Swarm robot multi-target searching method in unknown environment

A swarm robot and unknown environment technology, applied in the field of robot target search, can solve the problems of not being able to know the global map and not being able to obtain environmental information in advance

Active Publication Date: 2021-02-26
HUNAN UNIV OF SCI & TECH
View PDF7 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In an unknown environment, the environmental information of multi-target search by swarm robots cannot be obtained in advance, and the robot cannot know the global map, but only the obstacles, targets, etc. within the detection range of the sensor, and the communication between robots can only be within the allowed range exchange their information

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Swarm robot multi-target searching method in unknown environment
  • Swarm robot multi-target searching method in unknown environment
  • Swarm robot multi-target searching method in unknown environment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0094] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0095] like figure 1 As shown, a multi-target search method for swarm robots in an unknown environment includes the following steps:

[0096] Step 1: Construct unknown environment model and target response function.

[0097] The process of building an unknown environment model is:

[0098] Finite two-dimensional space R 2 Inside, there exists a universal set U={R∪T∪B}, where group robots R={R i |i=1,2,...,i max ,i max ≥10}, R i is the i-th robot, i max is the total number of robots; target T={T j |j=1,2,...,j max ,j max >1},T j is the jth target, j max is the total number of targets; obstacle B={B s |s=1,2,...,s max ,s max ≥1}, B s is the sth obstacle, s max is the total number of obstacles; R i , T j , B s The positions are denoted as X i (t), T(x j ,y j ), B(x s ,y s ); in this environment, the group robot R acts as the search...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a swarm robot multi-target searching method in an unknown environment. The swarm robot multi-target searching method comprises the following steps that an unknown environment model is constructed; a robot detects a target signal, dynamic division is carried out based on a target response function, and a set where robots completing the same sub-task are located forms a sub-alliance; closed-loop regulation is introduced, resource allocation of each sub-task is evaluated, and a new sub-alliance is formed; robots which do not form the sub-alliance perform roaming search; and the robots forming the sub-alliance search a target based on a particle swarm algorithm of position estimation and an obstacle avoidance strategy of boundary scanning. By means of the swarm robot multi-target searching method in the unknown environment, according to the obstacle avoidance strategy of boundary scanning, the distance and angle relation between the nearest two points and the boundary points and the robots is used for obstacle avoidance; and according to the particle swarm algorithm of position estimation, the approximate position of the target point can be deduced by using theavailable target signal, the particle swarm algorithm is matched, the target position is quickly reached, so that the path and the searching time during target searching are reduced.

Description

technical field [0001] The invention relates to a robot target search method, in particular to a group robot multi-target search method in an unknown environment. Background technique [0002] Swarm intelligence is inspired by the group behavior of social creatures in nature. It is the ability of simple information processing units to solve problems in the interaction. The information processing units are independent of each other and it is a distributed method. The swarm robot system is a swarm intelligence system with simple robots as information processing units, which has typical distributed characteristics, while individual robots have the characteristics of isomorphism and simple structure. There are simple interactions between robots and between robots and the environment. According to the information obtained from the interaction, each robot performs distributed motion, but intelligent behavior emerges on the entire robot system, and then certain tasks can be complet...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): B25J9/16
CPCB25J9/16B25J9/1682B25J9/1676B25J9/1664
Inventor 周游王茂陈安华张红强周少武
Owner HUNAN UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products