AMME1362 is an introductory course in engineering materials. The unit aims to develop students' understanding of the structures, mechanical properties and manufacture of a range of engineering materials as well as how the mechanical properties relate to microstructure and forming and treatment methods. The unit has no prerequisite subject and is therefore intended for those with little or no previous background in engineering materials. However the unit does require students to take a significant degree of independent responsibility for developing their own background knowledge of materials and their properties. The electrical, magnetic, thermal and optical properties of materials are a critical need-to-know area where students are expected to do most of their learning by independent study.

The unit aims to provide students with an understanding of and competence in solving statics and introductory dynamics problems in engineering. Tutorial sessions will help students to improve their group work and problem solving skills, and gain competency in extracting a simplified version of a problem from a complex situation. Emphasis is placed on the ability to work in 3D as well as 2D, including the 2D and 3D visualisation of structures and structural components, and the vectorial 2D and 3D representations of spatial points, forces and moments. Introduction to kinematics and dynamics topics includes position, velocity and acceleration of a point; relative motion, force and acceleration, momentum, collisions and energy methods.

Equilibrium of deformable structures; basic concept of deformation compatibility; stress and strain in bars, beams and their structures subjected to tension, compression, bending, torsion and combined loading; statically determinate and indeterminate structures; energy methods for bar and beam structures; simple buckling; simple vibration; deformation of simple frames and cell box beams; simple two-dimensional stress and Morh's circle; problem-based applications in aerospace, mechanical and biomedical engineering.

This unit of study will focus on the principles governing the state of motion or rest of bodies under the influence of applied force and torque, according to classical mechanics. The course aims to teach students the fundamental principles of the kinematics and kinetics of systems of particles, rigid bodies, planar mechanisms and three-dimensional mechanisms, covering topics including kinematics in various coordinate systems, Newton's laws of motion, work and energy principles, impulse and momentum (linear and angular), gyroscopic motion and vibration. Students will develop skills in analysing and modelling dynamical systems, using both analytical methods and computer-based solutions using MATLAB. Students will develop skills in approximating the dynamic behaviour of real systems in engineering applications and an appreciation and understanding of the effect of approximations in the development and design of systems in real-world engineering tasks.

This unit of study aims to allow students to develop an understanding of methods for modeling and controlling linear, time-invariant systems. Techniques examined will include the use of differential equations and frequency domain approaches to modeling of systems. This will allow students to examine the response of a system to changing inputs and to examine the influence of external stimuli such as disturbances on system behaviour. Students will also gain an understanding of how the responses of these mechanical systems can be altered to meet desired specifications and why this is important in many engineering problem domains.
The study of control systems engineering is of fundamental importance to most engineering disciplines, including Mechanical, Mechatronic, Biomedical, and Aerospace Engineering. Control systems are found in a broad range of applications within these disciplines, from aircraft and spacecraft to robots, automobiles, manufacturing processes, and medical diagnostic systems. The concepts taught in this course introduce students to the mathematical foundations behind the modelling and control of linear, time-invariant dynamic systems. In particular, topics addressed in this course will include:
1. Techniques for modelling mechanical systems and understanding their response to control inputs and disturbances. This will include the derivation of differential equations and use of frequency domain (Laplace transform) methods for their solution and analysis.
2. Representation of systems in a feedback control system as well as techniques for determining what desired system performance specifications are achievable, practical and important when the system is under control
3. Techniques including Root Locus, Bode Plots, and State Space for analysis and design of feedback control systems.
4. Case studies inspired by real-world problems in control engineering.

This unit of study aims to develop knowledge of the fundamental concepts and building blocks of electrical and electronics circuits. This is a foundation unit in circuit theory. Circuit theory is the electrical engineer's fundamental tool.
The concepts learnt in this unit will be made use of heavily in many units of study (in later years) in the areas of electronics, instrumentation, electrical machines, power systems, communication systems, and signal processing.
Topics: a) Basic electrical and electronic circuit concepts: Circuits, circuit elements, circuit laws, node and mesh analysis, circuit theorems, energy storage, capacitors and inductors, circuits with switches, transient response, sine waves and complex analysis, phasors, impedance, ac power. ; b) Project management, teamwork, ethics; c) Safety issues

Modern Electronics has come to be known as microelectronics which refers to the Integrated Circuits (ICs) containing millions of discrete devices. This course introduces some of the basic electronic devices like diodes and different types of transistors. It also aims to introduce students the analysis and design techniques of circuits involving these discrete devices as well as the integrated circuits.
Completion of this course is essential to specialise in Electrical, Telecommunication or Computer Engineering stream.

