Mismatching determination method of indoor environment robot line characteristic ICNN data association

A technology of robot line and indoor environment, applied in the field of data association, can solve the problem of low association accuracy of standard ICNN algorithm

Active Publication Date: 2019-08-20
HARBIN ENG UNIV
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Problems solved by technology

[0003] In order to solve the problem of low correlation accuracy of the standard ICNN algorithm, the present invention prop

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  • Mismatching determination method of indoor environment robot line characteristic ICNN data association
  • Mismatching determination method of indoor environment robot line characteristic ICNN data association
  • Mismatching determination method of indoor environment robot line characteristic ICNN data association

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Embodiment Construction

[0061] The present invention will be further described below in conjunction with the accompanying drawings.

[0062] A line-feature-oriented improved ICNN data association method based on mismatch judgment rules, comprising the following steps:

[0063] Step 1: Construct the global coordinate system and local coordinate system, and set the sensor working mode;

[0064] The coordinate origin of the global coordinate system is defined as the initial motion position of the robot, and the initial heading of the robot is the X-axis direction.

[0065] The local coordinate system includes the laser sensor coordinate system and the local coordinate system of the mobile robot. The coordinate origin of the laser sensor coordinate system is located in the X-axis direction of the robot coordinate system, and the distance between the coordinate origins of the two coordinate systems is set according to the simplified model of the robot. for a c .

[0066] The working mode of the laser s...

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Abstract

The invention belongs to the data association field and especially relates to a mismatching determination method of indoor environment robot line characteristic ICNN data association. The invention provides an improved ICNN data association method of a decision rule of mismatching and mismatching prevention based on a line segment position relationship. The method is characterized by extracting anenvironmental line characteristic based on laser sensor data, re-selecting a line characteristic parameter, and summarizing line segment position relationships in a same two-dimensional plane; and for a problem that mismatching is easy to generate during line segment parallel or collineation, giving a mismatching evaluation model; and based on that, providing an improved ICNN algorithm. In the improved algorithm, computational time similar to the time of a standard algorithm is used to achieve higher correlation accuracy.

Description

technical field [0001] The invention belongs to the field of data association, and in particular relates to a wrong matching judgment method for ICNN data association of line features of indoor environment robots. Background technique [0002] Simultaneous positioning and map construction of mobile robots SLAM refers to mobile robots relying on their own sensors to detect the surrounding environment in an unknown environment, incrementally create a map of the environment and self-position. Among them, data association refers to matching the information obtained by the sensor at the current moment with the features that have been added to the map. The accuracy of data association is related to the effect of the entire SLAM algorithm. The independent and compatible nearest neighbor data association algorithm ICNN is suitable for situations where the environment is relatively simple, and has the characteristics of small amount of calculation and easy storage, but it is easy to ...

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Application Information

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IPC IPC(8): G01C25/00G01C9/00
CPCG01C25/00G01C9/00
Inventor 王宏健张明伟肖瑶杜雪许秀军王莹
Owner HARBIN ENG UNIV
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