We won the Amazon Robotics Challenge 2017! 🏆
More info here: http://Juxi.net/projects/AmazonRoboticsChallenge
(Press includes: BBC, MIT TechReview, Engadget, Wired, ...)

We are hiring!

Join us at the Australian Centre for Robotic Vision as part of our great team at QUT in Brisbane, solving real world problems using robotic and computer vision technologies. In particular, we have Robotic Manipulation postdoctoral positions available (2yrs+, salary up to 110k AUD/year + super) ! E-Mail me or go here for more info: https://qut.nga.net.au/cp/index.cfm?event=jobs.listJobs&jobListid=73e3bb51-1aa7-db29-2ea3-52af99b4f747
I am a researcher at the Australian Centre of Excellence for Robotic Vision (ACRV), where I lead the Manipulation group (previously Vision and Action project). My research focus is on integrating Robotics, Computer Vision and Machine Learning/Artificial Intelligence (AI) for robust grasping and manipulation in real-world scenarios. In 2017 we won the Amazon Robotics Challenge. I am active in the local Brisbane deep-tech ecosystem and started Brisbane.AI and the brisbane robotics interest group.
Before joining the ACRV node in Peter Corke's lab at QUT I worked at the IDSIA Robotics Lab and received a PhD from the Università della Svizzera Italiana (USI) for my work on robotic learning for visual perception and actions on the iCub humanoid. Previously I worked on Space Security and AI at the Advanced Concepts Team of the European Space Agency. I studied Space Robotics in a Joint European Master Programme (SpaceMaster) at Aalto (TKK) and the Kiruna Space Campus (LTU). Most of my work has been published in (Space) Robotics, ML and AI conferences.

News and Current Projects

ACRV wins Amazon Robotics Challenge!

Team ACRV (Australian Centre of Excellence for Robotic Vision) won the 2017 Robotics Challenge held in Nagoya! Cartman outperformed 15 other teams to win us 80000 USD prize money! 🏆
More information here!

Australian Centre of Robotic Vision

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.

icVision - Robotic Vision Framework

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 ...

More info