Tom O'Reilly

Coordinated sampling of dynamic oceanographic features with underwater vehicles and drifters

We extend existing oceanographic sampling methodologies to sample an advecting feature of interest using autonomous robotic platforms. GPS-tracked Lagrangian drifters are used to tag and track a water patch of interest with position updates provided periodically to an autonomous underwater vehicle (AUV) for surveys around the drifter as it moves with ocean currents. Autonomous sampling methods currently rely on geographic waypoint track-line surveys that are suitable for static or slowly changing features. When studying dynamic, rapidly evolving oceanographic features, such methods at best introduce error through insufficient spatial and temporal resolution, and at worst, completely miss the spatial and temporal domain of interest. We demonstrate two approaches for tracking and sampling of advecting oceanographic features. The first relies on extending static-plan AUV surveys (the current state-of-the-art) to sample advecting features. The second approach involves planning of surveys in the drifter or patch frame of reference. We derive a quantitative envelope on patch speeds that can be tracked autonomously by AUVs and drifters and show results from a multi-day off-shore field trial. The results from the trial demonstrate the applicability of our approach to long-term tracking and sampling of advecting features. Additionally, we analyze the data from the trial to identify the sources of error that affect the quality of the surveys carried out. Our work presents the first set of experiments to autonomously observe advecting oceanographic features in the open ocean.

Towards mixed-initiative, multi-robot field experiments: Design, deployment, and lessons learned

With the advent of Autonomous Underwater Vehicles (AUVs) and other mobile platforms, marine robotics have had substantial impact on the oceanographic sciences. These systems have allowed scientists to collect data over temporal and spatial scales that would be logistically impossible or prohibitively expensive using traditional ship-based measurement techniques. Increased dependence of scientists on such robots has permeated scientific data gathering with future field campaigns involving these platforms as well as on entire infrastructure of people, processes and software, on shore and at sea. Recent field experiments carried out with a number of surface and underwater platforms give clues to how these technologies are coalescing and need to work together. We highlight one such confluence and describe a future trajectory of needs and desires for field experiments with autonomous marine robotic platforms. Our 2010 inter-disciplinary experiment in the Monterey Bay involved multiple platforms and collaborators with diverse science goals. One important goal was to enable situational awareness, planning and collaboration before, during and after this large-scale collaborative exercise. We present the overall view of the experiment and describe an important shore-side component, the Oceanographic Decision Support System (ODSS), its impact and future directions leveraging such technologies for field experiments.

Instrument interface standards for interoperable ocean sensor networks

The utility and cost-effectiveness of instrument networks are enhanced by instrument interoperability. Todays oceanographic instruments are characterized by very diverse non-standard software protocols and data formats. This diversity of protocols poses serious challenges to integration of large-scale sensor networks. Standard instrument protocols are now being developed to address these challenges. Some of these standards apply at the IP-network level and enable integration of existing “lower level” proprietary instrument protocols and software components. Other approaches are intended to be implemented by the instrument device itself. These native instrument protocol standards offer the possibility of more uniform and simpler system architectures. We compare these various approaches, describe how they can be combined with one another, and describe some prototypes that implement them.

MBARI's buoy based seafloor observatory design

There has been considerable discussion and planning in the oceanographic community toward the installation of long-term seafloor sites for scientific observation in the deep ocean. The Monterey Bay Aquarium Research Institute (MBARI) has designed a portable mooring system for deep ocean deployment that provides data and power connections to both seafloor and ocean surface instruments. The surface mooring collects solar and wind energy for powering instruments and transmits data to shore-side researchers using a satellite communications modem. A specialty anchor cable connects the surface mooring to a network of benthic instrumentation, providing the required data and power transfer. Design details and results of laboratory and field testing of the completed portions of the observatory system are described

ODSS: A decision support system for ocean exploration

We have designed, built, tested and fielded a decision support system which provides a platform for situational awareness, planning, observation, archiving and data analysis. While still in development, our inter-disciplinary team of computer scientists, engineers, biologists and oceanographers has made extensive use of our system in at-sea experiments since 2010. The novelty of our work lies in the targeted domain, its evolving functionalities that closely tracks how ocean scientists are seeing the evolution of their own work practice, and its actual use by engineers, scientists and marine operations personnel. We describe the architectural elements and lessons learned over the more than two years use of the system.

