A multi-agent cooperative target search method based on particle swarm optimization

A particle swarm algorithm and target search technology, which is applied in the field of swarm intelligence and multi-agent target search, can solve problems such as failure of moving time tasks, and achieve the effect of reducing moving distance and search time, realizing performance, and reasonable design.

Active Publication Date: 2022-06-07
TONGJI UNIV
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But it is also because the particles in the particle swarm optimization algorithm are virtual individuals, that is, they do not consume energy, have infinite speed, and can move instantly. Chance to stop working due to lack of energy, or cause mission failure due to moving for too long

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
  • A multi-agent cooperative target search method based on particle swarm optimization
  • A multi-agent cooperative target search method based on particle swarm optimization
  • A multi-agent cooperative target search method based on particle swarm optimization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0040] as Figure 1 As shown in the present embodiment, the pluralistic agent collaborative target search method, specifically comprising the following steps:

[0041] Step 1.1: In the application scenario, the multi-agent is distributed, the multi-agent is treated as a particle swarm, the individual agents are treated as particles, the environment is modeled, and the field source signal value detected by the agent sensor is used as the fitness index of the particle swarm algorithm.

[0042] Step 1.2: Initialize the particle swarm algorithm parameter settings: particle swarm size n=50, optimization dimension D=2, maximum number of iterations G=10000.

[0043] Step 1.3: Randomly initialize the initial position of n particles x= {x 1 ,x 2 ,...,x n } and speed v={v 1 ,v 2 ,...,v n }, initialize the position of m agents S={S 1 ,S 2 ,...,S m } and speed V=1.

[0044] Step 1.4: Multi-agents perform optimal path planning through a local search strategy to traverse all current particle pos...

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 present invention proposes a multi-agent cooperative target search method based on the particle swarm algorithm, which introduces the particle swarm algorithm for virtual navigation, and uses entity agents with certain communication and perception capabilities to replace the virtual particle realization source in the particle swarm algorithm Location search. For the first time in the particle swarm algorithm, the moving distance and search time of the particles are considered, and the weight cost function is established. According to the target position generated by each generation of the particle swarm, the path with the least cost is planned for the agent through the local search strategy. Accordingly, the multi-agent system can greatly reduce energy consumption, enhance battery life, and improve search efficiency without affecting the target search accuracy. The invention is a multi-agent target search method with generality, and the particle swarm algorithm based on it can be any particle swarm variant.

Description

Technical field [0001] The present invention relates to swarm intelligence and multi-agent target search field, specifically a multi-agent collaborative target search method based on particle swarm algorithm. Background [0002] In recent years, the problem of source positioning has attracted widespread attention and has gradually developed into a research hotspot. This problem assumes that there is a static source in an unknown environment that continuously transmits signals to the outside world, and multiple agents need to coordinate the location of the source based on the signal strength detected in each region. Due to the phenomenon of reflection and refraction of spatial signals and the error of sensor measurements, there are different degrees of noise in the detection area, which greatly increases the difficulty of the task. From another point of view, this problem can be transformed into an optimization problem, modeling the signal strength of each location in the search s...

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 Patents(China)
IPC IPC(8): G06N3/00G06Q10/04G06F16/9536
CPCG06N3/006G06F16/9536G06Q10/047Y02D10/00
Inventor 张军旗卢烨昊王成臧笛刘春梅康琦
Owner TONGJI UNIV
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap