- UCAS course code
- GG14
- UCAS institution code
- M20
Bachelor of Science (BSc)
BSc Computer Science and Mathematics
Duration: 3 years
Year of entry: 2025
UCAS course code: GG14 / Institution code: M20
- Key features:
Scholarships available
- Typical A-level offer: A*A*A including specific subjects
- Typical contextual A-level offer: AAA including specific subjects
- Refugee/care-experienced offer: AAB including specific subjects
- Typical International Baccalaureate offer: 38 points overall with 7,7,6 at HL, including specific requirements
Course unit details:
Cognitive Robotics
| Unit code | COMP34212 |
|---|---|
| Credit rating | 10 |
| Unit level | Level 3 |
| Teaching period(s) | Semester 2 |
| Available as a free choice unit? | Yes |
Overview
This unit provides an in-depth understanding of the field of cognitive robotics. This will analyse the selection, use and combination of methods and approaches in robotics, in artificial intelligence and in psychology and neuroscience to design intelligent behaviour and cognitive skills in interactive robots.
Aims
This unit provides an in-depth understanding of the field of cognitive robotics. This will analyse the selection, use and combination of methods and approaches in robotics, in artificial intelligence and in psychology and neuroscience to design intelligent behaviour and cognitive skills in interactive robots.
Learning outcomes
At the end of this course a student will be able to:
1. analyse the methods and software/hardware technologies for robotics research and applications
2. understand how our psychology and neuroscience understanding of behaviour and intelligence informs the
design of robotics models and applications
3. compare, select and apply different machine learning methods for intelligent behaviour in robots
4. Discuss the state of the art in cognitive and intelligent robotics models, and how this informs the design of future robot applications
5. Discuss the role of ethics and responsible research and innovation in robotics
Syllabus
Lecture topics: Introduction to Cognitive Robotics Overview of robot technologies, sensors and actuators Robot platforms Machine learning for robotics Developmental Robotics Neuro-robotics Evolutionary and swarm robotics Social robotics and human-robot interaction Language learning and speech interfaces Robot tutors for children Ethics for robotics and AIPractical Labs: The practical lab sessions will focus on the use of machine learning methods, such as deep learning, for robot vision and language and on the software tools for robotics.
Teaching and learning methods
16 Lectures and 4 labs
Employability skills
- Analytical skills
- Innovation/creativity
- Problem solving
- Research
- Written communication
Assessment methods
| Method | Weight |
|---|---|
| Written exam | 70% |
| Written assignment (inc essay) | 30% |
Feedback methods
Feedback on report and additional oral feedback during office/surgery hours and during labs.
Recommended reading
Cangelosi & Asada (2022), Cognitive Robotics. MIT Press.
Additional reading material provided in the online learning platform.
Study hours
| Scheduled activity hours | |
|---|---|
| Lectures | 16 |
| Practical classes & workshops | 8 |
| Independent study hours | |
|---|---|
| Independent study | 76 |
Teaching staff
| Staff member | Role |
|---|---|
| Angelo Cangelosi | Unit coordinator |