
Greenroom Robotics, a leader in autonomous maritime technology, has partnered with premier global shipbuilder Austal Australia for the Patrol Boat Autonomy Trial (PBAT).
Greenroom Robotics is set to showcase its maritime autonomy capabilities with GAMA (Greenroom Advanced Maritime Autonomy), a state-of-the-art Autonomous Surface Vessel (ASV) control software package.
By integrating GAMA into Sentinel, a decommissioned Armidale-class Patrol Boat, the vessel becomes outfitted with modern autonomous navigation, remote pilotage and control, as well as advanced mission planning and operational capabilities.
The PBAT, a joint effort among Austal, Trusted Autonomous Systems, and the Royal Australian Navy’s Warfare Innovation Navy (WIN) Branch, seeks to integrate robotic, automated and autonomous features into patrol boats.

This trial serves as a prototype to showcase the potential for optionally manned or fully autonomous operations within the Royal Australian Navy. Additionally, it also delves into the legal and regulatory aspects necessary for the operation of autonomous vessels in maritime environments.
Greenroom Robotics state that their partnership with Austal Australia in the PBAT paves the way for transformative developments in naval autonomy and highlights a shared commitment to advancing maritime innovation and technology.
Harry Hubert, Chief Technology Officer of Greenroom Robotics said; “GAMA is an effective autonomous maritime capability from an Australian partner, offering innovation, adaptability, and efficiency. We’re thrilled to be working with Austal on the Patrol Boat Autonomy Trial and looking forward to demonstrating our locally developed technology on Sentinel.”
Glenn Callow, Chief Technology Officer at Austal Australia, stated; “We’re delighted to welcome Greenroom Robotics to the Patrol Boat Autonomy Trial and look forward to GAMA integrating seamlessly with the vessel’s command and control systems, including Austal’s proven MARINELINK technology. GAMA’s specifications and capabilities align perfectly with the objectives of the trial which includes a number of risk reduction activities, fleet optimisation and learnings objectives.”