Bo Li, Associate Professor

Nanjing University of Aeronautics and Astronautics (China)

Biography: Bo Li works as the Associate Professor at the College of Mechanical and Electrical Engineering of Nanjing University of Aeronautics and Astronautics. He is the recipient of Outstanding Youth Fund of Jiangsu Natural Science Foundation. His research interests include robot dynamics and high-accuracy control, and robotic intelligent manufacturing technology and equipment. He has hosted and completed 7 national and provincial/ministerial projects. He has published 3 monographs/textbooks, more than 30 articles, and received over 20 invention patents and software copyrights. He has won one First Prize of National Defense Science and Technology Progress Award, one First Prize of Jiangsu Province Teaching Achievement Award, one First Prize of Science and Technology of Nanjing University of Aeronautics and Astronautics, and one Innovation Award of "Young Scholar" of Nanjing University of Aeronautics and Astronautics.

Speech Title: Robotic In-Situ Manufacturing Technology and Equipment for Large Weakly Rigid Aerospace Assembly Structures

Abstract: The integration and lightweight requirements of next-generation aerospace equipment necessitate the utilization of large-scale weak-rigid assembly structures, which possess significant characteristics such as extensive dimensions, low rigidity, complex shapes, and high precision. The conventional manufacturing mode has emerged as a major bottleneck for the rapid development of aerospace equipment due to increased manufacturing costs and research cycles caused by the structural effects of large scale and weak rigidity. Therefore, there is an urgent need to develop and innovate robotic in-situ manufacturing methods. However, this approach encounters two primary challenges: low positioning accuracy and severe processing vibrations. This report comprehensively presents a series of accomplishments achieved by our research group in terms of robotic in-situ machining of aerospace large components from three perspectives: error compensation of robot body, vibration suppression of robotic machining systems, and standardized development of robotic in-situ manufacturing equipment. We have established a mobile robotic drilling-milling in-situ manufacturing technology system that offers novel manufacturing techniques and equipment for the advancement of large-scale complex assembly structures in aerospace industry.

Caixu Yue, Professor

Harbin University of Science and Technology (China)

Biography: Caixu Yue is currently the associate dean, professor, and doctoral supervisor in the School of Mechanical and Power Engineering, Harbin University of Science and Technology. He won the Yangtze River Scholars 'Young Scholars', the high-level leading Talents of Heilongjiang Province, the Longjiang Scholars 'Young Scholars', the Heilongjiang Provincial Youth Science and Technology Award, and the Heilongjiang Provincial May Fourth Youth Medal. Also, he is the deputy director of the “Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education” and the deputy director of the “National Local Joint Engineering Laboratory of Efficient Cutting and Cutting Tools”. His academic part-time is the Deputy Secretary-General of the Heilongjiang Tool Technology Association and the Standing Committee of the Production Engineering Branch of the China Society of Mechanical Engineering. He presided over more than 10 national key research and development projects, national natural science fund projects, provincial and ministerial fund projects. He published 113 SCI/EI academic papers, including 2 highly cited 'ESI' papers, 5 published works, applied for 44 patents, obtained 4 software copyrights, and participated in the development of 1 national standard. He won one first prize for the technological invention of China's machinery industry and one second prize for the scientific and technological progress of China's machinery industry.

Speech Title: Research on the Optimization of Complex Surface Machining Process for Precision Control

Abstract: Impeller blades and other complex curved thin-walled parts are the key parts of aerospace equipment, and their machining quality and accuracy directly affect the performance and reliability of aerospace equipment. Compared with foreign countries, at present, in the optimization process of such complex surface parts machining process often only consider the theoretical geometric model for machining path planning, in the machining of deformation compensation and process parameter optimization is often empirically based. How to break through the machining accuracy of this key part has become a problem that constrains the high-quality development of China's aerospace industry and needs to be solved. The report is oriented to the demand for high machining quality of complex curved thin-walled parts, and introduces in detail the latest theoretical results on the prediction of milling force for multi-axis machining of complex curved surfaces and the effective optimization and compensation of machining deformation. The research results can provide important technical support for the processing of complex curved thin-walled parts to shorten the development cycle, product qualification rate and performance improvement.

Changsheng Dai, Professor

Dalian University of Technology (China)

Biography: His research focuses on robotic cell manipulation and medical image analysis. Dr. Dai has published over 20 peer-reviewed papers in premium journals and international conference proceedings such as Nature Reviews Urology, IEEE Transactions on Robotics, and IEEE Transactions on Medical Imaging, and has received the Best Paper Award in Automation at 2019 IEEE International Conference on Robotics and Automation (ICRA), IEEE Robotics and Automation Letters Best Paper Award-Honorable Mention, and First Prize Video Awards at 2020 and 2021 Scientific Congress of American Society of Reproductive Medicine. He served as a peer reviewer for several journals such as IEEE Transactions on Robotics and IEEE/ASME Transactions on Mechatronics.

Speech Title: Robotic Cell Manipulation for Intracytoplasmic Sperm Injection (ICSI)

Abstract: Intracytoplasmic sperm injection (ICSI) is the most widely used technique for in vitro fertilization, but the manual operation suffers from low success rate and inconsistency. In this talk, robotic system to perform ICSI is introduced. Automated non-invasive sperm analysis is firstly proposed to achieve subcellular-resolution measurement. For robotic cell manipulation, two key tasks are described: robotic cell orientation control and cell injection. By deformation modeling, path planning and optimal control, cell deformation can be minimized during manipulation. Future perspectives of robotics for in vitro fertilization will be discussed.

Francesco Maurelli, Professor

Constructor University (Germany)

Biography: Dr. Francesco Maurelli is a Professor in Marine Systems and Robotics at Jacobs University Bremen (Germany, EU), where he also serves as Program Chair for the Robotics and Intelligent Systems Program. He has obtained his PhD at the Oceans Sytems Lab, Heriot-Watt University (Edinburgh, Scotland) with a thesis on intelligent AUV localisation. He has been Scientific Manager at Technical University of Munich (Germany, EU) where he lead the Echord++ program, to support moving robotics technology from the lab to the market. After a research stay at Massachusetts Institute of Technology (Cambridge, MA, USA), in the framework of a Marie Curie Fellowship, he has accepted a faculty position in Jacobs University Bremen. Dr. Maurelli's research interests are focused on persistent autonomy for marine robotics, autonomous navigation, intelligent decision making, sensor data processing and fault management. Dr. Maurelli is co-chair of the IEEE RAS Marine Robotics Technical Committee, IEEE OES Young professional laureate and member of the Global Young Academy.

Speech Title: The Long Way to Persistent Autonomy in Underwater Robotics

Abstract: The future vision for ocean observatories foresees a multitude of permanently deployed autonomous vehicles, communicating with each other, and having intelligent decision-making capabilities in navigation, energy management, and error handling. There is however a stark contrast with respect to current capabilities: commercial vehicles are very good in blindly executing pre-defined paths, they easily get stuck when conditions change and limited on-board decision making severely limits the types and length of missions. What are the main challenges to bridge our future vision with the current reality?
This talk will present the results of various projects in the last few years, aiming at increasing vehicles' capabilities. The role of a dynamically updated probabilistic knowledge-base opens up the door to the use of AI techniques like KR and reasoning. Classical AI Planning can be applied to robotics missions, instead of using efficient but not very adaptable state machines. Recent advances in Deep Learning can provide important improvements in sensor processing and object recognition. Adding on-board sensor-processing, decision making, fault management, underwater vehicles seem to significantly move forward in the field of autonomy. However, how promising research results, which are still validated during relatively controlled conditions, can be generalised to produce a real impact in the field?

Fugui Xie, Associate Professor

Tsinghua University (China)

Biography: Dr. Fugui Xie is currently working as an associate professor and doctoral supervisor with the Department of Mechanical Engineering at Tsinghua University. He received his B. Eng. in Mechanical Engineering from Tongji University in 2005, and Ph.D. degree from Tsinghua University in 2012. He worked as a postdoctoral researcher at Tsinghua University from 2012 to 2014. He was an Alexander von Humboldt (AvH) Research Fellow at Fraunhofer Institute for Machine Tools and Forming Technology (IWU) in Germany in 2016. His research interests include robotics and mechanisms, parallel mechanisms and mobile machining robots. He has authored and co-authored 1 book, more than 100 technical papers including more than 70 journal articles. He has been authorized more than 90 invention patents. He has won the first prize of the Chinese Machinery Industry Science and Technology Award. He was awarded the National Science Fund for Excellent Young Scholars. He has also served as an editorial board member of Machines.

Speech Title: An Adsorption Machining Robot: Design, Key Technologies and Application

Abstract: In the fields such as aerospace, energy and shipbuilding, manufacturing of large-scale components for major technical equipment is in urgent need of portable or movable high-performance multi-axis NC equipment. Typical examples include the machining of large-scale structural parts in large cabins, heavy-duty gas turbines and remote maintenance of large-scale equipment. In order to realize the innovative design of such high-performance machining equipment and the R & D of the whole machine system, this report firstly studies a five-axis parallel machining robot with focuses on innovative design of its mechanism and kinematics optimization. Thereafter, it probes into the key technologies such as stiffness and elastic dynamics modeling, velocity planning, accuracy assurance and vibration suppression, for high-efficiency and high-quality machining applications. This report also covers the development of a series of mobile robotic systems derived from this robot, and their applications in the machining of typical parts such as the frame-type structural parts and large cabin, and in the drilling of structural components.

Genliang CHEN, Professor

Shanghai Jiao Tong University (China)

Biography: Prof. Genliang CHEN received his B.S. and Ph.D. degrees both in Mechanical Engineering from Shanghai Jiao Tong University, Shanghai, China, in 2006 and 2014, respectively. He is currently the Deputy Direction of the META Robotics Institute, Shanghai Jiao Tong University. His research interests include mechanism design, flexible parallel robots, and multibody dynamics. Prof. Chen received the Outstanding Youth Fund from the National Natural Science Foundation of China and awarded as the Xiong-Youlun Zhihu Outstanding Young Scholar in 2018. He is correctly serving as the associated editors of Robotica and Meccanica. Prof. Chen has published more than 60 SCI papers, including IEEE T-RO, Science Advances and MMT, etc. and four times of best paper awards of international conferences.

Speech Title: Flexible Mechanisms with Large-deflection Elastic Links: Modeling, Sensing, and Actuation

Abstract: Flexible mechanisms with large-deflection elastic links represent an emerging form of robotics that bridges the gap between traditional rigid-body linkages and soft robots. Leveraging the inherent structural compliance of elastic links, this novel kind of mechanism promises a broad range of potential applications in biomimetic robotics and Human-Robot collaboration. However, due to the large deflection problems, there are still significant challenges in kinetostatic modeling, environmental perception, and actuation of active deflections. In this talk, I will present our recent progress in this topic, including kinetostatic modeling, contact sensing, and pneumatic actuation. A wide variety of case studies will be provided to demonstrate the advantages of such a kind of novel flexible mechanism, such as adaptivity to unstructured environments, sensor-based interactive manipulation, and fast-response operation. Furthermore, the future research prospects and challenges for these flexible mechanisms will be addressed at the end of this talk.

Guoteng Zhang, Associate Professor

Shandong University (China)

Biography: Guoteng Zhang received his B. Eng. degree in automation, and the D. Eng. degree in pattern recognition and intelligent system from Shandong University, Jinan, China, in 2011 and 2016, respectively. From 2016 to 2019, he was a Senior Researcher with Ritsumeikan University, Shiga, Japan. He is currently an Associate Research Professor at the School of Control Science and Engineering, Shandong University, where he is also working as the Vice Director for the Department of Robotics Engineering. His research interests include legged robots and dynamic control.

Speech Title:Design and Control of BRAVER: A Bipedal Robot Actuated Via Proprioceptive Electric Motors

Abstract: The aspiration to design human-like mechanisms capable of traversing challenging terrain is as old as humanity itself. This presentation introduces the design and control of BRAVER, a Bipedal Robot Actuated Via proprioceptive Electric motoRs. The robot, which weighs 8.6 kg and is 0.36 m tall, has six active degrees, all of which are driven by custom back-driveable modular actuators, which enable high-bandwidth force control and proprioceptive torque feedback. The robot’s hardware design, including the actuator, leg, foot, and onboard control systems will be presented. Then this presentation will deliver a comprehensive overview of the optimal control framework for legged locomotion, encompassing methodologies implemented in BRAVER. These methodologies include model-predictive controllers, whole-body controllers, state estimators, and learning-based locomotion algorithms.

