Setting up a mixed reality simulator for using teams of autonomous UAVs in air pollution monitoring

Abstract

A framework based on a mixed reality simulator for coordinating teams of autonomous Unmanned Aerial Vehicles (UAVs) is been developed. This framework would serve as a tool to facilitate crossing the reality gap for different applications; particularly when using these UAVs teams for air pollution monitoring and measurement. The system is built on a co-evolutionary simulator that makes use of data transmitted from some real UAVs to integrate them within a team of simulated UAVs. The system allows the progressive increase of the number of real UAV in the team. This facilitates the setting-up of a single UAV control system and also of the UAV collaboration schemes for different scenarios. A specific implementation of this system focussed on mapping the pollutant dispersion of a plume in the atmosphere is presented. Implementing an appropriate pollution dispersion model within the simulator is a key aspect of the system. This model should require few computational resources, should be easy to adapt in real time to ambient changes, and it should have a fair accuracy.