 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | ROAS 6000K |
| DESCRIPTION | This course provides a comprehensive introduction to soft robotics, focusing on the design, fabrication, and application of compliant and flexible robots. Students will explore the fundamental principles of soft materials, actuation methods, and sensing technologies that enable soft robots to interact safely with complex, unstructured environments. It covers key topics including material selection, mechanical modeling, control strategies, and manufacturing techniques. Through detailed case studies, students will examine how specific materials and design choices improve the functionality and efficiency of these robots for applications in healthcare and exploration. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6760) | We 09:00AM - 11:50AM | Rm 202, E1 | YASA, Oncay | 20 | 5 | 15 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | ROAS 6000L |
| DESCRIPTION | Formal methods originate from theoretical computer science and have been seamlessly integrated with dynamical systems. At its core, formal methods involve formulating specifications to form proof obligations, verifying that the systems indeed meet their specifications via algorithmic proof search, and designing systems to meet those obligations. This course bridges fundamental gaps between formal methods and control theory. It introduces fundamental theories and techniques of formal methods that apply broadly to various dynamical systems, such as robots, autonomous systems and cyber physical systems. Particularly, the following topics will be covered: symbolic system modeling, regular and omega-regular properties, linear temporal logic, model checking, system simulation and abstraction, game theoretic control synthesis and cutting-edge engineering applications. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6155) | Mo 09:00AM - 11:50AM | Rm 101, W2 | JI, Yiding | 20 | 10 | 10 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | ROAS 6000M |
| DESCRIPTION | Learning about the core principles and latest developments in Robotics is crucial for nurturing innovative students in this field. This course provides a comprehensive overview of the core concepts in robotics. Students will mainly explore the principles of robot kinematics, dynamics, planning and control. In addition, some latest advancements in robotics integrated with artificial intelligence will also be discussed, such as VLA and robot foundation models. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6156) | We 03:00PM - 05:50PM | Rm 222, W1 | NIE, Qiang | 30 | 11 | 19 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | ROAS 6000J |
| DESCRIPTION | This course explores the forefront of computer vision through the lens of novel neural 3D representations. Students will investigate advanced techniques that leverage deep learning to enhance the understanding and interpretation of 3D data. Key topics include the development and application of innovative neural architectures for processing point clouds, voxel grids, and implicit surfaces, as well as the integration of these representations into real-world applications such as augmented reality, autonomous navigation, and robotics. Through a blend of theoretical insights and practical projects, students will engage with state-of the-art methodologies and contribute to ongoing research in the field. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6761) | Mo 07:00PM - 09:50PM | Rm 201, W1 | SONG, Jie | 20 | 11 | 9 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | ROAS 6000D |
| DESCRIPTION | This course introduces the essential fundamentals, including modeling, sensing, signal transmission and conversion, actuation, control, simulation, and implementation technologies used within the mechatronics design for robots and autonomous systems. It will give a holistic view of advanced automation technologies in industrial applications, taking electric vehicles and robots as examples. Also, this course will provide the essential skills to design intelligent mechatronics systems, and students will be allocated Arduino and STM32 development kits to participate in mechatronics design in the course project. Through this course, students can enhance their understanding of the cross-disciplinary integration and systematic optimization of mechatronics systems involving the knowledge of mechanics, electronics, control engineering, and computer science. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6157) | Th 09:00AM - 11:50AM | Rm 201, E1 | ZHAO, Hang | 40 | 35 | 5 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | ROAS 6000C |
| DESCRIPTION | This course introduces the advanced methodologies in the context of motion planning and control for robotics and autonomous systems. Various methodologies are introduced, including search-based methods, grid-based methods, sampling-based methods, optimization-based methods, learning-based methods, etc. In general, this course covers modern approaches, deep theory, and good practice envisions. In addition to the fundamental knowledge in motion planning and control, the students will also have the opportunity to discover and learn cutting-edge methodologies in the related field, aligning with the substantial developments in robotics, autonomous driving, UAVs, etc. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6158) | Fr 01:30PM - 04:20PM | Rm 101, W4 | MA, Jun | 48 | 48 | 0 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | ROAS 6000G |
| DESCRIPTION | This course will present how to utilize many advanced learning techniques and modules to analyze and interpret diverse medical image modalities (such as ultrasound, CT, MRI, X-ray, and so on) in recent years. The techniques to be covered include supervised learning, video understanding, multi-modal learning, transformer, self supervised learning, semi-supervised learning, domain adaptation, generative models, large models, and so on. The course will cover an overview of medical image modalities, traditional medical image processing methods, deep learning techniques and their applications in medical image analysis, and advanced data-efficient learning on medical imaging. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6762) | Tu 03:00PM - 05:50PM | Rm 201, W2 | ZHU, Lei | 40 | 23 | 17 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| EXCLUSION | INTR 5260 |
| CO-LIST WITH | INTR 5260 |
| DESCRIPTION | The course will cover a wide range of engineering psychology topics as well as how the research in these directions can affect policies and regulations in vehicle design and surface transportation. The students will gain an understanding of the characteristics and limitations of human beings from engineering psychology perspectives of view and how the design of traffic control devices, the roadway, the in-vehicle devices, regulations and traffic rules can be affected by the research in these directions. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6160) | We 09:00AM - 11:50AM | TBA | HE, Dengbo | 15 | 6 | 9 | 0 | The classroom is W1-521H. |
| VECTOR | [0-1-0:0] |
|---|---|
| DESCRIPTION | Seminar topics presented by students, faculty and guest speakers. Students are expected to attend regularly and demonstrate proficiency in presentation in accordance with the program requirements. Graded P or F. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| T01 (6162) | Mo 04:30PM - 05:20PM | Rm 101, E1 | NIE, Qiang | 100 | 100 | 0 | 0 |
| VECTOR | 1 credit |
|---|---|
| DESCRIPTION | An independent study on selected topics carried out under the supervision of a faculty member. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6779) | TBA | TBA | TBA | 50 | 9 | 41 | 0 |
| DESCRIPTION | Master's thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6020) | TBA | No room required | TBA | 80 | 58 | 22 | 0 |
| DESCRIPTION | Original and independent doctoral thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6022) | TBA | No room required | TBA | 120 | 32 | 88 | 0 |