A new case study focuses on improving the endurance and navigational precision of underwater autonomous systems.
Sonardyne, designer and manufacturer of underwater positioning and inertial navigation, describes the challenges to increase navigation capability for subsea monitoring and inspections. Sonardyne joined with the National Oceanography Centre (NOC) and L3Harris ASV on a two-year project to develop new positioning technologies to extend the limits of AUVs and UUVs.
The project — Precise Positioning for Persistent AUVs (P3AUV) — is supported with £1.4 million in funding through Innovate UK’s research and development competition for robotics and artificial intelligence in extreme and challenging environments.
Sending autonomous and unmanned underwater vehicles (AUV, also known as UUVs) out on missions that will last for days or weeks, unaided by vessels or other supporting offshore infrastructure, is a major goal for the ocean science, offshore energy and defense sectors.
Sustained Ocean Observation. The research community aims for sustained ocean observation without the need for ship support, especially in ice-covered polar areas. Long-duration navigational capability is also a key enabler for persistent covert surveillance operations in the defence sector. And emerging applications include resident seabed-based systems, deep-sea mining, aquaculture and UXO surveys for renewable installations.
Autonomous AUVs would remove the need for a surface vessel, reduce risk to personnel, and reduce costs. Users could survey more seabed for longer and with fewer or even no people offshore.
The team is developing ways to provide greater positioning accuracy for long-endurance operations in deep water, while also reducing power requirements. The team will also be increasing the use of autonomy to make long baseline (LBL) positioning transponder box-in faster and easier, with onboard data processing and calibration.
High-power INS input. Central to this work is the AUV’s acoustic and inertial navigation system (INS). Low-power sensors have much lower navigation accuracy and often have to surface to correct positioning error with a GPS fix. The team seeks to integrate low- and high-power sensors to achieve high performance at much lower power consumption.
For instance, the NOC’s Autosub Long Range (ALR) uses a low-power microelectronic mechanical system (MEMS) supported by separate Doppler velocity log (DVL) and ADCP input to calculate how far it has traveled on missions, which can be several months long. To increase the ALR’s positioning accuracy over longer distances, the team is using the Sonardyne SPRINT-Nav all-in-one subsea navigation instrument alongside MEMS technology to work towards high-precision solutions that save space and power.
Accuracy during ascent and descent. The project also involves improving positioning accuracy when subsea vehicles transition through the water column. This is a notoriously difficult area for AUV deployments, because it relies on the Doppler velocity log (DVL) being able to lock on to the seafloor (bottom lock), so that vehicle XYZ velocities can be calculated, supported by pressure data.
However, DVLs are range limited, so there is often a period where the DVL is out of range. When there are thousands of meters of water between the surface and the seabed, this can introduce significant positioning uncertainty.
By using the acoustic Doppler current profiler (ADCP) capability in Sonardyne’s SPRINT-Nav INS instrument (looking down) and a second Syrinx DVL (looking up), the team could then build up a layer-by-layer profile of the water column velocities to be used as tracking layers.
The objective is to reduce positioning errors significantly during both the dive and surfacing phases of an operation. Results depend on the variability of the current in any given area.
The data collected during the descent and surfacing phases can be processed to provide a full ocean-depth current profile — collection of which is required for many offshore energy projects and can be valuable for ocean research.
Read more about the case study here.