As a Ph.D. student, his research aims to autonomously deploy sensors for environmental monitoring within the challenging environment of forest canopies. This task requires a holistic approach, starting with state-of-the-art manufacturing methods and materials to ensure secure attachment of the sensors, to machine learning based computer vision for perception and scene understanding. Finally, novel planning, control, and sensing approaches are needed to successfully navigate the dense, cluttered, and compliant environment of tree canopies.
Christian Geckeler, born in Reutlingen (Germany) in 1994, joined the Environmental Robotics Laboratory at ETH Zürich as a Ph.D. student in 2021.
He received his B.Sc. in Computer Science in 2017, and his M.Sc. in Computer Science in 2020, both from the University of Tübingen. During these studies he focused strongly on robotics, working as a research assistant and participating in the 2018 SICK robot competition. During his work as a research assistant he was part of the FarmingIOS project, developing autonomous unmanned aerial vehicle (UAV) based hyperspectral mapping solutions for early detection of fungal infections in agricultural crop fields. Now, he seeks to use these skills to tackle the challenging task of allowing robots to perform useful tasks in forest canopies.