ENN584 Robot Systems
To view more information for this unit, select Unit Outline from the list below. Please note the teaching period for which the Unit Outline is relevant.
| Unit code: | ENN584 |
|---|---|
| Prerequisite(s): | (ENN581 and ENN586) or EGH445 |
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
| CSP student contribution | $1,118 |
| Domestic tuition unit fee | $3,672 |
| International unit fee | $5,040 |
Unit Outline: Semester 1 2024, Gardens Point, Internal
| Unit code: | ENN584 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | ENN581 and ENN586 |
| Coordinator: | Will Browne | will.browne@qut.edu.au |
Overview
The unit will be focused on two main aspects of robotic systems, 1) simultaneous localization and mapping (SLAM) and 2) Mobile Robotics. Mapping and localization are key capabilities for artificial agents that move (e.g. robots, autonomous vehicles, or drones). The unit will provide a theoretical and practical foundation for developing and implementing mapping and localization systems for a range of robotics-related applications. Further, half of the robotics field concerns robots and systems that move: mobile service and consumer robots, social robots, drones, autonomous vehicles, and unmanned autonomous ground vehicles in sectors including mining, agriculture, ports, planetary exploration etc. Therefore, the second half of the unit will provide students with an overview of the key concepts in mobile robots and autonomous systems, while also providing the opportunity to explore the human-machine interaction in areas such as social robotics.
Learning Outcomes
On successful completion of this unit you will be able to:
- Identify and reflect on key theoretical and practical characteristics of different mapping and localization approaches.
- Apply mapping and localization methods on a robot/ dataset and perform appropriate engineering solutions to maximize function.
- Analyse critically and communicate how mobile robots and autonomous systems are currently used in real-world settings.
- Analyse critically and select key hardware/software components of a mobile robot or autonomous system based on a given deployment environment and task requirements.
Content
Interactive lectures will focus on the following content :
- Foundation on SLAM Concepts.
- Advance SLAM Techniques for Challenging Environments.
- Software and Algorithms for Mobile Robotics.
- Mobile Robots and Applications.
- Human-Machine Interaction and Social Robotics.
Learning Approaches
You can expect the following activities in this unit:
- Lectures by well-experienced teaching staff and the opportunity to interact with the lecturers and get deep feedback on your research ideas and progress.
- Tutorials
- Practicals will be based on providing a hands-on experience in both robot localization and mapping, and mobile robot deployment (with standard kits remotely or with virtual robots in a simulation environment.)
Feedback on Learning and Assessment
Feedback will be given regularly throughout the semester by tutors and lecturers, following your oral and written presentations early, mid-semester and at the end of the semester. Tutors and lecturers are available for feedback and advice in the lab sessions.
Assessment
Overview
Assessment in this unit includes quizzes to validate the knowledge gained on the SLAM approaches and laboratory/practical sessions to assess the learning outcomes related to SLAM and software as used in mobile robotics. Furthermore, you will be required to produce a written report on mobile robot specifications.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Quizzes
Interactive, computer-based coding about SLAM and related software as applied to mobile robots.
Assessment: Mobile Robot Specification (Written report)
This is an authentic report on robot systems and mobile robot specification. This report will use knowledge gathered in this unit to specify a mobile robot design, including description of motivation and justification for hardware and sensor choices made with consideration of the robot's need to function in a specified real-world environment.
Assessment: Laboratory/ Practical
The practical sessions involve the completion of short programming tasks that implement algorithms in MATLAB or Python software. These algorithms contribute to the deployment of a full SLAM system and also the deployment of a mobile robot including hardware and sensor components suitable for operation in a specified environment.
Academic Integrity
Students are expected to engage in learning and assessment at QUT with honesty, transparency and fairness. Maintaining academic integrity means upholding these principles and demonstrating valuable professional capabilities based on ethical foundations.
Failure to maintain academic integrity can take many forms. It includes cheating in examinations, plagiarism, self-plagiarism, collusion, and submitting an assessment item completed by another person (e.g. contract cheating). It can also include providing your assessment to another entity, such as to a person or website.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Further details of QUT’s approach to academic integrity are outlined in the Academic integrity policy and the Student Code of Conduct. Breaching QUT’s Academic integrity policy is regarded as student misconduct and can lead to the imposition of penalties ranging from a grade reduction to exclusion from QUT.
Resources
You have access to lab spaces and workshops at QUT and can use a range of tools after receiving an induction.
Learning material in this unit will be managed from its Canvas site.
