A fuzzy-swarm based approach for the coordination of unmanned aerial vehicles

Abstract

In this paper, we propose a hybrid mechanism based on fuzzy logics and swarm intelligence for the coordination of multiple Unmanned Aerial Vehicles (UAVs). In a previous work we have developed a finite state machine to control the swarm of robots by pre-defining expected behaviors. The main goal of our proposal is to replace the finite state machine by a Takagi-Sugeno fuzzy mechanism that smoothly changes the expected behavior of the UAVs aiming to obtain the dynamic behavior required by real-time critical systems. We deployed three different metrics to compare our proposal to the previous one, such as the target tracking capability, the anti-collision rate and the cohesion rate aiming to catch the most important aspects desired in a group of UAVs tracking targets. We performed simulations varying the number of UAVs in the environment and the number of targets to be tracked. The results indicate that the proposed mechanism diminished the number of collisions and increased the cohesion rate.