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Autonomous Systems Clinic (ELEN90090)
Graduate courseworkPoints: 12.5On Campus (Parkville)
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About this subject
Contact information
Semester 1
Assoc. Prof. Gavin Buskes
Overview
Availability | Semester 1 |
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Fees | Look up fees |
AIMS:
Students work collaboratively in small groups to engineer an autonomous system that performs a specified task. This includes carrying out steps such as: task analysis; proposing multiple solutions; feasibility analysis through prototyping and computer-aided design; detailed design, construction, and testing of the chosen solution; and demonstrating the solution in a proving ground. The lectures will cast content from the pre-requisite subjects into the context of the task at hand, as well as covering additional topics relevant to the task. Each student group is expected to demonstrate initiative and independence while pursuing the goal of designing and building their autonomous system, with a focus of the subject being that students learn through hands-on experience, implementation, and verification.
INDICATIVE CONTENT:
Successful completion of the project requires the student to draw upon knowledge, understanding, and skills learned in the prerequisite subjects, namely:
• Embedded System Design - including topics such as: finite, extended, and hierarchical state machines; modelling cyber-physical systems; scheduling, multi-tasking, and real-time issues; interfacing to the analogue world.
• Control Systems - including topics such as: modelling; linearisation; feedback interconnections; proportional, integral, derivative (PID) control; actuator constraint considerations.
• Signal Processing - including topics such as: design and implementation of digital filters (low-, high-, band-, all- pass filters); ARMA systems; up-sampling and down-sampling.
Additional topics, specific to the task as hand, will be covered, such as: ideation, prototyping, and design practices; image processing and computer vision tools; software introductions; safety and failure analysis.
A range of materials, components, and fabrication facilities are provided, from which the students are expected to utilise a subset for designing and building their autonomous system, such as: electric motors, range sensors, camera, voltage converters, compute power, sheet wood, soldering stations, laser wood cutting, 3D printing. The task to be performed is motivated by a real-world application of autonomous systems, such as: operating in hazardous environments or performing repetitive tasks.
Intended learning outcomes
Upon completion of this subject, students should be able to:
- 1. Apply established engineering design methodologies to assist in the design and implementation of autonomous systems
- 2. Analyse and devise solutions to autonomous systems design problems, drawing upon fundamental principles underpinning autonomous systems from areas such as embedded systems, control systems and signal processing
- 3. Determine the integrity and reliability of structures, circuits, and algorithms, in order to robustly design against failure
- 4. Demonstrate competency with modern hardware components and software frameworks for autonomous systems through hands-on engagement
- 5. Apply systematic approaches to the conduct and management of a relatively complex electrical engineering design project in a small team
- 6. Communicate effectively with professionals across different engineering disciplines, through media such as concise technical reports and informational videos.
Generic skills
- Ability to realistically assess the scope and dimensions of a project or task, and employ appropriate planning and time management skills to achieve a substantial outcome
- Ability to undertake problem identification, formulation and solution
- Ability to utilise a systems approach to design and operational performance
- Capacity for independent critical thought, rational inquiry, creativity, innovation, and self-directed learning
- Ability to work effectively in a team environment in order to produce a satisfactory project outcome.
- Ability to communicate effectively, with the engineering team and with the community at large
Last updated: 31 January 2024