Course Overview
Course Title: Sustainable Ocean Intelligent Autonomous Monitoring
Relevant SDGs: Goal 14: Conserve and sustainably use the oceans, seas and marine resources
Credit(s): 2 credits
Course Description:
This course focuses on the theme of "protection and sustainable utilization of oceans and marine resources to promote sustainable development". The course adopts a combination of theory and practice to introduce related technologies and typical applications of ocean intelligent autonomous monitoring. Typically, the course includes unmanned surface vehicle(USV),unmanned aerial vehicle(UAV), autonomous underwater vehicle(AUV), and related algorithms for data processing. After successfully completing this course, students are able to:
- have a comprehensive and preliminary understanding of the field of sustainable ocean intelligence autonomous monitoring.
- understand and master the overall architecture and key technologies of the three important autonomous systems of USV, UAV, and AUV.
- implement basic ocean intelligent autonomous monitoring system with programming software.
What skills will students get?
- Understand the meaning of autonomous monitoring of ocean intelligence, explain the key technologies of autonomous systems such as unmanned surface vehicle(USV),unmanned aerial vehicle(UAV), autonomous underwater vehicle(AUV).
- Exploit unmanned system technology to analyze and solve practical problems of sustainable ocean intelligent autonomous monitoring.
- Understand the basic algorithms of intelligent autonomous system.
Mode of Teaching
Lectures & Discussion & Exercises & Project demos
Grading
Lectures 24h, exercise sessions 8 h, independent work 30 h. Students are awarded 2cr for completing the course.
- Attendance: 30%
- Group presentation: 70%
Course-specific Restrictions
Students from all study programs are welcome, and thus no formal requirements are set. Students with no background in engineering are encouraged to glance through, e.g., knowledge of signals and systems, estimation theory, and the excellent material of Elements of AI.
Class Schedule
Week |
Date |
Week Day |
Time
(UTC+8)
|
Topic |
|
Teaching mode |
Instructor in charge |
|
19/06 |
Monday |
15:00-17:00 |
Background of ocean intelligent autonomous monitoring |
2 |
Lecture |
Zhihuan Hu Rui Gao |
|
21/06 |
Wednesday |
15:00-17:00 |
Machine learning algorithms for intelligent autonomous monitoring
|
2 |
Lecture& Ice breaker |
AlexJung Tian Yu Rui Gao |
|
23/06 |
Friday |
15:00-17:00 |
2 |
Lecture& Exercise |
||
|
26/06 |
Monday |
15:00-17:00 |
2 |
Lecture& Exercise |
||
|
28/06 |
Wednesday |
15:00-17:00 |
2 |
Lecture& Exercise |
||
|
30/06 |
Friday |
15:00-17:00 |
2 |
Lecture& Exercise |
||
|
03/07 |
Monday |
15:00-17:00 |
Autonomous underwater vehicle (AUV) |
2 |
Lecture |
Fabio Ruggiero |
|
05/07 |
Wednesday |
15:00-17:00 |
2 |
Lecture |
||
|
07/07 |
Friday |
15:00-17:00 |
Unmanned aerial vehicle (UAV) |
2 |
Lecture |
Fabio Ruggiero |
|
10/07 |
Monday |
15:00-17:00 |
Unmanned aerial vehicle (UAV) |
2 |
Lecture |
Roland Siegwart |
|
12/07 |
Wednesday |
15:00-17:00 |
Path-planning algorithms for Autonomy |
2 |
Lecture& Exercise |
Howard Li |
|
14/07 |
Friday |
15:00-17:00 |
2 |
Lecture& Exercise |
||
|
17/07 |
Monday |
15:00-17:00 |
Unmanned aerial vehicle (UAV) |
2 |
Lecture |
Fabio Ruggiero |
|
20/07 |
Wednesday |
15:00-18:00 |
Project demos of sustainable ocean intelligent autonomous monitoring |
3 |
Lecture |
Rui Gao Jian Wang |
|
21/07 |
Friday |
15:00-18:00 |
Project demos of sustainable ocean intelligent autonomous monitoring |
3 |
Lecture |
Rui Gao Jian Wang |
Total |
32 |
|
Instructors
Rui Gao
Jian Wang
Alex Jung
Fabio Ruggiero
Roland Siegwart
Howard Li
Course Contact
GAO Rui: rgao@sjtu.edu.cn