Robert S. McEwen

A deliberative architecture for AUV control

Autonomous Underwater Vehicles (AUVs) are an increasingly important tool for oceanographic research demonstrating their capabilities to sample the water column in depths far beyond what humans are capable of visiting, and doing so routinely and cost-effectively. However, control of these platforms to date has relied on fixed sequences for execution of pre-planned actions limiting their effectiveness for measuring dynamic and episodic ocean phenomenon. In this paper we present an agent architecture developed to overcome this limitation through on-board planning using Constraint- based Reasoning. Preliminary versions of the architecture have been integrated and tested in simulation and at sea.

Docking Control System for a 54-cm-Diameter (21-in) AUV

The Monterey Bay Aquarium Research Institute (MBARI, Moss Landing, CA) has developed a 54-cm-diameter (21-in) docking AUV and companion docking station. This program resulted in four consecutive successful autonomous homing and docking events in the open ocean, which included downloading data, uploading a new mission plan, recharging the battery, and complete power cycling of the AUV. We describe the design, simulation, and at-sea test of the homing and docking control system.

Efficient propulsion for the Tethys long-range autonomous underwater vehicle

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 systems power consumptions were measured in both Bollard pull tests and during the vehicles flights. Preliminary results of power consumptions and efficiency are shown to be close to the theoretical predictions.

Closed-loop terrain relative navigation for AUVs with non-inertial grade navigation sensors

Terrain Relative Navigation (TRN) has the potential to enable drift-free, low-cost navigation for a wide range of underwater vehicles. Current underwater TRN systems have demonstrated meter-level navigation accuracy by utilizing high-accuracy inertial navigation systems in combination with both low and high quality sonar sensors and bathymetry maps. No studies, however, have considered the application of underwater TRN to vehicles with non-inertial-grade navigation systems, an extension which would greatly increase its applicability. The use of low-grade motion sensors in TRN is problematic due to the presence of large errors which can cause highly inaccurate alignment of successive sonar pings. To address this, a TRN filter is developed in which information present in the terrain correlations is used to help identify and mitigate large motion sensor errors. The resulting filter consists of a tight coupling between TRN and the onboard navigation, yielding a significantly improved navigation solution. The development of this TRN system is detailed for an AUV with an Attitude, Heading and Reference System (AHRS)-based dead reckoning navigation, which has an observed accuracy of 5 — 25% distance traveled. Field trials in Monterey Bay, CA demonstrate the ability of the TRN filter to acheive 5 — 10m navigational precision. Field trials are also presented demonstrating successful real-time, closed-loop TRN on the AUV. For these trials, the combined TRN/AHRS system enabled the vehicle to fly to a known beacon location with ability comparable to an acoustic homing system. The presented results demonstrate that TRN technology can successfully be applied to non-inertial-grade vehicle platforms, greatly improving the navigation capabilities of such systems.

The Development and Ocean Testing of an AUV Docking Station for a 21" AUV

The Monterey Bay Aquarium Research Institute (MBARI) has developed an AUV docking station for a 21-inch (54 cm) diameter AUV. The system was designed for operation with cabled undersea observatories in water depths up to 4 km deep and has been demonstrated in the open ocean, though at much shallower depths. The program demonstrated successful autonomous homing and docking, data downloads, uploading of new mission plans, battery recharging, and complete power cycling of the AUV. We describe the design, and at-sea tests.

Performance of an AUV navigation system at Arctic latitudes

In October of 2001 MBARI operated an AUV in the Arctic at latitudes exceeding 80/spl deg/. The navigation instruments consisted of a ring-laser gyro INS coupled with a DVL and GPS, a separate fiber-optic based gyrocompass, and a traditional flux-gate AHRS system. This paper describes the performance of these instruments at high latitudes.In October 2001, the Monterey Bay Aquarium Research Institute (MBARI) operated an autonomous underwater vehicle (AUV) in the Arctic at latitudes exceeding 80/spl deg/. The navigation instruments consisted of a ring-laser gyro inertial navigation system (INS) coupled with a DVL and GPS, a separate fiber-optic-based gyro-compass, and a traditional flux-gate AHRS system. The instruments were tested on deck, in open water, and under ice. This paper describes the performance of these instruments at high latitudes.

