World's Best Scientists 2026 revealed!
Roland Siegwart

Roland Siegwart

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Electronics and Electrical Engineering
Switzerland
2026
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Mechanical and Aerospace Engineering
Switzerland
2026

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
134
Citations
81881
World Ranking
8
National Ranking
1

Electronics and Electrical Engineering

D-Index
136
Citations
83716
World Ranking
31
National Ranking
1

Roland Siegwart publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Roland Siegwart sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 114 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 61 scientists 317–326 publications: 69 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 1,100 publications — 100th percentile

100% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Roland Siegwart D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Roland Siegwart sits on this spectrum.

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 125 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 106 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 99 scientists
30 D-Index 93+

This scientist: 134 D-Index — 100th percentile

100% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Electronics and Electrical Engineering in Switzerland Leader Award
  • 2026 - Research.com Mechanical and Aerospace Engineering in Switzerland Leader Award
  • 2025 - Research.com Electronics and Electrical Engineering in Switzerland Leader Award
  • 2025 - Research.com Mechanical and Aerospace Engineering in Switzerland Leader Award
  • 2022 - Research.com Electronics and Electrical Engineering in Switzerland Leader Award
  • 2022 - Research.com Mechanical and Aerospace Engineering in Switzerland Leader Award
  • 2008 - IEEE Fellow For contributions to mobile, networked, and micro-scale robots

Overview

Roland Siegwart is affiliated with ETH Zurich in Switzerland and has a substantial body of research primarily spanning the fields of engineering and computer science. Their work covers multiple subfields including computer vision and pattern recognition, aerospace engineering, control and systems engineering, artificial intelligence, and biomedical engineering.

The research topics explored by Siegwart encompass robotics and sensor-based localization, robotic path planning algorithms, robot manipulation and learning, advanced neural network applications, advanced vision and imaging, advanced image and video retrieval techniques, and robotic locomotion and control.

Among their recent published papers are:

  • An Efficient Sampling-Based Method for Online Informative Path Planning in Unknown Environments (2020), published in IEEE Robotics and Automation Letters
  • CERBERUS in the DARPA Subterranean Challenge (2022), published in Science Robotics
  • An informative path planning framework for UAV-based terrain monitoring (2020), published in Autonomous Robots
  • LQR-Assisted Whole-Body Control of a Wheeled Bipedal Robot With Kinematic Loops (2020), published in IEEE Robotics and Automation Letters
  • The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation (2021), published in International Journal of Computer Vision

Siegwart has collaborated frequently with several researchers, including César Cadena, Lionel Ott, Jen Jen Chung, Hermann Blum, and Juan Nieto, reflecting a collaborative approach within the robotics and automation research community.

Their work has been published extensively across a range of venues, with notable frequency in arXiv (Cornell University), IEEE Robotics and Automation Letters, Zenodo (CERN European Organization for Nuclear Research), the 2022 International Conference on Robotics and Automation (ICRA), and IEEE Transactions on Robotics.

Recognition for their contributions includes being named an IEEE Fellow in 2008, acknowledging their work related to mobile, networked, and micro-scale robots.

Best Publications

  • BRISK: Binary Robust invariant scalable keypoints

    Stefan Leutenegger;Margarita Chli;Roland Y. Siegwart

  • Introduction to Autonomous Mobile Robots

    Roland Siegwart;Illah R. Nourbakhsh;Davide Scaramuzza

  • Keyframe-based visual-inertial odometry using nonlinear optimization

    Stefan Leutenegger;Simon Lynen;Michael Bosse;Roland Siegwart

  • The EuRoC micro aerial vehicle datasets

    Michael Burri;Janosch Nikolic;Pascal Gohl;Thomas Schneider

  • PID vs LQ control techniques applied to an indoor micro quadrotor

    S. Bouabdallah;A. Noth;R. Siegwart

  • Backstepping and Sliding-mode Techniques Applied to an Indoor Micro Quadrotor

    S. Bouabdallah;R. Siegwart

  • Design and control of an indoor micro quadrotor

    S. Bouabdallah;P. Murrieri;R. Siegwart

  • Full control of a quadrotor

    S. Bouabdallah;R. Siegwart

  • Comparing ICP variants on real-world data sets

    François Pomerleau;Francis Colas;Roland Siegwart;Stéphane Magnenat

  • Unified temporal and spatial calibration for multi-sensor systems

    Paul Furgale;Joern Rehder;Roland Siegwart

  • From Coarse to Fine: Robust Hierarchical Localization at Large Scale

    Paul-Edouard Sarlin;Cesar Cadena;Roland Siegwart;Marcin Dymczyk

  • A Toolbox for Easily Calibrating Omnidirectional Cameras

    Davide Scaramuzza;Agostino Martinelli;Roland Siegwart

  • A Review of Point Cloud Registration Algorithms for Mobile Robotics

    François Pomerleau;Francis Colas;Roland Siegwart

  • A novel parametrization of the perspective-three-point problem for a direct computation of absolute camera position and orientation

    Laurent Kneip;Davide Scaramuzza;Roland Siegwart

  • A robust and modular multi-sensor fusion approach applied to MAV navigation

    Simon Lynen;Markus W. Achtelik;Stephan Weiss;Margarita Chli

  • Robust visual inertial odometry using a direct EKF-based approach

    Michael Bloesch;Sammy Omari;Marco Hutter;Roland Siegwart

  • Social Integration of Robots into Groups of Cockroaches to Control Self-Organized Choices

    José Halloy;Grégory Sempo;Gilles Caprari;Colette Rivault

  • Receding horizon “next-best-view” planner for 3D exploration

    Andreas Bircher;Mina Kamel;Kostas Alexis;Helen Oleynikova

  • Control of a Quadrotor With Reinforcement Learning

    Jemin Hwangbo;Inkyu Sa;Roland Siegwart;Marco Hutter

  • A Flexible Technique for Accurate Omnidirectional Camera Calibration and Structure from Motion

    D. Scaramuzza;A. Martinelli;R. Siegwart

  • Vision based MAV navigation in unknown and unstructured environments

    Michael Blosch;Stephan Weiss;Davide Scaramuzza;Roland Siegwart

  • Robot learning from demonstration

    Aude Billard;Roland Siegwart

Frequent Co-Authors

Juan Nieto
Juan Nieto Microsoft (United States)
Cesar Cadena
Cesar Cadena ETH Zurich
Marco Hutter
Marco Hutter ETH Zurich
Davide Scaramuzza
Davide Scaramuzza University of Zurich
Kai O. Arras
Kai O. Arras Robert Bosch (Germany)
Kostas Alexis
Kostas Alexis Norwegian University of Science and Technology
Paul Beardsley
Paul Beardsley Weta Digital
Paul Furgale
Paul Furgale ETH Zurich
Javier Alonso-Mora
Javier Alonso-Mora Delft University of Technology
C. David Remy
C. David Remy University of Stuttgart

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