41013 Industrial Robotics
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Subject handbook information prior to 2025 is available in the Archives.
Credit points: 6 cp
Subject level:
Undergraduate
Result type: Grade, no marksRequisite(s): (48622 Embedded Mechatronics Systems AND 33230 Mathematics 2 AND (41039 Programming 1 OR 48430 Fundamentals of C Programming OR 37171 Introduction to Programming OR 48221 Engineering Computations OR 48023 Programming Fundamentals))
Description
This subject is an introduction to industrial robotics and the underlying algorithms and mathematics. Students develop an understanding of the representation of an industrial robot’s manipulator pose, kinematics and control. Students are given the opportunity to learn about the variety of robot manipulation tasks that are, or could potentially be performed by robots. In teams, students build their own simulated industrial robot. This includes the opportunity to model the robot arm then write control and planning software so that it can perform motion tasks.
This subject integrates safety into the design and working procedure, and encourages students to be aware of safety engineering to lower risk and prevent robot-related accidents from occurring. This subject also investigates ethical questions related to the inevitable increase of robots in industry and our daily lives. Discussions are encouraged around the implications these changes have on society, and specifically a human workforce that may no longer be required due to no fault of their own.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
1. | Describe mathematically and programmatically the relative position/ orientation of robots and objects. (D.1) |
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2. | Describe which safety systems can be used in robotics and reflect on safety engineering in relation to robotics. (B.1) |
3. | Reflect on your learning of what robots are, their advantages/disadvantages, their future role, and ethical implications of robots on humans in the global community. (B.1) |
4. | Model robots in a workspace to enable collision detection and avoidance. (C.1) |
5. | Describe, implement and apply straightforward path planning techniques used for industrial robots. (D.1) |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):
- Socially Responsible: FEIT graduates identify, engage, interpret and analyse stakeholder needs and cultural perspectives, establish priorities and goals, and identify constraints, uncertainties and risks (social, ethical, cultural, legislative, environmental, economics etc.) to define the system requirements. (B.1)
- Design Oriented: FEIT graduates apply problem solving, design and decision-making methodologies to develop components, systems and processes to meet specified requirements. (C.1)
- Technically Proficient: FEIT graduates apply abstraction, mathematics and discipline fundamentals, software, tools and techniques to evaluate, implement and operate systems. (D.1)
Contribution to the development of graduate attributes
Engineers Australia Stage 1 Competencies
This subject contributes to the development of the following Engineers Australia Stage 1 Competencies:
- 1.3. In-depth understanding of specialist bodies of knowledge within the engineering discipline.
- 2.1. Application of established engineering methods to complex engineering problem solving.
- 2.2. Fluent application of engineering techniques, tools and resources.
- 3.1. Ethical conduct and professional accountability.
- 3.3. Creative, innovative and pro-active demeanour.
Teaching and learning strategies
In this subject, students will be given the opportunity to learn through online lecture videos, interactive tutorial/lab classes, collaborative quizzes, external research and reflections. Students will be given formative feedback throughout the subject from academic staff whilst completing weekly hands-on lab exercises, assignments, and formative and summative feedback via online quizzes. Quizzes are low-stakes assessments that will both accumulate marks for the subject, but also require that if the student does not achieve the required benchmark, they will be required to re-complete the quiz as many times as necessary, until such time as they achieve the required understanding benchmark. Prior to attending classes, students are required to go through the allocated materials such as: watching the online lectures, reading the designated textbook and attempting the lab exercises. Regular in-class individual quizzes will assess the students’ level of understanding, and team quizzes will encourage collaborative learning amongst the group as students are given many opportunities for interaction. Collaborative lab exercises and group discussions will be facilitated by academic staff such that the guided robotics learning exercise promote inquiry. Labs and assignments are designed to present students with an opportunity to apply the theory from pre-work material, learn and reinforce practical skills, as well as reflect upon their own level of understanding.
Students are expected to attend all classes during the teaching session.
Content (topics)
- Foundations of robotics: kinematics and dynamics for manipulator and mobile robots.
- Motion planning: path and trajectory planning with collision detection/avoidance.
- Industrial robotics safety and ethical considerations.
Assessment
Assessment task 1: In-class Exercises
Intent: | This task involves exercises that are run in-class time, such as individual and collaborative quiz and tasks, and group discussions. The quizzes are intended to check the understanding of the pre-work so that the labs will be beneficial and everyone in the class is bringing knowledge which they can disseminate. The group discussions are intended to provide the opportunity for students to collaboratively share ideas about open-ended robotics questions. |
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Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 4 and 5 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1 and D.1 |
Type: | Quiz/test |
Groupwork: | Group, group and individually assessed |
Weight: | 25% |
Criteria: | Five (5) in-class exercises worth 5% each, totalling 25% of the subject mark. Generally, everyone gets different questions, values and sequences. Attempt the individual quiz once at the specified times during class:
Specific online formative feedback is returned soon after the class in which the quiz or exercise attempt is submitted. Generalised feedback will be given in class to address common difficulties students had with the questions. The quiz and exercises are run in class time with mobile phones, laptops, tablets or a lab PC. |
Assessment task 2: Lab Assignment 1
Intent: |
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Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3, 4 and 5 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): B.1, C.1 and D.1 |
Type: | Laboratory/practical |
Groupwork: | Individual |
Weight: | 20% |
Assessment task 3: Lab Assignment 2
Intent: |
Notes: Demonstration, technical, coding implementation, design and testing is done as a group and marked by tutors. Spark+ is used to self/group assess for the group portion. |
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Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3, 4 and 5 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): B.1, C.1 and D.1 |
Type: | Laboratory/practical |
Groupwork: | Group, group and individually assessed |
Weight: | 35% |
Assessment task 4: Viva Voce (Exit Interview)
Intent: |
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Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3, 4 and 5 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): B.1, C.1 and D.1 |
Type: | Presentation |
Groupwork: | Individual |
Weight: | 20% |
Minimum requirements
In order to pass the subject, a student must achieve an overall mark of 50% or more.
Required texts
There are no required textbooks.
Recommended texts
Several e-Learning resources will be provided on the subject Learning Management System (CANVAS/Blackboard).