Courses Offered

COMP3356 Robotics

2025-26

Instructor(s):

Pan Jia

(Class A)

No. of credit(s):

Recommended Learning Hours:

Lecture:

39.0

Pre-requisite(s):

MATH1013 or MATH1853 or MATH2014; and COMP2121 or SDST2601 or STAT2601; and COMP2118 or COMP2119 or FITE2000

Co-requisite(s):

Mutually exclusive with:

Remarks:

Course Learning Outcomes

1.	[1] Understand the motivations and principles for building autonomous robotic system based on sensory perception, control principles, and AI algorithms; and how robotics relates to the broader field of artificial intelligence
2.	[2] Formulate problems associated with domain specific data (e.g., obstacle avoidance and robotic arm manipulation) in terms of abstract models of robotics and AI algorithms
3.	[3] Implement solutions to robotics problems using tools such as Matlab, apply numerical optimization and machine learning algorithms

Mapping from Course Learning Outcomes to Programme Learning Outcomes
	PLO a	PLO c	PLO j
CLO 1	T		T
CLO 2	T	T
CLO 3	T	T

T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to here.

Syllabus

Calendar Entry:
This course provides an introduction to mathematics and algorithms underneath state-of-the-art robotic systems. The majority of these techniques are heavily based on probabilistic reasoning and optimization – two areas with wide applicability in modern AI. We will also cover some basic knowledge about robotics, namely geometry, kinematics, dynamics, control of a robot, as well as the mathematical tools required to describe the spatial motion of a robot will be presented. In addition, we will cover perception, planning, and learning for a robotic system, with the obstacle avoidance and robotic arm manipulation as typical examples. Note: The focus of the course is on mathematics and algorithms; we will not study mechanical or electrical design of robots.

Detailed Description:

Geometry and Mechanics	Mapped to CLOs
Principles of robotics	1
Transformation, robot state representation, configuration space	1, 2
Kinematics, dynamics and basic control	1, 2
Motion planning	Mapped to CLOs
Search for a path	2, 3
Trajectory optimization	2, 3
Inverse kinematics	2, 3
Perception	Mapped to CLOs
Point clouds	2, 3
Pose estimation	2, 3
Multi-view geometry	2, 3
Advanced topics and applications	Mapped to CLOs
Multiple-robot system	2, 3
Applications	1, 2

Assessment:
Continuous Assessment: 50%
Written Examination: 50%

Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)

Courses Offered

COMP3356 Robotics

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