PhD Candidate towards autonomous and real-time UAV mapping

UAVs represent one of the most relevant emerging technologies in the remote sensing domain of the last two decades, becoming a valid alternative to traditional acquisition techniques in a wide range of applications. In common practice, UAVs flights are pre-planned before starting the mission while data processing is performed offline after the acquisition. These methods, however, strongly limit the applicability of UAVs in dynamic and complex contexts. Examples of UAVs able to fly autonomously on an interest area, acquire complete data, understand the scene and take autonomous decisions are still in their very early stage. However, these solutions would promise to open new opportunities for more advanced applications.

Your tasks

You will work at the crossroad of photogrammetric computer vision, deep learning and robotics to develop the next generation of algorithms for reliable and autonomous real-time UAV mapping. The research will combine autonomous navigation algorithms with 2D and 3D semantic understanding of the scene to develop the next generation of autonomous drones able to perform complex tasks. Different applications such as patrolling, search and rescue in outdoor and indoor environments, and precision farming will be considered during this period.