Aim: For students to experience a realistic the design process and to develop good engineering skills.
Course Objectives- To develop an understanding of: 1) The need for and use of standard drawings in the communication and definition of parts and assemblies to AS1100; 2) Efficient use of a CAD package; 3) Creativity; 4) The design process from initial idea to finished product; 5) Methods used to analyse designs; 6) Appreciation and analysis of standard components; 7) An understanding of power transmission elements.

This unit aims to apply some newly acquired skills to begin to understand how stress and strain are distributed in the more common categories of machine parts. Reducing the loads in standard parts to just the most significant, leads to a range of relatively simple analyses. By using different degrees of simplification and a proportional amount of effort, the examination of components can provide results of corresponding accuracy. To lead the student to utilise and be aware of modern computer methods, to be aware of past methods and be prepared of future developments. Not all the analysis of mechanical components are covered in the course but the ones that are deal with exemplify principles that can be applied to novel items that our graduates may encounter in their professional life.
At the end of this unit students will be able to: apply fatigue life prediction in general to any component; design a bolted joint to carry tensile and or shear loads: use a numerical solver to arrive at the optimal dimensions of a component, given its loads and sufficient boundary conditions; design shafts to carry specified steady and alternating bending moments and torques; design and construct a space frame, such as that for a dune buggy, to meet requirements of strength and rigidity; be able to arrive at the principle parameters of a pair of matched spur gears, and to be able to extend this to helical gears.
Course content will include: stress and strain in engineering materials; yield and ultimate fail conditions in malleable and brittle materials; spatial, 3D frameworks; deflections due to forces, moments and torques.

The unit aims to teach the fundamentals of manufacturing processes and systems in mechanical, mechatronic and biomedical engineering, including traditional and advanced manufacturing technologies.
This unit aims to develop the following attributes: to understand the fundamental principles of manufacturing technologies for the above mentioned engineering areas; to gain the ability to select existing manufacturing processes and systems for direct engineering applications; to develop ability to create innovative new manufacturing technologies for advanced industrial applications; to develop ability to invent new manufacturing systems.
At the end of this unit students will have a good understanding of the following: merits and advantages of individual manufacturing processes and systems; principles of developing new technologies; comprehensive applications and strategic selection of manufacturing processes and systems.
Course content will include:
CAD / CAM: An introduction into the use of CAD and manual CNC coding as separate tools combined with an introduction into the kinematics and structural requirements in the construction of a CNC machine.
Rapid Engineering: An introduction into the most current Rapid Engineering methods currently in use.
Manufacturing Processes: Common processes and their science (machining, casting, powder metallurgy, metal working, welding) and their relative merits and limitations.

This unit of study aims to provide a foundation for the study of systems and embedded programming for the degree in Mechatronic Engineering.
It is based around a systems engineering approach to requirements capture, software design, implementation, debugging and testing in the context of the C programming language. Problem definition and decomposition; the design process; designing for testing and defensive coding methods; modular code structure and abstract data types; best practice in programming. Programming in teams; documentation and version control.
The C language: Preprocessor, tokens, storage classes and types; arithmetic, relational and bit manipulation operators; constructs for control flow: if, switch, for, do and while; arrays; pointers and character strings; dynamic memory allocation; functions and parameter passing; derived storage classes: structures and unions; file I/O.

This unit of study aims to provide an introduction to the basic hardware elements of mechatronic systems.
Basic electrical theory: Ohms law, Kirchoff's voltage and current laws, passive component characteristics (resistors, capacitors and inductors).
Number systems and codes; Logic gates and Boolean algebra, universal (NAND) logic gates; Digital arithmetic: operations and circuits, Two's complement addition and subtraction, overflow; Combinational logic circuits; Flip-flops and related devices; Counters and registers, shift register applications; sequential circuits, designs of synchronous, cascadable counters (BCD and binary). Integrated circuit logic families and interfacing; practical issues including, fan out, pull-up/down, grounds, power supplies and decoupling; timing issues, race conditions. Tri-state signals and buses; MSI logic circuits, multiplexers, demultiplexers, decoders, magnitude comparators; Introduction to programmable logic devices.
Brushed DC Motors: Introduction to characteristics and control, motor specifications, torque-speed characteristics, power and efficiency, thermal considerations.
Introduction to BJTs and FETs as switches. PWM control of DC motors; half- and full-bridge configurations; Feedback and operational amplifiers; selected op-amp applications circuits with an emphasis on sensor and actuator interfacing.
The unit of study will include a practical component where students design and implement logic and linear circuits. Purchase of a basic laboratory tool kit as described in classes will be required.

