具有能量约束的空中机器人分布区域近最优覆盖路径规划

Zeba Khanam, K. Mcdonald-Maier, Shoaib Ehsan
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引用次数: 3

摘要

无人驾驶飞行器(uav)在环境监测、排雷、搜索和救援等领域的应用范围覆盖方面获得了极大的普及。现有的区域覆盖研究大多只考虑了单个区域,而最近的研究很少考虑多个分布区域的覆盖。无人机在覆盖分布的多个区域时受到的限制之一是能量约束,其中不可能完全覆盖区域。从战略的角度出发,提出了一种新的算法,解决了一种区域覆盖问题的变体,即由于能量约束导致的路径长度限制,无人机的目标是实现接近最优的区域覆盖。在本文中,通过首先提出问题,然后提出解决方案来进行初步研究。该解决方案被划分为两个相互依赖的子问题:i)区域间覆盖,ii)区域内覆盖。通过在一组详尽的测试用例场景中分析算法的特性,并将其与两种最先进的区域覆盖方法进行比较,对算法的性能进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Near-Optimal Coverage Path Planning of Distributed Regions for Aerial Robots with Energy Constraint
Unmanned Aircraft Vehicles (UAVs) have gained immense popularity for area coverage having applications such as environmental monitoring, demining, search and rescue, among others. Most of the existing studies exploring area coverage have considered only a single region, however, few recent studies have considered coverage of multiple distributed regions. One of the limitations which UAV suffers while covering distributed multiple regions is energy constraints where complete area coverage is not possible. From a strategical point of view, we propose a novel algorithm which solves a variant of area coverage problem where the UAV aims to achieve near-optimal area coverage due to path length limitation caused by the energy constraint. In this paper, a preliminary study is conducted by first formulating the problem and later on presenting a solution. The solution has been partitioned into two inter-dependent sub-problems: i) inter-region coverage, ii) intra-region coverage. The performance of the algorithm has been evaluated by analysing its properties over an exhaustive set of test case scenarios and comparing it against two state-of-the-art area coverage approaches.
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