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MEC4406 Robotics and Machine Vision

Semester 2, 2022 Toowoomba On-campus
Units : 1
Faculty or Section : Faculty of Health, Engineering and Sciences
School or Department : School of Engineering
Student contribution band : Band 2
Grading basis : Graded
Version produced : 27 June 2022


Examiner: Tobias Low


Pre-requisite: MEC2401 or ELE2103 or Students must be enrolled in one of the following Programs: MENS or GCEN


Robotics and machine vision are specialised aspects of mechatronics. Robotics is the fusion of digital control with sensors, electronics and mechanisms to realise an application of value to manufacturing and other industries. Machine vision is an advanced sensing technique with applications in robotic guidance and automated systems. Key to the development of these systems is the design of mechatronic control systems embracing nonlinearities in both the system and the controller. This capstone course within the mechatronics major will utilise interdisciplinary knowledge from previous courses and combine it with more advanced methods and techniques to further develop and equip a mechatronic student with advanced system integration skills. It will prepare students to tackle robotic and automated system development in their future career using state-of-the-art and rapidly evolving technologies.

Kinematic methods are taught for the design and analysis of robot manipulators and similar mechanisms. Aspects of control theory cover modelling and synthesis of nonlinear controllers such as the saturating drives demanded for real life actuator systems. The vision syllabus ranges over the variety of image acquisition systems now available, leading on to methods of image analysis. Image filtering and edge detection are compared with more pragmatic methods and examples are taken from research outcomes such as a vision guidance system for agricultural tractors and mobile robot systems.

Course learning outcomes

The course objectives define the student learning outcomes for a course. On completion of this course, students should be able to:

  1. appreciate and analyse kinematics and positional control of articulated manipulators;
  2. design techniques for controlling mechanical systems;
  3. appreciate basics of machine vision concepts applicable to robotics.


Description Weighting(%)
1. Kinematics and inverse kinematics for robots 30.00
2. Control for robots 30.00
3. Robot programming principles 5.00
4. Introduction to sensing for robots 10.00
5. Machine vision for robots 25.00

Text and materials required to be purchased or accessed

There are no texts or materials required for this course.

Student workload expectations

To do well in this subject, students are expected to commit approximately 10 hours per week including class contact hours, independent study, and all assessment tasks. If you are undertaking additional activities, which may include placements and residential schools, the weekly workload hours may vary.

Assessment details

Approach Type Description Group
Weighting (%) Course learning outcomes
Assignments Design Design 1 Yes 20 1,2,3
Assignments Design Design 2 No 30 2,3,4,5
Examinations Non-invigilated Time limited online examinatn No 50 1,2,3,4,5
Date printed 27 June 2022