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.