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 ?	AMME2000 and 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

Assessment

The census date for this unit availability is 31 August 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam	Final Exam Supervised final exam	50%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Practical skill	Object-oriented design and implementation tasks Five short pass/fail design and C++ implementation tasks	0%	Multiple weeks Closing date: 06 Nov 2026	5 tasks, 2 hours each	AI allowed
Outcomes assessed:
Practical skill	Lab Exercise 1 Code design and implementation plus short report	10%	Week 04	Two weeks	AI allowed
Outcomes assessed:
Practical skill	Lab Exercise 2 Code design & implementation, plus short report	10%	Week 06	Two weeks	AI allowed
Outcomes assessed:
Written work	Project 1 Code design & implementation, plus report	10%	Week 09 Due date: 09 Oct 2026 at 23:59	Three weeks	AI allowed
Outcomes assessed:
Interactive oral	Project 2 oral presentation Design & implement complex system: demo, code, report. Part 2: interactive presentation with Q&A	10%	Week 12	3 hour cohort presentation session	AI prohibited
Outcomes assessed:
Written work	Project 2 written report Design & implement complex system: demo, code, report. Part 1: report	10%	Week 13	Five weeks	AI allowed
Outcomes assessed:
= hurdle task ? = group assignment ?

Assessment summary

Object-oriented design and implementation tasks. A series of five short, individual tasks that build and check the foundational object-oriented design and applied C++ skills introduced cumulatively in lectures. Each task is submitted via Canvas. This is a compulsory pass/fail (hurdle) assessment: each of the five tasks must be passed to a satisfactory standard in order to pass the unit. Tasks are first assessed across the early weeks of semester, and re-attempts of any task not yet passed are accepted at scheduled grading occasions up to the end of Week 13.

Lab Exercises. In groups, students complete system design and coding exercises that apply the system-design and C++ programming skills covered cumulatively in lectures. Groups submit both code and a brief report communicating key design choices.

Project 1. In groups, students complete a simple ROS-based mechatronic system design and implementation. Groups submit both code and a brief report communicating key design choices and documenting the project.

Project 2. In groups, students complete a moderately scaled ROS-based mechatronic system design and implementation. Groups submit code and a brief report communicating key design choices and project outcomes, and demonstrate their work in an interactive presentation and Q&A session during their final lab session.

Final Exam. A supervised two-hour exam.

Due dates and times. The five skills tasks are first due 11:59 pm Friday of Weeks 1, 2, 3, 4, and 6; re-attempts of any not-yet-passed task are accepted until 11:59 pm Friday of Week 13. Lab Exercises are due prior to the group's scheduled lab session in Weeks 4 and 6 (Friday sessions) or Weeks 5 and 7 (Monday sessions). Project 1 reports are due 11:59 pm Friday of Week 9. Project 2 reports are due 11:59 pm Friday of Week 13, and Project 2 must be presented in the group's scheduled lab session in Week 12 (Friday sessions) or Week 13 (Monday sessions).

Student laptops / computers. It is helpful for students to have access to laptops or computers outside scheduled lab time that can run the software used in this unit: Ubuntu Linux and ROS 2. Installation instructions will be provided ahead of semester via Canvas.

Group work. All group members must be enrolled in the same practical session.

Assessment criteria

Labs are due at the start of your scheduled lab session, two weeks after the session in which they are set.

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). Sparkplus may be used for self and peer feedback for group activities and marks may be adjusted based on Sparkplus results.

Requirements to pass this unit of study. To pass this unit of study, a student must satisfy all three of the following:

pass all five compulsory object-oriented design and implementation tasks, each of which is assessed pass/fail; re-attempts are accepted until the end of Week 13;
obtain a mark of at least 45% across all non-examination assessments combined (the Lab Exercises and Projects, including the Project 2 presentation); and
obtain a mark of at least 45% in the examination component.

A student who does not satisfy all three requirements cannot be awarded a pass for the unit, and the maximum mark that will be awarded is 45%.

The object-oriented design and implementation tasks are included as a compulsory requirement to ensure that each student individually attains a minimum working competence in the foundational object-oriented design and C++ programming skills on which the rest of the unit depends, before those skills are applied in the group projects and assessed under examination conditions. The tasks are short, carry no weight toward the final mark, provide formative feedback, and may be re-attempted to reach the required standard.

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. A component of the final project grade is based on the condition of the returned hardware.

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.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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 University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	1. Introduction; 2. The OOP paradigm	Lecture (2 hr)
Week 01	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Week 02	1. Inheritance, UML; 2. Polymorphism	Lecture (2 hr)
Week 02	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Week 03	1. Project management; 2. STL Containers	Lecture (2 hr)
Week 03	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Week 04	1. Modern C++xx, pointers; 2. Object-oriented design	Lecture (2 hr)
Week 04	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Week 05	1. ROS introduction; 2. ROS publishers and subscribers	Lecture (2 hr)
Week 05	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Week 06	1. ROS launching and interfaces; 2. STL iterators, algorithms, templating	Lecture (2 hr)
Week 06	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Week 07	1. ROS simulation and visualisation; 2. Namespaces and asynchronous programming	Lecture (2 hr)
Week 07	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Week 08	1. Streams and overloading; 2. ROS transforms and parameters	Lecture (2 hr)
Week 08	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Week 09	1. Design patterns; 2. Skills review	Lecture (2 hr)
Week 10	1. Architectural thinking; 2. ROS lifecycle nodes & executors	Lecture (2 hr)
Week 10	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Week 11	1. ROS localisation and mapping; 2. ROS computer vision and perception	Lecture (2 hr)
Week 11	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Week 12	1. ROS navigation and planning; 2. Threading	Lecture (2 hr)
Week 12	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Week 13	1. Unit Review; 2. Exam Review	Lecture (2 hr)
Week 13	Hands-on assignments and projects completed in the mechatronics teaching lab.	Practical (3 hr)
Weekly	Independent reading and research, preparing for lectures by watching and understanding prerecorded material, completing practice questions, completing lab exercises and projects.	Self-directed learning (68 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 object-oriented software by partitioning the program into classes and implementing it in C++
LO2. design and document software using modelling tools
LO3. design, plan for, and execute a significant software project in a team
LO4. design and implement software using contemporary robotic operating system middleware
LO5. develop the capacity to think creatively and independently about new design problems
LO6. manage time and complete technical work in a timely manner
LO7. work collegially and effectively in a shared laboratory environment

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 student feedback we are introducing short, individual, pass/fail design and programming tasks in the early weeks to give structured practice on core C++ and design skills, with feedback and repeated attempts. We are introducing fewer and more comprehensive labs, covering some new concepts through live coding rather than conventional lectures, adding structure to support project management, clarifying ROS video recording pacing, and standardising how we convey expectations around code and design diagrams. We are providing earlier Turtlebot hardware access, and updating materials affected by software upgrades. We will maintain the strengths identified, including the hands-on and practical lab work; engaging lectures with live coding and AI; the progression from C++ to ROS to hardware; challenging group projects; industry-relevant content including object-oriented design, C++, and ROS; and a supportive teaching team committed to your learning outcomes.

Additional information

Work, health and safety

Students are always expected to follow university and lab guidelines to maintain safety, including monitor email closely for any changes in policy.

Students are required to complete an online lab safety induction prior to entry into the lab.

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

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

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

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

MTRX3760: Mechatronic Systems Design

Semester 2, 2026 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

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