This course covers the introduction to robotics and its applications in biomedical engineering including diagnosis, surgery, and medical simulation. Students will learn the classification of robot systems, forward and inverse kinematics associated to manipulator motion, robot design, control, sensing, and programming.

This course provides a theoretical and practical guidance on how to design parts to gain the maximum benefit from what additive manufacturing (AM) can offer. It begins by describing the main AM technologies and their respective advantages and disadvantages. It then examines strategic considerations in the context of designing for additive manufacturing (DfAM), such as designing to avoid anisotropy, designing to minimize print time, and post-processing, before discussing the economics of AM. The course then focuses on computational tools for design analysis and the optimization of AM parts, part consolidation, and tooling applications. Both designing for polymer AM and metal AM and its corresponding design guidelines will be provided. The main benefit of the course is its combined theoretical and practical approach, which provides directly applicable, “hands-on” information and insights to help students adopt AM in their daily practice.

This course is designed to equip students with the knowledge of modern control systems analysis and design, and skills of control theory for practical applications of industrial automation systems. It will cover the following topics: state space representation, realizability, stability, controllability, observability; linear control design methods including pole placement, observer, asymptotic tracking and disturbance rejection, internal model design, and feedforward design; introduction to nonlinear systems. Various examples, e.g., robot control, satellite’s attitude control and servomechanism are included.

The contents of this course include overview of smart materials technology, characteristics of smart materials such as piezoelectric materials, magnetorheological fluids, and shape memory alloys. It covers smart actuators and sensors; structural modelling and design; dynamics and control for smart structures; integrated system analysis; and applications in buildings, automobiles, trains, robots, manufacturing systems, and medical devices.

This is a foundational course, designed to provide students with an in-depth understanding of essential robotics principles and systems. It also provides students with the understanding of the ethical, societal, and environmental impacts of robotics technologies and systems. This course is indispensable for students keen on advanced studies or careers in robotics.

The course will concentrate on fundamental technical concepts of robotics, including robotic kinematics, dynamics, sensors, actuators, robotic programming, basic applications of AI and machine learning, robot ethics and impacts.

The primary objective of this course is to equip students with the foundational and practical knowledge necessary for executing real-world robotic systems. It aims to help students understand the needs and requirements of robotic experiments and applications, teaching them about various hardware components, software architectures, and development tools.

The course covers the following main topics: foundations of robotic systems, robot electronics, sensors and actuators in robotics, robot networking and data communication, introduction to robot operating system (ROS), advanced ROS programming, interfacing with sensors and actuators, robot sensing and control, measurement devices for robot performance, robot experiment setup, operations in robot experiments.

The course aims to provide students with an in-depth understanding of autonomous robots principles and applications. This course is particularly relevant for students targeting careers in robotics, AI, or related fields, given the growing integration of autonomous mobile robots across various industries.

The course covers key areas such as fundamentals of autonomous mobile robots, robot perception, robot localization, mapping, path planning, robot control, multi-robot systems, robot navigation, robot communication, autonomous aerial robots, autonomous ground robots, future of autonomous robots.

The goal of this course is to introduce various types of actuators and mechanisms that would enable robots to perform a multitude of tasks within manipulation. This course will teach both the fundamental working principles of different mechanisms and actuators and the practical design and implementation of such devices.

This course will include the following main topics: different types of actuators (including motors, pneumatics, hydraulics, smart materials), transmission mechanisms (including cable-driven systems, gears and belt drives), parallel mechanisms, closed-loop mechanisms, robot grippers and hands, vacuum grippers, and flexible and soft mechanisms.

This course aims to systematically introduce the fundamental knowledge of emerging and interdisciplinary research fields-micro-/nanorobotics and soft robotics. Through a combination of theoretical learning and practical operations, students will gain a comprehensive understanding of the historical development and state-of-the-art of this field, as well as acquire skills related to designing and manufacturing micro-nano and soft robots. The main topics covered in this course are as follows: historical development and basic principles of micro-nano and soft robots; structural design, material selection, actuation methods, and motion control of micro-nano and soft robots; applications of micro-nano and soft robots in fields such as biomedicine and engineering. Throughout the course, students will not only grasp the fundamental concepts of small-scale robotics and soft robotics, but also learn how to design and construct these robots firsthand. The comprehensive learning experience provided by this course can foster students’ scientific and technological innovation thinking, as well as enhance their practical skills, providing a solid foundation for their future research and/or work in related fields.

The main goal of this course is to comprehensively introduce the principles and technical methods used in modern robot learning and control techniques. This course will not only teach students how to use data-driven methods to design, control and optimize robot systems through theoretical learning and practical operations, but will also delve into relevant basic knowledge and skills, to ensure that students can fully master and apply these important skills. Practical assignments will give students the opportunity to implement these techniques on simulated and real robot systems, providing them with a comprehensive educational experience.

his course will include the following main topics: robot kinematics and dynamics, optimal control, reinforcement learning in robots, teaching learning, embodied intelligent learning, trajectory optimization and robot perception, human-robot interactive and collaborative learning used in robot control and perception, machine learning, etc.

This is a cutting-edge course as a response to the rapid technological advancements and increasing industry demands in this domain. This course aims to provide students with a comprehensive understanding of theoretical foundations and practical implementations of unmanned systems, for example unmanned aerial vehicle (UAV), remotely operated vehicle (ROV), autonomous driving vehicles. The course is specifically designed to expose students to the challenges and opportunities present in the design, control, and application of unmanned systems, thereby preparing them for impactful careers in this rapidly evolving field.

The course will cover essential technical elements including introduction to unmanned systems, system architecture, autonomous control, sensors for unmanned systems, sensor fusion, path planning, navigation systems, AI for unmanned systems, unmanned aerial vehicles, underwater and surface vehicles, autonomous driving vehicles, future challenges and opportunities.

Robotics is a rapidly evolving field, with new technologies emerging every day. The course offers students timely and updated coverage of a wide range of topics relevant to robotics tapping on the latest and diverse range of developments in the repertoire of the subject area, such as the delivery of a measured collation of advanced and unconventional robotics designs applied to real problems of a diverse nature and which are not easily and directly available from standard literature. The nature of the course allows the flexibility for recent topics, problems and solutions to be shared with the students.

Topics might include but not limited to cutting-edge technologies in robotics platforms, unmanned systems, modeling and control, communications systems, vision systems, sensing and information processing, navigation and path planning, information fusion, multi-agent robotics systems, mission management, machine intelligence, artificial intelligence, human-machine collaboration, and digital twins systems, as well as innovative application case studies.

This course acknowledges the growing role of high technologies such as robotics in various sectors and the increasing demand for innovators and entrepreneurs in this dynamic field. This course aims to bridge the gap between technical expertise in the technical field and the entrepreneurial skills needed to bring innovative ideas to market.

The course will cover key aspects of entrepreneurship tailored specifically to the robotics sector. Topics will include: introduction to advanced technologies, identifying market opportunities in robotics, understanding the process of commercializing a robotics product, company setup and navigating the legal and regulatory landscape, team formation, product identification, project management, Business Model for robotics, sales and marketing, account and finance, budgeting and funding, business plan and investment deck, and final presentation for a start-up. Practical aspects of starting and running a start-up, such as team building, fundraising, and pitching to investors, will also be covered.

In this course, each student will conduct research project on a topic within the robotics areas of study. Faculty members from the department will supervise the project. Upon completion, students must submit a written report and deliver an oral presentation for performance evaluation.