 |
| 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 (6124) | Fr 09:00AM - 11:50AM | Rm 149, E1 | MA, Jun | 45 | 31 | 14 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This course covers the concept of information process for robotics, i.e. to understand, estimate and predict based on sensor data. Basic knowledge of machine learning will be taught to tackle robotic perception problems. Target applications include IoT, self-driving vehicle, UAV and service robot. The emphases are on hands-on experience in real projects with real-time algorithms. Applications of provided libraries or tools are expected. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6126) | 22-JAN-2024 - 14-MAR-2024 Mo 07:30PM - 10:20PM | Rm 147, E1 | LIU, Ming | 45 | 5 | 40 | 0 | |
| 15-MAR-2024 - 10-MAY-2024 Mo 07:30PM - 10:20PM | Rm 201, W1 | LIU, Ming |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This course introduces fundamental theories in formal methods, and how to integrate formal methods, control theory, and artificial intelligence (AI) to develop autonomous, reactive, and trustworthy robotic systems. Formal methods are concerned with generating precise, non-ambiguous task specifications or constraints that an autonomous agent (not limited to robots) is expected to satisfy. The major three topics covered in the course are formal specification, formal verification and formal synthesis. The first part includes automata theory and temporal logics, which provide a mathematical paradigm to characterize tasks of autonomous systems. The second part is mostly concerned with probabilistic planning, model-based and model-free reinforcement learning methods with formal specifications, as well as game-theoretic planning in sequential decision making. The third part introduces bisimulation and abstraction-based methods, reachability analysis and safety verification for continuous dynamical systems, and game-theoretic control design for games. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6127) | 22-JAN-2024 - 14-MAR-2024 TuTh 10:30AM - 11:50AM | Rm 147, E1 | JI, Yiding | 30 | 8 | 22 | 0 | |
| 15-MAR-2024 - 10-MAY-2024 TuTh 10:30AM - 11:50AM | Rm 201, E4 | JI, Yiding |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This course will present many advanced learning techniques and modules (multi-modal learning, self-supervised learning, transformer, semi-supervised learning, domain adaptation) in recent years. Moreover, I will also focus on presenting how to utilize these learning algorithms for addressing diverse medical imaging tasks on different medical image modalities, such as ultrasound, CT, MRI, and so on. By taking this course, the students can learn the advanced learning techniques in recent years and have a deeper understanding of medical image analysis. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6128) | 22-JAN-2024 - 14-MAR-2024 Mo 03:00PM - 05:50PM | Rm 101, E1 | ZHU, Lei | 30 | 8 | 22 | 0 | |
| 15-MAR-2024 - 10-MAY-2024 Mo 03:00PM - 05:50PM | Rm 202, W2 | ZHU, Lei |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | Materials play a pivotal role in the development of robotics by serving as the building blocks that determine the capabilities, durability, and versatility of these intelligent machines. Understanding the properties and applications of different materials is fundamental to pushing the boundaries of robotics, enabling the creation of robots that excel in precision, strength, flexibility, and even biocompatibility. This course provides a comprehensive understanding on smart materials that are used to build nano, micro, and soft robots. It covers principles to design such robots by considering their scales, materials properties, operation environments, and actuation modalities, e.g., acoustic, electric, magnetic, and biological actuation. It also features different manufacturing techniques used to create these robots, including molding, lithography, and 3D printing, while emphasizing material-specific considerations. Finally, it examines real-world cases where specific materials have been instrumental in enhancing the performance, durability, and efficiency of robotic platforms. Overall, exploring the diverse range of smart materials available for robotics unveils a world of possibilities, driving innovation and pushing the frontiers of what robots can achieve in different fields, from manufacturing and healthcare to exploration and beyond. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6277) | We 09:00AM - 11:50AM | Rm 150, E1 | YASA, Oncay | 30 | 5 | 25 | 0 | The instructor is Prof. Oncay Yasa. |
| 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 (6191) | Tu 03:00PM - 03:50PM | Rm 101, W1 | JI, Yiding | 85 | 72 | 13 | 0 |
| VECTOR | [1-3 credit(s)] |
|---|---|
| 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 (6369) | TBA | TBA | TBA | 10 | 1 | 9 | 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 (6130) | TBA | TBA | TBA | 70 | 25 | 45 | 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 (6131) | TBA | TBA | TBA | 60 | 24 | 36 | 0 |