Australian Research Council Centre of Excellence for Robotic Vision
The Australian Centre for Robotic Vision is an unincorporated collaborative venture with funding of $25.6m over seven years to pursue a research agenda tackling the critical and complex challenge of applying robotics in the real world.[1]
The Centre notable won the 2017 Amazon Robotics Challenge, with their robot Cartman. [2]
Research organisations
The Center is made up of an interdisciplinary team from four leading Australian universities
- Queensland University of Technology (QUT),
- The University of Adelaide (UoA),
- The Australian National University (ANU),
- Monash University, and
research organisations and international universities
- Data61 (previously known as NICTA or National ICT Australia Ltd),
- INRIA Rennes Bretagne,
- Georgia Institute of Technology,
- Imperial College London,
- The Swiss Federal Institute of Technology Zurich, and
- The University of Oxford.
Goals
The Centre aims to achieve breakthrough science and technology in robotic vision by addressing four key research objectives: robust vision, vision and action, semantic vision, and algorithms and architecture. Together the four research objectives form the Centre’s research themes, which serve as organisational groupings of the Centre’s research projects.[3]
Robust vision
Will develop new sensing technologies and robust algorithms that allow robots to use visual perception in all viewing conditions: night and day, rain or shine, summer or winter, fast moving or static.
Vision and action
Will create new theory and methods for using image data for control of robotic systems that navigate through space, grasp objects, interact with humans and use motion to assist in seeing.
Semantic vision
Will produce novel learning algorithms that can both detect and recognise a large, and potentially ever increasing, number of object classes from robotically acquired images, with increasing reliability over time.
Algorithms and Architectures
Will create novel technologies and techniques to ensure that the algorithms developed across the themes can be run in real-time on robotic systems deployed in large-scale real-world applications.
References
- ↑ "Robotic Vision | About Us". roboticvision.org. Retrieved 2016-03-16.
- ↑ "Amazon Robotics Challenge 2017 won by Australian". bbc.com. Retrieved 2018-09-14.
- ↑ "Robotic Vision | Research". roboticvision.org. Retrieved 2016-03-16.