QUT Centre for Robotics researchers are leading a project that has been awarded a grant to investigate how robotics and autonomous vehicles can better respond to the world around them.
The University of Adelaide’s Centre for Advanced Defence Research in Robotics and Autonomous Systems (CADR RAS) has awarded the $614,000 grant to the research project involving QUT’s Professor Michael Milford and Helen Carson, and Professor Iman Shames of the Australian National University.
Professor Michael Milford, Joint Director of the Centre for Robotics, said the project would look at the challenge of how autonomous systems navigate in challenging environmental conditions, as well as detect and deal with deliberate attempts by “adversaries” to interfere with their navigation systems.
“Positioning systems for robots performing critically important operations are useless unless they can adapt to changing environmental conditions, and respond to deliberate interference by adversaries,” Professor Milford said.
“This project aims to give robot and autonomous navigation systems the ability to detect and react to interference from adversaries, as well to adverse conditions in the natural environment.”
“It’s an exciting team, bringing together a roboticist, a control theorist, and an aerospace and autonomous vehicle industry veteran, and we can’t wait to get started”
PhD researcher Ms Carson spent 20 years working in Defence on major aerospace projects before joining a Silicon Valley startup building autonomous robo-taxis.
“Guaranteeing high integrity navigation performance under all conditions is key to deploying fully autonomous robotics — it’s a problem that has to be solved before we can truly remove human supervision,” she said.
“I’m really eager to develop solutions that will unlock our ability to deploy autonomous systems in the real world.”
Professor Shames, whose areas of expertise include the mathematical aspects of control theory, said: “We aim to untangle the hacks that have dominated the field, so we can formally understand the conditions under which modern positioning algorithms work.”