Area coverage with heterogeneous UAVs using scan patterns

In this paper we consider a problem of scanning an outdoor area with a team of heterogeneous Unmanned Air Vehicles (UAVs) equipped with different sensors (e.g. LIDARs). Depending on the availability of the UAV platforms and the mission requirements there is a need to either minimise the total mission time or to maximise certain properties of the scan output, such as the point cloud density. The key challenge is to divide the scanning task among UAVs while taking into account the differences in capabilities between platforms and sensors. Additionally, the system should be able to ensure that constraints such as limit on the flight time are not violated. We present an approach that uses an optimisation technique to find a solution by dividing the area between platforms, generating efficient scan trajectories and selecting flight and scanning parameters, such as velocity and flight altitude. This method has been extensively tested on a large set of randomly generated scanning missions covering a wide range of realistic scenarios as well as in real flights.