Note: This is an archived Handbook entry from 2016.
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2016:Semester 2, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 36 hours of lectures, 24 hours of tutorials and laboratory work. |
Total Time Commitment:
Study Period Commencement:
Semester 1, Semester 2
Plus ONE of the following -
Study Period Commencement:
|Recommended Background Knowledge:||None|
|Non Allowed Subjects:||None|
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.
It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability
CoordinatorAssoc Prof Denny Oetomo
The subject aims to introduce the students to the automation technologies, specifically: robotics and process automation. The use of robots and automated systems in carrying out various tasks will be discussed and the fundamental computational techniques associated with the operation of a robotic manipulator and a general automated system will be introduced. The subject will familiarise the students with the roles, strengths, and capabilities of robotics and automation technologies, as well as how to achieve the said capabilities.
Artificial Intelligence and Computer Vision (8 hours of lectures and 3 hours of tutorials): Introduction to neural network and vision-based systems in automation.
Networked control and optimization (6 hours of lectures and 3 hours of tutorials): Concepts for the automated factory environment with networked stations and networked control, use of Ethernet, wireless technology and protocols, safety and security issues.
INTENDED LEARNING OUTCOMES (ILO)
Having completed this unit the student is expected to have the skills to:
|Breadth Options:|| |
This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
On completion of this subject students should have the following skills:
LEARNING AND TEACHING METHODS
The subject will be delivered through a combination of lectures and tutorials. The tutorials will initially cover the exercises to complement the lecture material. When a level of proficiency is attained, the subject will further focus on the discussion of the design of an automation system. The students will also engage in three assignments throughout the subject.
INDICATIVE KEY LEARNING RESOURCES
Students will have access to lecture notes, lecture slides, tutorials, tutorial solutions and assignments on the LMS site.
Doctor of Philosophy - Engineering |
Master of Philosophy - Engineering
B-ENG Mechanical Engineering stream |
Master of Engineering (Mechanical)
Master of Engineering (Mechatronics)
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