Course Title: Autonomous Systems

Part A: Course Overview

Course Title: Autonomous Systems

Credit Points: 12.00

Important Information:

Please note that this course may have compulsory in-person attendance requirements for some teaching activities.

To participate in any RMIT course in-person activities or assessment, you will need to comply with RMIT vaccination requirements which are applicable during the duration of the course. This RMIT requirement includes being vaccinated against COVID-19 or holding a valid medical exemption.

Please read this RMIT Enrolment Procedure as it has important information regarding COVID vaccination and your study at RMIT: https://policies.rmit.edu.au/document/view.php?id=209.

Please read the Student website for additional requirements of in-person attendance: https://www.rmit.edu.au/covid/coming-to-campus

Please check your Canvas course shell closer to when the course starts to see if this course requires mandatory in-person attendance. The delivery method of the course might have to change quickly in response to changes in the local state/national directive regarding in-person course attendance.


Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MANU2206

Bundoora Campus

Undergraduate

115H Aerospace, Mechanical & Manufacturing Engineering

Face-to-Face

Sem 2 2012,
Sem 2 2013,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016

MANU2206

Bundoora Campus

Undergraduate

172H School of Engineering

Face-to-Face

Sem 2 2017,
Sem 2 2018,
Sem 2 2019,
Sem 2 2020,
Sem 1 2021,
Sem 1 2022

MANU2480

RMIT University Vietnam

Undergraduate

172H School of Engineering

Face-to-Face

Viet3 2018,
Viet1 2020,
Viet1 2021

Course Coordinator: Dr Tu Le

Course Coordinator Phone: +61 3 9925 2216

Course Coordinator Email: tu.le@rmit.edu.au

Course Coordinator Location: 57.01.10

Course Coordinator Availability: Mon 10-11am & Fri 10-11am


Pre-requisite Courses and Assumed Knowledge and Capabilities

Assumed Knowledge:

It is assumed that students have successfully completed the courses Automatic Control Systems (MANU1174), as well as Introduction to Mechatronics (MANU2205), or equivalent to those two courses, before attempting this course.


Course Description

This course introduces you to various concepts and components of autonomous systems in an autonomous mobile robotics context. The main concepts covered include locomotion, vehicle kinematics, autonomous navigation and intelligent path planning and perception. System components include various types of sensors and actuators and state-of-the-art technologies.

In the laboratory practicals, you will devise strategies and create behaviours to be exhibited by an autonomous mobile robot. The robot equipped with the autonomous behaviours that you have designed and created, is expected to perform a complex set of tasks autonomously.

Please note that if you take this course for a bachelor honours program, your overall mark in this course will be one of the course marks that will be used to calculate the weighted average mark (WAM) that will determine your award level.
This applies to students who commence enrolment in a bachelor honours program from 1 January 2016 onwards. See the WAM information web page for more information.


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes:

  • Comprehensive, theory-based understanding of the underpinning natural and physical sciences and the engineering fundamentals applicable to the engineering discipline
  • Fluent application of engineering techniques, tools and resources
  • Application of systematic engineering synthesis and design processes
  • Effective oral and written communication in professional and lay domains.
  • Creative, innovative and pro-active demeanour
  • Effective team membership and team


On completion of this course you should be able to:

  • CLO 1:  Clarify problem definition based on a client’s needs for a system to achieve a level of autonomy, and devise a layout of locomotion and sensing requirements of the system that would be able to meet the client’s needs in an autonomous manner;
  • CLO 2:  Design a system with sensing, actuating and embedded processing components, required to run the defined task autonomously;
  • CLO 3:  Program the embedded processor of your designed system to gain machine intelligence in terms of perception and actuation; and 
  • CLO 4:  Work effectively as part of a team to devise and implement experimental benchmarks to examine the performance of your designed system and the extent of its autonomy, stability and robustness. 


Overview of Learning Activities

In the pre-recorded lectures, you will learn the fundamentals of how to devise autonomous behaviours in an intelligent machine. In the tutorials, you will learn how to create programs in MATLAB and Simulink to implement the autonomous behaviours. In the lab sessions, you will put theory into practice.

All the lectures and other resources you need to complete the project, will be made available online in CANVAS. This course will significantly enhance your employability by enriching your technical skills in the context of machine intelligence, and your teamwork and communication skills.  


Overview of Learning Resources

You will be able to access course information and learning materials through CANVAS and may be provided with additional materials in class. Lists of relevant reference books and digitalised materials at RMIT libraries will be available as well. You will also use equipment and software packages in the laboratory for putting theory into practice in your practicals. During the course, students will be directed to many websites to enhance your knowledge and understanding of difficult concepts.


Overview of Assessment

This course has no hurdle requirements.

The assessment tasks are in one of two schedules: A or B. You will be advised at the start of the teaching period which of the schedules apply for any given teaching period and location.


Schedule A (Melbourne offering MANU2206)

Assessment Task 1:  Multiple-choice online quizzes
Weighting 10%
This assessment task supports CLOs 2 & 3

Assessment Task 2:  Programming and knowledge tests
Weighting 45%
This assessment task supports CLO 1 & 2 & 3

Assessment Task 3:  Laboratory tests
Weighting 25%
This assessment task supports CLOs 1 & 2 & 3

Assessment Task 4:  Final test
Weighting 20%
This assessment supports CLOs 1 & 2 & 3


Schedule B (Vietnam offering MANU2480)

Assessment Task 1:  Practical Assessments

Practical with Programming Test 1
Weighting 10%
This assessment task supports CLOs 1

Practical with Problem Solving Activity 2
Weighting 15%
This assessment task supports CLO 1-2

Practical with Problem Solving Activity 
Weighting 15%
This assessment task supports CLOs 1-2

Assessment Task 2:  Lab Tests

Lab Test 1
Weighting 20%
This assessment task supports CLOs 1-4

Lab Test 2
Weighting 20%
This assessment task supports CLOs 1-4

Assessment Task 3:  Class Test
Weighting 20%
This assessment task supports CLOs 1-4