A peak-capture algorithm used on an autonomous underwater vehicle in the 2010 Gulf of Mexico oil spill response scientific survey

During the Gulf of Mexico Oil Spill Response Scientific Survey on the National Oceanic and Atmospheric Administration Ship Gordon Gunter Cruise GU-10-02 (27 May–4 June 2010), a Monterey Bay Aquarium Research Institute autonomous underwater vehicle (AUV) was deployed to make high-resolution surveys of the water column in targeted areas. There were 10 2-liter samplers on the AUV for acquiring water samples. An essential challenge was how to autonomously trigger the samplers when peak hydrocarbon signals were detected. In ship hydrocasts (measurements by lowered instruments) at a site to the southwest of the Deepwater Horizon wellhead, the hydrocarbon signal showed a sharp peak between 1,100- and 1,200-m depths, suggesting the existence of a horizontally oriented subsurface hydrocarbon plume. In response to this finding, we deployed the AUV at this site to make high-resolution surveys and acquire water samples. To autonomously trigger the samplers at peak hydrocarbon signals, we modified an algorithm that was previously developed for capturing peaks in a biological thin layer. The modified algorithm still uses the AUVs sawtooth (i.e., yo-yo) trajectory in the vertical dimension and takes advantage of the fact that in one yo-yo cycle, the vehicle crosses the horizontal plume (i.e., the strong-signal layer) twice. On the first crossing, the vehicle detects the peak and logs the corresponding depth (after correcting for the detection delay). On the second crossing, a sampling is triggered when the vehicle reaches the depth logged on the first crossing, based on the assumption that the depth of the horizontal oil layer does not vary much between two successive crossings that are no more than several hundred meters apart. In this paper, we present the algorithm and its performance in an AUV mission on 3 June 2010 in the Gulf of Mexico. In addition, we present an improvement to the algorithm and the corresponding results from postprocessing the AUV mission data.

Mapping payload development for MBARI's Dorado-class AUVs

The Monterey Bay Aquarium Research Institute (MBARI) is developing an autonomous seafloor mapping capability for deep ocean science applications. The MBARI Mapping AUV is a 0.53 m (21 in) diameter, 5.1 m (16.7 ft) long, Dorado-class vehicle designed to carry four mapping sonars. The primary sensor is a 200 kHz multibeam sonar producing swath bathymetry and sidescan. In addition, the vehicle carries 100 kHz and 410 kHz chirp sidescan sonars, and a 2-16 kHz sweep chirp subbottom profiler. Navigation and attitude data are obtained from an inertial navigation system (INS) incorporating a ring laser gyro and a 300 kHz Doppler velocity log (DVL). The vehicle also includes acoustic modem, ultra-short baseline navigation, and long-baseline navigation systems. A single cylindrical pressure housing contains all of the mapping sonar electronics, and the main vehicle control and acoustic communications electronics are housed in a separate glass ball. The Mapping AUV is powered by three 2 kWhr Li-polymer batteries, providing an expected mission duration of 12 hours at a typical speed of 1.5 m/s. The assembled package is rated to 6000 m depth, allowing MBARI to conduct high-resolution mapping of the deep-ocean seafloor. Initial at-sea testing commenced in May 2004 using the subbottom profiler and 100 kHz sidescan. The sonar package will also be mountable on ROV Ventana, allowing surveys at altitudes < 10 m at topographically challenging sites. The MBARI Seafloor Mapping team is now working towards integration of the multibeam sonar and towards achieving regular operations during 2005.

Preliminary Results for Model-Based Adaptive Control of an Autonomous Underwater Vehicle

We discuss a novel autonomous system which integrates onboard deliberation with execution and probabilistic state estimation for an adaptive Autonomous Underwater Vehicle for deep sea exploration. The work is motivated by the need to have AUVs be goal-directed, perceptive, adaptive and robust in the context of dynamic and uncertain conditions. The challenges leading to deployment required dealing with modeling uncertainty and integrating control loops at different levels of abstraction and response for a dynamic environment. The system is general-purpose and adaptable to other ocean going and terrestrial platforms.

Thermocline tracking based on peak-gradient detection by an autonomous underwater vehicle

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.