Risk Assessment Statement
You will undertake lectures and tutorials in the traditional classrooms and lecture theatres. As such, there are no extraordinary workplace health and safety issues associated with these components of the unit.
You will be required to undertake practical sessions in the laboratory under the supervision of the lecturer and technical staff of the School. In any laboratory practicals you will be advised of the requirements of safe and responsible behaviour and will be required to wear appropriate protective items (e.g. closed shoes).
You will undergo a health and safety induction before the commencement of the practical sessions and will be issued with a safety induction card. If you do not have a safety induction card you will be denied access to laboratories.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.EN52 Master of Robotics and Artificial Intelligence
- Demonstrate and apply advanced and specialist discipline knowledge, concepts and practices in Robotics and AI
Relates to: Quizzes, Mobile Robot Specification (Written report), Laboratory/ Practical - Critically analyse, evaluate and apply appropriate methods to Robotics and AI problems to achieve research-informed solutions
Relates to: Mobile Robot Specification (Written report), Laboratory/ Practical - Apply systematic approaches to plan, design, execute and manage projects in Robotics and AI
Relates to: Laboratory/ Practical - Communicate complex information effectively and succinctly in oral and written form for diverse purposes and audiences
Relates to: Mobile Robot Specification (Written report)
EN72 Master of Advanced Robotics and Artificial Intelligence
- Demonstrate and apply advanced and specialist discipline knowledge, concepts and practices in Advanced Robotics and AI and Data Analytics domains
Relates to: Quizzes, Mobile Robot Specification (Written report), Laboratory/ Practical - Critically analyse, evaluate and apply appropriate methods to problems to achieve research-informed solutions in Advanced Robotics and AI and Data Analytics domains
Relates to: Mobile Robot Specification (Written report), Laboratory/ Practical - Apply systematic approaches to plan, design, execute and manage projects in Advanced Robotics and AI and Data Analytics domains
Relates to: Laboratory/ Practical - Communicate complex information effectively and succinctly in oral and written form for diverse purposes and audiences
Relates to: Mobile Robot Specification (Written report)
EN79 Graduate Diploma in Engineering Studies
- Demonstrate and apply advanced discipline knowledge, concepts and practices as they relate to contemporary Engineering practice
Relates to: Quizzes, Mobile Robot Specification (Written report), Laboratory/ Practical - Analyse and evaluate Engineering problems using technical approaches informed by contemporary practice and leading edge research to achieve innovative, critically informed solutions
Relates to: Mobile Robot Specification (Written report), Laboratory/ Practical - Apply innovative, systematic approaches to plan, design, deliver and manage Engineering projects in a way that assures sustainable outcomes over their whole lifecycle
Relates to: Laboratory/ Practical - Effectively communicate Engineering problems, related complex data and information, and solutions in contemporary professional formats for diverse purposes and audiences
Relates to: Mobile Robot Specification (Written report)
Unit Outline: Semester 1 2024, Online
| Unit code: | ENN584 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | ENN581 and ENN586 |
Overview
The unit will be focused on two main aspects of robotic systems, 1) simultaneous localization and mapping (SLAM) and 2) Mobile Robotics. Mapping and localization are key capabilities for artificial agents that move (e.g. robots, autonomous vehicles, or drones). The unit will provide a theoretical and practical foundation for developing and implementing mapping and localization systems for a range of robotics-related applications. Further, half of the robotics field concerns robots and systems that move: mobile service and consumer robots, social robots, drones, autonomous vehicles, and unmanned autonomous ground vehicles in sectors including mining, agriculture, ports, planetary exploration etc. Therefore, the second half of the unit will provide students with an overview of the key concepts in mobile robots and autonomous systems, while also providing the opportunity to explore the human-machine interaction in areas such as social robotics.
Learning Outcomes
On successful completion of this unit you will be able to:
- Identify and reflect on key theoretical and practical characteristics of different mapping and localization approaches.
- Apply mapping and localization methods on a robot/ dataset and perform appropriate engineering solutions to maximize function.
- Analyse critically and communicate how mobile robots and autonomous systems are currently used in real-world settings.
- Analyse critically and select key hardware/software components of a mobile robot or autonomous system based on a given deployment environment and task requirements.
Content
Interactive lectures will focus on the following content :
- Foundation on SLAM Concepts.
- Advance SLAM Techniques for Challenging Environments.
- Software and Algorithms for Mobile Robotics.
- Mobile Robots and Applications.
