Algorithmic Robotics (12062.1)
Please note these are the 2026 details for this unit
Available teaching periods | Delivery mode | Location |
---|---|---|
View teaching periods | On-Campus |
Bruce, Canberra |
EFTSL | Credit points | Faculty |
0.125 | 3 | Faculty Of Science And Technology |
Discipline | Study level | HECS Bands |
Academic Program Area - Technology | Level 3 - Undergraduate Advanced Unit | Band 2 2021 (Commenced After 1 Jan 2021) Band 3 2021 (Commenced Before 1 Jan 2021) |
The unit provides a critical understanding of algorithmic thinking and its application in robotics. Within the Sense, Think, Act loop framework, the unit will delve deep into key algorithmic concepts and techniques, such as recursive state estimation techniques and Gaussian filters, including linear and nonlinear filters such as the Extended Kalman Filter. Key algorithmic concepts in robot localisation and mapping, including Simultaneous Localisation and Mapping (SLAM) will be discussed in detail which have paved the way for self-driving cars and other autonomous technologies. Additionally, the unit will provide a clear understanding of foundational algorithmic concepts in Planning and Control, including Markov Decision Processes and Partially Observable Markov Decision Processes.
1. Understand algorithmic thinking and related robotics topics such as the Sense, Think, Act loop;
2. Understand recursive state estimation techniques, and Gaussian Filters, including linear and nonlinear filters such as the Extended Kalman Filter;
3. Understand key robot motion and perception algorithms used in modern robotics;
4. Apply key algorithmic concepts in the application of robot localisation and mapping, including Simultaneous Localisation and Mapping; and
5. Understand foundational algorithmic concepts in Planning and Control, including Markov Decision Processes and Partially Observable Markov Decision Processes.
1. UC graduates are professional - communicate effectively
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
1. UC graduates are professional - work collaboratively as part of a team, negotiate, and resolve conflict
2. UC graduates are global citizens - communicate effectively in diverse cultural and social settings
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development
6698 Discrete Mathematics
Learning outcomes
Upon successful completion of this unit, students will be able to:1. Understand algorithmic thinking and related robotics topics such as the Sense, Think, Act loop;
2. Understand recursive state estimation techniques, and Gaussian Filters, including linear and nonlinear filters such as the Extended Kalman Filter;
3. Understand key robot motion and perception algorithms used in modern robotics;
4. Apply key algorithmic concepts in the application of robot localisation and mapping, including Simultaneous Localisation and Mapping; and
5. Understand foundational algorithmic concepts in Planning and Control, including Markov Decision Processes and Partially Observable Markov Decision Processes.
Graduate attributes
1. UC graduates are professional - employ up-to-date and relevant knowledge and skills1. UC graduates are professional - communicate effectively
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
1. UC graduates are professional - work collaboratively as part of a team, negotiate, and resolve conflict
2. UC graduates are global citizens - communicate effectively in diverse cultural and social settings
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development
Prerequisites
12058 Robot Dynamics AND6698 Discrete Mathematics
Corequisites
None.Incompatible units
None.Equivalent units
None.Assumed knowledge
None.
Availability for enrolment in 2026 is subject to change and may not be confirmed until closer to the teaching start date.
Year | Location | Teaching period | Teaching start date | Delivery mode | Unit convener |
---|---|---|---|---|---|
2026 | Bruce, Canberra | Semester 1 | 02 February 2026 | On-Campus | Dr Luke Nguyen-Hoan |
2026 | Bruce, Canberra | Semester 2 | 27 July 2026 | On-Campus | Dr Luke Nguyen-Hoan |
The information provided should be used as a guide only. Timetables may not be finalised until week 2 of the teaching period and are subject to change. Search for the unit
timetable.