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Robots and autonomous systems are changing the way we live, work and play.

They’re used in industries like health, transport, manufacturing, mining, agriculture, and even in energy and environmental sensing.

Our work focuses on the development of technology that can be used to improve our understanding and management of the world around us.

Real graduates


Our goal is to create robots that can operate in and interact with the world in the same complex ways as humans.

Our research has already led to the development of prototypes including:

  • autonomous robots for optimised underground mining operations
  • crop-harvesting robots
  • flying robots for large-scale infrastructure monitoring
  • ground-based mobile robots for sustainable agricultural productivity
  • on-water and underwater robots for environmental monitoring
  • robots to help surgeons perform minimally invasive surgery
  • social and health-related applications for humanoid robots.

Find out more about our research

Australian Centre for Robotic Vision

Researchers from our discipline lead the Australian Centre for Robotic Vision, headquartered at QUT, which is creating a new generation of robots.

These robots can understand their environment using the sense of vision, a missing capability preventing robots from performing useful tasks in complex and changing environments.

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Research Engineering Facility

The Research Engineering Facility (REF) provides specialist, cross-organisational research engineering services and is hosted within the Institute for Future Environments (IFE).

REF has a proud history of providing services for both manned and unmanned aircraft, and supports QUT’s core strengths in robotics and autonomous systems through design, engineering and operations of airborne, terrestrial and marine robots.

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Navigating under the forest canopy and in the urban jungle

ARC Project
Project leader

Associate Professor Felipe Gonzalez



Project summary

This project aims to develop a framework for unmanned aerial vehicles (UAV), which optimally balances localisation, mapping and other objectives in order to solve sequential decision tasks under map and pose uncertainty.

Expected outcomes include enabling UAVs to solve multiple objectives under map and pose uncertainty in GPS-denied environments. This will provide significant benefits, such as more responsive disaster management, bushfire monitoring and biosecurity, and improved environmental monitoring.

Superhuman place recognition with a unified model of human visual processing and rodent spatial memory

ARC Project
Project leader

Professor Michael Milford



Project summary

Current robotic and personal navigation systems leave much to be desired; GPS only works in open outdoor areas, lasers are expensive and cameras are highly sensitive to changing environmental conditions. In contrast, nature has evolved superb navigation systems.

This project aims to solve the challenging problem of place recognition, a key component of navigation, by modelling the visual recognition skills of humans and the rodent spatial memory system.

This project looks to combine the best understood and most capable components of place recognition in nature to create a whole more capable than its parts, produce advances in robotic and personal navigation technology and lead to breakthroughs in understandings of the brain.

View our student topics

Our topics

Are you looking to study at a higher or more detailed level? We are currently looking for students to research topics at a variety of study levels, including PhD, Masters, Honours or the Vacation Research Experience Scheme (VRES).View our topics

Our experts

We host an expert team of researchers and teaching staff, including Head of School and discipline leaders. Our discipline brings together a diverse team of experts who deliver world-class education and achieve breakthroughs in research.
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