AIMS’ vision for marine monitoring extends from space to the seafloor using an integrated, multi-layered suite of tools working together to collect and translate field data into information efficiently

Our objective is to deliver twice the information in half the time and at half the unit cost (AIMS Strategy 2025 Enhanced Capability Target 2).

Autonomous platforms are at the heart of scaling AIMS’ routine observations.

AIMS’ engineers have demonstrated the utility of autonomous platforms for coral reef observations deployed in a layered approach at John Brewer Reef.

A detailed bathymetric map of John Brewer Reef was produced using a small tender equipped with a multibeam sonar and overlaid with an orthomosaic collected by drones launched from the RV Cape Ferguson (Figure 1). The resulting map provided a foundation for developing a survey plan for directing aerial, surface and underwater autonomous platforms to collect the required data from the field. The high-resolution drone map also enabled additional areas of interest to be identified for further investigation.

Autonomous platforms can bring benefits in safety and improved quality, accuracy, and acquisition of data. AIMS has aerial drones with hyperspectral and regular imaging capabilities, and emerging autonomous underwater platforms. To assess an autonomous surface vessel capability, AIMS teamed up with Queensland University of Technology (QUT) to configure their sophisticated Wave Adaptive Modular Vessel WAM-V with a variety of payloads including camera systems, sonar systems and a towed platform to collect underwater georeferenced survey data of reef zones (this autonomous vessel was awarded 2nd place in the last two biennial International Maritime RobotX competitions).

The survey plan directed the WAM-V to survey reef flats and reef slopes, and a hyperspectral drone and Rangerbot autonomous underwater vehicle to survey reef transects (Figure 2). Although capable of full autonomous operation, each platform was operated under human control for additional safety and environmental compliance assurance.

In addition to data acquisition technologies, AIMS is developing a modular, configurable, cloud-based data workflow and processing system known as the Research Data Platform (RDP). This is AIMS’ next generation data framework which incorporates machine learning, pre-processing and integrated data product elements. The datasets acquired by the autonomous platforms were all georeferenced and timestamped to inform the RDP development, ensuring AIMS develops an enduring marine monitoring system using an end-to-end systems approach. Figure 3 presents examples of the data captured.

This project demonstrated the feasibility of operating multiple autonomous platforms together to perform a single co-ordinated multi-layered mission from AIMS’ vessels. Lessons learned will inform:

• operational logistics and optimal configuration of autonomous platform deployed for future routine monitoring;
• decisions concerning platform and sensor selection and development, and vessel design and configuration;
• experimental design, sampling strategies and mission planning; and
• data management and analysis workflows and data system specifications.

Whilst led by the Technology Development Engineering team, this project achieved its objective through AIMS-wide support and through collaboration with partners.