The aim of the unit is to introduce students to microprocessor and microcomputer systems, emphasising assembly language programming and building on the digital logic foundations from first year. In particular, the following subjects are addressed:
Introduction to microprocessors, stored-program computer architecture, instruction codes and addressing modes, instruction execution cycle; Memory devices. Computer architecture and assembly language programming. Microprocessor and microcontroller systems, memory and IO interfacing, interrupts and interrupt handling. Serial and parallel communications. System design, documentation, implementation, debugging and testing.
MTRX2700 is the introductory course in the basics of real Mechatronic systems. This course builds on knowledge obtained in the courses ENGG1801, MTRX1701, ELEC1103 and MTRX1702, MTRX1705. This course extends this knowledge by introducing students to their first practical applications in Mechatronic Engineering. By passing this subject, the student will have obtained the necessary skills to undertake Mechatronics 3 (MTRX3700).

This unit of study aims to provide experience, confidence and competence in the design and implementation of microprocessor-based products and instruments; to impart a detailed knowledge of the software and hardware architecture of a typical modern microcontroller, and an understanding of the use of these resources in product design; and to provide experience of working in a project team to prototype a realistic product to meet a specification.
At the end of this unit students will understand microprocessor system organisation, and the organisation of multiple and distributed processor systems, special purpose architectures (DSPs etc. ) and their application. The student will have a detailed knowledge of the software and hardware architecture of a modern microcontroller. This knowledge will include an in-depth understanding of the relationship between assembly language, high-level language, and the hardware, of the utilisation and interfacing of microcontroller hardware resources, and of the design and development of software comprised of multiple interrupt-driven processes. The student will have the competence to develop prototype microprocessor-based products.
Course content will include single processor systems, multiple and distributed processing systems, special purpose architectures (DSPs etc) and their application; real-time operating systems for microcontrollers; standard interfacing of sensor and actuation systems; ADC/DAC, SSI, parallel, CAN bus etc. ; specific requirements for microprocessor-based products; problem definition and system design; tools for design, development and testing of prototype systems; the unit of study will include a project, where groups of students design, develop and commission a microprocessor-based product.

This unit of study follows a systems engineering approach to the integration of hardware and software components to form mechatronic systems.
Sensors: dead reckoning and inertial sensors; external sensors including ultrasonic, laser, radar and GPS; sensor interfaces, serialisation and data streams.
Methodologies for object-oriented design; the C++ language: classes and class design; overloading; inheritance and polymorphism; iostreams.
Operating system: introduction to structure and principles; facilities for interprocess communication and synchronisation; device drivers and applications programming; Gnu software tools; make and related utilities; communications middleware for distributed software.
Students will complete a six-week project working in groups to design and implement a distributed mechatronic system.

This unit of study introduces students to vision sensors, computer vision analysis and digital image processing. This course will cover the following areas: fundamental principles of vision sensors such as physics laws, radiometry, CMOS/CDD imager architectures, colour reconstruction; the design of physics-based models for vision such as reflectance models, photometric invariants, radiometric calibration. This course will also present algorithms for video/image analysis, transmission and scene interpretation. Topics such as image enhancement, restoration, stereo correspondence, pattern recognition, object segmentation and motion analysis will be covered.

This unit introduces engineering design via optimisation, i. e. finding the "best possible" solution to a particular problem. For example, an autonomous vehicle must find the fastest route between two locations over a road network; a biomedical sensing device must compute the most accurate estimate of important physiological parameters from noise-corrupted measurements; a feedback control system must stabilise and control a multivariable dynamical system (such as an aircraft) in an optimal fashion. The student will learn how to formulate a design in terms of a "cost function", when it is possible to find the "best" design via minimization of this "cost", and how to do so. The course will introduce widely-used optimisation frameworks including linear and quadratic programming (LP and QP), dynamic programming (DP), path planning with Dijkstra's algorithm, A*, and probabilistic roadmaps (PRMs), state estimation via Kalman filters, and control via the linear quadratic regulator (LQR) and Model Predictive Control (MPC). There will be constant emphasis on connections to real-world engineering problems in control, robotics, aerospace, biomedical engineering, and manufacturing.

