This course provides an introduction to modern robotics. The focus is on robot kinematics, sensing techniques, localization, and mapping. Topics to be covered include robot spatial configuration, homogeneous coordinate transformation, mobile robot locomotion, mobile robot kinematics, robot motion control, sensors and perception, robot localization, simultaneous localization and mapping SLAM, robotic system architecture.The applied component of the course includes experimental work with a programmable mobile robotic platform equipped with sensors. This applied component is aimed at integrating sensor measurements to build a representation of the environment and perform a robotic task.
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Requisite and Incompatibility
To enrol in this course you must be studying Master of Engineering in Electrical Engineering or Master of Machine Learning and Computer Vision. Incompatible with ENGN4627.
Referenced entries (1)
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- ENGN4627 · 2027 · saved source not linked
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
Discuss the history, concepts and key components of robotics technologies.
Describe and compare various robot sensors and their perception principles that enable a robot to analyse their environment, reason and take appropriate actions toward the given goal.
Analyse and solve problems in spatial coordinate representation and spatial transformation, robot locomotion, kinematics, motion control, and localization and mapping.
Apply and demonstrate the learned knowledge and skills in practical robotics applications.
Critically appraise current research literature and conduct experiments with state of the art robotic algorithms on a robotic platform.
Effectively communicate engineering concepts and design decisions using a range of media.
Published offerings
Future offerings are indicative. Only recognised 2027 sessions with a published class number are offered in the enrolment demo.
| Year | Session | Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|---|---|
| 2027 | First Semester | 5145 | 22 Feb 2027 | 01 Mar 2027 | 31 Mar 2027 | 28 May 2027 | In Person | N/A |
| 2027 | Second Semester | 8746 | 26 Jul 2027 | 02 Aug 2027 | 31 Aug 2027 | 29 Oct 2027 | In Person | N/A |
| 2028 | First Semester | 6538 | 21 Feb 2028 | 28 Feb 2028 | 31 Mar 2028 | 26 May 2028 | In Person | N/A |
| 2028 | Second Semester | 9723 | 24 Jul 2028 | 31 Jul 2028 | 31 Aug 2028 | 27 Oct 2028 | In Person | N/A |
Complete offering text
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage. The list of offerings for future years is indicative only. Class summaries, if available, can be accessed by clicking on the View link for the relevant class number. 2027 2028 First Semester Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary 5145 22 Feb 2027 01 Mar 2027 31 Mar 2027 28 May 2027 In Person N/A Second Semester Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary 8746 26 Jul 2027 02 Aug 2027 31 Aug 2027 29 Oct 2027 In Person N/A First Semester Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary 6538 21 Feb 2028 28 Feb 2028 31 Mar 2028 26 May 2028 In Person N/A Second Semester Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary 9723 24 Jul 2028 31 Jul 2028 31 Aug 2028 27 Oct 2028 In Person N/A
Source evidence (1 saved copy)
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