Underwater Biomimetic Vehicle–Manipulator System and its Autonomous Operations
Shuo Wang, Professor, Ph.D.
Institute of Automation,Chinese Academy of Sciences
Underwater vehicle-manipulator systems are widely used in the field of civil and military applications.Anunderwater vehicle-manipulator system propelledby undulatory fins is introduced.The theoretical and technical foundations fordesign and control of such a novel underwater biomimetic vehicle-manipulator system (UBVMS)are focused on to meet the requirements of new generation of underwater robots with low noise, environmentalfriendliness, high motion stability, and high anti-disturbance performance.The methods on system design, 3-dimentional motion control, depthcontrol, course control, path planning and path-following control are presentedforthe UBVMS. The control schemes for autonomous operations such as approaching, grasping are proposed, and the pool experimental results are given. Finally themarine product graspingexperiments of theUBVMS in Underwater Robot Pocking Contest by NSFC are introduced.
Bio: Shuo Wang received thePh.D.degree from Institute of Automation of the Chinese Academy of Sciences in 2001. He is a professor with the state key laboratory of management and control for complex systems, Institute of Automation of the Chinese Academy of Sciences. He is also with Center for Excellent in Brain Science and Intelligence Technology,Chinese Academy of Sciences.His research interestsincludebiomimetic robot system, underwater vehicle-manipulator system and multi-robot systems. He serves as a committee member of ISO TC299, a program committee member of CCC, a technical committee member of ISOPE. He has published around 80 papers in refereed professional journals and international conference proceedings. He received National Natural Science Award Second Prize (2017), Beijing science and Technology Awards (2004, 2009, 2013).
Humanoid Robotics: Manipulation and Movement
Rong Xiong, Professor, Ph. D.
Humanoids are machines that have the form and function of humans, which is more acceptable in Human-Robot interaction and more adaptive to human’s environments and tools. This talk will introduce our work on humanoid robotics, including the legged motion technologies, and perception, cognition, learning and control to enable the robot intelligently manipulate dynamic object and move in large scale and dynamic environments for long term. Some technologies have been successfully applied to industrial applications.
Bio: Rong Xiong, PhD, Professor. She is the leader of the Robotics Laboratory at Institute of Cyber-Systems and Control, Zhejiang University, the co-director of ZJU-UTS Joint Center on Robotics Research, the expert member for key special project on intelligent robot of Ministry of science and technology, China, and the member of international trustee committee of RoboCup.
Her research interests include perception, learning and control for mobile robot, manipulator and humanoid robot. She conducted her group successfully develop two humanoid robots which can demonstrate table tennis rally with each other and against a human player, as well as quadruped running robot “Chitu”. She has successfully verified the techniques on mobile robots in industry applications and productions, such as patrol robot for substation, nature navigation AGV for factory and warehouse, automatic delivery robot in campus and etc. She has published more than 80 academic papers, been authorized 46 national invention patents and 1 USA invention patent.
Development of Key Technology for Human Cooperative Wearable robots and Its Applications
Zhijun Li, Professor, Ph. D.
Department of Automation, University of Science and Technology of China
The development of human cooperative robotic systems capable of sharing with humans the load of heavy tasks has been one of the primary objectives in robotics research. At present, in order to fulfil such an objective, a strong interest in the robotics community is collected by the so-called wearable robots, a class of robotics systems that are worn and directly controlled by the human operator. Wearable robots, together with powered orthoses that exploit robotic components and control strategies, can represent an immediate resource also for allowing humans to restore manipulation and/or walking functionalities. The present talks deals with wearable robotics systems capable of providing different levels of functional and/or operational augmentation to the human beings for specific functions or tasks. Prostheses, powered orthoses, and exoskeletons are described for upper limb, lower limb, and whole body structures. State-of-theart devices together with their functionalities and main components are presented for each class of wearable system. Critical design issues and open research aspects are reported.
Bio: Zhijun Li received the Ph.D. degree in mechatronics, Shanghai Jiao Tong University, P. R. China, in 2002. From 2003 to 2005, he was a postdoctoral fellow in Department of Mechanical Engineering and Intelligent systems, The University of Electro-Communications, Tokyo, Japan. From 2005 to 2006, he was a research fellow in the Department of Electrical and Computer Engineering, National University of Singapore, and Nanyang Technological University, Singapore. Since 2017, he is a Professor in Department of Automation, University of Science and Technology of China. He was supported by China National Ten-thousand Talents Program (China 2018), and received the prestigious award of National Distinguished Young Scholar (NSFC 2016), and Distinguished Young Scientist Award (CAA 2017), Best Associate Editor Award (IEEE SMC) Toshio Fukuda Best Mechatronics Award (ICARM 2017), etc.. From 2016, he has been the founders and Co-Chairs of Technical Committee on Bio-mechatronics and Bio-robotics Systems (IEEE SMC), and Technical Committee on Neuro-Robotics Systems (IEEE RAS). He is serving as an Editor-at-large of Journal of Intelligent & Robotic Systems, and Associate Editors of several IEEE Transactions. He was the founder of IEEE Conference on Advanced Robotics and Mechatronics (IEEE ARM). He was the General Chair and Program Chair of 2016 and 2017 IEEE Conference on Advanced Robotics and Mechatronics, respectively. Dr. Li’s current research interests include service robotics, teleoperation systems, nonlinear control, neural network optimization, etc.
