Semiautonomous Drone System for Mapping and Measuring of Agricultural Fields and Forest Stands

Abstract

Unmanned Aerial vehicles are increasingly used in many applications and particularly in agriculture and forestry. This study develops a semi-autonomous quadcopter drone system for mapping and measuring of a given area of land, either agricultural field or forest stand.

A coverage path planning algorithm which generates an optimal path for covering the area to be mapped is developed. The coverage path planning considers three types of area configurations: convex polygon area, concave polygon area and finally a general polygon area with holes in its interior. In order to cover the area by the drone, the dynamic model of the quadcopter system is identified and used to design the position controller. The drone is programmed and the images collection is carried out. The resulting images are used in a image mosaicing algorithm, developed by this study, to build a 2D map of the area of interest.

The resulting system can effectively generates a coverage path in any area which has any polygonal shape configuration. The position controller accuracy allows to collect the images of a given area with specified image overlaps. The images can also to be used to build the map of the area with accuracy that is acceptable to the current application of mapping agricultural or forest fields.