
A $1.2 million partnership between Charles Darwin University (CDU), Civiltech Solutions and the Additive Manufacturing Cooperative Research Centre (AMCRC) is set to bring robotic road repair technology to Australia, combining AI, LiDAR scanning and additive manufacturing to tackle one of infrastructure’s most persistent challenges.
The project will integrate LiDAR-based road scanning with artificial intelligence and robotics to detect cracks earlier and carry out precise repairs, reducing the reliance on manual inspections and reactive maintenance.
With more than 800,000km of roads across Australia—most managed by local councils—early intervention is critical, yet current methods can miss early-stage defects and lead to inconsistent outcomes.
Researchers from CDU’s Centre for Asphalt and Road Technologies (CART), backed by $500,000 in funding, will contribute expertise in robotics, materials engineering and additive manufacturing, building on Civiltech’s existing scanning platform.

CART Director, Ali Rajabipour, said the collaboration highlights how emerging technologies can be applied to real-world infrastructure challenges.
“This project brings together a range of technologies and industry insights to solve real-world infrastructure problems while building advanced engineering capability in the Northern Territory,” he said.
Civiltech Solutions CEO, Leigh Carnall, added that the system could modernise road maintenance by shifting it from a largely manual, reactive process to a more proactive and precise approach.
Additive manufacturing will play a key role in producing lightweight, customised components for the robotic system, enabling it to operate effectively in remote and harsh environments.
AMCRC Managing Director, Simon Marriott, said the project showcases how advanced manufacturing can unlock new approaches to infrastructure maintenance, delivering scalable solutions that improve productivity and sustainability.
Once proven, the technology could be rolled out across Australia, helping councils extend pavement life, cut maintenance costs and improve road safety through data-driven repairs.