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Multi-agent control method based on maximum angle aggregation strategy

A multi-agent and control method technology, applied in the direction of program control manipulators, manufacturing tools, manipulators, etc., can solve the problems of not meeting the real-time requirements of multi-agent control and low efficiency, so as to meet the real-time requirements and improve efficiency Effect

Active Publication Date: 2022-04-29
CHONGQING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the low efficiency of existing technologies such as the SPPL model in the prior art, which cannot meet the real-time requirements of multi-agent control, and provide a multi-agent control method based on the maximum angle aggregation strategy

Method used

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  • Multi-agent control method based on maximum angle aggregation strategy

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0055] This embodiment provides a multi-agent control method based on the maximum angle aggregation strategy, and judges the behavior state of the control agent according to the position of each simple agent and the position of the control agent, including the following steps:

[0056] When there is a distance between a simple agent and the global center of the simple agent group that is greater than the preset aggregation degree f(N) of the simple agent group, the collection behavior of the control agent is triggered; the control agent selects the group with the largest angle The simple agent is used as the target point to gather; the first angle is the angle with the control agent as the vertex, the connection between the control agent and the global center as the starting edge, and the connection between the control agent and the simple agent as the end edge angle value;

[0057] When the distance between all simple agents and the global center of the simple intelligent gro...

Embodiment 2

[0107] The goal of controlling the agent is to control the group of simple agents to move to the destination until all the simple agents are in the target area. When the simple agent group is too scattered, the control agent collects the group; when all the simple agents are collected together, the control agent drives the population towards the target point. The strategy of how to collect and how to expel is the focus of discussion. In this embodiment, the traditional SPPL model will be compared with the MAM and DMAM models proposed by the present invention to verify the effectiveness of the present invention.

[0108] All calculation examples are run on 12GB memory, 2.9GHz Intel CPU, 64-bit windows operating system. Simulation and data analysis use Python3.7, standard graphical interface tool suite Tkinter.

[0109] The simulation process of the multi-agent control method (MAM and DMAM) based on the maximum angle aggregation strategy includes the following steps:

[0110]...

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Abstract

The invention discloses a multi-agent control method based on the maximum angle aggregation strategy, judging the behavior state of the control agent according to the position of each simple agent and the position of the control agent, including the following steps: when there is a simple agent and When the distance of the global center of the group is greater than the preset aggregation degree f(N) of the simple intelligent group, the collection behavior of the control agent is triggered; the control agent selects the simple agent with the largest first angle in the group subset as the target point to gather; The above-mentioned first angle is the included angle between the connection line between the control agent and the global center and the connection line between the control agent and the simple agent; when the distances between all the simple agents and the global center of the group are less than or equal to When f(N), trigger the driving behavior of the control agent; control the movement of the agent, and control the simple intelligent group to advance to the target point, and complete the control task when the simple intelligent group reaches the target area.

Description

technical field [0001] The invention relates to the field of swarm intelligence heuristic algorithms, in particular to a multi-agent control method based on a maximum angle gathering strategy. Background technique [0002] Because the swarm intelligence solutions found in nature are very effective, bionic algorithms have become a research hotspot in recent years, including ant colony algorithms, bird swarm algorithms, and control agent algorithms. Inspired by nature, swarm intelligence systems can be described as interactions between relatively basic individuals in the system. Multi-agent control in swarm intelligence systems is a complex problem that can be divided into high-level path planning and low-level single-agent dynamics. Multi-agent control is a control method to control a group of simple intelligent agents (weak agents) by controlling agents (strong agents). [0003] A typical application scenario of multi-agent control is a shepherd dog chasing sheep, which is...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B25J9/16
CPCB25J9/1602B25J9/1628
Inventor 姚军李佳李涛崔梓林孙天昊
Owner CHONGQING UNIV