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COMP34212 Cognitive Robotics syllabus 2019-2020

COMP34212 Cognitive Robotics

Level 3
Credits: 10
Enrolled students: 64

Course leader: Angelo Cangelosi


Additional staff: view all staff

Requisites

  • Pre-Requisite (Compulsory): COMP24111

Assessment methods

  • 70% Written exam
  • 30% Report
Timetable
SemesterEventLocationDayTimeGroup
Sem 2 Lecture 1.4 Fri 10:00 - 11:00 -
Sem 2 Lecture 1.4 Mon 14:00 - 15:00 -
Sem 2 w23-26 Lab 1.8 Tue 11:00 - 13:00 -

Overview

The course will provide an introduction to the methods and software/hardware technologies for robotics. It will analyse the selection and application of AI and machine learning methods, such as deep learning, for designing intelligent behaviour and cognitive skills (e.g. vision, motor control, language, social skills). It will discuss a series of cognitive robotics models and experiments to understand how our knowledge of animal and human cognition and neuroscience can inform the development of intelligent skills in robots. The course will also discuss the role of ethics and responsible research and innovation in robotics research and applications.

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.

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 AI

Practical 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 methods

Lectures

24 in total, 2 per week

Labs with TA support plus coursework and exam preparation and independent study

 

 

Feedback methods

Feedback on report and additional oral feedback during office/surgery hours and during labs.

Study hours

  • Assessment written exam (2 hours)
  • Lectures (24 hours)
  • Practical classes & workshops (8 hours)

Learning outcomes

Learning outcomes are unknown for COMP34212.

Reading list

TitleAuthorISBNPublisherYearCore
Developmental robotics: from babies to robotsCangelosi, Angelo and Matthew Schlesinger9780262028011MIT Press2015
Deep learningGoodfellow, Ian et al9780262035613MIT Press2016
Artificial cognitive systems: a primerVernon, David9780262028387MIT Press2014