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Aims:

The aims of this module are to:

1. Provide students with a practical introduction to techniques included in the planning, design and construction of systems to solve engineering problems.
2. Support students in problem solving to create practical solutions in robotics an AI against functional and non-functional user requirements, testing and assessing those in simulated and real-world environments and articulating the limitations of those assessments.
3. Provide students with the tools for critical analysis for reasoning about the appropriateness and quality of practical solutions produced in the context of the problems defined.
4. Support students to develop their skills in the reasoning more broadly about the place of robotics and AI in society, the challenges that arise in practical deployment in which humans are involved, and individual responsibility for ethical behaviour in systems development and the choices of systems that it is appropriate to develop.

Intended learning outcomes:

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

1. Design a complex system as part of a group, considering: (i) the practicality of implementing it in the real-world; and (ii) performance criteria and broader user requirements.
2. Plan a project subject to resource constraints that would be expected to deliver that system.
3. Identify risks and suggest mitigations for those risks.
4. Consider wider societal and human aspects of deployment.
5. Present the results of this process in regular design reviews and in the form of a final report and presentation.

Indicative content:

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

• Cyber-physical systems - what are they, what do we care about in CPS, designing robust CPS.
• Systems engineering for real time systems.
• Overview of the process, different perspectives (waterfall, V, agile).
• Model-Based Systems Engineering.
• Motivation, approach, tools.
• SysML.
• Product improvement processes.
• Risk management in projects.
• Security – threats, vulnerabilities, and mitigations.
• Dealing with humans, both during the design process and in deployed systems.
• Real time embedded systems implementation considerations.
• Hard vs firm vs soft real time.
• Real-time systems programming.
• Prioritisation.
• Scheduling algorithms.
• Synchronisation.
• Time/utility function real-time resource management.
• Real-time operating system kernel design.
• Modelling real time systems.
• Tolerance to failure.
• Real time software performance analysis.
• Metrics.
• Static/ dynamic analysis.
• Ethical considerations in robotics and AI.

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.