系统工程与电子技术 ›› 2020, Vol. 42 ›› Issue (1): 166-171.doi: 10.3969/j.issn.1001-506X.2020.01.22

• 制导、导航与控制 • 上一篇    下一篇

基于分层SLAM的空地多智能体协同导航

王晓龙(), 刘海颖(), 王景琪()   

  1. 南京航空航天大学航天学院, 江苏 南京 210016
  • 收稿日期:2019-04-29 出版日期:2020-01-01 发布日期:2019-12-23
  • 作者简介:王晓龙(1996-),男,硕士研究生,主要研究方向为多智能体协同导航。E-mail:dragon_19960320@nuaa.edu.cn|刘海颖(1980-),男,副教授,博士,主要研究方向为导航制导与控制。E-mail:liuhaiying@nuaa.edu.cn|王景琪(1995-),男,硕士研究生,主要研究方向为相对导航。E-mail:617730662@qq.com
  • 基金资助:
    中央高校基本科研业务费专项资金(NS2019047);江苏省自然科学基金(BK20161490)

Collaborative navigation of air-ground multi-agent based on hierarchical SLAM

Xiaolong WANG(), Haiying LIU(), Jingqi WANG()   

  1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2019-04-29 Online:2020-01-01 Published:2019-12-23
  • Supported by:
    中央高校基本科研业务费专项资金(NS2019047);江苏省自然科学基金(BK20161490)

摘要:

针对单一智能体在导航过程中存在全球导航卫星系统(global navigation satellite system,GNSS)易受遮挡或干扰,惯性导航存在误差累积的问题,提出基于视觉的分层即时定位与地图构建(simultaneous localization and mapping,SLAM)空地多智能体协同算法。通过建立系统模型,采用基于扩展卡尔曼滤波融合欧氏点、逆深度点、锚定同质点3种不同特征点的分层SLAM算法,实现了对导航系统的辅助和增强。针对空地协同场景设计并开展了仿真实验。结果表明,空地多智能体协同算法可以将位置误差降低40%;而在使用锚定同质点以后,误识别率由49%降低至4%。实验验证该算法具有良好的定位精度、实用性和有效性。

关键词: 视觉导航, 空地多智能体, 分层即时定位与地图构建, 协同导航, 广义回环检测, 扩展卡尔曼滤波

Abstract:

Aiming at the problem that global navigation satellite system(GNSS) is easily occluded or interfered in the navigation process and error accumulation of inertial navigation, a vision-based hierarchical simultaneous localization and mapping (SLAM) air-ground multi-agent coordination algorithm is proposed. By establishing the system model, the hierarchical SLAM algorithm based on the extended Kalman filter is used to fuse three different feature points including the Euclidean point, the inverse depth point and the anchor one, so the navigation system is assisted and enhanced. The simulation experiment is designed and carried out for the air-ground collaborative scene. The results show that the air-ground coordination method can reduce the position error down by 40%; after using the anchored homogenous point, the false recognition rate is reduced from 49% to 4%. The experimental results show that the algorithm has good positioning accuracy, practicability and effectiveness.

Key words: visual navigation, air-ground multi-agent (AGMA), coordination navigation, hierarchical simultaneous localization and mapping (SLAM), general loop closure, extended Kalman filter (EKF)

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