Assoc. Prof. Fu Zhang
The University of Hong Kong,China
Biography：Dr. Fu Zhang is an Associate Professor in the Mechanical Engineering Department at the University of Hong Kong (HKU). His research focuses on the unmanned aerial vehicles (UAVs) and light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM). Dr. Zhang has worked on various topics of UAVs, including design, navigation, control, and perception, as well as LiDAR SLAM algorithms, such as odometry, place recognition, mapping, and multi-sensor fusion. His team received the IROS’23 Best Paper Award on Robot Mechanisms and Design and the ICRA23 Best Mechanical Design Award in workshop on Agile Movements: Animal Behavior, Biomechanics, and Robot Devices. His work are selected for the TMECH’23 Best Paper Award Finalist, IROS’23 Best Paper Award Finalists (two), and ICRA’23 Outstanding Navigation Paper Finalist. His papers in Science Robotics are selected as the cover page of the journal or visually featured on the website of Science. Dr. Zhang’s work in this field has also led to numerous championships in international SLAM challenges and has found wide applications in the community.
Speech Title: A LiDAR-centric approach for reliable UAV navigation
Abstract: Over the last decades, unmanned aerial vehicles (UAVs) have received intensive research interests. These UAVs have shown promising potential for various applications, including aerial photography, farming, delivery, mapping, and surveying. However, for these applications to be successful, autonomous flights in unknown environments are necessary. In this talk, we will discuss our work on developing autonomous UAVs using lidar navigation. Specifically, we will explore recent advancements in lidar technologies and focus on navigation algorithms, including localization, mapping, planning, and control. We will showcase how lidar sensors can be utilized on UAVs to enable complex navigation tasks, such as high-speed flight navigation, environment exploration, and estimation of agile UAV motion.
Assoc. Prof. Yong Zhong
South China University of Technology, China
Biography：Zhong Yong, Ph.D., is currently an assistant professor (special researcher) at Wu Xianming School of Intelligent Engineering, South China University of Technology. He is a member of IEEE, member of RAS, member of ASME, and has published/accepted more than 30 papers in important international journals and conferences (e.g., IEEE TMECH, IEEE TIM, IEEE RA-L and other authoritative journals), and has accepted more than 6 patents for inventions. He has received more than 6 patents for his inventions, and has been shortlisted for 1 best paper award in an international conference. He is now the associate editor of one international journal and reviewer of more than 20 international journals. He is the chair of 2 provincial and ministerial level projects, and many horizontal projects.
Dr. Laihao Yang
Xi'an Jiaotong University, China
Biography：Dr. Laihao Yang received his Ph.D. Degree in the School of Mechanical Engineering from Xi’an Jiaotong University. He was a research fellow of the Structural Dynamics & Acoustic Systems Laboratory (SDASL). He is now in the faculty of the School of Mechanical Engineering at Xi’an Jiaotong University. His research interests include nonlinear vibration modeling and analysis, data-driven structural dynamics, compressive sensing, interpretable AI, and soft robotics. He is the recipient of the first Prize of Science and Technology Award of Shaanxi Higher Education Institutions and the best paper award of CMMNO 2024. He is currently serving on the Junior Editorial Board Member of Soft Science and Robot Learning, the council member of the Professional Committee for Dynamic Testing in the Chinese Society of Vibration Engineering.
Speech Title: Mini-Invasive Maintenance Continuum Robots for Aero-Engines
Abstract: Mini-invasive maintenance (inspection and repair) is crucial for the safety insurance and economic purpose of aero-engines. This presentation addresses this issue by developing high-performing tendon-driven continuum robot systems. Specifically, the design issues related to compression-induced buckling, low torsion resistance, and insufficient load capacity and the modeling issues related to the high-fidelity morphology characterization method and time-space varying tendon friction modeling method will be extensively and comprehensively addressed. Various experiments are performed to verify the effectiveness of both our designed hardware and algorithm. It is demonstrated that the robotic system with such hardware and algorithm achieving the torsional stiffness outperforms the twin-pivot design at least 24 times, stiffness enhancement > 100 times, morphology error < 2.5% of the manipulator length, and avoiding the first-order instability. Additionally, we demonstrate the navigation experiment by using two developed control strategies to show the performances of the robotic system for blade-array inspection of aero-engines.
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