Author(s) :

Florian Lerch.

Volume/Issue :

Abstract :

Search and Rescue (SAR) operations often happen in complex, unpredictable environments where there are a lot of risks and logistical challenges. Autonomous Unmanned Aerial Vehicle (UAV) swarms have arisen as a solution to improve the speed, safety, and coverage of SAR missions. This paper reviews and analyzes bio-inspired algorithms that draw from principles observed in nature that enable decentralized, robust, and adaptive coordination among UAVs. This paper examines how these algorithms can be combined, each addressing a certain phase of an SAR mission, like area exploration, target detection, collision avoidance, and target escorting. The strengths and limitations of each algorithm are discussed, and notably their scalability, communication requirements, environmental adaptability, and real-world feasibility. This work demonstrates the potential of hybrid biomimetic systems and outlines crucial future research that needs to happen in order to have real-world SAR missions.