Behavior-based swarm robotic search and rescue using fuzzy controller.

Highlights • A self-contained dynamic goal-seeking mechanism using behavior-based approach has been implemented for searching targets in an unknown environment. • Bio-inspired dynamic virtual leaders are used, who steer and drive the swarm from current goal to the reference goal. • An avoid past behavior has been designed to help goal-seeking behavior more efficiently. Abstract Search and rescue (SAR) is one of the foremost issues in disaster management. A robust SAR mechanism can significantly reduce the number of causalities. This paper presents a behavior-based model for a swarm of small robots to perform an efficient SAR operation in an unknown environment. The swarm is guided by a dynamically selected virtual leader (VL). A self-contained dynamic goal-seeking mechanism, using behavior-based approach, is designed to search targets (victims). Under the leadership of VL, the proposed model retains the integrity of the swarm while driving it from its current position to referenced goals. Fuzzy logic has been used to design constituent behavioral modules, namely obstacle avoidance, alignment, and inter-robot cohesion. The model has been simulated to validate its efficiency and the findings reveal that robots moving as a swarm are more effective in the SAR process as compared to multiple single robots. Graphical abstract Image, graphical abstract [ABSTRACT FROM AUTHOR]