Science and Engineering

Robotics and autonomous systems

Overview

Research

The key goal of our discipline is to create robots that can operate in and interact with the world in the same complex ways as humans.

Our projects include and are applied to:

  • robotic vision
  • sustainable agriculture
  • lifelong autonomy for robots
  • neuroscience and robotics
  • flying, ground and underwater robotics.

Research strengths

Researchers from our discipline lead the Australian Research Council Centre of Excellence for Robotic Vision (ACRV), headquartered at QUT, which is creating a new generation of robots that can visually sense and understand complex and unstructured real-world environments.

We also play a major role in the Brisbane-based Australian Research Centre for Aerospace Automation (ARCAA), which investigates the various practical uses of unmanned aerial vehicles (UAVs).

Our areas of research interest include:

  • autonomous localisation, mapping and navigation
  • vision for robotics and automation
  • sensor networks
  • biologically or neurologically inspired robots
  • indoor and outdoor autonomous aerial robotics
  • field robotics for monitoring terrestrial ecosystems
  • compliant mechanisms for locomotion, manipulation and human robot interaction
  • learning and adaptive systems
  • unmanned aerial vehicles
  • health and medical robotics.

Online robotics courses

We offer free open online courses (MOOCs) in robotics and robotic vision. These courses are open to everyone, and provide a platform for an introduction to robotics research.

See all our available online courses, including courses in introductory robotics and robotic vision.

Projects

The Category 1 funded research projects we are currently leading are:

ARC Centre of Excellence for Robotic Vision

Project leader
Professor Peter Corke
Dates
2014-2020
Project summary

Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity and impending labour shortages, however, the work and workplaces of our most important industries are unstructured and changeable, and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them.

Our research will create the fundamental science and technologies that will allow robots to "see" as we do, and overcome the last barrier to the ubiquitous deployment of robots into society for the benefit of all.

ARC Centre of Excellence for Robotic Vision

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

Project leader
Dr Michael Milford
Dates
2014-2018
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.

Human cues for robot navigation

Project leader
Professor Gordon Wyeth
Dates
2014-2016
Project summary

The world has many navigational cues for the benefit of humans: sign posts, maps and the wealth of information on the internet. Yet, to date, robotic navigation has made little use of this abundant symbolic information as a resource.

This project will develop a robot navigation system that can navigate using information beyond the robot's range sensors by incorporating knowledge gained by reading room labels, following human route directions or interpreting maps found on the web.

This project will demonstrate the robot's navigation ability by comparing its performance with a human as it learns to find its way around campus by asking for directions, reading signs and maps, and searching the internet for clues.

Interdisciplinary and inter-institution projects

Some of the projects we are contributing to with other disciplines and institutions are:

  • Revolutionising protection against air pollution, 2015-2017

Student topics

Are you looking to further your career by pursuing study at a higher and more detailed level? We are currently looking for students to research in these broad themes:

Robotic vision

The Australian Centre for Robotic Vision (ACRV) has a large range of PhD opportunities in robotic vision spanning a range of topic areas:

  • robust vision, including novel vision sensing hardware and computational techniques
  • deep learning-based computer vision techniques for scene, object and place recognition
  • vision for human robot interaction and action recognition
  • semantic vision
  • visual servoing.

Find a supervisor in this research theme:

Agricultural robotics

The Australian Centre for Robotic Vision (ACRV) has a range of PhD opportunities in agricultural robotics including:

  • optimal robot vehicle design
  • robotic guidance and navigation
  • computer vision for weed and crop detection
  • vision for robotic crop manipulation.

Contact the supervisor for this research theme:

General robotics topics

The QUT Robotics laboratory has a range of project opportunities including:

  • autonomous localisation, mapping and navigation
  • vision for robotics and automation
  • sensor networks
  • biologically or neurologically inspired robots
  • indoor and outdoor autonomous aerial robotics
  • field robotics for monitoring terrestrial ecosystems
  • compliant mechanisms for locomotion
  • manipulation and human robot interaction
  • learning and adaptive systems
  • unmanned aerial vehicles
  • robotic control.

Find a project supervisor:

Contact

School of Electrical Engineering and Computer Science

  • Level 12, S Block, Room 1221
    Gardens Point

  • Postal address:
    School of Electrical Engineering and Computer Science
    GPO Box 2434
    Brisbane QLD 4001