Many offshore and nearshore operations, from inspection to hydrographic surveys, require precise station-keeping.
Pipeline inspection is particularly demanding: vessels must follow a remotely operated vehicle (ROV) or autonomous underwater vehicle (AUV) as it tracks pipeline systems with centimetre-level accuracy.
Until now, this has typically meant using a fully DP-classed vessel. The alternative — relying on skilled crew to make constant thruster corrections — is prone to human error under sustained operational demands.
A collaboration between Australian vessel operator Tenggara Explorer maritime autonomy and AI specialist Greenroom Robotics, Sonardyne, and Unique Group has demonstrated there’s another way.
Together, they equipped the 111'6"-long Tenggara Explorer multipurpose vessel with integrated DP-level control and Ultra-Short BaseLine (USBL) positioning for ROV-follow capability for a medium-size inspection-class ROV.
“For vessel operators like Tenggara Explorer, it means new mission types – allowing them to use their existing workboat to take on tasks that historically required a DP-class vessel, unlocking a broader variety, and potentially higher-value, jobs,” said Aidan Thorn, marine robotics business development manager at Sonardyne.
The core of the solution was the integration of two key systems, Greenroom Robotics’ autonomy software, GAMA, and Sonardyne’s Mini-Ranger 2 USBL system, he said. GAMA is advanced autonomy software that is hardware agnostic and can be retrofitted to existing vessels to enable remote, hybrid, and autonomous control.
GAMA’s Dynamic Predictive Control (DP-C) independently controls thrusters, propellers, and rudders using sensor feedback and control algorithms to counter wind, waves, and current. This provides DP-level control to smaller, more agile workboats, like the Tenggara Explorer, enabling precision positioning.
This means survey teams on smaller vessels can execute complex manoeuvres and survey patterns with high precision, at day rates around 80% less than a DP-class vessel, and with lower risk than manual precision control.
Sonardyne’s Mini-Ranger 2 USBL system is engineered for high-performance tracking of underwater targets from surface vessels in shallow waters and coastal environments. Its portability makes it easy to integrate into smaller vessels, including smaller uncrewed surface vessels (USVs). Installed on the Tenggara Explorer, Mini-Ranger 2 provides the high-accuracy positioning data required to track the ROV during inspection tasks and survey work. Unique Groups’ team was the crucial integration partner, ensuring the vessel’s complex systems worked together, enabling its transformation to DP-level control and ROV-follow capability.
Mini-Ranger 2 was expertly integrated into the vessel along with human-machine interfaces and GAMA, and Sonardyne displays into pre-existing Simrad units on the Bridge. This was followed by extensive in-water testing, performance verification, and calibration.
Through this work, Unique Group enabled GAMA to perform critical autonomous functions, including precise ROV following, station-keeping, and survey line tracking off Australia’s West Coast.
“What stood out most was the stability during ROV/AUV following,” said Kai Lebens, director and operations manager at Tenggara Explorer. “We consistently held position and heading within DP-equivalent tolerances, even in variable wind and swell, while following a moving subsea target through USBL updates. The feel is ‘DP-like’ - the helm simply stayed where it needed to be, without the constant micro-corrections they were used to.
“With GAMA managing fine vessel motion, bridge teams can maintain higher vigilance and focus on project oversight, data quality, and safety. It’s also an advancement on the autonomy roadmap – helping to unlock the benefits of autonomy, alongside DP-level control.”
“Mini-Ranger 2 provided the reliability and fidelity needed for predictive tracking,” added Peter Baker, General Manager of Growth, at Greenroom Robotics. “It provides high update rates, dependable accuracy, and stable performance in the shallow-to-midwater environments typical of survey and inspection work.
“That consistency is essential as the autonomy needs trustworthy subsea positioning to predict vessel motion relative to the ROV/AUV. Sonardyne effectively gave us the ‘subsea truth source’ that GAMA’s Dynamic Predictive Control depends on.”
“Unique Groups’ integration work was the linchpin that allowed the Tenggara Explorer to fully leverage the GAMA package and Mini-Ranger 2's capabilities, enhancing operational efficiency and safety while reducing environmental risk,” added Lebens. “Their contribution was fundamental to the success of this project.”
Greenroom Robotics has its sights set on expanding this capability, not just rolling it out to more work boats, but also building in and enabling more autonomy.
This includes scaling from single-vessel deployments to fleet-level collaborative capability, using Dynamic Predictive Control to support multiple vessels coordinating station-keeping, target following, launch/recovery, and survey tasks.
They’ll also be building in more of their AI perception to directly inform the control loop, enabling vision-informed station-keeping and obstacle-aware positioning.
"The power of hybrid autonomy is that it unlocks autonomous functionality for ROV-follow type operations while enabling the vessel to operate with a leaner crew. This represents the next logical step in the evolution of maritime operations and a huge opportunity for innovative operators like Tenggara Explorer,” said Baker at Greenroom.
“It also aligns with current regulatory frameworks that still require human oversight, while demonstrating the real-world value of autonomy in commercial service.
"As autonomy is proven under human supervision, confidence will build with classification societies and regulators, enabling a gradual transition to fully autonomous operations.”
“The key to future autonomy is demonstrating that these systems can complete missions successfully without requiring any human intervention” added Thorn. “Helping to prove this capability builds the evidence base needed to move toward fully autonomous operations with confidence."
