Multi-UAV Area Coverage Based on Relative Localization: Algorithms and Optimal UAV Placement

This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained...

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Vydáno v:Sensors (Basel, Switzerland) Ročník 21; číslo 7; s. 2400
Hlavní autoři: Zhang, Ziyong, Xu, Xiaoling, Cui, Jinqiang, Meng, Wei
Médium: Journal Article
Jazyk:angličtina
Vydáno: Switzerland MDPI AG 31.03.2021
MDPI
Témata:
Accuracy
Algorithms
Communication
coverage control
Localization
Optimization
relative localization
Sensors
ultra-wide band (UWB) sensors
Unmanned aerial vehicles
unmanned aerial vehicles (UAVs)
coverage control
ultra-wide band (UWB) sensors
unmanned aerial vehicles (UAVs)
relative localization
ISSN:1424-8220, 1424-8220
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Shrnutí:This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained among the UAVs by using ultra-wide band (UWB) sensors. In this case, multi-UAV relative localization and cooperative coverage control have to be run simultaneously, which is a quite challenging task. In this paper, we propose a single-landmark-based relative localization algorithm, combined with a distributed coverage control law. At the same time, the optimal multi-UAV placement problem was formulated as a quadratic programming problem by compromising between optimal relative localization and optimal coverage control and was solved by using Sequential Quadratic Programming (SQP) algorithms. Simulation results show that our proposed method can guarantee that a team of UAVs can efficiently localize themselves in a cooperative manner and, at the same time, complete the area coverage task.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s21072400