilizing entropy and gray correlation degree, calculation and information storage cost is reduced to greatest extend, and data processing robustness is improved; environment features are updated through entropy when a robot wanders, so that instantaneity and accuracy of sonar data processing are improved; indoor environment feature extraction based on entropy and gray correlation degree can be effectively used in moving robot positioning, map building and path planning, so that accuracy and robustness of robot navigation tasks are improved.

Description

technical field [0001] The invention relates to the technical field of mobile robot navigation, in particular to an indoor environment feature extraction method based on entropy and gray relational degree. Background technique [0002] With the development of artificial intelligence, robots have gradually transformed from simple laborers who do not have the ability to think and communicate and can only operate according to pre-programmed programs to "able to perceive and extract information in the environment, and can use environmental knowledge to effectively A machine that works in a purposeful, meaningful, and safe manner". The representation of environmental knowledge by agents is the core and hotspot of artificial intelligence research at present. It is mainly to seek the mapping between environmental spatial knowledge and spatial entity representation. The problems to be solved are: 1) how to qualitatively express knowledge; 2) how to reflect Information incompletenes...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
Inventor 陈宗海屈薇薇王鹏
Owner UNIV OF SCI & TECH OF CHINA
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