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In this module, students will work autonomously on a substantial project to gain the experience of attempting to solve a challenging problem. Each project is unique to the student, and so the methodology will differ. However, it is expected in all cases that students will learn and demonstrate a range of skills, including:

• Clearly defining and describing a challenging robotics research problem.
• Conduct a literature review to identify suitable related literature and to critically identify relevant literature, together with identifying relevant gaps.
• Designing a proposed method.
• Implementing a proposed method.
• Evaluating the method.
• Presenting their work in a written form in a thesis and verbally through a presentation or viva.

Students will apply and extend the knowledge developed through the programme in the design and implementation of a range of robotic systems with different sensing, actuation, and processing modalities, in varying environments, including those running in simulation and in the real-world, using a variety of specialist tools and techniques.

The module will also integrate research skills experience built though the taught modules, allowing students to demonstrate through their individual project, research skills and experimental design including critically reviewing the literature, the formation of research arguments, as well as designing sound experimental scenarios, considering the various variables, hypothesis, and research questions, with quantitative and qualitative analysis. The module will also enable students to demonstrate how they have reflected on and applied a range of aspects of consideration in robotics and AI in areas of economics, law, ethics and the interaction between technology and society.

Aims:

The aims of this module are to:

• Support students to demonstrate with increasing autonomy a holistic understanding of the practical application of theory and developing knowledge of AI–based robotic systems gained throughout the programme.
• Provide students with an independent context through which they select different approaches in the problem domain of AI –based robotic systems.
• Further build on students’ understanding of how AI-based robotic domain problems move from problem to different solutions in the context of research and development.
• Develop students’ mastery of research skills in conducting experimental research, covering novel scientific methods.
• Support students in communicating their critiques and designs clearly but with precision, forming coherent narratives that progress in a logical manner.

Intended learning outcomes:

On successful completion of the module, a student will be able to:

1. Demonstrate mastery in understanding of the ability to critically evaluate the main principles, theories, and concepts underpinning AI-based robotics.
2. Demonstrate practical aptitude in the design and implementation of a range of robotic systems with different sensing, actuation, and processing modalities, in varying environments, including those running in simulation and in the real-world, using a variety of specialist tools and techniques.
3. Apply, independently, research skills and experimental design including critically reviewing the literature, the formation of research arguments, as well as designing sound experimental scenarios, considering the various variables, hypothesis, and research questions, with quantitative and qualitative analysis.
4. Articulate key aspects of law, ethics and the interaction between technology and society in relation to the specific individual project.
5. Demonstrate a range of transferrable skills such as project management, adaptability, problem solving, and collaboration and communications skills developed through an individual robotics and artificial intelligence project.

Indicative content:

The following are indicative of the topics the module will typically cover:

• Tele-manipulation and integration of haptic interfaces.
• Robot assisted imaging and sensing.
• Environment mapping for robot navigation and action planning.
• Robotic control systems.
• Learning methods.
• Applied robotics.

Requisite conditions:

To be eligible to select this module as optional or elective, a student must be registered on a programme and year of study for which it is formally available.