Hongmiao Tian, Professor

Xi’an Jiaotong University (China)

Biography: Hongmiao Tian received the Ph.D. degree from Xi’an Jiaotong University, Xi’an, China, in 2014. He is currently a Professor at the State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University. His research interests include bionic manufacturing, dry adhesives, artificial muscles and soft robots. Prof. Tian is/was the Principal Investigator in several projects funded by National Natural Science Foundation of China and Department of science and technology of China. He has published more than 40 papers in prestige international journals, such as Nature Communications, Science Advances, Advanced Materials, and so forth, accompanied with several cover papers in multi-disciplinary journals including Materials Horizons, Small, ACS Applied Materials & Interfaces, etc. Moreover, he holds more than 40 invention patents. Prof. Tian was issued the first prize of natural science award of Shaanxi Province, the first prize of natural science award of the Ministry of Education, the special award and the first prize of outstanding achievements in Shaanxi universities, and the national Young Scholar.

Speech Title: Gecko-Inspired Dry Adhesives: Fabrication and Application

Abstract: Inspired by the outstanding climbing ability from geckos, the design of biomimetic dry adhesive functional structures as well as the study of their interface behaviors have attracted widely attention in academic field. Especially, mushroom-shaped feature at micro/nano-scale has been confirmed as an optimal structural design for artificial surfaces with strong adhesion function because of its prominent adhesive strength, which has exhibited potential application prospects in grasping manipulators, biomimetic climbing robots, space operations, etc. However, mass fabricating mushroom-shaped adhesive structures at micro/nano-scale, stable attachment on rough surfaces and controllable detachment from the adhered surfaces are still the great challenges that restricting the engineering application of gecko-inspired dry adhesives. This report focuses on the recent progress of the research group in electrically induced growth of gecko-inspired adhesive structures, the adhesion enhancement on rough surfaces controlled by structural stiffness, the switchability of attachment/detachment via artificial muscle, which may promote the engineering application of gecko-inspired adhesive structures in industrial robots, climbing robots and other fields.

Jianwei Ma, Professor

Dalian University of Technology (China)

Biography: Jianwei Ma, is currently a professor and a PhD candidate supervisor in School of Mechanical Engineering, Dalian University of Technology, China. The research team focuses on the direction of mechanical manufacturing, mainly engaged in the research work of surface machining and process control of difficult-to-machine materials, laser precision machining and process control, robot-assisted machining planning and control. He has successively undertaken more than 10 scientific research projects including the National Natural Science Foundation of China, the National Science and Technology Major Project of China, the National Key Research and Development Program of China, et al.

Speech Title: Robotic Multifunctional Collaborative Processing Technology for Large Composite Components

Abstract: The high-quality and efficient manufacturing of surface coatings on large composite components is crucial for ensuring their high performance. Conventional processing equipment struggles to achieve precise grinding and polishing of component blanks, severely limiting the development and batch production of high-performance composite components. To overcome the challenges of high-reliability processing for such components, a multifunctional collaborative processing technology based on a force feedback mechanism for trajectory planning and in-situ measurement is proposed. This technology employs a parallel robot, which minimizes the accumulation of geometric errors across joints, to perform in-situ measurements of the actual profile of the components. The three-dimensional information of the components to be processed are then fed back to the multi-axis serial robot. Based on the force feedback mechanism, a multi-objective optimization model is established at the end-effector of the multi-axis serial robot. This model ultimately generates an optimal processing trajectory for the multi-axis serial robot, characterized by high equivalent stiffness, smooth joint movements, and low vibrations. This approach address the issues of inadequate adaptability to diverse and complex surfaces and the difficulty in effectively ensuring processing accuracy for weakly rigid and easily deformable components during automated robotic grinding and polishing. The research outcomes will provide new processing solutions for the development and optimization of key components in high-end equipment within the aerospace sector in China.

