Manuel Werlberger

Papers

Total Citations

130

H-Index

About

Manuel Werlberger is a leading researcher in autonomous aerial robotics, with a primary focus on real-time 3D perception and planning for micro aerial vehicles (MAVs). His most impactful work, "Continuous on-board monocular-vision-based elevation mapping applied to autonomous landing of micro aerial vehicles" (2015, 100 citations), introduced a resource-efficient system that leverages a single downlooking camera and an inertial measurement unit to reconstruct 3D terrain and detect safe landing spots. Remarkably, this system runs on a smartphone-grade processor, demonstrating a breakthrough in lightweight, on-board autonomy. Werlberger also advanced decision-making under uncertainty in "Exploiting Photometric Information for Planning Under Uncertainty" (2017, 30 citations), integrating visual cues into probabilistic planning frameworks. His contributions bridge the gap between efficient perception and robust navigation, enabling MAVs to operate in GPS-denied environments with minimal hardware. By pushing the boundaries of monocular vision and computational efficiency, Werlberger has paved the way for practical, low-cost autonomous systems, making his work essential reading for researchers in aerial robotics, computer vision, and embedded AI.