Australian Centre for Robotic Vision (Team ACRV)
Robotronica

Teach a Robot how to Grasp

Instruction Video

Teach Grasping
Teach Grasping
Teach Grasping
Teach Grasping
Teach Grasping
 

Cartman News

Cartman wins the Amazon Robotics Challenge!

7News Brisbane (July, 2017)

QUT STUDENT?! ARE YOU LOOKING FOR A FINAL YEAR PROJECT?!?

We are currently on the lookout for motived students to be involved in a QUT-led team entry for the 2017 Amazon Robotics Challenge. We are specifically interested in students interested in working on state-of-the art computer vision, hardware, machine learning/intelligence, and software integration on our robotic platforms (a Baxter robot, Harvey a mobile platform and a currently being built Cartesian robot). Here's a YouTube playlist of last year's team, which came 6th: https://www.youtube.com/playlist?list=PLOqMcGR_zUyEjTO6hE7wM2VpkKGSvRiFg
Requirements are experience with either C++ or Python and Linux. Any prior work with ROS is highly desirable but not a requirement. As this is a competition with a deadline of end of July this year, we are looking for motivated students that are willing to put in the extra work until then. Although this will mean a lot of hours on campus during this time, the second half of your year will be more relaxed and may only need to be report writing (something to be discussed with supervisor). Further, the competition is being held in Japan at the end of July and team members (not all but some) will get an awesome experience and trip to RoboCup to compete live!
Team ACRV (which also involves researchers from Adelaide in addition to QUT) has been selected as one of 16 teams worldwide to again take part this year. We are looking for students to start on this ASAP so if you are keen, please email Juxi Leitner (j.leitner@qut.edu.au) from the QUT Robotics and Autonomous Systems Discipline with your name and student number and prior experience so that we can organise a time to meet.
Media Coverage from last year's competition: BBC, ZDnet
 

 
 

Contact Information

Juxi

Juxi Leitner

j.leitner@roboticvision.org
Queensland University of Technology (QUT)
Research Fellow