Modern Defense Technology ›› 2025, Vol. 53 ›› Issue (1): 164-172.DOI: 10.3969/j.issn.1009-086x.2025.01.018

• SIMULATION TECHNOLOGY • Previous Articles     Next Articles

Method for Transmission of Point Cloud and Tele-presence of Map Under Wireless and Low Bandwidth Condition

Xinyu LIU1, Haiting SHEN2, Rui GUO1, Qin ZHANG1   

  1. 1.Beijing Institute of Electronic System Engineering,Beijing 100854,China
    2.Four Academics and Four Departments of Aerospace Science and Industry,Beijing 100854,China
  • Received:2023-10-12 Revised:2024-02-24 Online:2025-02-28 Published:2025-02-27

无线低带宽条件下点云传输和地图远程呈现方法

刘欣宇1, 申海艇2, 郭睿1, 张琴1   

  1. 1.北京电子工程总体研究所,北京 100854
    2.北京机电工程总体设计部,北京 100854
  • 作者简介:刘欣宇(1994-),女,北京人。工程师,博士,研究方向为人工智能。

Abstract:

Intelligent unmanned weapons and equipment are playing an increasingly vital role in modern warfare and have become essential for replacing and assisting soldiers in combat. In unmanned battlefields, rear commanders monitor the battlefield environment through communication. Given the limited bandwidth of military communication equipment, a method for real-time point cloud transmission and remote map presentation is proposed and implemented. The method first estimates the real-time pose using the FAST-LIO algorithm, then compresses the 3D point cloud (keyframe) using the Draco algorithm, and transmits the real-time pose and point cloud via Protobuf-UDP. Finally, the SC-PGO algorithm is used to optimize and generate the global map. This is the first engineering solution to achieve real-time point cloud compression and transmission based on the ROS platform. The experimental results demonstrate that the proposed method provides effective compression and stable transmission quality for real-time point clouds, addressing the challenges of point cloud transmission and remote map presentation under low-bandwidth wireless conditions, and enabling commanders to perceive the battlefield environment in real time.

Key words: remote map presentation, point cloud transmission, FAST-LIO, Draco, point cloud compression

摘要:

智能化无人武器装备在现代化作战中发挥日益重要的作用,已成为替代和辅助士兵作战的必要装备。在无人化战场中,后方指挥人员通过通信对战场环境保持关注。鉴于军用通信设备带宽有限,设计并实现了一种低带宽条件下的点云传输和地图远程呈现方法。方法通过FAST-LIO算法估计实时位姿,利用Draco算法对三维点云(关键帧)进行压缩,并基于Protobuf-UDP完成位姿和点云的实时传输,采用SC-PGO算法优化并产生全局地图,是首个基于ROS平台实现点云实时压缩和传输的工程。实验结果表明,所提方法对于实时点云表现出较好的压缩效果和稳定的传输质量,解决了无线低带宽条件下点云传输和地图远程呈现的问题,实现了指挥人员对战场环境的实时感知。

关键词: 地图远程呈现, 点云传输, FAST-LIO, Draco, 点云压缩

CLC Number: