A Cloud-Based Visual Map Reconstruction for UAV Navigation Using Wireless Streaming

A. Q. Nguyen, M. Ha, T. Tran, Dung Daniel Ngo, N. P. Dao, D. T. Tran, J. Pestana
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Abstract

Obstacle maps are essential for autonomous UAVs to achieve navigation. Different kinds of sensors are used for 3D map reconstruction, such as: LIDAR, radar and cameras. However, 3D obstacle map reconstruction from UAVs has been still a challenging task due to the limitation of on-board computational resources. With the development of wireless streaming technologies, a cloud-based solution for visual map reconstruction would solve the issue. A collaborative aerial-ground system for visual map reconstruction using wireless streaming includes several drones and a fixed or mobile ground station. Images are taken from equipped cameras on the UAV while being streamed to a ground station through a high-speed wireless link, such as: WiFi or the mobile network (4G, 5G). The map is then quickly reconstructed from the images by means of a very strong computer, and the output obstacles map is then sent back to the UAV for navigation tasks. In this paper, we propose and implement a cloud-based visual map reconstruction for UAV navigation with a WiFi link. The system worked well for both indoor and outdoor experiments with achieved transfer times per image of less than 0.29 s and a total 3D reconstruction time of less than 205 s for 87 images with a resolution of 1920x1080 px.
基于云的无人机无线流导航视觉地图重建
障碍物地图是自主无人机实现导航的关键。用于三维地图重建的传感器有:激光雷达、雷达和摄像头。然而,由于机载计算资源的限制,从无人机上重建三维障碍物地图仍然是一项具有挑战性的任务。随着无线流媒体技术的发展,一种基于云的可视化地图重建方案将解决这一问题。使用无线流媒体进行视觉地图重建的协同空中-地面系统包括几架无人机和一个固定或移动地面站。图像从无人机上配备的摄像头拍摄,同时通过高速无线链路(如WiFi或移动网络(4G, 5G))流式传输到地面站。然后通过非常强大的计算机从图像中快速重建地图,然后输出障碍物地图被发送回无人机进行导航任务。在本文中,我们提出并实现了一种基于云的无人机导航视觉地图重建与WiFi链路。该系统在室内和室外实验中均表现良好,每张图像的传输时间小于0.29 s,在分辨率为1920x1080 px的87张图像中,总3D重建时间小于205 s。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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