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Dr Weisong WEN

Dr Weisong WEN

Assistant Professor

  • PQ408
  • 3400 8234
  • welson.wen@polyu.edu.hk
  • Navigation, pedestrian trajectory data analysis, autonomous driving

Biography

BEng (BISTU); MEng (CAU); Ph.D. (PolyU); Member IEEE; Member ION.

 

Area of Specialization

Multi-sensory integrated positioning, GNSS, LiDAR-aided GNSS positioning, LiDAR/Visual SLAM, safety-assured control and path planning, reinforcement learning, safety-assured autonomous systems, unmanned aerial vehicles (UAV), connected autonomous driving vehicles

 

Short Description

Dr. Wen received a BEng degree in Mechanical Engineering from Beijing Information Science and Technology University (BISTU), Beijing, China, in 2015, and an MEng degree in Mechanical Engineering from the China Agricultural University, in 2017. After that, he received a PhD degree in Mechanical Engineering from The Hong Kong Polytechnic University (PolyU), in 2020. He was also a visiting PhD student with the Faculty of Engineering, University of California, Berkeley (UC Berkeley) in 2018. Before joining PolyU as an Assistant Professor in 2023, he was a Research Assistant Professor at AAE of PolyU since 2021. He has published 30 SCI papers and 40 conference papers in the field of GNSS (ION GNSS+) and navigation for Robotic systems (IEEE ICRA, IEEE ITSC), such as autonomous driving vehicles. He won the innovation award from TechConnect 2021, the Best Presentation Award from the Institute of Navigation (ION) in 2020, and the First Prize in Hong Kong Section in Qianhai-Guangdong-Macao Youth Innovation and Entrepreneurship Competition in 2019 based on his research achievements in 3D LiDAR aided GNSS positioning for robotics navigation in urban canyons. The developed 3D LiDAR-aided GNSS positioning method has been reported by top magazines such as Inside GNSS and has attracted industry recognition with remarkable knowledge transfer. His mission and dedication are to investigate reliable methods to improve the GNSS positioning in urban canyons, which is of great importance for reliable robotic navigation.

 

Journal Publications on Aided Urban GNSS Positioning for Robotics Navigation: (*: Corresponding author)

  1. Li, X., Li, S., Shen, Z., Zhou, Y., Wang, X., Li, X., and Wen, W., 2021. Continuous and precise positioning in urban environments by tightly coupled integration of GNSS, INS, and Vision, IEEE Robotics and Automation Letters.
  2. Wen, W., and Hsu, L.T., 2021. 3D LiDAR Aided GNSS NLOS Mitigation in Urban Canyons. IEEE transactions on intelligent transportation systems. (PaperVideo)
  3. Bai, X., Wen, W.* and Hsu, L.T., 2022. Time-correlated Window Carrier-phase Aided GNSS Positioning in Urban Canyons, IEEE Transactions on Aerospace and Electronic Systems. (Paper)
  4. Wen, W., Zhang, G. and Hsu, L.T., 2021. Gnss outlier mitigation via graduated non-convexity factor graph optimization. IEEE Transactions on Vehicular Technology, 71(1), pp.297-310. (Paper)
  5. Wen, W., Pfeifer, T., Bai, X. and Hsu, L.T., 2021. Factor graph optimization for GNSS/INS integration: A comparison with the extended Kalman filter. NAVIGATION, Journal of the Institute of Navigation, 68(2), pp.315-331. (PaperVideo)
  6. Zhang, G., Ng, H.F., Wen, W. and Hsu, L.T., 2020. 3D mapping database aided GNSS based collaborative positioning using factor graph optimization. IEEE Transactions on Intelligent Transportation Systems. (Paper)
  7. Zhang, G., Wen, W., Xu, B. and Hsu, L.T., 2020. Extending shadow matching to tightly-coupled GNSS/INS integration system. IEEE Transactions on Vehicular Technology, 69(5), pp.4979-4991. (Paper)
  8. Wen, W., Zhang, G. and Hsu, L.T., 2020. Object-Detection-Aided GNSS and Its Integration With Lidar in Highly Urbanized Areas. IEEE Intelligent Transportation Systems Magazine, 12(3), pp.53-69. (Paper)
  9. Bai, X., Wen, W. * and Hsu, L.T., 2020. Using Sky-pointing fish-eye camera and LiDAR to aid GNSS single-point positioning in urban canyons. IET Intelligent Transport Systems, 14(8), pp.908-914. (Paper)
  10. Wen, W., Bai, X., Kan, Y.C. and Hsu, L.T., 2019. Tightly coupled GNSS/INS integration via factor graph and aided by fish-eye camera. IEEE Transactions on Vehicular Technology, 68(11), pp.10651-10662. (Paper)
  11. Wen, W., Zhang, G. and Hsu, L.T., 2019. GNSS NLOS exclusion based on dynamic object detection using LiDAR point cloud. IEEE transactions on intelligent transportation systems. (Paper)
  12. Wen, W., Zhang, G. and Hsu, L.T., 2019. Correcting NLOS by 3D LiDAR and building height to improve GNSS single point positioning. Navigation, 66(4), pp.705-718. (Paper)
  13. Zhang, G., Wen, W. and Hsu, L.T., 2019. Rectification of GNSS-based collaborative positioning using 3D building models in urban areas. GPS solutions, 23(3), pp.1-12. (Paper)

 

Journal Publications on LiDAR/Visual SLAM for Robotics Navigation: (*: Corresponding author)

