上海交通大学学报

上海交通大学学报 >

2024 , Vol. 58 >Issue 11: 1783 - 1797

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2024.209

制导、导航与控制

基于动态密度引导的多机器人编队队形变换方法

  • 曹凯 ,
  • 陈阳泉 ,
  • 李康 ,
  • 陈超波 ,
  • 阎坤 ,
  • 刘伟超
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  • 1.西安工业大学 电子信息工程学院,西安 710021
    2.加州大学默塞德分校 MESA Lab,美国 默塞德 CA 95343
曹 凯(1984—),副教授,从事多机器人控制、集群控制、源定位的研究;E-mail:caokai@xatu.edu.cn.

收稿日期: 2024-06-06

  修回日期: 2024-06-22

  录用日期: 2024-06-24

  网络出版日期: 2024-07-04

基金资助

国家自然科学基金青年基金(62103315);信息融合技术教育部重点实验室开放基金(202312-IFTKFKT-007);陕西省科技厅项目(2022QFY01-16);陕西省科技厅项目(2023-ZDLNY-61)

收起

Dynamic Density-Guided Method for Multi-Robot Formation Transformation

  • CAO Kai ,
  • CHEN Yangquan ,
  • LI Kang ,
  • CHEN Chaobo ,
  • YAN Kun ,
  • LIU Weichao
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  • 1. School of Electronic Information Engineering, Xi’an Technological University, Xi’an 710021, China
    2. MESA Lab, University of California, Merced CA 95343, USA

Received date: 2024-06-06

  Revised date: 2024-06-22

  Accepted date: 2024-06-24

  Online published: 2024-07-04

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摘要

针对地面移动机器人编队的队形控制问题,提出了一种基于动态密度引导的多机器人编队队形切换方法.为实现机器人编队不同队形的切换,使用质心维诺划分(CVT)编队控制算法,避免机器人队形切换过程中的碰撞.根据CVT算法的特性,通过给定队形的密度函数,构建初始队形密度函数与期望密度函数之间的过渡密度生成动态密度,并利用CVT算法引导编队中的机器人移动,完成编队队形的切换与重构.仿真结果表明,相比直接使用期望密度函数引导队形切换,该方法不仅成功解决了部分形态编队切换失败问题,而且降低了切换过程中编队整体的平均位置误差.

关键词： 多机器人; 质心维诺划分; 编队控制; 队形切换

本文引用格式

曹凯 , 陈阳泉 , 李康 , 陈超波 , 阎坤 , 刘伟超 . 基于动态密度引导的多机器人编队队形变换方法[J]. 上海交通大学学报, 2024 , 58(11) : 1783 -1797 . DOI: 10.16183/j.cnki.jsjtu.2024.209

Abstract

This paper addresses the formation control problem for ground mobile robot formations and proposes a formation transition method based on dynamic density guidance. To achieve different formation transitions, a centroidal Voronoi tessellations (CVT) formation control algorithm is utilized to avoid collisions during the transition process. By leveraging the properties of the CVT algorithm, a dynamic density is generated by constructing a transition density function between the initial formation density function and the desired density function. The CVT algorithm then guides the robots in the formation to move and complete the transition and reconstruction of the formation. The simulation results demonstrate that, compared to using the desired density function directly, this method not only successfully resolves certain formation transition failures but also reduces the average positional error of the formation during the transition process.

Key words： multi-robot; centroidal Voronoi tessellations; formation control; formation transformation

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