Jixiang Yang, Professor

Huazhong University of Science and Technology (China)

Biography: Dr. Yang is currently a Professor of the State Key Laboratory of Intelligent Manufacturing Equipment and Technology at Huazhong University of Science and Technology (HUST), Wuhan, China. He received the Ph.D. degree in Mechanical Engineering from HUST in 2015. From 2012 to 2014, he was a joint Ph.D. student with the University of British Columbia (UBC) Vancouver, Canada. From 2015 to 2017, and from 2017 to 2019, he was a Postdoctoral Research Fellow in HUST and UBC, respectively. His research interests include measurement, trajectory optimization, dynamics modeling, position/force control of robotic manufacturing. He has published 38 journal papers as the first or corresponding author on Robotics and Computer-Integrated Manufacturing, International Journal of Machine Tools and Manufacture, ASME Journal of Manufacturing Science and engineering, etc. He has received several awards for his research and teaching.

Speech Title: Profile Accuracy and Surface Quality Control for Robotic Conformal and Compliant Machining of Complex Curved Parts

Abstract: In order to address the problem of low machining accuracy induced by the large individual differences in the allowance of complex curved parts, a local feature segmentation and registration method based on point cloud analysis is developed to obtain the machining allowance of each part effectively, and the adaptive machining of the individual difference parts is realized. The high efficiency and high precision removal of machining allowance of complex parts is realized through robot posture optimization with minimum contour error under milling force disturbance. In view of the high surface quality requirements, the robotic grinding technology with force-controlled actuator is developed, and the surface quality control of complex curved parts is realized by carrying out the research on the material removal mechanism of curved surface flexible grinding, and the optimization and control of grinding force-position under the mixed constraints of material removal accuracy and surface quality.

Junhui Zhang, Associate Professor

Zhejiang University (China)

Biography:Junhui Zhang received the Ph.D. degree in mechatronics engineering from Zhejiang University, Hangzhou, China, in 2012. He is currently a Tenured Associate Professor with the Institute of Mechatronic Control Engineering, and the Deputy Director of the State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University. He has authored or coauthored more than 80 papers indexed by SCI and applied more than 30 National Invention Patents with granted. He is supported by the National Science Fund for Excellent Young Scholars. His research interests include high-speed hydraulic pumps/motors, heavy-duty hydraulic manipulators and hydraulic quadruped robots.

Speech Title: Is There Still a Future in the Research of Hydraulic Driven Legged Robots?

Abstract: In the field of robotics, Boston Dynamics' hydraulic humanoid robots and quadruped robots have always been the ceiling of robotic performance. However, against the backdrop of the vigorous development of electric foot-type robots, star robots such as Bigdog and Atlas have retired in succession. Boston Dynamics has shifted from hydraulic legged robots to electric robots, which has seriously dampened the enthusiasm of domestic and foreign scholars to study hydraulic driven legged robots. The report analyzes the differences between hydraulic-driven legged robots and electric robots in terms of hardware integration and motion control, as well as the technical difficulties in the development of hydraulic driven legged robots. Besides, it introduces some recent technical progress and reflections of the team in the field of hydraulic driven legged robots.

Liming Xin, Professor

Shanghai University (China)

Biography: Liming Xin is Vice-Dean, Research and International. He is currently a Professor at the School of Computer Engineering and Science at Shanghai University. His research interest resides in robotics. In recent years, he has extended his research to biomedical instruments and embodied intelligence. He serves as the AE of IEEE Robotics and Automation Letters. He is the recipient of numerous research awards, including the Frontiers of Science Award, the MARSS Best Application Paper Award, the National Youth Talent Program, etc. He has also been recognized for exceptional contribution to the education by Shanghai Municipal Education Commission.

