I am a Ph.D. candidate at The Hong Kong University of Science and Technology (HKUST), with research interests in SLAM, AR/VR, and robotics.My previous work in LiDAR SLAM focused on two core topics: covariance estimation and geometric degeneracy. For covariance estimation, I study observability in long-duration nonlinear multi-sensor fusion systems. For degeneracy, I analyze rank-deficient geometric constraints and their impact on state estimation.

My current interests include feed-forward 3D reconstruction, open-vocabulary semantic mapping, and 3D Gaussian Splatting (3DGS), with applications to world-model and simulation pipelines for embodied AI.

I am open to research and engineering opportunities in SLAM, AR/VR, robotics, and related areas. I am also available for part-time technical consulting on mapping and localization systems, including cloud-based map construction and update pipelines. Feel free to reach me at xhubd@connect.ust.hk.

• Ph.D. Candidate, The Hong Kong University of Science and Technology (Sep 2021 - Present)
• M.Sc. in Software Engineering, Beihang University (Sep 2018 - Feb 2021)
• B.Sc. in Detection Guidance and Control Technology, North University of China (Sep 2013 - Jul 2017)

• Visiting Ph.D. Student, Toronto Robotics and AI Laboratory, University of Toronto (Mar 2025 - Sep 2025)
• Ph.D. Candidate, Robotics Institute, Intelligent Autonomous Driving Center (IADC), HKUST (Sep 2021 - Present)
• Research Intern (Supervisor: Prof. Dongbin Zhao), Institute of Automation, Chinese Academy of Sciences, Beijing (Apr 2019 - Nov 2019)

I have had the privilege to collaborate with Prof. Jin Wu, Prof. Xieyuanli Chen, Dr. Jianhao Jiao, Linwei Zheng, Hexiang Wei, Zuhao Zou, Dr. Huaiyang Huang, and Dr. Zhenhua Xu.

1. X. Hu, X. Chen et al. "DCReg: Decoupled Characterization for Efficient Degenerate LiDAR Registration," arXiv:2509.06285.
2. X. Hu, J. Wu et al. "MS-Mapping: An Uncertainty-Aware Large-Scale Multi-Session LiDAR Mapping System," arXiv:2408.03723.
3. X. Hu, J. Wu et al. "MapEval: Towards Unified, Robust, and Efficient SLAM Map Evaluation Framework," IEEE Robotics and Automation Letters (RA-L), Feb 2025. DOI: 10.1109/LRA.2025.3548441.
4. X. Hu, L. Zheng et al. "PALoc: Advancing SLAM Benchmarking With Prior-Assisted 6-DoF Trajectory Generation and Uncertainty Estimation," IEEE/ASME Transactions on Mechatronics (T-MECH), vol. 29, no. 6, pp. 4297-4308, Dec 2024. DOI: 10.1109/TMECH.2024.3362902.
5. X. Hu*, J. Wu* et al. "AM-Align: Globally Optimal Estimation of Accelerometer-Magnetometer Misalignment," IEEE Transactions on Instrumentation and Measurement (T-IM), Sep 2024. DOI: 10.1109/TIM.2025.3541657.
6. J. Jiao*, H. Wei*, T. Hu*, X. Hu* et al. "FusionPortable: A Multi-Sensor Campus-Scene Dataset for Localization and Mapping Accuracy Evaluation," IROS 2022, pp. 3851-3856, Kyoto, Japan. DOI: 10.1109/IROS47612.2022.9982119.
7. H. Wei*, J. Jiao*, X. Hu, et al. "FusionPortableV2: A Unified Multi-Sensor Dataset for Generalized SLAM Across Diverse Platforms and Scalable Environments," The International Journal of Robotics Research (IJRR). DOI: 10.1177/02783649241303525.
8. Z. Chen, Y. Qi, D. Feng, X. Zhuang, H. Chen, X. Hu, J. Wu, K. Peng, and P. Lu. "Heterogeneous LiDAR Dataset for Benchmarking Robust Localization in Diverse Degenerate Scenarios." The International Journal of Robotics Research (IJRR), 2024:02783649251344967.
9. J. Wu, Y. Zheng, Z. Gao, Y. Jiang, X. Hu, Y. Zhu, et al. (2022). "Quadratic Pose Estimation Problems: Globally Optimal Solutions, Solvability/Observability Analysis, and Uncertainty Description." IEEE Transactions on Robotics (T-RO), 38(5), 3314-3335.

Selected repositories from my Ph.D. research process, including SLAM tools, dataset resources, and evaluation frameworks:

• SLAMTools: utilities and scripts for SLAM research workflows.
• MS-Dataset: dataset resources for mapping and localization studies.