Cross-Modal Perception for Human-Friendly Robotics
Tactile and visual modalities frequently occur in human-friendly robotics. Their matching problem is of highly interesting in many practical scenarios since it provides different properties about objects. In this paper, we investigate the active visual-tactile cross-modal matching problem which is formulated as retrieving the relevant sample in unlabeled gallery visual dataset in response to the tactile query sample. Such a problem exhibits a nontrivial challenge that there does not exist sample-to-sample pairing relation between tactile and visual modalities. To this end, we design a shared dictionary learning model which can simultaneously learn the projection subspace and the latent shared dictionary for the visual and tactile measurements. In addition, an optimization algorithm is developed to effectively solve the shared dictionary learning problem. Based on the obtained solution, the visual-tactile cross-modal matching algorithm can be easily developed. Finally, we perform experimental validations to show the effectiveness of the proposed visual-tactile cross-modal matching framework and method. In addition, we will present some other applications of cross-modal perception in robotics.
Bio: Huaping Liu received the Ph.D. degree from Tsinghua University, Beijing, China. He is an Associate Professor with the Department of Computer Science and Technology, Tsinghua University, Beijing, China. His current research interests include robotic perception and learning. Dr. Liu serves as an Associate Editor of some journals including the IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Industrial Informatics, IEEE Robotics and Automation Letters, Neurocomputing, Cognitive Computation, and some conferences including ICRA, IROS. He also served as Area Chair of Robotic Science and Systems(2018), Publicity Chair of WCCI(2020), Senior Program Member of IJCAI(2018), etc. He is the receipt of Andy Chi Best Paper Award of IEEE Trans. on Instrumentation and Measurements (2017).
Human-Centered Exoskeleton Systems for Rehabilitation Medicine
Hong Cheng, Professor, Ph. D.
Center for Robotics, University of Electronic Science and Technology of China
Recently, exoskeleton systems have been designed and developed to provide functional motion assistance to disabled and elderly people in daily activities. The difference between traditional robots and exoskeleton systems is that pilots play an important role in the aspect of exoskeleton design and usage. This talk will discuss key techniques of exoskeleton systems, which include ergonomics, multisensor based physical human-robot interaction, wearable computing, human intention estimation, multimodal interaction and cooperation. The related advances in UESTC exoskeletons will also be introduced in this talk, which includes reinforcement learning in pHRI and our exoskeleton systems, AIDER system for walking assistance and HUALEX system for human augmentation.
Bio: Hong Cheng is a full professor of University of Electronic Science and Technology of China (UESTC), school of Automation and Engineering. He serves as an executive director of the Center for Robotics since 2014. He was a visiting scholar at School of Computer Science, Carnegie Mellon University, USA from 2006 to 2009. Before this, he received his Ph.D degree in Pattern Recognition and Intelligent Systems from Xi’an Jiaotong University in 2003 and became an associate Professor of Xi’an Jiaotong University since 2005. He joined UESTC since 2010. His current research interests include machine learning in human robot hybrid systems. Prof. Cheng has over 100 academic publications including three books- “Digital Signal Processing (Tsinghua University Press, Sep. 2007)”, “Autonomous Intelligent Vehicles: Theory, Algorithms and Implementation (Springer, Dec. He served/is serving as a General Chair of VALSE 2015, Program Chair of CCPR 2016, and a General Chair for CCSR 2016. Now, he is a senior member of IEEE.
Development and Control of Walking-Aid Robot
Prof. Jian Huang
Huazhong University of Science and Technology
The mobility of elderly degrades with age, which affects not only their daily life, but also the life quality and causes dependence of other in their daily life. The walking-aid robot which applies robotic technologies can help the elderly to restore the ability of walking, get the chance of independent and improve the quality of their life, which are very important to the rehabilitation care system of forthcoming elderly society. Several walking-aid robots are developed and presented in this talk. In the motion control of these robots, recognizing the user’s walking intention plays an important role. To quantitatively describe the user’s walking intention, a concept called “intentional direction (ITD)” is proposed. Both the state model and the observation model of ITD are obtained by enumerating the possible walking modes and analyzing the relationship between the human–robot interaction force and the walking intention. The user’s walking intention can be online estimated using the filtering techniques. Based on the estimated intention, a new admittance motion control scheme is proposed for the walking-aid robot.
Bio: Jian Huang graduated from Huazhong University of Science and Technology (HUST), China in 1997 and received the Master of Engineering degree from HUST in 2000. He received his Ph.D from HUST in 2005. From 2006 to 2008, he was a postdoctoral researcher in the Department of Micro-Nano System Engineering and Department of Mechano-Informatics and Systems, Nagoya University, Japan. In 2015, he was a research fellow in Nagoya University supported by JSPS invitation fellowship. He is currently a full professor with the School of Automation, HUST. He is also a guest professor in Nagoya University of Japan and University Paris-Est Créteil (UPEC) of France. His main research interests include rehabilitation robot, robotic assembly, networked control systems and bioinformatics.
He is an IEEE Senior Member and has published more than 170 papers (including 16 research articles in several IEEE Transactions and more than 50 conference papers in many IEEE conferences). Currently he serves as the editor of ROBOMECH Journal – Springer.
He has got 12 authorized patents, the grand prize of science and technology award of China General Chamber of Commerce and was awarded golden medal at Geneva Inventions in 2017.