Conducting research with multiple underwater vehicles takes a huge amount of deliberation and coordination that is based on data gathered well before the work even takes place. But what happens if the environment you work on is constantly changing? Then the information you are basing your research on isn’t up to date. Additionally, there is a mismatch between the time it takes to digest collected data and the daily cycle of robotics deployment, limiting how well informed in-the-field decisions can be…until now.
Dr. Blair Thornton of the University of Southampton, and his international team of scientists and engineers are trying to address this problem using underwater robots and algorithms that are smarter than before. The group will perform deployments of multiple different types of underwater platform, along with concurrent in-situ chemical and biological sensing. While on board Falkor, the team plans to demonstrate how large volumes of data can be efficiently viewed and interpreted as part of a daily operational workflow, allowing for better informed decision making and increasing the scientific value of an at-sea expedition. The underwater robots used will not be just mindless gathers of data, but will make important decisions based on an increased awareness of their surroundings.
Not just intelligent but adaptive robots
The data collected will be used to update plans for underwater robot deployments on the fly, taking strategic approaches to gathering data in complex, dynamically changing environments like cold seeps. The information will be compiled onto a single geo referenced frame so humans, as well as machines, can recognize patterns that might be of interest and biological hot spots that we would want to know more about.
Hot spots in the deep
By developing tools for rapid visualization and machine-assisted interpretation, Dr. Thornton and his team will be able to focus observational efforts and generate a new framework that can cover larger ground with better resolution where it is most needed. This means biological hot spots will be easily identified providing a representative picture of the benthic ecosystem. The team will apply this concept by studying environmental aspects that shape the distribution of animal life in gas hydrate fields or “cold seeps.”
Gas hydrate fields and cold seeps sustain some of the richest known ecosystems on the seafloor. They only exist in cold, deep waters where the pressure is high. At the same time, hydrate fields cover vast regions, so the only way to study these systems and grasp an understanding of their influence on deep-sea ecology, is to make high-resolution observations over large areas. Understanding these systems is important for both benthic ecology, climate, and geo hazards research. Unfortunately, in the past we have not had the ability to intelligently investigate these systems in the time frames relevant to their dynamic changing environment.
Barkley Canyon and Hydrate Ridge are the two sites that will be explored during this expedition. Since these are continuously changing environments, the AUV will be sent out first to complete a screening survey of the seafloor. Using three AUVs and ROV Subastian, the vehicles will undertake data-gathering deployments in real time looking at how the chemical, physical and biological properties in the water column influence (or is influenced by) the distribution of animals on the seafloor. An AUV will first produce 1 cm resolution 3D visual reconstructions of vast regions flying at a higher distance in the water column looking for patterns of interest.
Once biological and chemical hot spots are found, artificial intelligence (AI) will be used to tell another vehicle where to do higher resolution photo mosaicking, generating submillimeter resolution 3D visual reconstructions, allowing scientists to gather data in the most interesting regions and interpret them in a way that would not be possible otherwise. Hovering closer to the seafloor, the vehicles will cover a smaller, targeted area, making in-situ chemical and biological measurements using instruments such as laser spectrometers.
Having this level of detail where it matters most will help to illuminate relationships and advance the understanding of these environments. The deep-ocean is one of the most challenging ecosystems to deploy technology, and this work will be a small step towards improving our understanding of these environments, and a big step towards improving how effective we are a gathering information from these ecosystems.