This course serves as a bridge between calculus and analytics, giving students rigorous training in logical thinking. The course content is based on the strict topology of real numbers. Students will have a rigorous and mathematically complete systematic learning of limits, continuity, differentiability, Riemann integrability, and function approximation of functions. Through this course, engineering students can complete the general shortcomings of engineering mathematics—”knowing but not knowing why” on the one hand, and cybernetics, optimization theory, mathematical modeling, probability and statistics, artificial intelligence on the other hand.
Bachelor of Communication, Shanghai Jiaotong University, 1982;
Master of Shanghai Jiaotong University in 1985;
Ph.D., Princeton University, 1991;
Doctor of Applied Mathematics, Professor of the Hong Kong University of Science and Technology.
This course is an entry-level course in the field of robotics. It begins with the language describing robot kinematics, then introduces kinematics, dynamics, and finally trajectory planning, with the goal of learning practicality, combining theory and practice, and judging foundation through multi-node assessment. To achieve the unity of what we have learned. This course adopts “theoretical concessions, practice first,” aiming to establish a good engineering awareness and cultivate its ability to create, integrate, and cooperate.
In 2013, he graduated from Harbin Institute of Technology with a doctoral degree. In the same year, he joined Dongguan Liqun Automation Technology Co., Ltd. in robot research and development.
Model-based design is a methodology that uses mathematics and visualization methods to solve problems. The advent of this engineering methodology has brought engineering and research out of the lab and into the office setting. Through the establishment of equipment models, design controllers, integrated simulation, and systems testing and verification, the four basic steps enable the realization of projects such as mobile control, industrial automation, aerospace, and automobiles by incorporating processing systems and communication systems quickly and efficiently. Unlike traditional methods, which involve complex software structure and lengthy code, model-based design uses pre-defined continuous or discrete module building models. Combined with the simulation tool, the built model can be directly used for rapid prototype testing, software test verification, and even use the hardware-in-the-loop simulation method to quickly and effectively check the dynamic system effect. In order to enable engineers and researchers to methodologically design their systems in their respective fields, this course teaches basic concepts, methods of implementation, and their application in robotics-related fields.
Dr. Zhang Yanliang
Robotics expert, vice president, and chief scientist of Dongguan Songshan Lake TechX Institute. He is the global strategic development manager of robotics and automation systems at MathWorks, USA, and the first product leader of the Robotics System Toolbox. He received his bachelor’s and doctorate degrees from Nanyang Technological University in Singapore and has worked on robot system development at the University of Toronto, Canada. Professor Zhang is also an independent founder of the MATLAB Chinese Forum.
Original MathWorks technical support, currently an assistant researcher at Dongguan Songshan Lake TechX Institute and focuses on process application and optimization based on model design. He is responsible for education course and product development, personnel training, and corporate consulting.
Famous French Scholar, G. Monge, successfully introduced calculus into mechanical design and engineering at the end of the 18th century. Through approximation and linearization, many engineering problems can finally be converted into European-style optimization problems. Calculus provides the simplest and most effective tool for the analysis and solution of these problems and has been widely used. In the past thirty years, however, many new problems emerging in the fields of robotics, control, agency design, and manufacturing automation cannot be simply described, analyzed, and solved in Euclidean space. The key to solving this kind of problem lies in breaking the limitation of Euclidean space and introducing a class of generalized spaces with similar properties.
Around these issues, Gauss, Reimann, Poincare, S. Lie, and others have worked for more than one hundred years to establish the concept of differential manifolds and Lie groups, and to develop manifolds and the calculus of Lie groups. Since then, it has created modern differential geometry and has become an important branch of modern mathematics. In the past two decades, the combination of modern differential geometry and cutting-edge issues in the fields of robotics, robotic operation, nonlinear control, and mechanical design has achieved unprecedented breakthroughs and attracted widespread attention from the engineering community. In order to enable the majority of engineering and scientific researchers to understand and master modern differential geometry and its application in the frontier fields, this course will teach the basic knowledge of modern differential geometry and its applications and prospects in robotics, institutional design, and manufacturing automation.
Professor Harald Loewe
Dr. Harald Loewe received a bachelor’s and doctorate degree in Mathematics from the University of Technology, Baunschweig, Germany. Since gaining his habilitation in 2001, Dr. Harald Loewe has taught at the Institute of Computational Mathematics at his alma mater’s department of mathematics. At present, he is committed to cooperative mathematics projects between various departments. His research direction focuses on geometry and its applications.
Professor Li Zexiang
Born in Hunan, China, Professor Li received his bachelor’s degree in Electrical Engineering and Economics from Carnegie Mellon University, a master’s degree in Mathematics from the University of California, Berkeley, and a doctorate in Electrical Engineering and Computer Science. He has been engaged in scientific research and teaching work at the MIT Artificial Intelligence Laboratory and the New York University Robotics Laboratory. Professor Li Zexiang currently teaches at the Department of Electrical and Computer Engineering at the Hong Kong University of Science and Technology (HKUST), and serves as Director of the Center for Automation Technology. Together with his students and colleagues, he established a succession of technology companies including Gushui, Dajiang Innovation, and Liqun Automation.
Professor Frank C. Park
Professor Park received a bachelor’s degree in Electrical Engineering from the Massachusetts Institute of Technology and a doctorate in applied mathematics from Harvard University. His research directions include robotics, trajectory planning and control, and vision and image processing. Professor Park is an IEEE fellow and currently Editor-in-Chief of IEEE Transactions on Robotics.
Special Guest Speakers:
Professor Dinesh Manocha, University of North Carolina at Chapel Hill
Professor Shen Wei, HKUST
Professor Pan Jia, City University of Hong Kong
Dr. Zhang Yanliang, Songshan Lake TechX Institute