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Method for creating adaptive grid map of robot based on novenary tree

A grid map and robot technology, applied in the direction of navigation computing tools, etc., can solve the problems of data explosion and occupying a large amount of storage space, and achieve the effect of saving storage space and avoiding the expansion of search range

Inactive Publication Date: 2018-11-30
BEIJING UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This invention solves the problem of traditional uniform-scale grid maps occupying a large amount of storage space in the process of creating large-scale maps, and avoids the data explosion caused by the expansion of the search range and the improvement of the grid resolution.

Method used

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  • Method for creating adaptive grid map of robot based on novenary tree
  • Method for creating adaptive grid map of robot based on novenary tree
  • Method for creating adaptive grid map of robot based on novenary tree

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Embodiment

[0044] In the first step, the entire unknown environment that the robot needs to recognize is considered as a map with an unknown state. The robot circles around the entire unknown environment and divides the entire unknown environment into a nine-square grid structure, that is, the map is divided into uniform Nine subrasters. The calculation method of the center coordinates (x, y) of each sub-grid is as follows:

[0045]

[0046]

[0047] The length and width of the environmental map scale are denoted by a and b respectively, and the number of the grid obtained after n times of subdivision is X 1 x 2 x 3 ...X n (n bits), i is selected from 0,1,2,3,4,5,6,7,8. When X 1 ,X 2 ,X 3 ,...,X n When 0, 3, or 6 are taken, λ 1 ,λ 2 ,λ 3 ,...,λ n = -1; when x 1 ,X 2 ,X 3 ,...,X n When taking 1, 4, 7, λ 1 ,λ 2 ,λ 3 ,...,λ n = 0; when x 1 ,X 2 ,X 3 ,...,X n When taking 2, 5, 8, λ 1 ,λ 2 ,λ 3 ,...,λ n =1. When X 1 ,X 2 ,X 3 ,...,X n When taking 0, 1, 2...

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Abstract

The invention discloses a method for creating the adaptive grid map of a robot based on a novenary tree. The method comprises the following steps: dividing a whole environment map to form a nine-blockbox structure, judging that every block box is in a completely occupied state, a partially occupied state or a vacant state, further subdividing the partially occupied block box to form a subordinatenine-block box structure, judging that every small block box is in a completely occupied state, a partially occupied state or a vacant state, and repeating the above division process until the searching of the entire map is finished and accuracy requirements are met. The final scale of the grid map is determined without the dependence on human experiences, and presents the self-adaptive characteristic. A simulation experiment result shows that the map construction method in the invention has a higher convergence than uniform scale grid methods, and the map obtained in the invention saves thestorage space compared with a uniform scale grid map.

Description

technical field [0001] The invention belongs to a method for creating an environment map of an indoor mobile robot. It divides and expresses the environment map based on the nine-fork tree idea in computer science. The method shows strong advantages in the creation of a large-scale environment. Background technique [0002] In recent years, indoor mobile robots have played an increasingly important role in medical care, catering, transportation, and home services. Our field of vision has received more and more attention. In this field, the problem of robot map creation is a hot and difficult point in the research of indoor mobile robots. [0003] There are three representation methods of the robot environment map: geometric feature method, topology method and grid method. Geometric feature maps represent the environment with related geometric features (such as points, lines, and surfaces). This method can search for the shortest path. At present, the common processing met...

Claims

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Application Information

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IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 阮晓钢周静朱晓庆张晶晶董鹏飞王飞
Owner BEIJING UNIV OF TECH
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