Speech Title: Heart Transplant Advances: Normothermic ex vivo Heart Perfusion Robotic System And Technology

Abstract: Although heart transplantation has rapidly increased in the past decades, the number of qualified organs for transplantation is far from the demand. Improving organ preservation and repair of lower-quality organs is one of the keys to solving the organ shortage crisis. In recent years, scientists with an interest in normothermic ex vivo perfusion began to engineer and utilize special medical robots to improve the preservation quality and extend the preservation time of donor organs. Ex vivo heart perfusion robot enables expansion of the donor pool and to date shows superior outcomes to the current standard cold static storage. We have developed an ex vivo heart perfusion robot that provides the isolated heart with oxygenated and nutrient-enriched perfusate to maintain the heart’s physiological aerobic metabolism. We have been doing some research on the system modeling method and control theory of this kind of robots which include the hearts and mechatronics system to better achieve a smooth and safe control. We have developed some functional assessment methods to quantitatively evaluate the heart’s viability for transplantation as well. Experiments using pig hearts and human hearts have been performed to evaluate our technology. In this presentation, we will show some of our research findings and discuss future works.

Tianliang Hu, Professor

Shandong University (China)

Biography: Tianliang Hu received his BS and Ph.D. in Mechanical Engineering from Shandong University in 2003 and 2009, respectively. He was a visiting Ph.D. student in the IMS Lab at the University of California, Davis, from February 2007 to February 2008, funded by CSC. He began his career at the School of Mechanical Engineering, Shandong University, in January 2009. In January 2020, he was honored with the title of Qilu Young Scholar Professor by Shandong University. Additionally, in January 2021, he was recognized as the Taishan Scholar (Young Expert) of Shandong Province. Presently, he holds the position of Director at the Shandong Provincial Engineering Research Center for Intelligent Manufacturing and Control System. Prof. Hu's research interests include intelligent manufacturing, digital twins, CNC technology, and robotics. His work has been supported by over 20 notable national and provincial research projects. Furthermore, Prof. Hu is highly active in the standardization work of the manufacturing industry. He holds the position of Vice Secretary of SAC/TC159/SC1 and serves as the working group convener of IEC/TC44/MT60204-34 and SAC/TC22/IWG4. He has contributed significantly to the development of more than 10 international and national standards related to the manufacturing industry.

Speech Title: Digital Twin Enhancing Human-Machine Integration

Abstract: In recent years, digital twins have received extensive attention and applications across various industries. This report, commencing from the issues in the development of human-machine integration, will discuss the advantages and implementation pathways of digital twins in the field of human-machine integration. First, it will introduce the evolution of human-machine integration and analyze the current problems and their root causes from a digital perspective. Then, it will explain the basic concept and evolution of digital twins, as well as their advantages in the field of human-machine integration. Subsequently, combined with a practical application example, it will elaborate on the implementation methods of digital twins in human-machine integration, including the implementation framework based on perception, decision-making, and execution utilizing digital twins. Finally, the challenges of digital twins in research and engineering applications will be explored.

Tianliang Li, Professor

Wuhan University of Technology (China)

Biography: Prof. Li received his Ph.D. degree from Wuhan University of Technology (WHUT), China, in 2014 and 2016, respectively. He is currently a Full Professor with WHUT. Prior to joining WHUT, he worked as a Research Fellow at Nanyang Technological University and the National University of Singapore, from 2016 to 2019.
His current research interests include advanced optical fiber sensing, structural health monitoring, and medical robotics. He has more than 70 papers in international journals and conferences. Out of these, Dr. Li has also been invited as a technical committee member of several conferences. He serves as Editor for several journals, such as Associate Editor for Frontiers in Manufacturing Technology.

Speech Title: Optical Fiber-based Catheter-tip 3-axis Force Sensing with Environmental Self-adaption for Interventional Surgical Robot

