COMP3414 Experiential Learning on Artificial Intelligence and Robotics (2019-20 Spring Semester)

Host department: Department of Computer Science

Course coordinators: Dr. Kenneth K.Y. Wong (CS), Dr. Loretta Y.K. Choi (CS), Dr. C.K. Chui (CS)

About the course

This is a multidisciplinary experiential learning course designed for Engineering students to learn about artificial intelligence (AI) and robotics. Students will learn AI and robot related technical disciplines (such as machine vision, embedded system design, mechanical control, inertial navigation, human-computer interaction, etc.) through designing and building intelligent robots, and forming teams to participate in robotics competitions such as RoboMaster Robotics Competition and AI Driving Olympics, etc

Course coordinators
Dr. Y.K. Choi (Loretta)
Department of Computer Science
The University of Hong Kong
Dr. K.Y. Wong (Kenneth)
Department of Computer Science
The University of Hong Kong
Dr. C.K. Chui (Kit)
Department of Computer Science
The University of Hong Kong
Course learning outcomes

On successful completion of the course, students should be able to:

  1. Apply their engineering knowledge to design and build intelligent robots for specific purposes;
  2. Communicate with peers with regard to technical concepts verbally (via meetings and presentations), in writing (via reports) and in action (via demonstrations);
  3. Collaborate with peers from different disciplines/backgrounds and be a good team player;
  4. Overcome unforeseen problems, make informed decisions, and work under the constraints of limited time, human and financial resources.

To enroll in this course, students are required to:

  • Have at least four months of experience in the respective teams (i.e., RoboMaster Team or AI-DO Team) to familiarize themselves with the rules of the respective competitions and acquire a fundamental technical background in building and programming robots.
  • Have individual contribution to the technical aspect of the project work related to artificial intelligence and robotics.
Course assessment

This course has 100% continuous assessment arragement.

Assessment tasks should consist of

  • A1. Project proposal (Individual assessment, weighting: 5%)
  • A2. Project website with poster and project video (Team assessment, weighting: 25%)
  • A3. First and final presentation (Team assessment, weighting: 5%)
  • A4. Final project technical report (focus on individual contribution on the technical aspects of the project related to artificial intelligence and robotics (Individual assessment, weighting: 60%)
  • A5. Project exhibition (Team assessment, weighting: 5%)
Assessment tasks Supervisor Co-supervisor Other assessors (project exhibition)
Project proposal



Project website with poster and project video




First and final presentation



Final project report



Project exhibition


Enrollment procedure
  • Step 1. Find a supervisor and co-supervisor

    Students should identify a project supervisor and a co-supervisor. Both have to be a teaching staff in the Engineering Faculty. Students should discuss with the supervisor about the project objectives and scope and seek for supervisor's endorsement.

  • Step 2. Submit application

    Students should obtain endorsement from project supervisor and submit an application at least 1 week before the end of the add/drop period.
    Please refer to the application section for the required information for application.

  • Step 3. Review and approval

    The Course coordinator will review the application and notify students and the Project supervisor about the result by email.

  • Step 4. Course registration via HKU SIS

    Students should register for the course after receiving notification of approval of the application, in the same semester that the application being approved only.

    Please note that:

    - Course coordinator and project supervisor will NOT enroll students in the course.

    - Students must register for the course on their own via HKU SIS.

    - The course registration procedure must be completed by the end of the add/drop period.


Students from the same project team can submit one application for all team members.

Please submit the application at least 1 week before the end of the add/drop period.

By submitting the application, the team acknowledges that besides the course assessment requirements, there are required project deliverable from the course COMP3414 Experiential Learning on Artificial Intelligence and Robotics.

The project group shall submit timely by the end of the project or each year:

  • An individual project completion report from each student team member.
  • Media links:
    • Poster 
    • Project images
    • A short video (preferably around one minute)
    • Showcase at the Engineering InnoShow event – A showcase carnival that celebrates innovative Engineering student projects at the end of every semester.
Useful links