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Swarm-robot mixed search method based on biological foraging behavior

A hybrid search and group robot technology, applied in the field of robotics, can solve problems such as complex structure, poor effect, and poor flexibility

Inactive Publication Date: 2017-01-04
JILIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Although a single robot can complete some simple tasks, due to the fact that a single robot is generally large in size, high in energy consumption, complex in structure, and poor in flexibility, it is not very effective when using a single robot for search tasks. , large number, simple structure, relatively flexible, strong robustness, easier to control than a single robot, and its fault tolerance is strong, even if one of the robots is broken, it will not affect the overall search and other characteristics. more and more attention

Method used

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  • Swarm-robot mixed search method based on biological foraging behavior
  • Swarm-robot mixed search method based on biological foraging behavior
  • Swarm-robot mixed search method based on biological foraging behavior

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Experimental program
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Embodiment Construction

[0046] The steps of the present invention are:

[0047] Step 1: Use the grid method to model the search environment:

[0048] search area , , divided into several grids,

[0049] , : The search area is a rectangle, is the length of the search region, is the width of the search area.

[0050] Step 2: Divide the search area into several sub-areas:

[0051] Use A to denote the entire search area, use Represents any sub-area that is divided, then the entire search area can be expressed as: , n: the number of sub-areas divided into the search area.

[0052] Step 3: Arrange the search order of each sub-area:

[0053] The search order of each sub-region is determined by the size of the regional utility function, so that the sub-region with a strong target signal concentration is searched first. The regional utility function is as follows:

[0054]

[0055] , : coefficient in the formula, 0 , 1, take the value according to the search environment and th...

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Abstract

The invention provides a swarm-robot mixed search method based on a biological feeding behavior and belongs to the technical field of robots. The invention aims at providing the swarm-robot mixed search method based on the biological feeding behavior, which utilizes swarm robots to search a target and promotes a swarm self-organization principle and cooperative behavior emerging principle. The swarm-robot mixed search method comprises the following steps: modeling a search environment by adopting a grid method; dividing a search region into a plurality of sub-regions and arranging a search sequence of each sub-region; and searching by adopting a mixed search method. According to the swarm-robot mixed search method, the robots are used for replacing people to finish a lot of work, such as searching of survivors of disasters including mine clearance and explosive handling, space detection and earthquakes, and mining accident searching and rescuing and so on.

Description

technical field [0001] The invention belongs to the technical field of robots. Background technique [0002] With the rapid development of application technologies such as microelectronics, computers, and networks, robot technology has made leaps and bounds. The advancement of robot software and hardware technology has continuously improved the various capabilities of mobile robots, and the field and scope of mobile robot applications are also constantly increasing. Expanding, it has become a trend to use robots instead of people to complete some simple tasks, such as using a single robot for cleaning or searching. [0003] Although a single robot can complete some simple tasks, due to the fact that a single robot is generally large in size, high in energy consumption, complex in structure, and poor in flexibility, it is not very effective when using a single robot for search tasks. , large number, simple structure, relatively flexible, strong robustness, easier to control ...

Claims

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Application Information

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IPC IPC(8): G06N3/00
CPCG06N3/006G06N3/008
Inventor 李寿涛田微杨蕊嘉丁辉韩风乔丽张路玉徐靖淳
Owner JILIN UNIV
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