[Show abstract][Hide abstract] ABSTRACT: For autonomous underwater vehicles (AUVs) to be successful in long duration deployments, they must be reliable in the face of subsystem failure and environmental challenges. The ability to detect performance anomalies and unexpected events in real time, especially in the vertical plane, is critical for the vehicle's survivability (the AUV must surface for recovery) and important for planning and vehicle operations. To this end, we have developed a vertical plane flight anomaly detection algorithm capable of comparing observed vehicle performance to references of expected behavior onboard the Tethys class long-range AUV in real time. The detection algorithm operates based on statistical characterization of training datasets that represent normal vertical plane performance. These datasets are taken directly from previous long-range AUV field operations. From this analysis we have derived a series of conditional tests that monitor representative components of the vehicle state (e.g., depth rate, pitch angle, and stern plane angle). In the months of January, February and March 2015, we conducted a series of tests in Monterey Bay, CA. The Daphne long-range AUV ran the algorithm to detect and flag vertical plane performance anomalies in real time. The AUV was successful in discriminating between expected vertical plane flight performance and anomalies during long-duration deployments lasting more than 11 days.
[Show abstract][Hide abstract] ABSTRACT: Phytoplankton patches in the coastal ocean have important impacts on the patterns of primary productivity, the survival and growth of zooplankton and fish larvae, and the development of harmful algal blooms (HABs). We desire to observe microscopic life in a phytoplankton patch in its natural frame of reference (which is moving with the ocean current), thereby permitting resolution of time-dependent evolution of the population. To achieve this goal, we have developed a method for a Tethys-class long range autonomous underwater vehicle (AUV) (which has a propeller and a buoyancy engine) to detect, track, and sample a phytoplankton patch in buoyancy-controlled drifting mode. In this mode, the vehicle shuts off its propeller and actively controls its buoyancy to autonomously find the peak-chlorophyll layer, stay in it, and trigger water sampling in the layer. In an experiment in Monterey Bay, CA in July 2015, the Makai AUV, which was equipped with a prototype 3rd-generation Environmental Sample Processor (3G-ESP), ran the algorithm to autonomously detect the peak-chlorophyll layer, and drifted and triggered ESP samplings in the layer.
[Show abstract][Hide abstract] ABSTRACT: Coastal upwelling is a wind-driven ocean process that brings cooler, saltier, and nutrient-rich deep water upward to the surface. The boundary between the upwelling water and the normally stratified water is called the “upwelling front.” Upwelling fronts support enriched phytoplankton and zooplankton populations, thus they have great influences on ocean ecosystems. Traditional ship-based methods for detecting and sampling ocean fronts are often laborious and very difficult, and long-term tracking of such dynamic features is practically impossible. In our prior work, we developed a method of using an autonomous underwater vehicle (AUV) to autonomously detect an upwelling front and track the front's movement on a fixed latitude, and we applied the method in scientific experiments. In this paper, we present an extension of the method. Each time the AUV crosses and detects the front, the vehicle makes a turn at an oblique angle to recross the front, thus zigzagging through the front to map the frontal zone. The AUV's zigzag tracks alternate in northward and southward sweeps, so as to track the front as it moves over time. This way, the AUV maps and tracks the front in four dimensions—vertical, cross-front, along-front, and time. From May 29 to June 4, 2013, the Tethys long-range AUV ran the algorithm to map and track an upwelling front in Monterey Bay, CA, over five and one-half days. The tracking revealed spatial and temporal variabilities of the upwelling front.
Journal of Field Robotics 07/2015; DOI:10.1002/rob.21617 · 1.43 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This paper presents the development effort toward demonstrating acoustic tracking and homing with a long-range AUV (LRAUV) at the Monterey Bay Aquarium Research Institute (MBARI). The acoustic tracking system uses a directional acoustic transponder (DAT) from Teledyne Benthos, backed by an acoustic baffle made from syntactic acoustic damping material (SADM). We discuss sensor integration into the LRAUV system, procedures and results from an in-house calibration, and field tests with both anchored and towed transponders.
