KF6007 - Artificial Intelligence and Robotics

Lectures will introduce theories and state-of-the-art AI techniques and research work by well-known researchers and experts in the field, in the areas of AI, intelligent robotics, affective computing, bioinformatics and computer vision etc. During lectures, you will be encouraged to ask questions and also engage in interactive activities.

Practical exercises will you give opportunities to practise and explore relevant techniques covered in the lectures, which will gradually equip you with the ability to create an AI and robotics related piece of work on your own. Additionally, during lectures and practical exercises you will also be guided on how to carry out research work by yourself, and materials on research methods will be embedded in the module content throughout.

Outside class contact time, you are expected to read research papers, conduct research in relevant areas and if possible pursue research publications based on your implemented creative research work. Guidance on accessing online or library resources will be given by the module team. In addition, outside class time, student volunteers may also have opportunities to be involved in the evaluation of PhD projects as testing subjects.

Inquiry-based learning is used throughout the module.

The module team will guide and support you in the lecture and workshop practical sessions. During the lectures, you will be required to conduct interactive activities based on the lecturers’ guidance. The module team will prepare diverse examples of real-life applications to support you in learning complex AI techniques. Advanced applications such as robot vision and emotion detection from facial and bodily expressions will be demonstrated in the lecture and workshop sessions. The module team will work closely with you in the practical sessions to conduct discussions and provide further detailed guidance on the subjects covered.

You can also request appointments with the module teaching team outside of scheduled class time to ask questions and seek advice.

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

Knowledge & Understanding:
1. Demonstrate knowledge and understanding of artificial intelligence techniques and robotics applications, and identify state-of-the-art developments in the field.

Intellectual / Professional skills & abilities:
2. Appraise machine learning and robotics applications and intelligent processes using appropriate methods.
3. Design and implement advanced artificial intelligence, robotics and machine learning applications.
4. Evaluate the effectiveness of implemented artificial intelligence applications, including using student developed methodologies where appropriate.

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
5. Practise research skills in the construction of project reports and presentation of the products.

Summative assessment
The module will be assessed two individual assignments, an application development (60%) and the 2000-word report (40%).

For assignment 1, you will practise the knowledge and skills learnt from this module by creating an AI or robotics application from a list of given topics. This will assess MLOs 2, 3, 4 and 5.

In assignment 2 you will write a report on research into AI and robotics topics. The report will mainly assess your ability to present research work and your knowledge of relevant techniques and topics. It will assess MLOs 1, 2, 4 and 5.

You will be provided with written, electronic, feedback for each of the summative assignments.

Formative assessment and feedback
The exercises in the practical sessions provide opportunities for formative assessment, helping you and your tutors to assess your progress. You will receive guidance and ongoing feedback on your work and progress verbally in lab sessions.

You will also have the opportunity to discuss your progress and the needs of the summative assessment informally in the practical class sessions.

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This module provides you with the opportunity to explore state-of-the-art technologies and research work in the areas of artificial intelligence (AI) theories and concepts and robotics. You will learn about machine learning approaches such as supervised, evolutionary and unsupervised learning techniques in the affective computing, intelligent robotics and computer vision fields. The module will also introduce applications including affect sensing from speech, facial expressions and body language, scene/human behaviour interpretation, robot vision and scene understanding, and robot human interaction applications. In addition you will also cover techniques on evolutionary algorithms, swarm intelligence for team AI, adaptive learning and bioinformatics.