Evaluation of Communication Paradigms in Swarm Robotics Simulation for Search and Rescue using Reynolds Flocking Rule

Abstract

Natural disasters, which are often unpredictable, 
pose a major threat to human life as they inevitably cause 
casualties. One of the measures to reduce mortality in such 
events is the implementation of Search and Rescue (SAR) 
operations after a disaster occurs. However, human limitations 
often cause SAR operations to be slow, delayed, or even result in 
more casualties due to extreme weather conditions and 
challenging rescue terrains. This study presents a potential 
solution to these problems through the application of swarm 
robots based on Reynolds Flocking Rule. The research simulates 
the use of three communication paradigms—Broadcast 
Communication Swarm, Heterogeneous Swarm, and Base 
Station Swarm—and compares the advantages and 
disadvantages of each paradigm. From 100 simulation runs, the 
Broadcast Communication Swarm achieved the lowest average 
number of iterations at 425.82. It can be concluded that the 
Broadcast Communication Swarm is highly suitable for SAR 
operations, where time is a critical factor.