Abstract: Fiber Bragg grating (FBG) sensing is a promising method in biological tissue force monitoring due to its inherent characteristics, such as biocompatibility, small size, and anti-electromagnetic interference. To solve the lack of contact information between catheter and tissue, and the serious coupling of force measurement accuracy with environmental parameters such as pressure and temperature, this presentation mainly introduces the recent progress of FBG-based catheter-tip 3-axis force sensors with environmental self-adaption for interventional surgical robots at Wuhan University of Technology. A 3-axis catheter force sensor for cardiac ablation has been developed. Its lateral resolution is 2.13 and 2.52 mN within -1~1 N, and 23.12 mN for the axial direction within 0~2 N, which facilitates improved surgical control and reduces tissue damage. An optimized 3-axis force sensor has been presented by integrating an additive manufacturing process to improve the force measurement accuracy. The structural design of FBGs suspended inside the elastomer maximizes the 3-axis force decoupling and temperature self-compensation. Experiments show that the axial force resolution of the sensor is 0.63 mN within 0~0.8 N, and temperature-induced errors for force detection are less than 6.5 %. To solve the coupled effect among the measured elements of 3-axis force catheters, a Rectified Linear Unit (ReLU)-based Back Propagation (BP) method has been adopted. The average relative errors of experiments are less than 2 %, which validates the feasibility and effectiveness of the method. To resist environmental parameters interference and FBG fracture risk, a wavelength-phase hybrid coded catheter-tip 3-axis force optical fiber sensor with uncertain environment self-adaptivity has been developed. The maximum full-scale relative errors of Fx, Fy, and Fz are less than 6% when one FBG is fractured. Experimental results in the heart-vascular model prove catheter-tissue force sensing and operating environment parameters detection capabilities. Based on the above techniques, an interventional surgical robot with a catheter-tip force sensor has been built. Several in vitro experiments have been implemented to verify the vascular protection, primary–secondary hand switching, and grading force control functions of the system. Such merits indicate that the designed robotic system has huge potential in the field of interventional surgery.

Weiran Yao, Associate Professor

Harbin Institute of Technology (China)

Biography: Weiran Yao received the bachelor's (with Hons.), master's, and doctor's degrees in aeronautical and astronautical science and technology from the School of Astronautics, Harbin Institute of Technology (HIT), Harbin, China, in 2013, 2015, and 2020, respectively. From 2017 to 2018, he was a Visiting Scholar with the Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada. In 2020, he joined the Department of Control Science and Engineering, HIT as an Assistant Professor, and was then promoted to an Associate Professor in 2021. At present, he is the assistant director of the Key Laboratory of Autonomous Intelligent Unmanned Systems (AIUS), MIIT, China.
Yao's research interests include autonomous decision-making of unmanned systems, multi-robot task planning and control, etc. He has published two research monographs and more than 30 research articles. He applied for more than 30 invention patents. In 2019, He won the first prize of China's a Ministerial Invention Award. In 2020, he won the second prize of China's the State Technological Invention Award. In 2021, he was the winner of Heilongjiang Provincial Science Fund for Excellent Young Scholars. In 2022, he was the winner of the Young Elite Scientist Sponsorship Program by China Association for Science and Technology, and was named the Youth Top-Notch Talent of HIT.

Speech Title: Information-Coupled Mission Planning for Multivehicle Systems

Abstract: Mission planning is the key for multivehicle system to complete complex tasks precisely and efficiently. Considering emergency and complex situations in future application scenarios, the vehicles should have the ability to carry out mission planning with information couplings, that is, to comprehensively use the information of the scenario and the other vehicles, and to develop effective task execution scheme for each individual. In recent years, our research group has carried out extensive and intensive research on the information-coupled mission planning problems. In our work, some methods for information strongly coupled mission planning are proposed to improve the mission execution performance under limited computation resources. This talk covers the methods for mission planning problems with information transferring coupling, information invoking coupling, and information coupling between vehicles, and discussions of these methods regarding their key problems and challenges in practical applications.

Xian Guo, Associate Professor

Nankai University (China)

Biography: Xian Guo received the B.S. degree in mechanical design, manufacturing, and automation from the Huazhong University of Science and Technology, Wuhan, China, in 2009, and the Ph.D. degree in mechatronics from the Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China, in 2016. From 2016 to 2018, he was a Postdoctoral Fellow with Nankai University, Tianjin, China, where he is currently an Associate Professor with the Institute of Robotics and Automatic Information Systems. In recent years, he has combined artificial intelligence algorithms with the motion control of bionic robots to explore the application of deep reinforcement learning in the motion control of bionic robots. At the same time, he has actively applied the deep reinforcement learning to robot game. At present, he has published more than 40 papers in important academic journals and conferences.

Speech Title: Gait Generation and Motion Control for Snake Robots.

