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基于USARSimROS的无人平台编队仿真系统

张浩杰 苏治宝 杨甜甜

张浩杰, 苏治宝, 杨甜甜. 基于USARSim和ROS的无人平台编队仿真系统. 自动化学报, 2021, 47(6): 1390−1400 doi: 10.16383/j.aas.c200102
引用本文: 张浩杰, 苏治宝, 杨甜甜. 基于USARSim和ROS的无人平台编队仿真系统. 自动化学报, 2021, 47(6): 1390−1400 doi: 10.16383/j.aas.c200102
Zhang Hao-Jie, Su Zhi-Bao, Yang Tian-Tian. Design of team formation simulation system for unmanned ground vehicles based on USARSim and ROS. Acta Automatica Sinica, 2021, 47(6): 1390−1400 doi: 10.16383/j.aas.c200102
Citation: Zhang Hao-Jie, Su Zhi-Bao, Yang Tian-Tian. Design of team formation simulation system for unmanned ground vehicles based on USARSim and ROS. Acta Automatica Sinica, 2021, 47(6): 1390−1400 doi: 10.16383/j.aas.c200102

基于USARSimROS的无人平台编队仿真系统

doi: 10.16383/j.aas.c200102
基金项目: 国家自然科学基金青年科学基金项目(61806183), 中央高校基本科研业务费项目(FRF-TP-19-006B1), 北京科技大学顺德研究生院科技创新专项资金(BK19AE014)资助
详细信息
    作者简介:

    张浩杰:北京科技大学自动化学院副教授. 2008年获中南大学交通设备信息工程专业工学学士学位, 2013年获北京理工大学车辆工程专业工学博士学位. 主要研究方向为地面无人平台的路径规划与跟踪控制. 本文通信作者. E-mail: haojie.bit@gmail.com

    苏治宝:中国北方车辆研究所兵器地面无人平台研发中心研究员. 1995年获吉林大学学士学位, 2001年获东北大学硕士学位, 2004年获北京理工大学工学博士学位. 主要研究方向为机器人控制系统架构及软件框架. E-mail: bitszb@163.com

    杨甜甜:中国兵器科学研究院研究员. 2002年获哈尔滨工业大学学士学位, 2008年获哈尔滨工业大学控制科学与工程专业工学博士学位. 主要研究方向为地面无人平台协同控制、任务规划与决策技术. E-mail: creance@126.com

Design of Team Formation Simulation System for Unmanned Ground Vehicles Based on USARSim and ROS

Funds: Supported by National Science Foundation of China (61806183), the Fundamental Research Funds for the Central Universities (FRF-TP-19-006B1), Scientific and Technological Innovation Foundation of Shunde Graduate School of University of Science and Technology Beijing (BK19AE014)
More Information
    Author Bio:

    ZHANG Hao-Jie Associate professor at the School of Automation and Electrical Engineering, University of Science and Technology Beijing. He received his bachelor degree from Central South University in 2008, and his Ph. D. degree in vehicle engineering from Beijing Institute of Technology in 2013. His research interest covers path planning and tracking control for unmanned ground vehicles. Corresponding author of this paper

    SU Zhi-Bao Research professor at China North Vehicle Research Institute. He received his bachelor degree from Jilin University in 1995, his master degree from Northeast University in 2001, and his Ph. D. degree from Beijing Institute of Technology in 2004. His research interest covers control system architecture and software framework for robots

    YANG Tian-Tian Research professor at China Research and Development Academy of Machinery Equipment. She received her bachelor degree and Ph. D. degree from Harbin Institute of Technology in 2002 and 2008, respectively. Her research interest covers mission planning and decision for unmanned ground vehicles

