Hunting in Unknown Complex Environments by Swarm Robots Based on Simplified Virtual-Force Model

ZHANG Hong-qiang; ZHANG Jing; ZHOU Shao-wu; ZENG Zhao-fu; WU Liang-hong

doi:10.3969/j.issn.0372-2112.2015.04.007

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Hunting in Unknown Complex Environments by Swarm Robots Based on Simplified Virtual-Force Model

更新时间：2025-07-16

- Hunting in Unknown Complex Environments by Swarm Robots Based on Simplified Virtual-Force Model
- Acta Electronica Sinica Vol. 43, Issue 4, Pages: 665-674(2015)
- 作者机构：
  
  1. 湖南大学电气与信息工程学院,湖南,长沙,410082
  2. 湖南科技大学信息与电气工程学院,湖南,湘潭,411201
  3. 湖南大学电气与信息工程学院,湖南,长沙,410082
  4. 湖南科技大学信息与电气工程学院,湖南,湘潭,411201
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2015.04.007
  CLC： TP24
- Published：2015
- 稿件说明：
移动端阅览
ZHANG Hong-qiang, ZHANG Jing, ZHOU Shao-wu, et al. Hunting in Unknown Complex Environments by Swarm Robots Based on Simplified Virtual-Force Model[J]. Acta Electronica Sinica, 2015, 43(4): 665-674.
DOI：

ZHANG Hong-qiang, ZHANG Jing, ZHOU Shao-wu, et al. Hunting in Unknown Complex Environments by Swarm Robots Based on Simplified Virtual-Force Model[J]. Acta Electronica Sinica, 2015, 43(4): 665-674. DOI： 10.3969/j.issn.0372-2112.2015.04.007.

摘要

针对未知非凸和凸以及动态障碍物环境下群机器人围捕

提出了一种基于简化虚拟受力模型的循障和围捕方法.首先给出了目标和动态障碍物的运动模型.然后通过对复杂环境下围捕行为的分解

抽象出简化虚拟受力模型.基于此模型

设计了个体循障和围捕方法

接着证明了系统的稳定性并给出了参数设置范围.仿真结果表明

本文围捕方法可以使群机器人在未知复杂环境下保持较好的围捕队形

并具有良好的避障性能和灵活性

同时分析了与基于松散偏好规则的围捕方法相比的优势.

Abstract

In this paper

a method based on a simplified virtual-force model is proposed for swarm robots hunting in unknown non-convex

convex and dynamic obstacles environments.First

the motion models for the hunting target and dynamic obstacles are presented.Then through the decomposition of hunting behaviors under complicated environments

a simplified virtual-force model is formed.Based on the model

the control method is designed for swarm robots following motions of barriers and the hunting target;the stability of the hunting system is analyzed and the control parameter ranges are given.Simulation results demonstrate that the proposed method can maintain a good hunting formation and has good performance of obstacles avoidance and flexibility.Finally

advantages of this method are presented

compared with the hunting method based on loose preference rule.

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