Prof. Graziano Chesi
The University of Hong Kong
Speech Title: SDP-Based Multiple-View Triangulation
Abstract: A key problem in computer vision consists of estimating the position in the scene of a point from the available estimates of its image projections on several cameras and the calibration parameters. This problem, known as multiple-view triangulation, has received a number of contributions given its importance. This talk explains how semidefinite programming, an area of convex optimization, can be exploited to address this problem in the common case where the reprojection error to be minimized is measured through the L2 norm. In particular, two methods are presented, one suitable for real time applications based on the fundamental matrices relating each pair of views, and the other more accurate based on the projection matrices that characterize each view. Both methods provide an estimate of the sought scene point together with a certificate of optimality. The talk also explains how occlusions can be considered in the presented framework.
BIO: Graziano Chesi is a full professor at the Department of Electrical and Electronic Engineering of the University of Hong Kong. He received the Laurea in Information Engineering from the University of Florence and the PhD in Systems Engineering from the University of Bologna. He served as associate editor for various journals, including Automatica, the European Journal of Control, the IEEE Control Systems Letters, the IEEE Transactions on Automatic Control, the IEEE Transactions on Computational Biology and Bioinformatics, and Systems and Control Letters. He founded the Technical Committee on Systems with Uncertainty of the IEEE Control Systems Society. He also served as chair of the Best Student Paper Award Committees of the IEEE Conference on Decision and Control and the IEEE Multi-Conference on Systems and Control. He authored the books "Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems" and "Domain of Attraction: Analysis and Control via SOS Programming". He is a Fellow of the IEEE, AAIA and AIIA.
Prof. Guoqiang Hu
Nanyang Technological University, Singapore
Speech Title: Human-Robot Collaboration via Control Barrier Functions and Optimization
Abstract: Human–robot collaboration (HRC) has emerged as a cornerstone for the next generation of intelligent manufacturing, service robotics, and human-centric automation. Unlike traditional industrial robots confined to isolated tasks, collaborative robots must share workspace, goals, and decision-making processes with humans, requiring real-time safety, adaptability, and efficiency. One of the challenges for multi-robot systems and human-robot systems is the design of effective algorithms that enable the robots to work cooperatively and safely with other robots or humans. Optimization provides a unifying mathematical framework to formalize these challenges. This talk will first give a brief review on human-robot collaboration, and then present some recent related research results.
BIO: Dr. Guoqiang Hu is currently a Professor of Intelligent Systems and Robotics in the School of Electrical and Electronic Engineering at Nanyang Technological University, Singapore. He received Ph.D. in Mechanical Engineering from University of Florida. His research interests include optimization and control, game theory, and learning algorithms, with applications to robotics and smart city systems. He was a recipient of several awards, including the Best Paper in Automation Award in the 14th IEEE International Conference on Information and Automation, the Best Paper Award in the 36th Chinese Control Conference, and the Best Paper Award in the 4th Asia Pacific Conference of the Prognostics and Health Management Society. He currently serves as Associate Editor for IEEE Transactions on Control Systems Technology and IEEE Transactions on Automatic Control.
Prof. Haoping Wang
Nanjing University of Science and Technology, China
Speech Title: Passive and Active Assisted as Needed Control for Rehabilitation Exoskeleton Robotic Systems
Abstract: Stroke and traumatic brain injury leave millions of survivors with physical disabilities, which result in great requirements for rehabilitation. Traditional therapies need great labor intensity, and they usually suffer from bad repetition and low efficiency. This gives rise to the research on exoskeleton robotic systems and their assistive control methods. This talk will begin with the introduction of a lower limb exoskeleton systems, then focus on the development of data-driven ultra-local model based model free trajectory tracking control (ULM-MFC), and their application in passive rehabilitation assistance of exoskeleton robots, Finally, with the application of series elastic actuators (SEA), a human–robot interaction evaluation-based Assisted As Needed (AAN) controller will be particularly presented in active rehabilitation exoskeleton robots.
