Kailai Li

Assistant Professor
Agile Sensing and Intelligence Group
Division of Automatic Control, Department of Electrical Engineering
Email: kailai.li[at]liu.se

Since 2026-09, I am an assistant professor at the Department of Electrical Engineering at Linköping University in Sweden. From 2024-05 to 2026-08, I was an assistant professor with the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence at the University of Groningen in the Netherlands, where I was tenured in 2025-08. Previously, I was a postdoctoral researcher at Linköping University, collaborating with Fredrik Gustafsson, and a postdoc at the Institute for Anthropomatics and Robotics, Department of Informatics, Karlsruhe Institute of Technology in Germany, where I obtained my PhD degree in computer science with highest distinction in 2022 (Defended in 2021. Advisor: Uwe D. Hanebeck). I received my MSc degree in Automation Engineering in 2017 from RWTH Aachen University in Germany, including a master’s thesis completed at ETH Zurich in Switzerland, and my bachelor degrees in 2014 from Tsinghua University (Wikipedia) in China.

My research interests focus on enabling agile and trustworthy sensing, inference, learning and control towards full-stack autonomy of mobile robotic systems in the domain of embodied AI. Please refer to my group homepage for more details.
Group News
  • 2026-06: Our paper A Third-Order Gaussian Process Trajectory Representation Framework with Closed-Form Kinematics for Continuous-Time Motion Estimation is now published on IEEE Transactions on Robotics! (link).
  • 2026-05: Kailai Li visited the Artificial Intelligence and Robotics group at the Sapienza University of Rome and give a talk.
  • 2026-04: Kailai Li was appointed as Guest Scholar at IMT School for Advanced Studies Lucca (with Prof. Alberto Bemporad) and gave a talk.
  • 2026-03: Kailai Li is now an Associate Editor of the IEEE Robotics and Automation Letters (RA-L)
  • 2025-12: Our paper Co-NavGPT: Multi-Robot Cooperative Visual Semantic Navigation Using Vision Language Models is now published on IEEE RA-L. Check out our project page!

Research Highlights
* indicates equal contribution.

REASAN: Learning Reactive Safe Navigation for Legged Robots
Qihao Yuan, Ziyu Cao, Ming Cao, Kailai Li
arXiv preprint, arXiv:2512.09537, 2025
arXiv / Code / Video / Website

RESPLE: Recursive Spline Estimation for LiDAR-Based Odometry
Ziyu Cao, William Talbot, Kailai Li
IEEE Robotics and Automation Letters, vol. 10, no. 10, pp. 10666-10673, Oct. 2025
arXiv / Code / Video / Website

On Embedding B-Splines in Recursive State Estimation
Kailai Li
IEEE Transactions on Aerospace and Electronic Systems, vol. 61, no. 5, pp. 13594-13604, Oct. 2025
arXiv / Paper / Video

A Third-Order Gaussian Process Trajectory Representation Framework with Closed-Form Kinematics for Continuous-Time Motion Estimation
Thien-Minh Nguyen, Ziyu Cao, Kailai Li, William Talbot, Tongxing Jin, Shenghai Yuan, Timothy D. Barfoot, Lihua Xie
IEEE Transactions on Robotics, 2026
arXiv / Paper / Code

Solving Zero-Shot 3D Visual Grounding as Constraint Satisfaction Problems
Qihao Yuan, Kailai Li*, Jiaming Zhang*
The British Machine Vision Conference (BMVC), 2025
arXiv / Code / Video / Website

IRIS: An Immersive Robot Interaction System
Xinkai Jiang, Qihao Yuan, Enes Ulas Dincer, Hongyi Zhou, Ge Li, Xueyin Li, Julius Haag, Nicolas Schreiber, Kailai Li, Gerhard Neumann, Rudolf Lioutikov
The Conference on Robot Learning (CoRL), 2025

Co-NavGPT: Multi-Robot Cooperative Visual Semantic Navigation using Vision Language Models
Bangguo Yu, Qihao Yuan, Kailai Li, Hamidreza Kasaei, and Ming Cao
IEEE Robotics and Automation Letters, 2025
arXiv / Paper / Code / Video / Website

Continuous-Time Ultra-Wideband-Inertial Fusion
Kailai Li, Ziyu Cao, Uwe D Hanebeck
IEEE Robotics and Automation Letters, vol. 8, no. 7, pp. 4338-4345, July 2023
arXiv / Paper / Code / Video

Towards High-Performance Solid-State-LiDAR-Inertial Odometry and Mapping
Kailai Li, Meng Li, Uwe D. Hanebeck
IEEE Robotics and Automation Letters, vol. 6, no. 3, pp. 5167-5174, July 2021
arXiv / Paper / Code / Video

Highly Parallelizable Plane Extraction for Organized Point Clouds Using Spherical Convex Hulls
Hannes Möls, Kailai Li, Uwe D. Hanebeck
Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France
© 2026 ASIG. All rights reserved. Using, copying, and redistributing the code in any form can be performed only under permission.