An embedded system architecture based on genetic algorithms for mission and safety planning with UAV.

The present paper describes an embedded system architecture, based on genetic algorithms, aiming safety mission execution by Unmanned Aerial Vehicles (UAVs). A two-dimensional non-convex environment is considered since obstacle avoidance happens. The embedded system integrates the Mission Oriented Sensor Array (MOSA) and In-Flight Awareness (IFA) systems, where MOSA is responsible for mission accomplishment and IFA stands for flight safety. The features of MOSA and IFA are combined under a platform that applies promising genetic algorithm approaches from literature to reach their goals. First, the genetic algorithms performance running from the embedded system is compared against their performance on a personal computer architecture. Next, the proposed system is evaluated in a real-world scenario using Software-In-The-Loop (SITL) technique. The computational results showed that the embedded system provides reliable results.