Sustainable marine environment intelligent monitoring

Course Overview

Course Title: Sustainable marine environment intelligent 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.

Academic Team

PI:

  • GAO Rui, Assistant Professor, rgao@sjtu.edu.cn
  • WANG Jian, Assistant Research Fellow, nsms_sjtu@sjtu.edu.cn

Collaborators:

  • Howard Li, University of New Brunswick, howard@unb.ca
  • Zhaobo Zheng, Honda Research Institute, zhaobo_zheng@honda-ri.com

What skills will students get?

  1. 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).
  2. Exploit unmanned system technology to analyze and solve practical problems of sustainable ocean intelligent autonomous monitoring.
  3. Understand the basic algorithms of intelligent autonomous system.

Mode of Teaching

Lectures & Discussion & Exercises & Project demos

Grading

  1. Attendance: 30%;
  2. Group Discussion: 30%;
  3. Final Group Presentation: 40%

Course-specific Restrictions

Basic knowledge of electrical engineering

Class Schedule

Week

Date 

Week Day

Time 

Topic

Credit hours

Teaching mode

(Lecture/Tutorial/Discussion)

Instructor in charge

 

23/06

Monday

 

12:00-12:45
12:50-13:35

 

13:40-14:25

14:30-15:15

Ice Break&Background of ocean intelligent autonomous monitoring

4

Lecture&Discussion

Rui Gao

Jian Wang

 

24/06

Tuesday

 

12:00-12:45
12:50-13:35

 

13:40-14:25

14:30-15:15

Machine learning algorithms for intelligent autonomous monitoring

4

Lecture&Discussion

 

Zhaobo Zheng
Rui Gao

 

 

25/06

Wednesday

 

12:00-12:45
12:50-13:35

 

13:40-14:25

14:30-15:15

Machine learning algorithms for intelligent autonomous monitoring

4

Lecture&Discussion

 

Zhaobo Zheng
Rui Gao

 

 

26/06

Thursday

 

12:00-12:45
12:50-13:35

 

13:40-14:25

14:30-15:15

Machine learning algorithms for intelligent autonomous monitoring

4

Lecture&Discussion

 

Zhaobo Zheng
Rui Gao

 

 

27/06

Friday

 

12:00-12:45
12:50-13:35

 

13:40-14:25

14:30-15:15

Unmanned aerial vehicle (UAV)

4

Lecture &Discussion

Howard Li

 

28/06

Saturday

 

12:00-12:45
12:50-13:35

 

13:40-14:25

14:30-15:15

Autonomous underwater vehicle (AUV)

4

Lecture &Discussion

Howard Li

 

29/06

Sunday

 

12:00-12:45
12:50-13:35

 

13:40-14:25

14:30-15:15

Autonomous underwater vehicle (AUV)

4

Lecture &Discussion

Howard Li

 

30/06

Monday

 

12:00-12:45
12:50-13:35

 

13:40-14:25

14:30-15:15

Project demos of sustainable ocean intelligent autonomous monitoring

4

Project Demonstration

Rui Gao

Jian Wang

Total

32

 

 

Instructors

GAO Rui
Rui Gao received the Doctor of Science (Tech.) degree in automation, systems and control engineering from Aalto University, Finland, in 2020. She was a Postdoctoral Researcher with the Department of Electrical Engineering and Automation, Aalto University in 2021. Since 2022, she is Assistant Professor at the School of Naval Architecture Ocean and Civil Engineering, Shanghai Jiao Tong University. Her research interests include autonomous systems, state estimation, and convex optimization.
WANG Jian
Jian Wang is Assistant Research Fellow at the School of Naval Architecture Ocean and Civil Engineering, Shanghai Jiao Tong University. He has published 15 related papers, applied for 4 invention patents and obtained 8 software Copyrights, and presided over a number of topics related to navigation control of USVs and cooperative control of USV formation. His research results "Test and verification technology and application of ship intelligent control System" won the first prize of Scientific and Technological Progress of the Chinese Society of Naval Architecture Engineering in 2021. His research interests include the design of Unmanned Surface Vehicle (USV) platform and the cooperative control of marine unmanned multi-agents.
Howard Li
Howard Li is a professor in the Department of Electrical and Computer Engineering, University of New Brunswick, Canada. He is a registered professional engineer in the Province of Ontario. He obtained his Ph.D. in Electrical and Computer Engineering and the Certificate in University Teaching from the University of Waterloo, Ontario. He received his certificate in Team Based Project Management from the School of Business, Queen’s University, Kingston, Ontario. He obtained his bachelor's degree in Electrical Engineering from Zhejiang University, China. Dr. Li is a board member of the IEEE SA Standards Board. He chairs the IEEE Charles Proteus Steinmetz Award committee, one of the highest technical recognitions given by the Institute of Electrical and Electronics Engineers professional society. He is honoured to chair the first autonomous robotics standard ever published by the IEEE, with over 100 group members from academia, industry, and government agencies from all continents. Dr. Li is a visiting professor of École Polytechnique Fédérale de Lausanne, Switzerland and Università di Pavia, Italy, etc. Before joining UNB, he was employed by Atlantis Systems International in the development of training systems for the F/A-18 Hornet fighter aircraft for the Boeing company, Canadian Forces, Royal Australian Air Force, and training systems for the Royal Danish Air Force. He has developed software and hardware for both civilian and military applications. Dr. Li’s research interests are UxVs (unmanned aerial vehicles, unmanned ground vehicles, unmanned underwater vehicles), motion planning, Simultaneous Localization And Mapping (SLAM), mechatronics, control systems, robotics, multi-agent systems, and artificial intelligence.
Zhaobo Zheng
Zhaobo Zheng is a senior scientist at Honda Research Institute USA, Inc (HRI) located in San Jose, California. His research mainly focuses on multimodal machine learning and human-computer interaction. At HRI, his research focuses on human state understanding in mobilities, such as driving style preference detection, workload estimation, and wellbeing predictions. He got his PhD in Mechanical Engineering from Vanderbilt University in 2021. At Vanderbilt, his research focused on pattern recognition and interaction design for individuals with Autism. Aspects of the dissertation include early detection of Autism, problem behavior prediction, and behavioral intervention games. He got his bachelor’s degree also in Mechanical Engineering, from Xi’an Jiaotong University in 2015. He exchanged at the University of Michigan, Dearborn in his senior year to study automobile engineering. Zhaobo serves on the organization committee of RO-MAN 2024.

Course Contact

GAO Rui, rgao@sjtu.edu.cn