Towards an efficient Multi-Robots Search and Rescue strategy

Abstract

Due to the hazardous and hostile conditions that arise following a natural disaster, multi-robot systems are employed as substitutes for human beings in the task of searching and rescuing victims. The exploration of unknown environments is considered as a paramount concern in the field of mobile robotics. It consists a foundational stage for various applications such as search and rescue, cleaning tasks, and foraging. We proposed in this work, a new swarm robotic search strategy for search and rescue operations. The proposed strategy is inspired by the hunting behavior of Penguins. It hybridizes the Penguin Search Optimization Algorithm with the Random Walk Algorithm to modulate the global and local search behaviors of robots. To evaluate the effectiveness of our strategy, we implemented it in the ARGoS multi-robot simulator and conducted a series of experiments. The results obtained from these experiments clearly demonstrate the efficiency and effectiveness of our proposed search strategy.