# Master of Automation and Robotics
Computer Systems Engineering Disciplines
# Compulsory courses
The following are compulsory for both the 120 and 180-point MRobotEng:
# Semester One: COMPSYS 726 Robotics and Intelligent Systems (15 points)
Robotics and intelligent systems, including: robot manipulators and mobile robots, navigation techniques, planning and programming of robot actions, sensors and actuators, kinematic analysis and may include topics in artificial intelligence, artificial neural nets, 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.
# Semester Two: COMPSYS 730 Robotics and Society (15 points)
Explores the moral, ethical and societal impacts of increasing automation in our society, and how both work and leisure will be impacted as robots become more commonplace. Topics also include legal issues, privacy, safety, standards, and indigenous and cultural issues and opportunities.
# Semesters One and Two: COMPSYS 792 Research Project (45 points)
# Non-technical elective courses
For both the 120 and 180-point MRobotEng, you will need to select one (15 points) of the following:
# Semester One: ENGGEN 732 Systems Thinking and Project Business Case
The business case as the tool of choice for many businesses for turning strategy into projects and the subsequent investment appraisals. Topics include systems thinking, the theory of constraints, value, cost/benefit analysis, quadruple bottom line, sensitivity analysis, risk analysis, investment appraisal, performance measurement and benefit realisation.
# Technical elective Courses
For the 180 point option, select up to six (90 points) of the following:
# Semester Two: COMPSYS 732 Mobile Autonomous Robotics
Techniques and principles for designing and developing mobile robots that interact autonomously with their environment. Topics include sensors and actuators, kinematic analysis, computer vision, state estimation and planning. Includes significant hands-on experience through the design and development of a mobile robot.
Prerequisite: 15 points from COMPSCI 230, 235, COMPSYS 302, ENGSCI 331, MECHENG 313, SOFTENG 306
# Semester Two: SOFTENG 762 Robotics Process Automation
Covers the fundamentals of Robotic Process Automation (RPA) systems. Students explore what RPA is and where it is useful, how RPA fits into current information technology setups, extracting and manipulating data from both external and internal sources, generating reports and statistics, and orchestrating multi-robot installations.
Prerequisite: SOFTENG 306
# Semester One: COMPSCI 767 Intelligent Agents
An introduction to the design, implementation and use of intelligent software agents (e.g., knowbots, softbots etc). Reviews standard artificial intelligence problem-solving paradigms (e.g., planning and expert systems) and knowledge representation formalisms (e.g., logic and semantic nets). Surveys agent architectures and multi-agent frameworks. Recommended preparation: COMPSCI 367.
# Semester One: COMPSCI 773 Intelligent Vision Systems
Computational methods and techniques for computer vision are applied to real-world problems such as 2/3D face biometrics, autonomous navigation, and vision-guided robotics based on 3D scene description. A particular feature of the course work is the emphasis on complete system design. Recommended preparation: COMPSCI 373 and 15 points at Stage II in Mathematics.
# Semester Two: COMPSCI 760 Data mining and Machine Learning
An overview of the learning problem and the view of learning by search. Techniques for learning such as: decision tree learning, rule learning, exhaustive learning, Bayesian learning, genetic algorithms, reinforcement learning, neural networks, explanation-based learning and inductive logic programming. Experimental methods necessary for understanding machine learning research. Recommended preparation: COMPSCI 361 or 762
# Semester Two: COMPSCI 761 Advanced Topics in Artificial Intelligence
The cornerstones of AI: representation, utilisation, and acquisition of knowledge. Taking a real world problem and representing it in a computer so that the computer can do inference. Utilising this knowledge and acquiring new knowledge is done by search which is the main technique behind planning and machine learning. Research frontiers in artificial intelligence. Recommended preparation: COMPSCI 220, 225.
# Planning
# Semester One
# Semester One: COMPSYS 726 Robotics and Intelligent Systems (15 points)
# Semester One: ENGGEN 732 Systems Thinking and Project Business Case (15 points)
# Semester One: COMPSCI 773 Intelligent Vision Systems (15 points)
# Semester One: COMPSCI 767 Intelligent Agents (15 points)
# Semester Two
# Semester Two: COMPSYS 730 Robotics and Society (15 points)
# Semester Two: SOFTENG 762 Robotics Process Automation (15 points)
# Semester Two: COMPSCI 760 Data mining and Machine Learning (15 points)
# Semester Two: COMPSCI 761 Advanced Topics in Artificial Intelligence (15 points)
# Semester Two: SOFTENG 762 Robotics Process Automation (15 points)
# Semester Three
# Semesters One and Two: COMPSYS 792 Research Project (45 points)
Extras:
# COMPSYS 202 - 15 Points
Object Oriented Design and Programming
A project-based course with extensive hands-on programming experience. Includes: an introduction to object oriented design including UML, sequence diagrams, use-case analysis; an introduction to object oriented programming in a modern high level language, algorithms, data abstraction and elementary data structures.
