Zichao Zhang



Zichao Zhang (张子潮)

MSc University of Zurich

Robotics and Perception Group

Department of Informatics

University of Zurich


Email: zzhang (at) ifi (dot) uzh (dot) ch

Office: Andreasstrasse 15, AND 2.12



Scholar GitHub



I am currently a PhD student at Robotics and Perception Group at University of Zurich, supervised by Prof. Dr. Davide Scaramuzza. I received my Bachelor degree in Detection, Guidance and Control from Beihang University (Beijing, China) in 2011 and Master degree in Computer Science from University of Zurich (Zurich, Switzerland) in 2016. From August to October 2019, I had the opportunity to work with Prof. Dr. Torsten Sattler at Chalmers University of Technology, exploring learning-based view synthesis for robust visual localization. My research interests include vision-based navigation, sensor fusion, robot state estimation and active vision.




Z. Zhang, D. Scaramuzza

Fisher Information Field: an Efficient and Differentiable Map for Perception-aware Planning

arXiv, August 2020.

PDF (PDF, 5927 KB) Video Code


Z.Zhang, T. Sattler, D. Scaramuzza

Reference Pose Generation for Visual Localization via Learned Features and View Synthesis

arXiv, May 2020.

PDF (PDF, 11633 KB)

Journal Papers



Z. Zhang, G. Gallego, D, Scaramuzza

On the Comparison of Gauge Freedom Handling in Optimization-based Visual-Inertial State Estimation

IEEE Robotics and Automation Letters (RA-L), 2018.

PDF (PDF, 1036 KB)  IROS18 Presentation (PPTX, 52250 KB)  Code


C. Forster, Z. Zhang, M. Gassner, M.Werlberger, D. Scaramuzza

SVO: Semi-Direct Visual Odometry for Monocular and Multi-Camera Systems

IEEE Transactions on Robotics, Vol. 33, Issue 2, pages 249-265, Apr. 2017.

PDF (PDF, 13022 KB) YouTube  Software

Book Chapters



Visual-Inertial Odometry of Aerial Robots                                          

D. Scaramuzza, Z. Zhang          

Encyclopedia of Robotics, Springer, 2020.

PDF (PDF, 490 KB)

Conference Papers


M. Muglikar, Z. Zhang, D. Scaramuzza

Voxel Map for Visual SLAM

IEEE International Conference on Robotics and Automation (ICRA), 2020.

PDF (PDF, 546 KB)


J. Kuo, M. Muglikar, Z. Zhang, D. Scaramuzza

Redesigning SLAM for Arbitrary Multi-camera Systems

IEEE International Conference on Robotics and Automation (ICRA), 2020.

PDF (PDF, 2290 KB)    Youtube



Z. Zhang, D. Scaramuzza

Beyond Point Clouds: Fisher Information Field for Active Visual Localization

IEEE International Conference on Robotics and Automation (ICRA), 2019.

PDF (PDF, 1560 KB) YouTube Code (Coming soon)



Z. Zhang, D. Scaramuzza

A Tutorial on Quantitative Trajectory Evaluation for Visual(-inertial) Odometry 

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, 2018.

PDF (PDF, 483 KB)  PPT (PPTX, 8041 KB)  VO/VIO Evaluation Toolbox


Z. Zhang, D. Scaramuzza

Perception-aware Receding Horizon Navigation for MAVs

IEEE International Conference on Robotics and Automation (ICRA), 2018.

PDF (PDF, 1617 KB)  Video  ICRA18 Video Pitch  PPT (PPTX, 96117 KB)


R. Gomez-Ojeda, Z. Zhang, J. Gonzalez-Jimenez, D. Scaramuzza

Learning-based Image Enhancement for Visual Odometry in Challenging HDR Environments

IEEE International Conference on Robotics and Automation (ICRA), 2018.

PDF (PDF, 1357 KB)  Video  ICRA18 Video Pitch  PPT (PPTX, 30628 KB)


Z. Zhang, C. Forster, D. Scaramuzza

Active Exposure Control for Robust Visual Odometry in HDR Environments

IEEE International Conference on Robotics and Automation (ICRA), 2017.

PDF (PDF, 1450 KB)  PPT (PPTM, 96927 KB)  Video


Z. Zhang, H. Rebecq, C. Forster, D. Scaramuzza

Benefit of Large Field-of-View Cameras for Visual Odometry

IEEE International Conference on Robotics and Automation (ICRA), Stockholm, 2016.

PDF (PDF, 6292 KB) PPT (PPTM, 21738 KB)  YouTube Research page (datasets and software)

Workshop Papers



Z. Zhang, D. Scaramuzza

Rethinking Trajectory Evaluation for SLAM: a Probabilistic, Continuous-Time Approach

ICRA19 Workshop on Dataset Generation and Benchmarking of SLAM Algorithms for VR/AR

Best Paper Award!

PDF (PDF, 333 KB)