Centre team wins Amazon Robotics Challenge with low cost robot—31 July 2017

 Researchers at an ARC Centre of Excellence, the Australian Centre for Robotic Vision (ACRV) headquartered at Queensland University of Technology (QUT), has won the 2017 Amazon Robotics Challenge at RoboCup in Nagoya, Japan. For winning the finals, the Centre will receive $80,000USD.

The skills challenge attracted sixteen teams of researchers from ten countries to compete. Two teams represented Australia, with teams tasked to build their own hardware and software to successfully pick and stow items in a warehouse. While Amazon is able to quickly package and ship millions of items to customers from their network of fulfillment centres, the commercial technologies to solve automated picking in unstructured environments are yet to be developed.

The challenge combined object recognition, pose recognition, grasp planning, compliant manipulation, motion planning, task planning, task execution, and error detection and recovery. The robots were scored by how many items they successfully picked and stowed in a fixed amount of time. Fifteen members of the Centre’s 27-strong team of researchers, sourced from QUT, The University of Adelaide and the Australian National University, were in Japan for the event.

The ACRV team developed their own Cartesian robot “Cartman” for the challenge. Cartman can move along three axes at right angles to each other, like a gantry crane, and featured a rotating gripper that allowed the robot to pick up items using either suction or a simple two-finger grip.

“We are world leaders in robotic vision and we’re pushing the boundaries of computer vision and machine learning to complete these tasks in an unstructured environment,” said team leader, Dr Juxi Leitner.

Media issued by the Australian Centre for Robotic Vision.

Image: Fifteen members of the Centre’s 27-strong team of researchers, sourced from QUT, The University of Adelaide and the Australian National University, were in Japan for the event.
Image credit:
Australian Centre for Robotic Vision.

Original Published Date: 
Monday, July 31, 2017