An ocean observatory sensor network application

We describe our implementation of a novel deep ocean sensor network, the MBARI Free Ocean CO2 Enrichment (FOCE). FOCE is a system designed for installation in the deep ocean to enable manipulative experiments that explore the impact of deep ocean increase in CO2 and resulting pH change on ocean biogeochemistry and ecology. This system uses control feedback and pH sensors to inject CO2 into a small volume of seawater, thus creating a controlled environment per science requirements. To implement this system, we utilized the MBARI-developed network middleware known as “SIAM”, which provides a standardized interface to instruments on a sensor network. For the FOCE application we integrated Open Source DataTurbine (OSDT) into SIAM. OSDT provides asynchronous communication links between distributed components, and is particularly well-suited to streaming instrument data. Combined with the existing synchronous SIAM framework, these features enabled a straightforward and efficient architecture for our application. We describe how we achieved our goals of software reuse of infrastructure and instrument services, instrument-in-the-loop control, and rapid assembly of a scalable end-to-end sensor network system.

A novel method of obtaining near real-time observations of phytoplankton from a mobile autonomous platform

Emerging marine observation technologies provide new opportunities to learn about phytoplankton communities with greater spatiotemporal resolution. Autonomous vehicles enable real-time ocean data collection and communications over long durations, in varying sea states and at lower cost than crewed ships. The Jupiter Research Foundation is developing a novel device to obtain near real-time phytoplankton observations from a mobile unmanned platform. The Jupiter Autonomous Microscope (JAM) is an autonomous microscope imaging system that acquires, crops and geo-tags phytoplankton images and sends them to a shore-based server via mobile phone or satellite networks. On-shore processing includes automated object measurements and classification, as well as statistical calculations. Images and corresponding data are made accessible on a dedicated website that allows filtering, annotation and sharing. Successfully deployed on Wave Gliders for several weeks at a time, JAM provides a unique view of phytoplankton community structure. This paper describes the overall JAM design and operation.

Range-only underwater target localization: Path characterization

Underwater localization using acoustic signals is one of the main components in a navigation system for an AUV as a more accurate alternative to dead-reckoning techniques. While different methods based on the idea of multiple beacons have been studied, other approaches use only one beacon, which reduces the system costs and deployment complexity. The inverse approach for single-beacon navigation is to use this method for target localization by an underwater or surface vehicle. In this paper we present a method of range-only target localization using a Wave Glider™, for which simulations and sea tests have been conducted to determine optimal parameters to minimize acoustic energy use and search time and to maximize location accuracy and precision.

Autonomous front tracking by a Wave Glider

Coastal upwelling brings cooler, saltier, and nutrient-rich deep water upward to the surface. Upwelling fronts support enriched phytoplankton and zooplankton populations, thus having great influences on ocean ecosystems. We have developed a method to enable a Wave Glider (an autonomous surface vehicle) to autonomously detect and track an upwelling front. Unlike an autonomous underwater vehicle (AUV) which runs on a yo-yo trajectory to measure vertical profiles of water properties, a Wave Gliders measurements are confined to the surface (from the “float”) and a fixed depth of only several meters (from the submerged “glider”). However, an upwelling front presents a strong surface signature that a Wave Glider can detect. Because the upwelling process brings up cold water from depth, surface temperature in an upwelling region is considerably lower than that in stratified water. A Wave Glider can detect the upwelling front based on the horizontal gradient of the near-surface temperature. We have tested the algorithm by using previous AUV data (only using near-surface temperature measurements) and Wave Glider data. We plan to run field experiments in the summer of 2016 and report the results in the presentation.

Intelligent sensors — Why they are so important for future ocean observing systems

The complexity of installations in the oceans to carry out observations on specific processes and for detecting long-term trends have grown significantly in the past years. This applies also to the type and number of sensors that are in use in observing systems. In these days, sensors shall be compatible to different platforms that are in use like floats, gliders or moorings, and accordingly also different data acquisition systems. Facilitating the integration process in existing or newly established observing systems comes with a real benefit for the operators and is important for the broader application of different sensors. However, how to achieve the goals is under debate. The most serious obstacle for all initiatives is the willingness of stakeholders to adopt a strategy and, even more so, to adopt a specific architecture to enable interoperability across platforms and observing systems. Therefore, the situation at this point in time is characterized by the fact that parallel approaches have been developed (IEEE 1451, the OGC set of standards, etc.) that are ready to be evaluated but still lacking the support by the community. Therefore it seems to be a good time to consider and to agree on the implementation of interoperability arrangements. These and related aspects shall be discussed in this paper.