👋 Hi there, I'm Xiangcheng Hu

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.

📫 Contact

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.

🎓 Education

• 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)

🔬 Research Experience

• 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)

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🤝 Collaborating Researchers

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.

📚 Publications and Manuscripts

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.

🔥 Important Repositories

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.