The Australian Centre of Excellence for Robotic Vision will play a key role in developing the underlying science and technologies that will enable robots to see, to understand their environment using the sense of vision, and to perform useful tasks in the complex, unstructured and dynamically changing environments in which we live and work.
I was team leader of the ACRV's team entering the APC in 2016. The core team mainly consisted of undergrad (BSc) students from QUT and 2 PhD students from the centre. We developed a perception and actuation pipeline to perform picking tasks in cluttered environments, such as shelves.
icVision is an easy-to-use, modular framework performing computer vision related tasks in support of cognitive robotics research on the iCub humanoid robot. The system currently allows object recognition, identification and localisation. One of the main design goals is to allow rapid ...
I create robots with more autonomous and more adaptive behaviours, leading to more `intelligent´ robots (video on the right). Using Machine Learning and Computer Vision, we make our robots `see', that is, we develop computer vision algorithms for object detection. On the left a first try to allow for easier control of a humanoid robot by an operator is shown.