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ECE5178 · Intelligent robotics

Official Handbook

2026 Handbook6 credit pointsLevel 5Department of Electrical and Computer Systems Engineering

Last checked: 23 Aug 2026 UTC

Overview

Intelligent robotics concerns the melding of artificial perception, strategic reasoning and robotic action in potentially unstructured and time-varying environments to fulfil useful physical tasks, whether in industry or for security, healthcare, search and rescue or civil defence etc. This unit covers topics underpinning the above requirements, including sensors, sensor fusion, machine perception, environmental mapping/monitoring, path planning, localisation, mechanisms, artificial intelligence methodologies and application domains.

Areas of study: E6017 Master of Advanced Engineering - Specialisation: Robotic construction engineering E6017 Master of Advanced Engineering - Specialisation: Robotics engineering

Offerings

CampusTeaching periodMode
ClaytonSecond semesterSome activities have a choice of on-campus or online teaching activities (FLEXIBLE)

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

#AssessmentTypeWeightHurdle
1Programming exercisesExercise20%
2Laboratory project miletsonesProject40%
3Final lab demonstration/competitionDemonstration40%

Continuous assessment: 100% The assessments of this unit are designed to demonstrate the achievement of the advanced learning outcomes and standards expected of Master’s level coursework.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

prohibitions

Learning outcomes

  1. Describe the physical structure, sensing/actuation and programming required to develop an intelligent robot.
  2. Specify the mechanism, sensors and actuators of a robotic system.
  3. Design algorithms for robot systems.
  4. Integrate robotic systems and algorithms into a functioning physical robot system to perform specific tasks.
  5. Critically appraise robot systems developed by others.

Workload

The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-8 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.

ActivityDuration
Workshops24 hours
Laboratories36 hours

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