Intelligent Coordination of UAV Swarm Systems

doi:10.3390/books978-3-0365-8658-8

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Intelligent Coordination of UAV Swarm Systems

Edited by

September 2023

554 pages

ISBN978-3-0365-8659-5 (Hardback)
ISBN978-3-0365-8658-8 (PDF)

https://doi.org/10.3390/books978-3-0365-8658-8

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This book is a reprint of the Special Issue Intelligent Coordination of UAV Swarm Systems that was published in

Engineering

Environmental & Earth Sciences

Summary

The reprint delves into the fascinating world of unmanned aerial vehicle (UAV) swarm systems and their intelligent coordination. This comprehensive collection of research papers explores advancements in UAV swarm systems, such as intelligent perception and cognition, swarm navigation and localization, autonomous decision and planning, cooperative guidance and control, and swarm intelligence. UAV swarm systems have gained significant attention in recent years due to their potential for revolutionizing various domains, including surveillance, search and rescue, environmental monitoring, and disaster response. Intelligent perception and cognition play a crucial role in enabling UAV swarm systems to perceive and understand their environment. Swarm navigation and localization techniques ensure precise positioning and effective movement coordination within the swarm. Autonomous decision and planning algorithms empower UAV swarm systems to make intelligent choices in real-time. Cooperative guidance and control strategies facilitate seamless collaboration among individual UAVs within the swarm. Swarm intelligence, inspired by the collective behavior of social insects, offers valuable insights into designing robust and scalable UAV swarm systems.

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Keywords

bionic algorithm; swarm robotic; environment exploration; distributed control; Lévy flight; multi-UAV; two-step auction; area coverage; obstacle avoidance; energy constraint; multi-UAV formation; velocity constraints; fixed-wing UAV; dataset; vehicle detection; UAV; complex scenes; area partitioning; connectivity; coverage mission; firefly algorithm; GAMA platform; heterogeneity; Micro Aerial Vehicles; Voronoi-tessellation; landing guidance; airborne monocular vision; large distance span; scale adaptive; pose tracking; formation flying; formation transformation; Hungarian algorithm; trajectory planning; task allocation; flight control; automatic obstacle avoidance; complete coverage path planning; few-shot object counting; multi-drone collaboration; Tibetan antelopes; Hoh Xil nature reserve; formation control; UAV swarm; quadrotor UAVs; VTOL UAVs; attitude synchronization; orientation estimation; bearing-based formation control; swarm maintenance; drone swarm; complex network; system reliability; multi-objective optimization; performance impact method; multi-agent scheduling; task rescheduling; distributed method; deadlock problem; search and rescue; UAV swarms; UAV; swarm; resiliency; multi agent system; real-time decision making; decentralized monitoring; swarm surveillance algorithm; autonomous quadcopters; swarm intelligence; multi-UAV; path planning; incomplete information; multi-objective; reinforcement learning; object detection; Unmanned Aerial Vehicle (UAV) swarm; lightweight model; attention mechanism; data augment; multiple UAVs; trajectory planning; task allocation; obstacle avoidance; intelligent search; Monte Carlo tree search; knowledge-based particle swarm optimization; fixed-wing UAV; formation keeping; reinforcement learning; unmanned aerial vehicles; three-dimensional localization; semidefinite programming; flipping ambiguity avoidance; gray wolf optimization; formation control; consistency theory; communication delay; constraints; UAV cooperative navigation; multi-agent reinforcement learning; autonomous decision making; centralized training and decentralized execution; curriculum learning; exploration of unknown environment; UAV cluster; sampling and optimization; distributed path planning; particle swarm optimization; swarm intelligence; swarm behaviors; swarm robotics; industrial swarm; swarm robotics applications; MAV/UAV; formation control; hybrid reinforcement learning; hybrid intelligent agent; waypoint-following guidance; varying speed; differential geometric curve theory; global energy optimization; suboptimal form; flight experiments; GPS spoofing; collaborative positioning; rigid structure; complex scene; yaw