Prerequisite: ENGGEN 131 or ENGSCI 131
Restriction: MECHENG 270
# COMPSYS 303 - 15 Points
Microcomputers and Embedded Systems
Embedded applications. Microprocessors, microcontrollers, architecture, organisation, programming memories, I/O interfacing. Sensors, actuators, analog interfaces. Hardware/Software partitioning and interfacing. Concurrency. Implementing data transformations and reactivity. Case studies.
Prerequisite: COMPSYS 201, and COMPSYS 202 or SOFTENG 251 or 281
# COMPSYS 723 - 15 Points
Embedded Systems Design
Concurrency and models of computation, task models and race conditions, real-time operating systems based approach, synchronous approach, safe state machines, key properties: determinism and reactivity, SoPC and MPSoC, cyber-physical embedded systems, static analysis techniques, case studies in smart grid, automotive, medical devices and the like.
Prerequisite: COMPSYS 303 or 304 or SOFTENG 370
Restriction: COMPSYS 402, 403, 727
# COMPSYS 704 - 15 Points
Advanced Embedded Systems - Level 9
Selected advanced topics from current research in embedded systems such as: embedded systems based on formal models of computation; centralised and distributed architectures for embedded systems; static and dynamic embedded systems; languages and frameworks for distributed embedded systems; actor and agent systems; verification. Includes a significant individual research project.
Prerequisite: COMPSYS 723, and 202 or SOFTENG 281
# COMPSYS 727 - 15 Points
Model-based Embedded Systems Design - Level 9
Traditional and advanced methods of embedded systems modelling and design, models of computation, hardware-software co-design, real-time and safety-critical systems, principles of embedded and real-time operating systems, design using the real-time operating systems approach and the synchronous approach, use of the networks in real-time embedded systems. The assessment includes a significant individual research project.
Prerequisite: COMPSYS 303
Restriction: COMPSYS 402, 403, 723
# Plan 03: Just the Course
Compulsory:
Semester One:
COMPSYS 726 Robotics and Intelligent Systems (15 points)
ENGGEN 732 Systems Thinking and Project Business Case
Semester Two:
COMPSYS 730 Robotics and Society (15 points)
Semesters One and Two: COMPSYS 792 Research Project (45 points)
Electives:
Semester one:
MECHENG 709 Industrial Automation
COMPSCI 765 Interactive Cognitive Systems
COMPSCI 767 Intelligent Agents
COMPSCI 773 Intelligent Vision Systems
Semester two:
COMPSYS 732 Mobile Autonomous Robotics
ELECTENG 704 Advanced Control Systems
COMPSCI 761 Advanced Topics in Artificial Intelligence
# Plan 04: The Course + Embedded Systems
Semester One:
COMPSYS 726 Robotics and Intelligent Systems (15 points)
ENGGEN 732 Systems Thinking and Project Business Case
COMPSCI 773 Intelligent Vision Systems
COMPSYS 303 - Microcomputers and Embedded Systems
Semester Two:
COMPSYS 732 Mobile Autonomous Robotics
COMPSYS 730 Robotics and Society (15 points)
SOFTENG 762 Robotics Process Automation
Electives:
Semester Three:
MECHENG 709 Industrial Automation
COMPSCI 765 Interactive Cognitive Systems
COMPSCI 767 Intelligent Agents
Semester Four:
ELECTENG 704 Advanced Control Systems
COMPSCI 761 Advanced Topics in Artificial Intelligence
Semesters One and Two: COMPSYS 792 Research Project (45 points)
- COMPSYS 727 - Model-based Embedded Systems Design - Level 9
Semester One and Two:
Semesters One and Two: COMPSYS 792 Research Project (45 points)
# Plan 05: The Course + Embedded Systems
Semester One:
ENGGEN 732 Systems Thinking and Project Business Case
COMPSCI 773 Intelligent Vision Systems
COMPSYS 303 - Microcomputers and Embedded Systems
Semester Two:
COMPSYS 732 Mobile Autonomous Robotics
COMPSYS 730 Robotics and Society (15 points)
SOFTENG 762 Robotics Process Automation
Electives:
Semester Three:
MECHENG 709 Industrial Automation
COMPSCI 765 Interactive Cognitive Systems
COMPSCI 767 Intelligent Agents
- COMPSYS 727 - Model-based Embedded Systems Design - Level 9
Semester Four:
ELECTENG 704 Advanced Control Systems
COMPSCI 761 Advanced Topics in Artificial Intelligence
Semesters One and Two: COMPSYS 792 Research Project (45 points)
Semester One and Two:
Semesters One and Two: COMPSYS 792 Research Project (45 points)
* COMPSYS 727 - Model-based Embedded Systems Design - Level 9
Model-based Embedded Systems Design - Level 9
Traditional and advanced methods of embedded systems modelling and design, models of computation, hardware-software co-design, real-time and safety-critical systems, principles of embedded and real-time operating systems, design using the real-time operating systems approach and the synchronous approach, use of the networks in real-time embedded systems. The assessment includes a significant individual research project.
