With the strict Paris climate goals, all eyes are set on the development of sustainable solutions that can replace or improve commercial solutions. This thesis revolves around the design and implementation of a subsystem for the creation of a solar powered drone. The goal of the solar powered drone is increasing the flight range of a commercial drone with the addition of photovoltaic (PV) panels. The subsystem designed and implemented in this thesis is split up into two separate systems namely, the control part and the image processing part. The control part revolves around the design, implementation and validation of Maximum Power Point Tracking (MPPT) for the PV panels. The image processing part revolves around the design, implementation and validation of an albedo processing pipeline.
For the MPPT, a variable step size perturb and observe algorithm has been implemented with a worse case tracking delay of 40 milliseconds during a change of irradiation from $900 W/m^2$ to $100 W/m^2$ and and more than 99\% power efficiency in steady state conditions. For the albedo pipeline, multiple RAW images are loaded one after another. Vignette correction is applied making the pixel values at the edges and the center of the image compatible with each other. The user can annotate a known reference target that is used to calibrate the albedo generation. Finally, the images are stitched together using Open Drone Map to create a complete albedo map. The results indicate accurate visible band albedo generation, however additional sensors would be needed to obtain wide band albedo generation.