Queensland University of Technology
🇦🇺 AU
Papers
728
Total Citations
37,949
H-Index
80
Researchers
563
About
Queensland University of Technology (QUT) has established itself as a world-leading research institution at the intersection of robotics, artificial intelligence, and intelligent systems, with a particularly distinguished reputation in mobile robotics and autonomous navigation. Based in Brisbane, Australia, QUT's research portfolio spans foundational AI theory through to real-world robotic applications, making it an exceptional destination for both emerging scholars and industry collaborators. QUT's most celebrated contributions lie in biologically inspired robotics and visual navigation. Landmark systems such as SeqSLAM and RatSLAM — the latter drawing on computational models of the rodent hippocampus — have fundamentally shaped how autonomous robots perceive and navigate dynamic environments across seasons and lighting extremes, accumulating nearly 1,400 combined citations. The institution's work on Visual Place Recognition, synthesized in a widely cited survey, has become essential reading for the mobile robotics community. The foundational textbook *Robotics, Vision and Control*, now in multiple editions with over 1,100 combined citations, reflects QUT's commitment to rigorous, accessible knowledge dissemination. Beyond navigation, QUT researchers have driven major advances in agricultural robotics through the DeepFruits system, robotic grasping via the influential GG-CNN framework, and deep learning methodology through a comprehensive review now cited nearly 7,500 times. The institution also pursues cutting-edge work in trustworthy AI for healthcare, smart cities, and multi-target tracking. Home to the Australian Centre for Robotic Vision (ACRV), QUT brings together world-class faculty, state-of-the-art facilities, and strong industry partnerships. Prospective students and collaborators will find an intellectually vibrant environment where foundational research meets transformative real-world impact.
Research Focus
Key Achievements
Top Papers
- 1
- 225th Anniversary Article: Engineering Hydrogels for Biofabrication1,874 citations · 2013
- 3DeepFruits: A Fruit Detection System Using Deep Neural Networks1,079 citations · 2016
- 4Visual Place Recognition: A Survey1,071 citations · 2015
- 5
- 6Robotics, Vision and Control671 citations · 2011
- 7
- 8On the performance of ConvNet features for place recognition532 citations · 2015
- 9Need for Speed: A Benchmark for Higher Frame Rate Object Tracking524 citations · 2017
- 10Robotic Process Automation: Contemporary themes and challenges520 citations · 2019
Faculty & Researchers
…