Roland Siegwart
ETH Zurich, École Polytechnique Fédérale de Lausanne, Board of the Swiss Federal Institutes of Technology, Centre National de la Recherche Scientifique, University of Minnesota System, University of Edinburgh, Institut Systèmes Intelligents et de Robotique, University of Zurich, University of Nevada, Reno, Institute of Robotics, Autonomous Healthcare, Tongji University, University of Surrey, Swiss National Science Foundation, University of California, Berkeley, SystemsX.ch, Technical University of Denmark, University of Tehran
Papers
654
Total Citations
38,560
H-Index
100
About
Roland Siegwart stands as one of the most influential figures in modern robotics, with his research spanning autonomous navigation, aerial robotics, sensor fusion, and human-robot interaction. A professor at ETH Zürich, Siegwart has fundamentally shaped how robots perceive and navigate their environments. His groundbreaking work on visual-inertial odometry, particularly the keyframe-based optimization approach (1,697 citations), has become a cornerstone of modern SLAM research, enabling robots to localize themselves with remarkable precision using complementary camera and inertial sensor data. Equally impactful are his pioneering contributions to quadrotor robotics — his 2004 papers on micro quadrotor design and PID versus LQ control techniques (collectively approaching 2,100 citations) helped establish the foundational engineering principles that today underpin commercial drones worldwide. Siegwart's lab has consistently pushed boundaries beyond conventional robotics, demonstrated memorably by his unconventional collaboration integrating robots into cockroach swarms to study self-organized collective behavior. His contributions extend further into autonomous exploration planning, multi-sensor calibration, point cloud registration, and end-to-end learned motion planning — reflecting an extraordinary breadth of vision. With tens of thousands of citations across his career, Siegwart's work continues to define the trajectory of intelligent autonomous systems research globally.
Research Focus
Key Achievements
Top Papers
- 1Keyframe-based visual–inertial odometry using nonlinear optimization1,697 citations · 2014
- 2PID vs LQ control techniques applied to an indoor micro quadrotor1,266 citations · 2004
- 3Design and control of an indoor micro quadrotor830 citations · 2004
- 4Full control of a quadrotor796 citations · 2007
- 5Unified temporal and spatial calibration for multi-sensor systems784 citations · 2013
- 6A Review of Point Cloud Registration Algorithms for Mobile Robotics686 citations · 2015
- 7Receding Horizon "Next-Best-View" Planner for 3D Exploration601 citations · 2016
- 8A robust and modular multi-sensor fusion approach applied to MAV navigation571 citations · 2013
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