  1. Zhong, Y., Huang, F., Zhang, J., Wen, W. * and Hsu, L.T., 2021. Low-cost Solid-state LiDAR/Inertial Based Localization with Prior Map for Autonomous Systems in Urban Scenarios. IET Intelligent Transport Systems.
  2. Wen, W., & Hsu, L. T. (2022). AGPC-SLAM: Absolute Ground Plane Constrained 3D Lidar SLAM. NAVIGATION: Journal of the Institute of Navigation69(3). (PaperVideo)
  3. Bai, X., Wen, W. and Hsu, L.T., 2021. Degeneration-Aware Outlier Mitigation for Visual Inertial Integrated Navigation System in Urban Canyons. IEEE Transactions on Instrumentation and Measurement, 70, pp.1-15. (Paper)
  4. Zhang, J., Wen, W. *, Huang, F., Chen, X. and Hsu, L.T., 2021. Coarse-to-Fine Loosely-Coupled LiDAR-Inertial Odometry for Urban Positioning and Mapping. Remote Sensing, 13(12), p.2371. (Paper)
  5. Yue, J., Wen, W. *, Han, J. and Hsu, L.T., 2021. 3D Point Clouds Data Super Resolution-Aided LiDAR Odometry for Vehicular Positioning in Urban Canyons. IEEE Transactions on Vehicular Technology, 70(5), pp.4098-4112. (Paper)
  6. Huang, F., Wen, W., Zhang, J. and Hsu, L.T., 2021. Point-wise or Feature-wise? Benchmark Comparison of Public Available LiDAR Odometry Algorithms in Urban Canyons. IEEE Intelligent Transportation Systems Magazine. [Accepted] (Paper)
  7. Bai, X., Wen, W. and Hsu, L.T., 2020. Robust visual-inertial integrated navigation system aided by online sensor model adaption for autonomous ground vehicles in urban areas. Remote Sensing, 12(10), p.1686. (Paper)
  8. Wen, W., Hsu, L.T. and Zhang, G., 2018. Performance analysis of NDT-based graph SLAM for autonomous vehicle in diverse typical driving scenarios of Hong Kong. Sensors, 18(11), p.3928. (Paper)
  9. Wen, W., Bai, X., Zhan, W., Tomizuka, M. and Hsu, L.T., 2019. Uncertainty estimation of LiDAR matching aided by dynamic vehicle detection and high definition map. Electronics letters, 55(6), pp.348-349. (Paper)

 

Selected Representative Conference/Workshop Publications (Past 5 Years):

  1. Wen, W., Li, B., Chen, J., Huang, Y. (2022, October). Workshop on Intelligent Vehicle Meets Urban: Safe and Certifiable Navigation and Control for Intelligent Vehicles in Complex Urban Scenarios, IEEE ITSC 2022. In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC). IEEE.
  2. Wen, W. (2022, September). Tutorial on Simultaneous Localization and Mapping (SLAM) Technologies for Indoor Positioning: Development and Challenges, In 2022 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE.
  3. Wen, W. and Hsu, L.T., 2022, September. Factor Graph Optimization for Tightlycoupled GNSS Pseudorange/Doppler/Carrier phase/INS Integration: Performance In Urban Canyons of Hong Kong. In Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022).
  4. Wen, W. and Hsu, L.T., 2021, September. 3D LiDAR Aided GNSS Real-time Kinematic Positioning. In Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021) (pp. 2212-2220). (PaperVideo)
  5. Wen, W., Meng, Q. and Hsu, L.T., 2021, September. Integrity Monitoring for GNSS Positioning Via Factor Graph Optimization in Urban Canyons. In Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021) (pp. 1508-1515). (PaperVideo)
  6. Wen, W. and Hsu, L.T., 2021, May. Towards Robust GNSS Positioning and Real-time Kinematic Using Factor Graph Optimization. In 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE. (PaperVideoCode)
  7. Wen, W., 2020, September. 3D LiDAR Aided GNSS and Its Tightly Coupled Integration with INS Via Factor Graph Optimization. In Proceedings of the 33rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2020) (pp. 1649-1672). (PaperVideo)
  8. Wen, W., Bai, X., Hsu, L.T. and Pfeifer, T., 2020, April. GNSS/LiDAR integration aided by self-adaptive Gaussian mixture models in urban scenarios: An approach robust to non-Gaussian noise. In 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) (pp. 647-654). (Paper)
  9. Wen, W., Zhou, Y., Zhang, G., Fahandezh-Saadi, S., Bai, X., Zhan, W., Tomizuka, M. and Hsu, L.T., 2020, May. Urbanloco: a full sensor suite dataset for mapping and localization in urban scenes. In 2020 IEEE International Conference on Robotics and Automation (ICRA) (pp. 2310-2316). IEEE. (PaperVideoCode)
  10. Wen, W., Kan, Y.C. and Hsu, L.T., 2019, September. Performance comparison of GNSS/INS integrations based on EKF and factor graph optimization. In Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019) (pp. 3019-3032). (PaperVideo)
  11. Wen, W., Zhang, G. and Hsu, L.T., 2018, September. Correcting GNSS NLOS by 3D LiDAR and building height. In Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018) (pp. 3156-3168). (Paper)
  12. Wen, W., Zhang, G. and Hsu, L.T., 2018, April. Exclusion of GNSS NLOS receptions caused by dynamic objects in heavy traffic urban scenarios using real-time 3D point cloud: An approach without 3D maps. In 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS) (pp. 158-165). IEEE. (Paper)

 

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