Multi-agent dynamic multi-target collaboration tracking method based on finite-state automata

A finite-state, automaton technology that is used in overall factory control, measuring devices, instruments, etc., to solve problems such as the absence of tracking methods

Inactive Publication Date: 2008-11-12
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is currently no general tracking

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  • Multi-agent dynamic multi-target collaboration tracking method based on finite-state automata
  • Multi-agent dynamic multi-target collaboration tracking method based on finite-state automata
  • Multi-agent dynamic multi-target collaboration tracking method based on finite-state automata

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Embodiment 1

[0068] The present invention proposes a multi-agent dynamic multi-target cooperative tracking method based on finite state automata, and its application basis is a multi-agent system (Multi-Agent System, referred to as MAS). This method is applied to an AI entity that can continue to function autonomously. It selects a finite automatic state machine (Deterministic Finite Automation, referred to as DFA) according to the environment and task requirements to maintain the behavioral state model of the compound AI entity, and then combines the video The environmental information sensed by the device sensor and the shared resources in the AI ​​entity group, communicates, collaborates and negotiates with other AI entities, performs modeling, prediction, planning, and decision-making, and guides the individual AI entities to control the actuators to perform certain actions. . The present invention abstracts the individual AI entity into a composite model. In this model, for the AI ​​e...

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Abstract

The invention discloses a multi-agent dynamic multi-objective cooperative tracking method which is based on a finite state automaton, which is characterized in that a combined agent selects one finite state automaton from a plurality of finite state automatons as the finite state automaton to maintain the behavior state model of the combined agent according to self-detected environmental information I, task information M which is sent by a server, other agents or a manager of agent groups and needs to be fulfilled, and/or artificially designated information H which is sent by the server. The agent is driven by behavior state, emotion information and other factors and can carry out centralized control or agent individual information interaction control by information interaction or by combining the server for team coordination. The method is suitable for different architectures such as centralized type, distributed type and hybrid type.

Description

technical field [0001] The invention belongs to the field of robot navigation and application, and relates to a dynamic multi-target cooperative tracking method based on finite state automata. Background technique [0002] The complexity and diversification of modern tasks have put a higher demand on the combination of multi-robots and the completion of team tasks. How to cooperate with multi-robots to conduct reconnaissance on the environment through existing video acquisition equipment, information interaction and fusion, The ability to guide behavior through vision is particularly important. However, there is currently no general tracking method in this regard that can be widely used. [0003] In an unknown environment, to use a large-scale robot team with visual equipment to observe and track dynamic multi-targets collaboratively, it is necessary to observe the environment in real time through the AI ​​real-time model on the multi-robots asynchronously and solve local p...

Claims

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Application Information

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IPC IPC(8): G05B19/418G01C21/00
CPCY02P90/02
Inventor 蔡自兴卢薇薇陈爱斌文志强
Owner CENT SOUTH UNIV
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