Matthias Faessler
Papers
5
Total Citations
1,212
H-Index
5
About
Matthias Faessler is a pioneering robotics researcher whose work sits at the intersection of autonomous systems, computer vision, and aerial robotics. Best known for his contributions to vision-based navigation and control of micro aerial vehicles (MAVs), Faessler has helped redefine what small, resource-constrained robots can accomplish in real-world environments. His most influential work, "A Machine Learning Approach to Visual Perception of Forest Trails for Mobile Robots" (2015, 694 citations), demonstrated that deep learning could enable robots to navigate complex natural environments using only a single monocular camera — a landmark result that inspired a generation of autonomous navigation research. Complementing this, his work on autonomous quadrotor flight with live dense 3D mapping (240 citations) advanced the practical deployment of MAVs in search-and-rescue scenarios, pushing toward systems that require minimal human intervention. Faessler also made notable contributions to failure recovery in aggressive flight, real-time terrain reconstruction for autonomous landing, and multi-robot collaboration between aerial and ground vehicles. Across these threads, a consistent theme emerges: making autonomous robots more robust, perceptive, and practically deployable. With hundreds of cumulative citations, his research has left a meaningful imprint on the field of autonomous aerial robotics.
Research Focus
Key Achievements
Top Papers
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- 5Aerial-guided navigation of a ground robot among movable obstacles70 citations · 2014