COMPSYS 726 : Robotics and Intelligent Systems

Engineering

2024 Semester Two (1245) (15 POINTS)

Course Prescription

Fundamentals of robotic and intelligent systems, including reactive and deliberative functionality, navigation techniques, planning and programming of robot actions, machine learning, artificial neural networks and may include topics in sensors and actuators, kinematic analysis, fuzzy systems, genetic algorithms. Core concepts are extended by an individual research project where a challenging robotics problem is analysed and a solution implemented and tested.

Course Overview

This course will focus on building intelligent agents and systems. The course will explore the how Artificial Intelligence (AI) and Machine Learning (ML) can be used to enhance and improve robots and other agents. The course theory will be supplemented by hands-on practical labs, where the students will learn to use AI and ML tools to develop their own autonomous agents through Reinforcement Learning. By the end of the course students should understand how to understand and apply AI and ML for real-world scenarios.

Course Requirements

Prerequisite: 15 points from COMPSYS 302, 306, ENGSCI 331, MECHENG 313, SOFTENG 306 Restriction: COMPSYS 406

Capabilities Developed in this Course

Capability 1: People and Place
Capability 3: Knowledge and Practice
Capability 4: Critical Thinking
Capability 5: Solution Seeking
Capability 8: Ethics and Professionalism

Learning Outcomes

By the end of this course, students will be able to:
  1. Demonstrate an understanding of an Intelligent Agent and the types of tasks it can perform (Capability 3.1, 3.2, 4.1, 4.2, 5.1 and 8.2)
  2. Demonstrate the use of Machine Learning techniques for robotic applications (Capability 3.1, 3.2, 4.1, 4.2 and 5.1)
  3. Critically evaluate algorithms used in AI applications (Capability 1.1, 3.1, 3.2, 4.1, 4.2 and 8.1)

Assessments

Assessment Type Percentage Classification
Practical 60% Individual Coursework
Reports 40% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3
Practical
Reports

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For this course, you can expect 36 hours of lectures, 10 hours of tutorials, 50 hours of reading and thinking about the content and 54 hours of work on assignments.

Delivery Mode

Campus Experience

Attendance is expected at scheduled activities including labs to receive credit for components of the course.
Lectures will be available as recordings. Other learning activities including labs will not be available as recordings.
The course will not include live online events.
The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Health & Safety

Students must ensure they are familiar with their Health and Safety responsibilities, as described in the university's Health and Safety policy.

The first lab will include a health and safety induction to the laboratories; if this is missed, students will be unable to attend the labs. The labs will be using physical robots; as such, there is a risk of harm. No food or drink is allowed in the robotics laboratories, and the teaching assistant's instructions must be followed. 

Student Feedback

At the end of every semester students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback and respond with summaries and actions.

Your feedback helps teachers to improve the course and its delivery for future students.

Class Representatives in each class can take feedback to the department and faculty staff-student consultative committees.

We will be focusing the content on the nature of an autonomous agents of which a robot is one. There will be additional technical support for completing the coursework and reports.

We have also changed the semester this course is offered in, so it is better aligned with COMPSYS 732.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed for potential plagiarism or other forms of academic misconduct, using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

Published on 31/10/2023 12:48 p.m.