  • 摘要: 针对越野非结构化环境下的地面无人平台(Unmanned ground vehicle, UGV)编队仿真系统存在功能模块不完善及算法集成测试困难等问题, 为便于有效测试地面无人平台编队协同控制方法性能及其适用的任务场景, 降低编队协同系统的开发成本, 本文提出了一种基于USARSim (Unified System for Automation and Robotics Simulator)和ROS (Robot Operating System)的地面无人平台编队协同仿真系统. 该仿真系统由人机交互界面、基于ROS架构的地面无人平台控制系统和基于USARSim的虚拟仿真场景三个部分组成, 其测试对象为地面无人平台编队协同控制算法. 通过充分利用ROS中集成的开源导航算法和USARSim中丰富的机器人及环境模型, 该系统为研究地面无人平台编队协同控制算法提供了新的思路和快速验证工具. 以领航者−跟随者编队控制方法为例进行该仿真系统的性能测试, 实验结果表明, 该仿真系统能够在外界条件一致的情况下完成对编队协同控制方法的性能测试, 系统稳定可靠.
  • 图  1  基于USARSim和ROS的地面无人平台编队协同仿真系统结构

    Fig.  1  The architecture of formation simulation system for UGV based on USARSim and ROS

    图  2  人机交互界面

    Fig.  2  The GUI of human-machine interface

    图  3  人机交互界面中的任务模块

    Fig.  3  Task modules in human-machine interface

    图  4  基于ROS架构的地面无人平台控制系统结构

    Fig.  4  The architecture of control system for UGV based on ROS

    图  5  地面无人平台控制器流程图

    Fig.  5  The flowchart of UGV controller

    图  6  ROS-USARSim接口数据流

    Fig.  6  The data flow of ROS-USARSim interface

    图  7  USARSim中的环境示例

    Fig.  7  Sample of 3D environments in USARSim

    图  8  USARSim中的地面无人平台模型

    Fig.  8  Models of UGVs in USARSim

    图  9  三角形编队示意图

    Fig.  9  The diagram of triangle formation

    图  10  仿真测试中的地面无人平台模型

    Fig.  10  The UGV model in simulation

    图  11  地面无人平台编队运动轨迹

    Fig.  11  The travelling path in formation control of UGV

    图  12  三角形编队任务中的速度变化

    Fig.  12  Velocity value during triangle formation control

    图  13  三角形编队任务中的跟随者航向角误差

    Fig.  13  Heading angle error for followers during triangle formation control

    图  14  三角形编队任务中的跟随者轨迹曲线

    Fig.  14  Trajectories for followers during triangle formation control

    表  1  仿真测试硬件配置

    Table  1  Hardware configuration in simulation

    计算机编号 操作系统 IP地址 角色
    1# Windows10 192.168.0.200 人机交互
    2# Windows10 192.168.0.201 USARSim
    3# ROS Melodic 192.168.0.100 领航者(UGV_0)
    4# ROS Melodic 192.168.0.101 跟随者(UGV_1)
    5# ROS Melodic 192.168.0.102 跟随者(UGV_2)
    下载: 导出CSV

    表  2  领航者−跟随者编队方法在不同仿真平台下的测试对比

    Table  2  The comparison of leader-follower formation in different simulation systems

    对比项本文仿真系统MATLABLabVIEW
    UGV_1 位置$x$绝对误差 2.18 cm $\Delta x\to 0$ $\Delta x\to 0$
    UGV_1 位置$y$绝对误差 3.14 cm $\Delta y\to 0$ $\Delta y\to 0$
    UGV_1 航向角相对误差 0.26 % $\Delta \theta\to 0$ $\Delta \theta\to 0$
    UGV_2 位置$x$绝对误差 4.89 cm $\Delta x\to 0$ $\Delta x\to 0$
    UGV_2 位置$y$绝对误差 3.38 cm $\Delta y\to 0$ $\Delta y\to 0$
    UGV_2 航向角相对误差 0.43 % $\Delta \theta\to 0$ $\Delta \theta\to 0$
    场景逼真度 $\bullet\bullet\bullet$ $\bullet$ $\bullet\bullet$
    人机交互 $\bullet\bullet\bullet$ $\bullet$ $\bullet\bullet$
    可扩展性 (感知及导航) $\bullet\bullet\bullet$ $\bullet\bullet$ $\bullet$
    开发简易性 $\bullet\bullet\bullet$ $\bullet\bullet$ $\bullet$
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-03-03
  • 录用日期:  2020-05-12
  • 网络出版日期:  2021-06-10
  • 刊出日期:  2021-06-10

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