Xieyuanli Chen (陈谢沅澧)
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Associate Professor,
College of Intelligence Science and Technology,
National University of Defense Technology,
Changsha, China
E-mail: chenxieyuanli@nudt.edu.cn
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Short CV
I'm an Associate Professor at NUDT. 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 a member of the Technical Committee of RoboCup Rescue Robot League (RRL), and AE for IROS, ICRA and RA-L.
[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 IROS, 2023-Present
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:
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 ]
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