无人机在市区追踪目标

Zhirong He, Jian-xin Xu, K. Lum
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引用次数: 1

摘要

在这项工作中,我们解决了使用固定翼无人机(uav)在城市地区自主跟踪一组地面静态目标的问题。在这种情况下,无人机配备的传感器受到城市区域遮挡的约束。假定市区的视线(LOS)遮挡信息是可用的。考虑固定翼产生的动力学约束,将每架无人机建模为杜宾斯汽车。搜索无人机最短路径即杜宾路径的运动规划问题是一个NP困难问题。我们提出了一种算法,该算法可以提供次优杜宾路径,从而为无人机连续跟踪静态目标群提供闭环路径,并最小化损失跟踪时间。该算法在基于新加坡CBD的可视化数据库上进行了仿真验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Targets tracking by UAVs in an urban area
In this work we address the problem of autonomously tracking a group of ground static targets in an urban area using fixed wing unmanned aerial vehicles (UAVs). In this scenario, UAVs are equipped with sensors that are subject to the constraints of urban area occlusions. Information regarding the line of sight (LOS) occlusions in the urban area is assumed available. Each UAV, considering the dynamic constrains arising from the fixed wing, is modeled as a Dubins car. The motion planning of searching the shortest path for UAVs, namely Dubins path, is a NP hard problem. We propose an algorithm, which can provide sub-optimal Dubins path, hence can bring a closed-loop path for UAVs to continuously track the group of static targets and minimize the time of loss track. The proposed algorithm is validated through simulations on a visual database that is based on the CBD in Singapore.
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