Sensors and artificial perception

The unit provides an introduction to the principles of sensing circuits and the inferential techniques required to deploy them for applications in artificial perception. We survey the components of a basic sensor’s circuit architecture in the context of a range of sensing technologies and provide hands-on practice in their construction and characterisation. Applications in biomedical technology, robotics and automation are considered alongside a theoretical framework for understanding the complexity of data collected in real-world environments. You will gain an appreciation for how decisions in circuit design and signal processing impact artificial sensation and perception in practice.

Online learning - The online lessons provide an in-depth theoretical background to the practical problems addressed in the laboratories.

Problem-based learning - The workshops and laboratories will focus on problem-based learning where you will solve increasingly sophisticated problems in artificial sensing and perception with a mixture of hardware and software applications.

Peer assisted learning - You will collaborate to complete projects in groups. Peer evaluation will be used to hold individual group members accountable for their contributions.

The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.