Ming Liu received the B.A. degree in Automation at Tongji University in 2005. He stayed one year in Erlangen-Nünberg University and Fraunhofer Institute IISB, Germany, as visiting scholar. He graduated as a PhD student from the Department of Mechanical and Process Engineering of ETH Zürich in 2013, supervised by Prof. Roland Siegwart.
He is a founding member of Shanghai SWing Automation Ltd. Co. He is also involved in several NSF projects, and National 863-Hi-Tech-Plan projects in China. He is PI of 20+ projects including projects funded by RGC, NSFC, ITC, SZSTI, etc. He published 70+ papers in major international journals and conferences. He won the second place of EMAV’09 (European Micro Aerial Vehicle Competition). He was the general chair of International Conference on Computer Vision Systems (ICVS) 2017; the program chair of IEEE International Conference on Real-time Computing and Robotics (IEEE-RCAR) 2016; the program chair of International Robotic Alliance Conference 2017.
Ming Liu’s research interests include dynamic environment modeling, 3D mapping, machine learning and visual control. He’s particularly interested in the investigation of novel, real-time online approaches in solving mobile robot mapping and navigation. In general, he can be stimulated by research in all robotic and intelligent system fields.
Please see ram-lab.com/publication for more information.
- Ming Liu, Robotic Online Path Planning on Point Cloud, IEEE Transactions on Cybernetics (TCYB), 2016 May;46(5):1217-28. doi: 10.1109 / TCYB.2015.2430526.
- Qiu Kejie, Fangyi Zhang, Ming Liu, Let There Be Light and Let The Light Guide us: VLC-based localization, IEEE Robotics and Automation Magazine (RAM), Vol 23, Issue 4, pp 174-183, Dec 2016
- Ming Liu, Roland Siegwart, Topological mapping and scene recognition with lightweight color descriptors for omnidirectional camera, IEEE Transactions on Robotics (TRO), Vol. 30, Issue 2, pp. 310- 324, April. 2014.
- Ming Liu, Cedric Pradalier, Roland Siegwart, Visual Homing from Scale with an Uncalibrated Omnidirectional Camera, IEEE Transactions on Robotics (TRO), Vol. 29, Issue 6, pp.1353 - 1365, Dec. 2013.
- Francis Colas, Srivatsa Mahesh, Francois Pomerleau, Ming Liu, Roland Siegwart, 3D Path Planning and Execution for Search and Rescue Ground Robots, Best RoboCup Paper Award IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2013
- Yuxiang Sun, Ming Liu, et al, Improving 3-D visual SLAM in dynamic environments: An RGB-D data-based motion removal approach, Robotics and Automation System (RAS), Vol 89, Pages 110-122, March 2017
- Lujia Wang, Ming Liu, et al., A Pricing Mechanism for Task Oriented Resource Allocation in Cloud Robotics, Springer Book on Robots and Sensor Clouds, 2016, ISSN 2198-4182, ISBN 978-3-319-22168-7
- Lujia Wang, Ming Liu, et al., A Hierarchical Auction-based Mechanism for Real-Time Resource Allocation in Cloud Robotic Systems, 11 Feb, IEEE Transactions on Cybernetics (TCYB), 2016. DOI: 10.1109/TCYB.2016.2519525
- Lujia Wang, Ming Liu, et al., Real-time Multi-sensor Information Retrieval for Cloud Robotic Systems, IEEE Transactions on Automation Science and Engineering (TASE), Vol.12, Number 2, April 2015.
- Ming Liu, Luc Oth, Francis Colas, Roland Siegwart, Incremental Topological Segmentation for Semi-structured Environments, Autonomous Robots (AURO), Vol. 37, Issue 3, Aug. 2014
- Francois Pomerleau, Ming Liu, Francis Colas, Roland Siegwart, Challenging Data Sets for Point Cloud Registration Algorithms International Journal of Robotics Research (IJRR), 2012
- Lei Tai, Shaohua Li, Ming Liu, Autonomous Exploration of Mobile Robots through Deep Neural Networks, International Journal of Advanced Robotic Systems. Vol 14, Issue 4, July-25-2017
- Lujia Wang, Yinting Luo, Luyu Wang and Ming Liu, Point-cloud Compression Using Data Independent Method - A 3D Discrete Cosine Transform Approach, IEEE International Conference Information and Automation (ICIA) Best Paper in Automation Award, July 18-20, 2017, Macau, China
- Lei Tai, Haoyang Ye, Qiong Ye, Ming Liu, PCA-aided Fully Convolutional Networks for Semantic Segmentation of Multi-channel fMRI, IEEE International Conference on Advanced Robotics (ICAR) Best Student Paper Award, July 10-12, 2017, Hong Kong, China