Biomechatronics is the application of mechatronic engineering to human biology, and as such it forms an important subset of the overall biomedical engineering discipline. This unit focusses on a number of areas of interest including auditory and optical prostheses, artificial hearts and active and passive prosthetic limbs and examines the biomechatronic systems (hardware and signal processing) that underpin their operation.

Syllabus Summary: This course starts by providing a background to the signals and transforms required to understand modern sensors. It goes on to provide an overview of the workings of typical active sensors (Radar, Lidar and Sonar). It provides insight into basic sensing methods as well as aspects of interfacing and signal processing. It includes both background material and a number of case studies.
The course covers the following topics:
a) SIGNALS: Convolution, The Fourier Transform, Modulation (FM, AM, FSK, PSK etc), Frequency shifting (mixing)
b) PASSIVE SENSORS: Infrared Radiometers, Imaging Infrared, Passive Microwave Imaging, Visible Imaging and Image Intensifiers
c) ACTIVE SENSORS THE BASICS: Operational Principles, Time of flight (TOF) Measurement and Imaging of Radar, Lidar and Sonar, Radio Tags and Transponders, Range Tacking, Doppler Measurement, Phase Measurement
d) SENSORS AND THE ENVIRONMENT: Atmospheric Effects, Target Characteristics, Clutter Characteristics, Multipath
e) ACTIVE SENSORS: ADVANCED TECHNIQUES: Probability of Detection, Angle Measurement and Tracking, Combined Range/Doppler and Angle Tracking, Frequency Modulation and the Fast Fourier Transform, High Range Resolution, Wide Aperture Methods, Synthetic Aperture Methods (SAR)
Objectives: The course aims to provide students with a good practical knowledge of a broad range of sensor technologies, operational principles and relevant signal processing techniques.
Expected Outcomes: A good understanding of active sensors, their outputs and applicable signal processing techniques. An appreciation of the basic sensors that are available to engineers and when they should be used.

This unit aims to present a broad overview of the technologies associated with industrial and mobile robots. Major topics covered are sensing, mapping, navigation and control of mobile robots and kinematics and control of industrial robots. The subject consists of a series of lectures on robot fundamentals and case studies on practical robot systems. Material covered in lectures is illustrated through experimental laboratory assignments. The objective of the course is to provide students with the essential skills necessary to be able to develop robotic systems for practical applications.
At the end of this unit students will: be familiar with sensor technologies relevant to robotic systems; understand conventions used in robot kinematics and dynamics; understand the dynamics of mobile robotic systems and how they are modeled; have implemented navigation, sensing and control algorithms on a practical robotic system; apply a systematic approach to the design process for robotic systems; understand the practical application of robotic systems in manufacturing, automobile systems and assembly systems; develop the capacity to think critically and independently about new design problems; undertake independent research and analysis and to think creatively about engineering problems.
Course content will include: history and philosophy of robotics; hardware components and subsystems; robot kinematics and dynamics; sensors, measurements and perception; robotic architectures, multiple robot systems; localization, navigation and obstacle avoidance, robot planning; robot learning; robot vision and vision processing.

Artificial Intelligence (AI) is all about programming computers to perform tasks normally associated with intelligent behaviour. Classical AI programs have played games, proved theorems, discovered patterns in data, planned complex assembly sequences and so on. This unit of study will introduce representations, techniques and architectures used to build intelligent systems. It will explore selected topics such as heuristic search, game playing, machine learning, neural networks and probabilistic reasoning. Students who complete it will have an understanding of some of the fundamental methods and algorithms of AI, and an appreciation of how they can be applied to interesting problems. The unit will involve a practical component in which some simple problems are solved using AI techniques.

Machine learning is the process of automatically building mathematical models that explain and generalise datasets. It integrates elements of statistics and algorithm development into the same discipline. Data mining is a discipline within knowledge discovery that seeks to facilitate the exploration and analysis of large quantities for data, by automatic and semiautomatic means. This subject provides a practical and technical introduction to machine learning and data mining.
Topics to be covered include problems of discovering patterns in the data, classification, regression, feature extraction and data visualisation. Also covered are analysis, comparison and usage of various types of machine learning techniques and statistical techniques.