Abstract: Snake robots are composed of multiple modules in series, which can generate many gaits, therefore, they have a strong ability to adapt to a variety of environments. This presentation firstly introduces the automatic gait generation method of planar snake robots based on fiber bundle theory and three-dimensional gait generation method based on curve for 3D snake robots. Then, the algorithm based on deep reinforcement learning is introduced for the problem of arbitrary path tracking of planar snake robots. Finally, an adaptive motion control method based on radius estimation is presented for the tree-climbing task of 3D snake robots and the future development is discussed.

Yinlong Zhang, Associate Professor

Shenyang Institute of Automation, Chinese Academy of Sciences (China)

Biography: Dr. Yinlong Zhang received his Ph. D. in control theory and control engineering from University of Chinese Academy of Sciences in 2019.  From 2016 to 2017, he was a visiting scholar at University of Tennessee, Knoxville. He is currently an Associate Professor at Shenyang Institute of Automation, Chinese Academy of Sciences. His research interests include intelligent robotics, multi-modal perception, computer vision, and visual surveillance for industrial safety & security. He has served as the Associate Editor of InderScience IJSISE and co-chair of the International Conference on Social Robotics in 2019. He has published over 60 academic papers, including the journal papers such as IEEE JAS, JBHI, TIM, RAS, and conference papers such as ICRA, IROS.

Speech Title：Automatic Guided Vehicle Navigation and Safety Manipulation in Digital Workshops

Abstract: An accurate and globally consistent navigation with safety manipulation is crucial for automatic guided vehicles (AGVs) in digital workshops. The light-weight multi-modal sensing (e.g., RGB-D camera, inertial measurement unit, QR sensor) is a promising solution for AGV navigation and safety manipulation. However, the existing sensing system have the inherent limitations, including long-term drift, tracking failures in textureless environments, lack of absolute references, failures in obstacle detection and relative depth estimation, unreasonable safety manipulations. In this talk, I will introduce the developed industrial AGV with the hybrid sensing modalities for vehicle navigation with globally consistent performance during AGV running and docking. Afterwards, I will introduce the safety-aware manipulation strategy for detecting the obstacles ahead, estimating the relative depth, and implementing the gradient operation. The challenges will be discussed at the end when we take into account the cybersecurity.

Changhong Cao, Assistant Professor

McGill University (Canada)

Biography: Dr. Changhong Cao is an Assistant Professor and the principal investigator of McGill Nanofactory in the Department of Mechanical Engineering at McGill University. He received his Ph.D. in Mechanical Engineering from the University of Toronto and worked as a postdoctoral fellow in the Department of Mechanical Engineering at MIT before joining McGill. His expertise includes experimental nano-mechanics studies of advanced structures, 2D materials, transfer printing technologies and 2D/3D printing of functional materials. He is the leading author in publications on prestigious journals including Science Advances, ACS Nano, Nano Letters, etc. In addition, he is the recipient of Young Scientist Award from Microsystem and Nanoengineering, Best Author Award from International Journal of Extreme Manufacturing and Young Leaders award from The Minerals Metals and Materials Society (TMS).

Speech Title: Micro Transfer Printing Technologies for the Manipulation of micro-LEDs

Abstract: Continued advances in engineering technologies demand novel manufacturing approaches to accelerate the transition of lab-scale inventions to the marketplace. μLED-based devices, such as ultrahigh-resolution televisions, augmented/virtual reality (AR/VR) glasses, and epidermal patches, hold promise for mainstream adoption due to their superior thermal and mechanical stability and exceptional electrical and optical properties (e.g., contrast ratio, brightness, response time, and power efficiency). However, these state-of-the-art products face high production costs, hindering mass commercialization. This is due to error-prone processes, complex manufacturing systems, and low production yields. Additionally, the thermal and chemical vulnerability of polymer materials typically used in circuit boards for hosting μLEDs prevents direct fabrication of μLEDs using conventional high-temperature processes. To overcome these limitations, μLEDs must be transfer-printed from their growth substrate to targeted places. Due to the small size of μLEDs, manipulating them in a controlled manner is challenging, as surface forces dominate over gravity at this scale. In this talk, I will introduce several transfer printing mechanisms that we have developed or are currently developing to address the manufacturing challenge of manipulating μLEDs. These innovations aim to enhance the efficiency, accuracy, and scalability of μLED production, paving the way for their widespread commercial use.