Xieyuanli Chen (陈谢沅澧)

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Research Assistant,
College of Intelligence Science and Technology,
National University of Defense Technology,
Changsha, China
E-mail: chenxieyuanli@hotmail.com

Short CV

I received my PhD degree in Robotics at the University of Bonn in 2022, my Master degree in Robotics at the National University of Defense Technology in 2017, and Bachelor degree in Electrical Engineering and Automation at the Hunan University in 2015. I'm also a member of the Technical Committee of RoboCup Rescue Robot League (RRL).

[Extended CV] | [中文简历].

Research Interests

Main area: SLAM, Localization, Scene Understanding, Robot Learning

Applications: Autonomous Vehicle; Rescue Robotics

Honors & Awards

  • Distinction PhD degree [Pdf][Website] - summa cum laude (highest grade) - Uni-Bonn, 2022

  • RSS Pioneer [Pdf][Poster][Website] - RSS, 2021

  • Finalist of Best System Paper - RSS, 2020

  • PhD Scholarship - CSC, 2018-2022

  • Best-in-Class Exploration and Mapping Scenario - RoboCup, 2022

  • Best-in-Class Search and Inspect - RoboCup, 2022

  • Best-in-Class Exploration and Mapping - RoboCup, 2021

  • In recognition of Exceptional Performance as Associate Judge - RoboCup, 2017

  • Winner of Rescue Robot Competition - SSRR, 2017

  • Best‑in‑Class Small Robot Mobility - RoboCup, 2016

Academic Working Experience

  • Associate Editor - IEEE ICRA, 2022-Present

  • Associate Editor - IEEE RA-L, 2022-Present

  • Research Assistant - StachnissLab, Uni-Bonn, 2019-2022

  • Technical Committee - RoboCup RRL, 2019-Present

  • Organizing Committee - RSS Pioneer, 2021-2022

  • Programme Committee - RoboCup Symposium, 2021-2022

  • Organizing Committee - RoboCup RRL, 2017-2019

Teaching Experience

  • Master Project: Visual LiDAR Odometry - Projet MSC, 2020

  • Advanced Techniques in Mobile Sensing and Robotics Course - Lecture MSC, 2020

  • Master Project: Semantic Place Categorization - Projet MSC, 2019

  • Sensors and State Estimation Course - Lecture MSC, 2019

Student Supervision as Responsible Supervisor

  • Deep Learning‑based Pole Extractor for Long‑term LiDAR Global Localization - Master Thesis, Hao Dong (homepage), 2022

  • LiDAR‑based Long‑term Place Recognition - Intern Project, Junyi Ma (homepage), 2022

  • LiDAR‑based Moving Object Segmentation - Intern Project, Jiadai Sun (homepage), 2022

  • Static Map Generation from Point Cloud Data - Intern Project, Mehul Arora (homepage), 2021

  • Pole‑based LiDAR Localization - Intern Project, Hao Dong (homepage), 2021

  • LiDAR Visual Odometry - Intern Project, Andrzej Reinke (homepage), 2021

  • Extracting Color and Semantic Information for LiDAR Point Clouds from Images - Bachelor Thesis, Verena Fitzke, 2020

Publication List

Full list of publications in Google Scholar.

* indicates the corresponding author.

PhD thesis:
  • X. Chen. LiDAR-Based Semantic Perception for Autonomous Vehicles.
    PhD thesis, University of Bonn, September 2022.
    bib | website | pdf ]

Selected peer-reviewed journal articles:
  • X. Chen, B. Mersch, L. Nunes, R. Marcuzzi, I. Vizzo, J. Behley, and C. Stachniss. Automatic Labeling to Generate Training Data for Online LiDAR-Based Moving Object Segmentation.
    IEEE Robotics and Automation Letters (RA-L), 7(3):6107--6114, 2022.
    bib | code | pdf ]

  • X. Chen, T. Läbe, A. Milioto, T. Röhling, J. Behley, and C. Stachniss. OverlapNet: A Siamese Network for Computing LiDAR Scan Similarity with Applications to Loop Closing and Localization.
    Autonomous Robots, 46:61--81, 2022.
    bib | code | pdf ]

  • X. Chen, S. Li, B. Mersch, L. Wiesmann, J. Gall, J. Behley, and C. Stachniss. Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data.
    IEEE Robotics and Automation Letters (RA-L), 6:6529--6536, 2021.
    bib | video | code | pdf ]

  • J. Ma, J. Zhang, J. Xu, R. Ai, W. Gu, and X. Chen*. Overlaptransformer: An efficient and yaw-angle-invariant transformer network for lidar-based place recognition.
    IEEE Robotics and Automation Letters (RA-L), 7(3):6958--6965, 2022.
    bib | code | pdf ]

  • L. Nunes, X. Chen*, R. Marcuzzi, A. Osep, L. Leal-Taixé, C. Stachniss, and Jens Behley. Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous Vehicles.
    IEEE Robotics and Automation Letters (RA-L), 2022.
    bib | code | pdf ]

  • J. Ma, X. Chen, J. Xu, and G. Xiong. SeqOT: Spatial-Temporal Transformer Networks for Place Recognition Using Sequential LiDAR Data.
    IEEE Trans. on Industrial Electronics, 2022.
    bib | code ]

