Multi-UAV Pre-Positioning and Routing for Power Network Damage Assessment

Lim, Gino J.; Kim, Seon Jin; Cho, Jae-Young; Gong, Yue; Khodaei, Amin

doi:10.1109/tsg.2016.2637408

Cited by 81 publications

(51 citation statements)

References 28 publications

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“…Some problems are worth the effort, such as system resilience, complexity and communication between the UAVs, navigation and cooperative control in harsh conditions, environmental sense and collision avoidance, detection of anomalies within the fleet and disruption handling including environmental obstacles, signal interference and attack [50,64]. Besides, how to configure the number of UAVs and plan flight routes to achieve optimal efficiency and performance is also a challenging issue [65,66].…”

Section: Combined Field Of Viewmentioning

confidence: 99%

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Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, applications, and prospects

Xiang

Xia

Zhang

2019

IEEE Geosci. Remote Sens. Mag.

149

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The past few decades have witnessed the great progress of unmanned aircraft vehicles (UAVs) in civilian fields, especially in photogrammetry and remote sensing. In contrast with the platforms of manned aircraft and satellite, the UAV platform holds many promising characteristics: flexibility, efficiency, highspatial/temporal resolution, low cost, easy operation, etc., which make it an effective complement to other remote-sensing platforms and a cost-effective means for remote sensing. Considering the popularity and expansion of UAV-based remote sensing in recent years, this paper provides a systematic survey on the recent advances and future prospectives of UAVs in the remote-sensing community. Specifically, the main challenges and key technologies of remote-sensing data processing based on UAVs are discussed and summarized firstly. Then, we provide an overview of the widespread applications of UAVs in remote sensing. Finally, some prospects for future work are discussed. We hope this paper will provide remotesensing researchers an overall picture of recent UAV-based remote sensing developments and help guide the further research on this topic.

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Section: Combined Field Of Viewmentioning

confidence: 99%

“…16. In fact, it is an important but challenging task to detect power facilities from cluttered background and identify their defects [66]. As one of the most important power infrastructures, power lines are often detected by line-based detection, supervised classification or 3D point cloud-based methods [192].…”

Section: Power Infrastructure Monitoringmentioning

confidence: 99%

Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, applications, and prospects

Xiang

Xia

Zhang

2019

IEEE Geosci. Remote Sens. Mag.

149

View full text Add to dashboard Cite

show abstract

“…A multi-platform UAV system for power line inspection was experimented in [11]. Similarly, a multi-UAV positioning and routing for power network damage assessment was introduced in [12] whereas some other studies developed inspection systems for buildings or bridges [27], [10]. However, those systems are rather limited in communication and coordination capability.…”

Section: Related Workmentioning

confidence: 99%

“…While the use of single UAVs has proved its applicability in inspection, recent works start to study the coordination of UAVs in a group to achieve higher time efficiency, performance and resilience [11], [12]. A multi-platform UAV system for power line inspection tasks [11] shows that the time to inspect 70 km of the power line can be reduced to 3 hours compared to a week as with the traditional inspection method.…”

Section: Introductionmentioning

confidence: 99%

System Architecture for Real-Time Surface Inspection Using Multiple UAVs

Hoang

Phung

Dinh

et al. 2020

IEEE Systems Journal

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This paper presents a real-time control system for surface inspection using multiple unmanned aerial vehicles (UAVs). The UAVs are coordinated in a specific formation to collect data of the inspecting objects. The communication platform for data transmission is based on the Internet of Things (IoT). In the proposed architecture, the UAV formation is established via using the angle-encoded particle swarm optimisation to generate an inspecting path and redistribute it to each UAV where communication links are embedded with an IoT board for network and data processing capabilities. Data collected are transmitted in real time through the network to remote computational units. To detect potential damage or defects, an online image processing technique is proposed and implemented based on histograms. Extensive simulation, experiments and comparisons have been conducted to verify the validity and performance of the proposed system.

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“…Due to such characteristics, UAVs have been really useful in a number of fields and applications, like remote sensing, real-time monitoring, disaster management, border and crowd surveillance, military applications, delivery of goods, or precision agriculture [10,11]. The use of UAVs has been also suggested for providing services in a number of industrial applications, like critical infrastructure inspections [12][13][14][15][16], sensor monitoring [17,18], automatic cargo transport [19,20], or logistics optimization of UAV swarms [21]. In the case of UAVs that operate in industrial environments, they require certain characteristics that may differ substantially from other applications [22].…”

Section: Introductionmentioning

confidence: 99%

A Review on IoT Deep Learning UAV Systems for Autonomous Obstacle Detection and Collision Avoidance

et al. 2019

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Advances in Unmanned Aerial Vehicles (UAVs), also known as drones, offer unprecedented opportunities to boost a wide array of large-scale Internet of Things (IoT) applications. Nevertheless, UAV platforms still face important limitations mainly related to autonomy and weight that impact their remote sensing capabilities when capturing and processing the data required for developing autonomous and robust real-time obstacle detection and avoidance systems. In this regard, Deep Learning (DL) techniques have arisen as a promising alternative for improving real-time obstacle detection and collision avoidance for highly autonomous UAVs. This article reviews the most recent developments on DL Unmanned Aerial Systems (UASs) and provides a detailed explanation on the main DL techniques. Moreover, the latest DL-UAV communication architectures are studied and their most common hardware is analyzed. Furthermore, this article enumerates the most relevant open challenges for current DL-UAV solutions, thus allowing future researchers to define a roadmap for devising the new generation affordable autonomous DL-UAV IoT solutions.

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Multi-UAV Pre-Positioning and Routing for Power Network Damage Assessment

Cited by 81 publications

References 28 publications

Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, applications, and prospects

Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, applications, and prospects

System Architecture for Real-Time Surface Inspection Using Multiple UAVs

A Review on IoT Deep Learning UAV Systems for Autonomous Obstacle Detection and Collision Avoidance

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