Outline

Overview

This unit of study follows a systems engineering approach to the integration of hardware and software components to form mechatronic systems. Methodologies for object-oriented design: Classes and interfaces, encapsulation, composition, inheritance, polymorphism; UML class diagrams; Design patterns, templating, smart pointers, streams, containers, overloading. Sensors: Taxonomy, calibration, fusion, sources of error; Serialisation and data streams. Project Management: Process models, incremental development, design for debug; Coding standards and review, revision control, build and test automation. Hands-on practice: C++, Linux and GNU software tools, standard libraries, ROS robotics middleware. Students will complete a major project working in groups to design and implement a complex mechatronic system.

Unit details and rules

Academic unit	Aerospace, Mechanical and Mechatronic
Credit points	6
Prerequisites ?	MTRX2700
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Donald Dansereau, donald.dansereau@sydney.edu.au
Lecturer(s)	Donald Dansereau, donald.dansereau@sydney.edu.au

Type	Description	Weight	Due	Length
Supervised exam ?	Final Exam Supervised final exam	40%	Formal exam period	2 hours
Outcomes assessed:
Small continuous assessment	Lab Exercise 1 Code design and implementation plus short report	5%	Week 02	One week
Outcomes assessed:
Small continuous assessment	Lab Exercise 2 Code design & implementation, plus short report	5%	Week 04	One week
Outcomes assessed:
Small continuous assessment	Lab Exercise 3 Code design & implementation, plus short report	5%	Week 05	One week
Outcomes assessed:
Small continuous assessment	Lab Exercise 4 Code design & implementation, plus short report	5%	Week 06	One week
Outcomes assessed:
Assignment	Project 1 Code design & implementation, plus report	10%	Week 09 Due date: 06 Oct 2023 at 23:59	Two weeks
Outcomes assessed:
Assignment	Project 2 Design & implement complex system: demo, code and report	30%	Week 13 Due date: 03 Nov 2023 at 23:59	Four weeks
Outcomes assessed:
= hurdle task ? = group assignment ?

Assessment summary

Lab Exercises 1-4: Students individually complete system design and coding tasks to demonstrate application of the fundamental system design and applied C++ programming skills covered cumulatively in lectures. Students submit both code and a brief report communicating key design choices.
Project 1: In groups, students complete a moderately scaled ROS-based mechatronic system design and implementation. Student groups submit both code and a brief report communicating key design choices and documenting the project’s performance.
Project 2: In groups, students complete a substantial ROS-based mechatronic system design and implementation. Student groups submit code, a brief report communicating key design choices and project outcomes, a video documenting the key aspects of the project, and are given an opportunity to answer questions in an interactive Q&A session during their final lab session.
Final Exam: The final exam is a supervised 2-hour exam.
Due Date and Time: Lab Exercises are due prior to the student’s next scheduled lab session in Weeks 2, 4, 5 and 6 (Thurs/Fri sessions) or Weeks 3, 5, 6 and 7 (Monday session). Project 1 and 2 reports are due at 11:59pm Friday of Weeks 9 and 13.
Demonstration: Project 2 must be demonstrated in the group’s scheduled lab session in Week 12 (Thurs/Fri sessions) or 13 (Monday session).
Moderation of Group Work Marks: Group marks will be moderated on the basis of individual effort and understanding, as perceived by the lecturer and tutor(s) and as self-reported by group members.
Must Pass Both Components: To pass this unit of study it is necessary to obtain a mark of not less than 45% in both the assignment and examination components. If you fail either the assignment component or the exam the maximum mark you can get for the unit of study is 45%.
Student Laptops / Computers: It is helpful for students to have access to laptops / computers outside of scheduled lab time that are capable of running the software used in this unit: Ubuntu 20.04 and ROS Noetic. Installation instructions will be provided ahead of semester start on Canvas.
Detailed information and due dates for each assessment task can be found on Canvas.

Assessment criteria

Note that labs are due a week after your lab session, before the start of your next lab session.

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Group marks for Project Work will be moderated on the basis of individual effort and understanding, as perceived by the Lecturer and Tutor(s). To pass this unit of study it is necessary to obtain a mark of not less than 45% in both the (assignment + project) and examination components. Otherwise, the maximum mark that will be awarded is 45%.

Students who borrow hardware as part of this unit must return the hardware in working condition. Failure to cooperate in returning hardware may result in the student’s final results being withheld.

