Master of Robotics and Artificial Intelligence (EN52)
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Course Details
| Course duration (full-time): | 1.5 years |
|---|---|
| Total credit points: | 144 |
| Standard credit points/full-time semester: | 48 |
| Discipline coordinator: | Faculty of Engineering |
| Course contact: | +61 7 3138 2000, engineering@qut.edu.au |
| Delivery: | Gardens Point |
| CRICOS code: | 111159J |
| Faculty: | Faculty of Engineering |
Study costs
Domestic students may need to pay the Student Services and Amenities Fee (SSAF).
Advanced standing (credit)
Course Structure
| Code | Title | Offered In | Requisites |
|---|---|---|---|
| CAB420 | Machine Learning |
| Prerequisites: (CAB201 or EGB202 or CAB202 or ITD121 or IFN501 or IFN556 or Admission to (EN50 or EN55 or EN52 or EN56 or EN57 or EN62 or EN72)) or (192cps in SV03 or IV04 or MV05 or EV08) or (144cps in EV10) or (enrolment in IV53 or IV54 or IV55 or IV56 or IV58).Antirequisites: IFN580 |
| EGH431 | Advanced Dynamic System Principles |
| Prerequisites: (Admission to EN52 or EN56 or EN62 or EN72) or EGH445 |
| EGH432 | Foundations of Kinematics and Algorithms in Robotics |
| Prerequisites: (Admission to EN52 or EN56 or EN62 or EN72) or 192 credit points of completed study |
| EGH437 | Robot Anatomy |
| Prerequisites: Admission to (EN52 or EN62 or EN56 or EN72) or 192 credit points of completed study in EV01 or EV02Assumed knowledge as described in entry requirements of EN52 |
| ENN541 | Research Methods for Engineers |
| Antirequisites: IFN600, INN700, INN701Basic engineering maths is assumed knowledge. |
| Code | Title | Offered In | Requisites |
|---|---|---|---|
| ENN595-1 | Project 1 |
| Prerequisites: ((ENN541 or equivalent) and Admission to (EN50 or EN51 or EN52 or EN53 or EN55 or EN54 or EN56 or EN57 or EN71 or EN75 or EN72 or EN73 or EN76 or EN74 or EN77 or EN80)) OR ((EGH404 or equivalent) and Admission to (EV51 or EV52 or EV53 or EV54 or EV57)). ENN541 can be enrolled in the same teaching period as ENN595-1. |
| ENN581 | Robot Motion, Control and Planning |
| Prerequisites: EGH432 and EGH437 |
| ENN582 | Reinforcement Learning and Optimal Control |
| Prerequisites: EGH431Assumed knowledge from the undergraduate unit on state-space control, including state space, vector ODEs, some intuition about optimisation, and vector functions |
| ENN586 | Decision and Control |
| Prerequisites: EGH431Assumed knowledge from prior learning on state-space control, including state space, vector ODEs, some intuition about optimisation, and vector functions |
| ENN583 | Foundations of Robotic Vision |
| Prerequisites: CAB420 |
| Code | Title | Offered In | Requisites |
|---|---|---|---|
| ENN595-2 | Project 2 |
| Prerequisites: ENN595-1 |
| ENN519 | Entrepreneurship and Applications |
| Prerequisites: EGH437 or Admission to (EV10 or EN57). EGH437 can be enrolled in the same teaching period as ENN519. |
| ENN584 | Robot Systems |
| Prerequisites: (ENN581 and ENN586) or EGH445 |
| ENN585 | Advanced Machine Learning |
| Prerequisites: (ENN582 or CAB320) and ENN583 |