  • T. Guadagnino, X. Chen, M. Sodano, J. Behley, G. Grisetti, and C. Stachniss. Fast Sparse LiDAR Odometry Using Self-Supervised Feature Selection on Intensity Images.
    IEEE Robotics and Automation Letters (RA-L), 2022.
    bib | pdf ]

  • B. Mersch, X. Chen, I. Vizzo, L. Nunes, J. Behley, and C. Stachniss. Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions.
    IEEE Robotics and Automation Letters (RA-L), 7(3):7503--7510, 2022.
    bib | video | code | pdf ]

  • H. Dong, X. Chen*, and C. Stachniss. Online Pole Segmentation on Range Images for Long-term LiDAR Localization in Urban Environments.
    Journal on Robotics and Autonomous Systems (RAS), 2022.
    bib | code | .pdf ]

  • M. Arora, L. Wiesmann, X. Chen*, and C. Stachniss. Static Map Generation from 3D LiDAR Point Clouds Exploiting Ground Segmentation.
    Journal on Robotics and Autonomous Systems (RAS), 2022.
    bib | code ]

  • L. Nunes, R. Marcuzzi, X. Chen, J. Behley, and C. Stachniss. SegContrast: 3D Point Cloud Feature Representation Learning through Self-supervised Segment Discrimination.
    IEEE Robotics and Automation Letters (RA-L), 7(2):2116--2123, 2022.
    bib | code | pdf ]

  • C. Shi, X. Chen, K. Huang, J. Xiao, H. Lu, and C. Stachniss. Keypoint Matching for Point Cloud Registration using Multiplex Dynamic Graph Attention Networks.
    IEEE Robotics and Automation Letters (RA-L), 6:8221--8228, 2021.
    bib | code | pdf ]

  • S. Li, X. Chen, Y. Liu, D. Dai, C. Stachniss, and J. Gall. Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform.
    IEEE Robotics and Automation Letters (RA-L), 7(2):738--745, 2022.
    bib | code | .pdf ]

  • L. Wiesmann, A. Milioto, X. Chen, C. Stachniss, and J. Behley. Deep Compression for Dense Point Cloud Maps.
    IEEE Robotics and Automation Letters (RA-L), 6:2060--2067, 2021.
    bib | video | code | pdf ]


Selected peer-reviewed conference papers:
  • X. Chen, T. Läbe, A. Milioto, T. Röhling, O. Vysotska, A. Haag, J. Behley, and C. Stachniss. OverlapNet: Loop Closing for LiDAR-based SLAM.
    In Proc. of Robotics: Science and Systems (RSS), 2020.
    bib | video | code | pdf ]

  • X. Chen, I. Vizzo, T. Läbe, J. Behley, and C. Stachniss. Range Image-based LiDAR Localization for Autonomous Vehicles.
    In Proc. of the IEEE Intl. Conf. on Robotics & Automation (ICRA), 2021.
    bib | video | code | pdf ]

  • X. Chen, T. Läbe, L. Nardi, J. Behley, and C. Stachniss. Learning an Overlap-based Observation Model for 3D LiDAR Localization.
    In Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2020.
    bib | video | code | pdf ]

  • X. Chen, A. Milioto, E. Palazzolo, P. Giguère, J. Behley, and C. Stachniss. SuMa++: Efficient LiDAR-based Semantic SLAM.
    In Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2019.
    bib | video | code | pdf ]

  • J. Sun, Y. Wang, M. Feng, D. Wang, J. Zhao, and X. Chen*. ICK-Track: A Category-Level 6-DoF Pose Tracker Using Inter-Frame Consistent Keypoints for Aerial Manipulation.
    In Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2022.
    bib | code |]

  • J. Sun, Y. Dai, X. Zhang, J. Xu, R. Ai, W. Gu, and X. Chen. Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object Segmentation.
    In Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2022.
    bib | code | pdf ]

  • B. Mersch, X. Chen, J. Behley, and C. Stachniss. Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks.
    In Proc. of the Conf. on Robot Learning (CoRL), 2021.
    bib | video | code | pdf ]

  • A. Reinke, X. Chen, and C. Stachniss. Simple But Effective Redundant Odometry for Autonomous Vehicles.
    In Proc. of the IEEE Intl. Conf. on Robotics & Automation (ICRA), 2021.
    bib | video | code | pdf ]

  • I. Vizzo, X. Chen, N. Chebrolu, J. Behley, and C. Stachniss. Poisson Surface Reconstruction for LiDAR Odometry and Mapping.
    In Proc. of the IEEE Intl. Conf. on Robotics & Automation (ICRA), 2021.
    bib | video | code | pdf ]

  • M. Arora, L. Wiesmann, X. Chen*, and C. Stachniss. Mapping the Static Parts of Dynamic Scenes from 3D LiDAR Point Clouds Exploiting Ground Segmentation.
    In Proc. of the Europ. Conf. on Mobile Robotics (ECMR), 2021.
    bib | code | pdf ]

  • H. Dong, X. Chen*, and C. Stachniss. Online Range Image-based Pole Extractor for Long-term LiDAR Localization in Urban Environments.
    In Proc. of the Europ. Conf. on Mobile Robotics (ECMR), 2021.
    bib | code | pdf ]

  • Mengjie Zhou, X. Chen, Noe Samano, Cyrill Stachniss, and Andrew Calway. Efficient localisation using images and openstreetmaps.
    In Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2021.
    bib | pdf ]