Sören Schwertfeger
Assistant Professor
Graduated School:Ph.D., Jacobs University Bremen, Germany
Tel:(021) 20685096
Major:Computer Science and Technology
Office:Room 1D-201A, SIST Building
Research Interests
Biography
Selected Publications

RESEARCH INTERESTS

  • Mobile Robotics

  • Robot Performance Evaluation, especially Map Evaluation

  • Mapping and Simultaneous Localization and Mapping (SLAM)

  • Robot Autonomy and Intelligence


BIOGRAPHY

Dr. Sören Schwertfeger joined ShanghaiTech University in August 2014 as an Assistant Professor. He graduated with a Diploma (German equivalent of the Master) in Computer Science in 2005 from the University of Bremen in Germany. In 2012 he received his Ph.D. in Computer Science from the Jacobs University Bremen. Between 2012 and 2014 he was a postdoctoral researcher at the Robotics Group of Prof. Andreas Birk at the Jacobs University Bremen. In 2010 Dr. Schwertfeger was a guest researcher at the National Institute of Standards and Technology (NIST) in Gaithersburg, Maryland, USA, and in 2015 he spend two months as a visiting researcher at University of California, Berkeley, USA.

His research interest is in robotics, especially inintelligent functions for mobile robots. Besides his work on map evaluation,Dr. Schwertfeger also worked and published on mapping, objectdetection and robot autonomy. He successfully participated in many robotcompetitions, both as team member and as judge and organizer. Dr. Schwertfegerwas the general chair of the 2017 IEEE International Symposium on Safety,Security, and Rescue Robotics (SSRR). He is an associate editor of the IEEERobotics and Automation Magazine and a guest editor for a special issue on SSRRin the Journal of Field Robotics as well as a guest editor for an IEEETransactions on Cognitive and Developmental Systems special issue on IntrospectiveMethods for Reliable Autonomy.


SELECTED PUBLICATIONS

  1. Chavez, A. Gomez, Q. Xu, C. Atanas Mueller, S. Schwertfeger, and A. Birk, “Adaptive Navigation Scheme for Optimal Deep-Sea Localization Using Multimodal Perception Cues”, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): IEEE Press, 2019.

  2. Hou, J., Y. Yuan, and S. Schwertfeger, “Area Graph: Generation of Topological Maps using the Voronoi Diagram”, 19th International Conference on Advanced Robotics (ICAR): IEEE Press, 2019. 

  3. Yuan, Y., L. Wang, and S. Schwertfeger, “Configuration-Space Flipper Planning for Rescue Robots”, IEEE International Symposium on Safety, Security, Rescue Robotics (SSRR): IEEE Press, 2019.

  4. Kuang, H., Q. Xu, and S. Schwertfeger, “Depth Estimation on Underwater Omni-directional Images Using a Deep Neural Network”, Workshop on Underwater Robotics Perception, 2019 IEEE International Conference on Robotics and Automation (ICRA): IEEE Press, 2019.

  5. Schwertfeger, S., and K. Ohno, “Editorial: Special issue on safety, security, and rescue robotics”, Journal of Field Robotics, vol. 36, pp. 639-640, 2019.

  6. Hou, J., H. Kuang, and S. Schwertfeger, “Fast 2D Map Matching Based on Area Graphs”, 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO): IEEE, 2019.

  7. He, Z., J. Hou, and S. Schwertfeger, “Furniture Free Mapping using 3D Lidars”, 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO): IEEE, 2019.

  8. Chen, H., and S. Schwertfeger, “Heterogeneous Multi-sensor Calibration Based on Graph Optimization”, 2019 IEEE International Conference on Real-time Computing and Robotics (RCAR): IEEE, 2019.

  9. Xu, Q., A. Gomez Chavez, H. Bülow, A. Birk, and S. Schwertfeger, “Improved Fourier Mellin Invariant for Robust Rotation Estimation with Omni-cameras”, 2019 26th IEEE International Conference on Image Processing: IEEE, 2019.

  10. Yuan, Y., and S. Schwertfeger, “Incrementally Building Topology Graphs via Distance Maps”, 2019 IEEE International Conference on Real-time Computing and Robotics (RCAR): IEEE, 2019.