Dynamic multi-UAV path planning for multi-target search and connectivity

Name: Dynamic multi-UAV path planning for multi-target search and connectivity
Author: Guven, Islam, Balanji, Hamid Majidi, Yanmaz, Evsen

İsim	Dynamic multi-UAV path planning for multi-target search and connectivity
Yazar	Guven, Islam, Balanji, Hamid Majidi, Yanmaz, Evsen
Basım Tarihi:	2024-07
Basım Yeri	- IEEE
Konu	Multi-target, Maintaining connectivity, Path planning, Relay positioning, Unmanned aerial vehicles, Drone networks, Task analysis, Monitoring, Search problems, Autonomous aerial vehicles, Drones, Sensors, Relays
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0018-9545
Kayıt Numarası	9da76e04-ce0b-4626-9de2-581396c2fec7
Lokasyon	Electrical & Electronics Engineering
Tarih	2024-07
Notlar	TÜBİTAK
Örnek Metin	In this work, we propose and analyze multi-drone path planners for multi-target search and connectivity. The goal of the unmanned aerial vehicle (UAV) mission is to search an unknown area to detect, connect and monitor multiple randomly distributed targets to the ground control station (GCS) while maintaining the connectivity of the UAVs to GCS. To this end, we propose to use two types of UAVs: search and relay. The search drones scan the area via onboard sensors, whereas relay UAVs provide connectivity. We propose three different responses to target detection with increasing adaptability: (i) follow pre-planned paths and inform GCS when possible, (ii) follow pre-planned paths and inject new UAVs to monitor the detected targets, (iii) assign a search UAV to monitor target, and re-plan remaining UAV paths. Furthermore, we implement multi-objective optimization-based planners for single-type UAVs, where the paths are optimized in terms of total coverage time and percentage connectivity. Our results show that less adaptive schemes detect all targets faster; however, the connectivity of the UAVs and the targets to GCS is significantly better for the adaptive schemes. The joint-optimization methods, on the other hand, in their basic form, trade-off detection time to improve connectivity. When they are used in conjunction with relays, the connectivity performance is improved; however, the overall mission times may be up to 40% higher than our proposed methods, depending on the number of UAVs and targets.
DOI	10.1109/TVT.2024.3363840
Cilt	73

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Dynamic multi-UAV path planning for multi-target search and connectivity

Yazar Guven, Islam, Balanji, Hamid Majidi, Yanmaz, Evsen

Basım Tarihi 2024-07

Basım Yeri - IEEE

Konu Multi-target, Maintaining connectivity, Path planning, Relay positioning, Unmanned aerial vehicles, Drone networks, Task analysis, Monitoring, Search problems, Autonomous aerial vehicles, Drones, Sensors, Relays

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0018-9545

Kayıt Numarası 9da76e04-ce0b-4626-9de2-581396c2fec7

Lokasyon Electrical & Electronics Engineering

Tarih 2024-07

Notlar TÜBİTAK

Örnek Metin In this work, we propose and analyze multi-drone path planners for multi-target search and connectivity. The goal of the unmanned aerial vehicle (UAV) mission is to search an unknown area to detect, connect and monitor multiple randomly distributed targets to the ground control station (GCS) while maintaining the connectivity of the UAVs to GCS. To this end, we propose to use two types of UAVs: search and relay. The search drones scan the area via onboard sensors, whereas relay UAVs provide connectivity. We propose three different responses to target detection with increasing adaptability: (i) follow pre-planned paths and inform GCS when possible, (ii) follow pre-planned paths and inject new UAVs to monitor the detected targets, (iii) assign a search UAV to monitor target, and re-plan remaining UAV paths. Furthermore, we implement multi-objective optimization-based planners for single-type UAVs, where the paths are optimized in terms of total coverage time and percentage connectivity. Our results show that less adaptive schemes detect all targets faster; however, the connectivity of the UAVs and the targets to GCS is significantly better for the adaptive schemes. The joint-optimization methods, on the other hand, in their basic form, trade-off detection time to improve connectivity. When they are used in conjunction with relays, the connectivity performance is improved; however, the overall mission times may be up to 40% higher than our proposed methods, depending on the number of UAVs and targets.

DOI 10.1109/TVT.2024.3363840

Cilt 73