电子学报 ›› 2020, Vol. 48 ›› Issue (9): 1777-1785.DOI: 10.3969/j.issn.0372-2112.2020.09.016

• 学术论文 • 上一篇    下一篇

基于刚性约束的双移动机器人协同定位

刘剑锋1, 孙力帆1,2, 普杰信1, 何子述2, 王燕玲1   

  1. 1. 河南科技大学信息工程学院, 河南洛阳 471023;
    2. 电子科技大学信息与通信工程学院, 四川成都 611731
  • 收稿日期:2019-08-30 修回日期:2019-12-17 出版日期:2020-09-25
    • 通讯作者:
    • 孙力帆
    • 作者简介:
    • 刘剑锋 男,1993年12月生于河南桐柏.现为河南科技大学信息工程学院博士研究生.主要研究方向为组合导航、多机器人智能系统.E-mail:liu_jfeng@163.com
      普杰信 男,1959年3月生于河南鹿邑.现为河南科技大学信息工程学院教授、博士生导师.主要研究方向为智能信息处理与模式识别、人工智能与认知计算、智能机器人控制.E-mail:pjx@haust.edu.cn
      何子述 男,1962年10月生于四川新繁.现为电子科技大学信息与通信工程学院教授、博士生导师.主要研究方向为雷达信号与信息处理、自适应及阵列信号处理、MIMO雷达与通信.E-mail:zshe@uestc.edu.cn
      王燕玲 女,1976年6月生于山西省晋城.现为河南科技大学信息工程学院博士研究生,洛阳师范学院副教授,主要从事目标跟踪方法研究.E-mail:ling_scu@163.com
    • 基金资助:
    • 国家"十三五"装备预研共用技术和领域基金 (No.61403120207); 国家国防基础研究计划 (No.JCKY2018419C001); 国家自然科学基金 (No.U1504619,No.61671139,No.61573020); 航空科学基金 (No.20185142003); 河南省科技攻关计划项目 (No.182102110397,No.192102210064,No.172102310636)

Cooperative Localization in a Team of Two Mobile Robots Based on Rigid Constraints

LIU Jian-feng1, SUN Li-fan1,2, PU Jie-xin1, HE Zi-shu2, WANG Yan-ling1   

  1. 1. School of Information Engineering, Henan University of Science and Technology, Luoyang, Henan 471023, China;
    2. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
  • Received:2019-08-30 Revised:2019-12-17 Online:2020-09-25 Published:2020-09-25
    • Corresponding author:
    • SUN Li-fan
    • Supported by:
    • National“13th Five-year Plan”Equipment Pre-research Common Technology and Field Fund (No.61403120207); National Defense Basic Research Program (No.JCKY2018419C001); National Natural Science Foundation of China (No.U1504619, No.61671139, No.61573020); Aeronautical Science Foundation of China, ASFC (No.20185142003); Technology Research and Development Program Fund of Henan Province (No.182102110397, No.192102210064, No.172102310636)

摘要: 准确、快速的状态估计是保证多机器人顺利完成协作搬运任务的关键.然而,大部分现有多机器人协同定位方法都存在一定的局限性,往往无法同时兼顾定位精度与计算复杂度.因此,本文从协作搬运任务的特点出发,将距离与方位的刚性约束条件引入协同定位中,同时根据机器人之间的紧密耦合关系建立起通用有效的运动模型和量测模型.最终在此刚性约束系统建模的基础上,提出一种基于高斯-厄米特求积分卡尔曼滤波(Quadrature Kalman Filter,QKF)的双移动机器人协同定位方法.仿真实验结果表明:与基于无约束模型的QKF协同定位方法相比,本文所提方法不但具有更高的定位精度,而且计算复杂度大大降低,有助于实现多机器人实时协同定位.

关键词: 协同定位, 协作搬运, 刚性约束, 求积分卡尔曼滤波, 双机器人系统, 时间复杂度分析

Abstract: Accurate and fast estimation for states is the key to the multi-robot cooperative transportation. However, the majority of the existing multi-robot cooperative localization approaches have a common limitation in which they cannot satisfy the requirements to the positioning accuracy and computational complexity. According to the task characteristics of cooperative transportation, the rigid constrains of the range and azimuth information are first introduced into the cooperative localization. Moreover, the close coupling relationship between robots is fully utilized to establish the general and effective kinematics and measurement models with the rigid constrains. This facilitates the derivation of an efficient approach to the dual-robot cooperative localization based on Gauss-Hermite quadrature Kalman filter (QKF). Experimental results demonstrate that the proposed approach has much higher positioning accuracy than the QKF cooperative localization approach based on unconstrained models, and reduces the computational complexity largely. This paves the way for the real-time cooperative localization in practical applications.

Key words: cooperative localization, cooperative transportation, rigid constraint, quadrature Kalman filter, dual-robot system, time complexity analysis

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