Prerequisite: COMPSYS 303
Restriction: COMPSYS 402, 403, 723
# Plan 06: The Course + Embedded Systems - Starting on semester 2
Semester One (2):
COMPSYS 732 Mobile Autonomous Robotics
COMPSYS 730 Robotics and Society (15 points)
COMPSYS 303 - Microcomputers and Embedded Systems
Maybe:
SOFTENG 762 Robotics Process Automation
Semester Two (1):
ENGGEN 731 Agile and Lean Project Management (15 points)
COMPSCI 773 Intelligent Vision Systems
MECHENG 709 Industrial Automation
Electives:
Semester Three(2):
COMPSIC 760 Machine Learning (15 points)
COMPSIC 761 Advanced Topics in Artificial Intelligence (15 points)
Semesters One and Two: COMPSYS 792 Research Project (45 points)
- COMPSYS 727 - Model-based Embedded Systems Design - Level 9
Semester Four:
Semesters One and Two: COMPSYS 792 Research Project (45 points)
Semester One and Two:
Semesters One and Two: COMPSYS 792 Research Project (45 points)
* COMPSYS 727 - Model-based Embedded Systems Design - Level 9
Model-based Embedded Systems Design - Level 9
Traditional and advanced methods of embedded systems modelling and design, models of computation, hardware-software co-design, real-time and safety-critical systems, principles of embedded and real-time operating systems, design using the real-time operating systems approach and the synchronous approach, use of the networks in real-time embedded systems. The assessment includes a significant individual research project.
Prerequisite: COMPSYS 303
Restriction: COMPSYS 402, 403, 723
# Plan 07: The Course + Embedded Systems - Starting on semester 2
🔴 = Compulsory
🔵 = Elective
🔵 🔴 = Replacing a Compulsory
Semester One (2):
🔵COMPSYS 732 Mobile Autonomous Robotics
🔴COMPSYS 730 Robotics and Society (15 points)
Semester Two (1):
🔴ENGGEN 731 Agile and Lean Project Management (15 points)
🔵COMPSCI 773 Intelligent Vision Systems
🔵MECHENG 709 Industrial Automation
🔵 🔴COMPSYS 723 - Embedded Systems Design
Electives:
Semester Three(2):
COMPSIC 760 Machine Learning (15 points)
COMPSIC 761 Advanced Topics in Artificial Intelligence (15 points)
Semesters One and Two: COMPSYS 792 Research Project (45 points)
- COMPSYS 727 - Model-based Embedded Systems Design - Level 9
Semester Four:
Semesters One and Two: COMPSYS 792 Research Project (45 points)
Semester One and Two:
Semesters One and Two: COMPSYS 792 Research Project (45 points)
* COMPSYS 727 - Model-based Embedded Systems Design - Level 9
Model-based Embedded Systems Design - Level 9
Traditional and advanced methods of embedded systems modelling and design, models of computation, hardware-software co-design, real-time and safety-critical systems, principles of embedded and real-time operating systems, design using the real-time operating systems approach and the synchronous approach, use of the networks in real-time embedded systems. The assessment includes a significant individual research project.
Prerequisite: COMPSYS 303
Restriction: COMPSYS 402, 403, 723