Health-Aware Coverage Control With Application to a Team of Small UAVs

Marier, Jean-Samuel; Rabbath, C.A.; Léchevin, N.

doi:10.1109/tcst.2012.2208113

Cited by 37 publications

(12 citation statements)

References 17 publications

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“…One well-studied scenario is to view UAVs as mobile access points serving GTs. For such a use case, algorithms for UAV coverage under variable coverage radii and possible UAV losses are proposed in [15]. For one UAV and one GT, [16] optimizes the UAV trajectory to achieve high throughput with low UAV energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Deployment and Trajectory Optimization of UAVs: A Quantization Theory Approach

Koyuncu

Shabanighazikelayeh

Seferoğlu

2018

IEEE Trans. Wireless Commun.

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Optimal deployment and movement of multiple unmanned aerial vehicles (UAVs) is studied. The considered scenario consists of several ground terminals (GTs) communicating with the UAVs using variable transmission power and fixed data rate. First, the static case of a fixed geographical GT density is analyzed. Using high resolution quantization theory, the corresponding best achievable performance (measured in terms of the average GT transmission power) is determined in the asymptotic regime of a large number of UAVs. Next, the dynamic case where the GT density is allowed to vary periodically through time is considered. For one-dimensional networks, an accurate formula for the total UAV movement that guarantees the best time-averaged performance is determined. In general, the tradeoff between the total UAV movement and the achievable performance is obtained through a Lagrangian approach. A corresponding trajectory optimization algorithm is introduced and shown to guarantee a convergent Lagrangian. Numerical simulations confirm the analytical findings. Extensions to different system models and performance measures are also discussed.

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Section: Introductionmentioning

confidence: 99%

Deployment and Trajectory Optimization of UAVs: A Quantization Theory Approach

Koyuncu

Shabanighazikelayeh

Seferoğlu

2018

IEEE Trans. Wireless Commun.

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“…文献 [38] 基于自适应神经网络进行无人机气动模型参数辨识, 利用鲁棒控制方法设计了容错控制器. 加拿大国防部研究中心考虑了多源异构传感器性能和故障条件下的编队无人机覆盖控制问题, 设计了一种自适应决策方法可根据无人机健康状态自动调整无人机覆盖范围 [39] . 为解决无人机空中加油时执行器突发故障的问题, 美国 Texas A&M University 的 Valasek 教授团队 [40] 设计了基于自适应动态逆的容错控制器, 保证了无人机的跟踪性能.…”

Section: 无人机容错控制方法与技术unclassified

Safety control system technologies for UAVs: review and prospect

Guo¹,

Yu²,

Zhang³

et al. 2020

Sci. Sin.-Inf.

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Formal verification of safety protocol in train control system SCIENCE CHINA Technological Sciences 54, 3078 (2011); Receding horizon control for multi-UAVs close formation control based on differential evolution SCIENCE CHINA Information Sciences 53, 223 (2010); Simultaneous cooperative relative localization and distributed formation control for multiple UAVs SCIENCE CHINA Information Sciences 63, 119201 (2020); New progress and prospect of oilfields development technologies in China

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“…Another research has been devoted to improve control over AUS (in the specific case UAV) in order to increase their capability to cover a selected region and provide the scientists with required information despite their performance indexes are very variable along the time. The proposed algorithms in such case are based on the communication among each swarm component: decrease of communication availability causes, as a consequence, reduction of a vehicle's capability in carrying out the assigned task (Marier et al, 2013).…”

Section: Networking and Communication Modelsmentioning

confidence: 99%

Simulation of autonomous systems in the extended marine domain

Tremori

Agresta²,

Ferrando³

2016

IJSPM

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This paper is focused on characteristics and goals of an integrated architecture which aims at reproducing joint interoperability among autonomous systems. The paper proposes an experimentation over a scenario developed for the maritime context that uses an innovative simulator. The authors' goal, during such research, consists of identifying requirements related to these simulators so that they accurately keep into account the most important elements affecting real operative context. This analysis is addressing training (Kennedy, 2010), engineering and it could be further developed for supporting or operation supervision. General architecture devoted to integrate such simulators within a federation, together with the approach that has been used in order to carry out this operation, represent the subjects of this paper; the mission environment has been created with the only goal to test the federation, and similarly simulation architecture and conceptual models are validated through proposed preliminary activities

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Health-Aware Coverage Control With Application to a Team of Small UAVs

Cited by 37 publications

References 17 publications

Deployment and Trajectory Optimization of UAVs: A Quantization Theory Approach

Deployment and Trajectory Optimization of UAVs: A Quantization Theory Approach

Safety control system technologies for UAVs: review and prospect

Simulation of autonomous systems in the extended marine domain

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