UAV-Based Rescue System and Seismic Zonation for Hazard Analysis and Disaster Management

Shahzad, Abdul Qahar; Lisa, Mona; Khan, Muhammad Alamgir; Khan, Irum

doi:10.1007/978-3-030-97113-7_14

Cited by 2 publications

(1 citation statement)

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“…Following natural disasters such as earthquakes, floods, and forest fires, governments can deploy multi-UAV systems for rapid disaster area reconnaissance to assess the situation, locate stranded individuals, and provide immediate and accurate information support for rescue decisions. A swarm of UAVs can work collaboratively to cover extensive search areas, significantly enhancing search efficiency and rescue speed [101][102][103][104].…”

Section: Emergency Management and Rescuementioning

confidence: 99%

A Review of Collaborative Trajectory Planning for Multiple Unmanned Aerial Vehicles

Wang,

Huang,

et al. 2024

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In recent years, the collaborative operation of multiple unmanned aerial vehicles (UAVs) has been an important advancement in drone technology. The research on multi-UAV collaborative flight path planning has garnered widespread attention in the drone field, demonstrating unique advantages in complex task execution, large-scale monitoring, and disaster response. As one of the core technologies of multi-UAV collaborative operations, the research and technological progress in trajectory planning algorithms directly impact the efficiency and safety of UAV collaborative operations. This paper first reviews the application and research progress of path-planning algorithms based on centralized and distributed control, as well as heuristic algorithms in multi-UAV collaborative trajectory planning. It then summarizes the main technical challenges in multi-UAV path planning and proposes countermeasures for multi-UAV collaborative planning in government, business, and academia. Finally, it looks to future research directions, providing ideas for subsequent studies in multi-UAV collaborative trajectory planning technology.

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Section: Emergency Management and Rescuementioning

confidence: 99%