Result name	Mark range	Description
High distinction	85 - 100	Work of exceptional standard. Work demonstrates mastery of the concepts and principles covered in class, as well as initiative and ingenuity in applying concepts to new situations. Work shows pointed and critical analysis of material as well as thoroughness and thoughtfulness. Demonstrates a comprehensive understanding of the unit material and its relevance in a wider context.
Distinction	75 - 84	Work of superior standard. Work demonstrates initiative, complex understanding and original analysis and application of subject matter in context; shows critical understanding of the principles and values underlying the unit of study. In particular, students who aim for a Distinction and higher will have to accomplish the requirements of a Credit and should be able to: Demonstrate in-depth understanding of material beyond the immediate scope of the lecture material. Generalise and apply concepts to more complicated scenarios. Analyse complex mechatronic systems, and apply a systems engineering approach in order to develop and demonstrate working systems following principled design practices.
Credit	65 - 74	Competent work. Evidence of initiative in learning, sound grasp of subject matter and appreciation of key issues and context. Engages critically and creatively with the material and attempts synthesis and application of material. Goes beyond solving of simple problems to seeing how material in different parts of the unit of study relate to each other by solving problems drawing on concepts and ideas from other parts of the unit of study. In particular, students who aim for a Credit will have to accomplish the requirements of a Pass and should be able to: Relate between the various components of the course and understand their interaction in terms of design and integration of mechatronic systems. Understand the taxonomy and limitations of key components of mechatronic systems. Understand and apply the principles of object oriented design to design basic mechatronic systems. Implement mechatronic systems using industry-standard tools including C++, Linux, the standard libraries, and ROS robotics middleware.
Pass	50 - 64	Work of acceptable standard. Work meets basic requirements in terms of reading and research and demonstrates a reasonable understanding of subject matter. Able to solve relatively simple problems involving direct application of particular components of the unit of study. In particular, students who aim for a Pass should be able to: Understand the principles of object oriented design. Analyse an existing mechatronic system and the underlying system design choices. Synthesise and communicate basic system designs using standard tools including UML class diagrams. Make basic use of standard tools in Linux, C++, and ROS robotics middleware.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Labs and projects will not be accepted more than a week after the due date.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	1. Introduction; 2. The OOP paradigm	Lecture and tutorial (5 hr)
Week 02	1. Inheritance, UML; 2. Polymorphism	Lecture and tutorial (5 hr)
Week 03	1. Project management; 2. STL Containers	Lecture and tutorial (5 hr)
Week 04	1. Modern C++xx, pointers; 2. Object-oriented design	Lecture and tutorial (5 hr)
Week 05	1. ROS introduction; 2. ROS publishers and subscribers	Lecture and tutorial (5 hr)
Week 06	1. ROS sensor messages; 2. STL iterators, algorithms, templating	Lecture and tutorial (5 hr)
Week 07	1. ROS visualisation and debugging; 2. Streams and overloading	Lecture and tutorial (5 hr)
Week 08	1. Namespaces and nesting 2. ROS TF transforms	Lecture and tutorial (5 hr)
Week 09	1. Sensors; 2. Software design patterns	Lecture and tutorial (5 hr)
Week 10	1. ROS services and actions; 2. ROS plugins / nodelets	Lecture and tutorial (5 hr)
Week 11	1. ROS localisation; 2. ROS computer vision	Lecture and tutorial (5 hr)
Week 12	1. ROS navigation stack; 2. Threading	Lecture and tutorial (5 hr)
Week 13	1. Exam Review A; 2. Exam Review B	Lecture and tutorial (5 hr)
Weekly	Independent reading and research, preparing for lectures by watching and understanding prerecorded material, completing practice questions, completing lab exercises and projects.	Independent study (78 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. design, plan for, and execute a significant software project in a team
LO2. design and implement object-oriented software in C++
LO3. partition a software design into classes and applications modules
LO4. document a software design using modelling tools
LO5. develop the capacity to think creatively and independently about new design problems
LO6. understand in detail the operating principals and interfaces of serially-attached sensors
LO7. demonstrate a detailed knowledge of fundamental aspects of a contemporary operating system, as they relate to the design of software to execute within the operating system.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

In response to feedback we will reduce the complexity of practice questions and provide in their place a set of simpler single-concept problems and solutions. We will simplify the scope of work required for the major project without removing its open-ended nature. We will more clearly identify lectures that are optional / for interest only. We will specify in the Syllabus that students may wish to locate computing resources capable of running Linux / ROS outside scheduled lab time. We will move code examples into a git repo, practising the advice presented in lecture. To increase clarity of assessment we will provide an explicit coding standard for the unit.

Additional information

Work, health and safety

COVID-19 and other safety matters: please refer to the unit's canvas site and monitor email for up-to-date information.

For those attending labs in person:

You will only have access to the lab during your scheduled lab sessions.
We have limited student numbers in each lab session to allow this physical distancing to be maintained.
Follow all Univeristy guidelines regarding COVID-related safety.
Obey all Lab signage including guidelines for sanitising workstations and hardware, PPE, and procedures for entry and exit.
If you are feeling unwell, please stay at home.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

MTRX3760: Mechatronic Systems Design

Semester 2, 2023 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect