Undergraduate Programme and Module Handbook 2026-2027
Module COMP4241: Robotics & Autonomous Systems
Department: Computer Science
COMP4241: Robotics & Autonomous Systems
| Type | Open | Level | 4 | Credits | 20 | Availability | Available in 2026/2027 | Module Cap | Location | Durham |
|---|
Prerequisites
- COMP3667 Reinforcement Learning
Corequisites
- None
Excluded Combination of Modules
- None
Aims
- To understand fundamental knowledge and techniques in real-world robotic systems.
- Learning how to design motion planning and control systems for mobile robots.
- Developing intelligent multi-robot systems for complex tasks.
Content
- Introduction to robotic systems
- Actuators and sensors
- Modelling and dynamics of mobile robots
- Open-loop and closed-loop controller design
- Introduction to Advanced control systems
- Motion planning and decision making
- Multi-robot systems and swarm intelligence
Learning Outcomes
Subject-specific Knowledge:
- On completion of the module, students will be able to:
- Explain the key features of real-world robotic systems.
- Propose and analyse state-of-the-art path planning and control algorithms.
- Explain how to apply advanced robotic technologies to real-world problems.
Subject-specific Skills:
- On completion of the module, students will be able to:
- Use modern programming libraries to design, validate and test robotic controllers.
- Analyse robot dynamics and design a mobile robot with appropriate actuators and sensors.
- Design advanced planning algorithms based on the problem and the environment including path planning and control problems in dynamic environments.
Key Skills:
- On completion of the module, students will be able to:
- Apply the scientific approach to real-world systems.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Lectures enable the students to learn new material relevant to robotics and autonomous systems, as well as its applications.
- Practical sessions enable students to acquire the necessary hardware skills, learn about the relevant hardware knowledge and receive feedback on their work.
- Summative assessments assess the knowledge of relevant libraries and application of methods and techniques.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | Attendance Monitored |
|---|---|---|---|---|---|
| Lectures | 10 | 1 per week in term 1 | 2 hours | 20 | |
| Lectures | 10 | 1 per week in term 2 | 1 hour | 10 | |
| Computer Classes | 10 | 1 every other week | 2 hours | 20 | |
| Preparation and Reading | 150 | ||||
| Total | 200 |
Summative Assessment
| Component: Coursework | Component Weighting: 100% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| In-Year Test | 30% | ||
| Assignment | 70% | ||
Formative Assessment:
Example formative exercises are given during the course. The first few lab practical are dedicated to formative assignments aimed at familiarising students with state-of-the-art packages and libraries used in robotics. Feedback will be provided to the students on the summative assignments and lecture materials during the practical.
■ Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.