- Human-Machine Interaction and Social Robotics.
Learning Approaches
You can expect the following activities in this unit:
- Lectures by well-experienced teaching staff and the opportunity to interact with the lecturers and get deep feedback on your research ideas and progress.
- Tutorials
- Practicals will be based on providing a hands-on experience in both robot localization and mapping, and mobile robot deployment (with standard kits remotely or with virtual robots in a simulation environment.)
Feedback on Learning and Assessment
Feedback will be given regularly throughout the semester by tutors and lecturers, following your oral and written presentations early, mid-semester and at the end of the semester. Tutors and lecturers are available for feedback and advice in the lab sessions.
Assessment
Overview
Assessment in this unit includes quizzes to validate the knowledge gained on the SLAM approaches and laboratory/practical sessions to assess the learning outcomes related to SLAM and software as used in mobile robotics. Furthermore, you will be required to produce a written report on mobile robot specifications.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Quizzes
Interactive, computer-based coding about SLAM and related software as applied to mobile robots.
Assessment: Mobile Robot Specification (Written report)
This is an authentic report on robot systems and mobile robot specification. This report will use knowledge gathered in this unit to specify a mobile robot design, including description of motivation and justification for hardware and sensor choices made with consideration of the robot's need to function in a specified real-world environment.
Assessment: Laboratory/ Practical
The practical sessions involve the completion of short programming tasks that implement algorithms in MATLAB or Python software. These algorithms contribute to the deployment of a full SLAM system and also the deployment of a mobile robot including hardware and sensor components suitable for operation in a specified environment.
Academic Integrity
Students are expected to engage in learning and assessment at QUT with honesty, transparency and fairness. Maintaining academic integrity means upholding these principles and demonstrating valuable professional capabilities based on ethical foundations.
Failure to maintain academic integrity can take many forms. It includes cheating in examinations, plagiarism, self-plagiarism, collusion, and submitting an assessment item completed by another person (e.g. contract cheating). It can also include providing your assessment to another entity, such as to a person or website.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Further details of QUT’s approach to academic integrity are outlined in the Academic integrity policy and the Student Code of Conduct. Breaching QUT’s Academic integrity policy is regarded as student misconduct and can lead to the imposition of penalties ranging from a grade reduction to exclusion from QUT.
Resources
You have access to lab spaces and workshops at QUT and can use a range of tools after receiving an induction.
Learning material in this unit will be managed from its Canvas site.
Risk Assessment Statement
You will undertake lectures and tutorials in the traditional classrooms and lecture theatres. As such, there are no extraordinary workplace health and safety issues associated with these components of the unit.
You will be required to undertake practical sessions in the laboratory under the supervision of the lecturer and technical staff of the School. In any laboratory practicals you will be advised of the requirements of safe and responsible behaviour and will be required to wear appropriate protective items (e.g. closed shoes).
You will undergo a health and safety induction before the commencement of the practical sessions and will be issued with a safety induction card. If you do not have a safety induction card you will be denied access to laboratories.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.EN52 Master of Robotics and Artificial Intelligence
- Demonstrate and apply advanced and specialist discipline knowledge, concepts and practices in Robotics and AI
Relates to: Quizzes, Mobile Robot Specification (Written report), Laboratory/ Practical - Critically analyse, evaluate and apply appropriate methods to Robotics and AI problems to achieve research-informed solutions
Relates to: Mobile Robot Specification (Written report), Laboratory/ Practical - Apply systematic approaches to plan, design, execute and manage projects in Robotics and AI
Relates to: Laboratory/ Practical - Communicate complex information effectively and succinctly in oral and written form for diverse purposes and audiences
Relates to: Mobile Robot Specification (Written report)
EN79 Graduate Diploma in Engineering Studies
- Demonstrate and apply advanced discipline knowledge, concepts and practices as they relate to contemporary Engineering practice
Relates to: Quizzes, Mobile Robot Specification (Written report), Laboratory/ Practical - Analyse and evaluate Engineering problems using technical approaches informed by contemporary practice and leading edge research to achieve innovative, critically informed solutions
Relates to: Mobile Robot Specification (Written report), Laboratory/ Practical - Apply innovative, systematic approaches to plan, design, deliver and manage Engineering projects in a way that assures sustainable outcomes over their whole lifecycle
Relates to: Laboratory/ Practical - Effectively communicate Engineering problems, related complex data and information, and solutions in contemporary professional formats for diverse purposes and audiences
Relates to: Mobile Robot Specification (Written report)