[Show abstract][Hide abstract] ABSTRACT: Most existing propeller-driven, cruising AUVs operate with a support ship and have an endurance of about one day. However, many oceanographic processes evolve over days or weeks, requiring propeller-driven vehicles be attended by a ship for complete observation programs. The Monterey Bay Aquarium Research Institute (MBARI) developed the 105 kg propeller-driven Tethys AUV to conduct science missions over periods of weeks or even months without a ship . Here we describe a three week deployment covering 1800 km at a speed of 1 m/s, supporting sensor power levels averaging 5 watts. Unlike buoyancy driven gliders, Tethys uses a propeller that allows level flight and a variable speed range of 0.5 - 1.2 m/s. The extended endurance enables operations in remote locations like under the ice, across ocean basins in addition to enabling continuous presence in smaller areas. Early success led to the construction of a second Tethys-class AUV with a third in planning. An AUV docking station that can be mated to a cabled observatory or standalone mooring is in development to further extend Tethys endurance.
[Show abstract][Hide abstract] ABSTRACT: Thermoclines play a key role in ocean circulation, marine ecology, and underwater acoustics. In oceanographic surveys, it is often desirable to detect the thermocline and track its spatio-temporal variation. Mobility of an autonomous underwater vehicle (AUV) makes it an efficient platform for thermocline tracking. In this paper, we present a fully autonomous algorithm for detecting and tracking the thermocline by an AUV. The key is detection of the peak gradient of temperature. We have tested the algorithm by post-processing data from a previous Dorado AUV survey over the northern Monterey Bay shelf. We are in preparation for field tests of the algorithm on the newly developed long-range AUV Tethys.
[Show abstract][Hide abstract] ABSTRACT: A scripting language for state configured layered control of a long range autonomous underwater vehicle (AUV) is introduced. The XML-based language has been designed to meet the complex requirements for long-term autonomous operation. It does not require that mission planners be programmers, yet allows them to have a high degree of certainty at deployment that the robot will do what they want it to do. The script is simple to execute on the vehicle, both to minimize CPU power usage and to minimize the chance of failure due to complexity. Users do not need a high-fidelity model of the AUV to plan a mission, as the robot may change in unexpected ways over the course of the mission. Those who wish to do more advanced programming of mission commands and behaviors can do so in the script and are not able to crash the vehicle's operating system. To address these needs, the “Tethys script” state-configured layered control language has been developed.
[Show abstract][Hide abstract] ABSTRACT: The Tethys autonomous underwater vehicle (AUV) is a 110 kg vehicle designed for long-range, high- endurance operations. Performance goals include supporting a payload power draw of 8 W for a range of 1000 km at 1 m/s, and a power draw of 1 W for 4000 km at 0.5 m/s. Achieving this performance requires minimizing drag and maximizing propulsion efficiency. In this paper, we present the design of the propulsion system, explore the issues of propeller-hull interactions, and present preliminary test results of power consumption and efficiency. In recent underwater experiments, the propulsion system's power consumptions were measured in both Bollard pull tests and during the vehicle's flights. Preliminary results of power consumptions and efficiency are shown to be close to the theoretical predictions.
[Show abstract][Hide abstract] ABSTRACT: The Monterey ocean observing system (MOOS) moored observatory hosts tens of instruments on multiple networked nodes distributed over the sea surface, water column, and seafloor. Commands and data are exchanged between instrument nodes over high-speed copper and fiber-optic links at 10 Megabits per second using TCP-IP protocols. Science and engineering instruments on each node acquire and log data at various rates; the current deployment of five instrument nodes logs tens of Megabytes of data per day. Approximately 5 Megabytes per day of telemetry is required to provide a subset of science data and system status information. The surface node periodically establishes a PPP connection to shore using the Globalstar satellite system, providing a link for remote system control, maintenance, and telemetry retrieval Telemetry retrieval is particularly challenging, given the capacity and cost of the 7800 bits per second communications link. The challenge is compounded by limited satellite availability, wave-driven motion of the surface buoy antenna, and occasional outages of hard-wired network connections between nodes. To address these issues, we have developed software strategies to manage the low- bandwidth satellite link in a highly efficient manner. Elements of our telemetry retrieval strategy include use of data summarization algorithms, PPP compression, multi-threaded utilization of the satellite link, optimized data packet size to reduce protocol overhead, and assertive reconnection of prematurely disconnected satellite links. We discuss the efficiency and trade-offs of various approaches, as well as overall observed improvements in telemetry rates. Our current implementation is capable of retrieving at least 10 Megabytes of telemetry per day, and we discuss further improvements which could substantially increase that rate.