MSc thesis subject: Autonomous UAVs for automated airborne pest monitoring

Drosophila suzukii, also known as the spotted wing fruit fly, has become a serious pest in Europe attacking many soft-skinned crops such as several berry species and grapevines since its spread in 2008 to Spain and Italy. An efficient and accurate monitoring system to identify the presence of D. suzukii in crops and their surroundings is essential for the prevention of damage to economically valuable fruit crops.

Current strategies to monitor the presence of D. suzukii (e.g. analyzing the contents of liquid bait traps under a microscope) are very labour intensive and time consuming. We are therefore exploring the feasibility of an automated way of monitoring D. suzukii flies using unmanned aerial vehicles (UAVs). The basic idea is to have a UAV that autonomously flies past sticky traps that are distributed in a farmers field. At the location of the traps, the UAV is supposed to take a photo, which will be later on used to determine the presence of D. suzukii. During its flight through the field, the UAV is supposed to avoid any collision with other objects and at the time it takes a photo, the UAV is supposed to positions itself at a proper distance and angle from the trap to take the best possible photo.


The main objective is the development of an autonomously flying UAV for the detection of pests in sticky traps. The thesis will focus on finding the best strategy to develop such a system in terms of hardware and software. Moreover, the development and testing of algorithms for autonomously flying, collision avoidance and fine positioning will be dealt with in this thesis.


  • Alsalam, Bilal, Gonzalez, Felipe, Morton, Kye, & Campbell and Duncan (2017). Autonomous UAV with vision based on-board decision making for remote sensing and precision agriculture. In: 2017 IEEE Aerospace Conference, 4-11 March 2017, Yellowstone Conference Center, Big Sky, Montana.


  • UAV enthusiast
  • Excited about automation
  • Preferable some programming skills, or willing to learn

Theme(s): Sensing & measuring