Xianjia Yu
PhD
Department of Computing xianjia.yu@utu.fi ORCID-tunniste: https://orcid.org/https://orcid.org/0000-0002-9042-3730 |
Robotics, Perception, Machine Learning, Computer Vision, Sensor Fusion, Federated Learning
Multi-robot system perception, machine learning, sensor fusion, federated learning
Dr. Xianjia Yu is a postdoctoral researcher at the TIERS Lab, University of Turku, and an automation researcher and engineer at Kaptas Oy. He earned his D.Sc. (Tech.) in Robotics and Autonomous Systems from the University of Turku in 2024, and holds dual Master’s degrees from the University of Turku and Fudan University. His research focuses on multi-modal sensing, sensor fusion, machine learning, and robotic perception.
multi-modal sensing, sensor fusion, machine learning, and robotic perception
Previously involved in three-course teaching:
Hardware Accelerators for Robotics & AI
Robotics and Autonomous Systems
Perception and Navigation in Robotics
- Comparison of Middlewares in Edge-to-Edge and Edge-to-Cloud Communication for Distributed ROS 2 Systems (2024)
- Journal of Intelligent and Robotic Systems
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Federated learning enhanced multi-modal sensing and perception in a collaborative multi-robot system (2024) Yu, Xianjia
(G5 Artikkeliväitöskirja) - A Benchmark for Multi-Modal LiDAR SLAM with Ground Truth in GNSS-Denied Environments (2023)
- Remote Sensing
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Benchmarking UWB-Based Infrastructure-Free Positioning and Multi-Robot Relative Localization: Dataset and Characterization (2023) 2023 IEEE Sensors Applications Symposium (SAS) Torrico Morón Paola, Salimpour Sahar, Fu Lei, Yu Xianjia, Peña Queralta Jorge, Westerlund Tomi
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Blockchain and Emerging Distributed Ledger Technologies for Decentralized Multi-robot Systems (2023)
- Current Robotics Reports
(A2 Vertaisarvioitu katsausartikkeli tieteellisessä lehdessä) - Exploiting redundancy for UWB anomaly detection in infrastructure-free multi-robot relative localization (2023)
- Frontiers in Robotics and AI
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - General-Purpose Deep Learning Detection and Segmentation Models for Images from a Lidar-Based Camera Sensor (2023)
- Sensors
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - LiDAR-Generated Images Derived Keypoints Assisted Point Cloud Registration Scheme in Odometry Estimation (2023)
- Remote Sensing
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Towards Robust UAV Tracking in GNSS-Denied Environments: A Multi-LiDAR Multi-UAV Dataset (2023) 2023 IEEE International Conference on Robotics and Biomimetics (ROBIO) Catalano Iacopo, Yu Xianjia, Peña Queralta Jorge
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - UAV Tracking with Lidar as a Camera Sensor in GNSS-Denied Environments (2023)
- International Conference on Localization and GNSS
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)