BIO: Haoping Wang is currently IEEE Senior member, Professor and Ph.D Supervisor at Automation School, Nanjing University of Science and Technology (NJUST), China. He received Ph.D. degree in Automatic Control and Computer Science from Lille University of Science and Technology (LUST), France. His research interests include the theory and applications of hybrid systems, data driven model free adaptive control, state observation design, visual servo control, renewable energy systems optimal control and rehabilitation and augmented exoskeletons design and intelligent control, etc. He was/is the Principal Investigators and coordinators of Chinese National key R & D projects of national international science and technology cooperation Project, National Science Foundation of China Projects, Chinese-French project of Cai Yuanpei, etc. He has published over 277 refereed international journal and conference papers, in which 147 SCI journal papers, authored 2 books, 15 patents, and co-author 5 chapters in books.
Prof. Wang is the editor of SCIE journal IJAMCS, and served as the General Chair of ICRCV 2024-2023, Publication Chair of ICCAD 2024, Co-chair of the ICRCV 2021, Co-Chair of Program Committee of the 27th IEEE Int. Conf. on Robot and Human Interactive Communication (ROMAN’2018), and participation to more than 30 conference organization. He was selected as World's Top 2% Scientists, based on Stanford and Elsevier Data, in 2024, and enlisted also in ‘Jiangsu Provincial 333 High-Level Talent Training Program’, ‘Jiangsu Provincial Project Blue: Young Academic Leader’, ‘Six Talent Peaks of High Level Talents’, etc. Prof. Wang is currently Dean of Zhizhi Academy of NJUST, Executive deputy Director of the Sino-French International Joint Laboratory of Automatic Control and Signal Processing, Deputy Director of the Jiangsu Enterprise Development Engineering Association, and Deputy Director of the Rehabilitation Medicine Engineering and Transformation Committee of the Jiangsu Rehabilitation Medicine Association, member of Chinese Association of Automation (CAA), Committee member of Data Driven Control Learning and Optimization Professional Committee (DDCLS-CAA), and the Committee member of the energy Internet Committee –CAA, etc.
Prof. Farshad Khorrami
New York University, USA
Speech Title: Resilient, Safe, and AI-Enabled Autonomous Robotic Systems
Abstract: The development of autonomous unmanned vehicle technologies and their deployment involves several core challenges in vehicle design, sensor data processing, data fusion, localization, navigation, world modeling, obstacle avoidance, path planning, collaborative mission planning and formation maneuvering, distributed sensing and monitoring, and control. To perform any of these tasks, robotic platforms need to fuse in real-time proprioceptive and exteroceptive sensor data for environment perception, building world models, localization, and task planning. To achieve this, a host of mathematical as well as machine learning-based algorithms have been developed. This talk will focus on controls (also machine learning-based approaches) and their safety, adaptability, and security for various robotic platforms. Additionally, the use of large-language models and vision language models for enhancing semantic awareness, natural language interfaces, and agile autonomy in uncertain environments will be explored. Lastly, methods to alleviate fragility of learning-based systems to adversarial perturbations, uncertainties/ambiguities, and domain shifts will be presented based on generative adversarial learning-based techniques, control barrier functions, and feedback-based introspection. Experimental studies on several robotic platforms will be presented.
BIO: Farshad Khorrami received his bachelor’s degrees in mathematics and electrical engineering in 1982 and 1984 respectively from The Ohio State University. He also received his master’s degree in mathematics and Ph.D. in Electrical Engineering in 1984 and 1988 from The Ohio State University. Dr. Khorrami is currently a professor of Electrical & Computer Engineering Department at NYU where he joined as an assistant professor in Sept. 1988. His research interests include system theory and nonlinear controls, robotics, machine learning, cyber physical system security, autonomous unmanned vehicles, embedded system security, and large-scale systems and decentralized control. Prof. Khorrami has published more than 380 refereed journal and conference papers in these areas. His book on “modeling and adaptive nonlinear control of electric motors” was published by Springer Verlag in 2003. He also has fifteen U.S. patents on novel smart micro-positioners and actuators, embedded system security, and wireless sensors and actuators. He has developed and directed the Control/Robotics Research Laboratory at Polytechnic University (Now NYU) and Co-Director of the Center for Artificial Intelligence and Robotics at NYU Abu Dhabi. His research has been supported by the Army Research Office, National Science Foundation, Office of Naval Research, DARPA, Dept. of Energy, Sandia National Laboratory, Army Research Laboratory, Air Force Research Laboratory, NASA, and several corporations. Prof. Khorrami has served as general chair and conference organizing committee member of several international conferences. He is also an IEEE Fellow.