Sensible behaviour strategies for AUVs in ASW scenarios

Hughes, David T.; Kemna, Stephanie; Hamilton, Michael; Been, Robert

doi:10.1109/oceanssyd.2010.5603640

Cited by 11 publications

(7 citation statements)

References 9 publications

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“…Unlike traditional behaviorbased control such as that championed by Brooks [4], the IvP Helm behaviors have state and therefore can run models and act on collected data, as is done in the behaviors presented in this work. MOOS-IvP has been used extensively in marine vehicle autonomy research, such as cooperative search tasks [5]- [7] and adaptive oceanographic sensing [8], [9].…”

Section: A Moos-ivp Autonomy Softwarementioning

confidence: 99%

Model-Based Adaptive Behavior Framework for Optimal Acoustic Communication and Sensing by Marine Robots

Schneider

Schmidt

2013

IEEE J. Oceanic Eng.

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Abstract-A hybrid data-and model-based autonomous environmental adaptation framework is presented which allows autonomous underwater vehicles (AUVs) with acoustic sensors to follow a path which optimizes their ability to maintain connectivity with an acoustic contact for optimal sensing or communication. The adaptation framework is implemented within the behavior-based MOOS-IvP marine autonomy architecture and uses a new embedded high-fidelity acoustic modeling infrastructure, the Generic Robotic Acoustic Model (GRAM), to provide real-time estimates of the acoustic environment under changing environmental and situational scenarios. A set of behaviors that combine adaptation to the current acoustic environment with strategies that extend the decision horizon beyond that of typical behavior-based systems have been developed, implemented, and demonstrated in a series of field experiments and virtual experiments in a MOOS-IvP simulation.

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Section: A Moos-ivp Autonomy Softwarementioning

confidence: 99%

Model-Based Adaptive Behavior Framework for Optimal Acoustic Communication and Sensing by Marine Robots

Schneider

Schmidt

2013

IEEE J. Oceanic Eng.

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“…MOOS-IvP has been used extensively in marine vehicle autonomy research, such as cooperative search tasks [30,81,82] and adaptive oceanographic sensing [83,84].…”

Section: Moos-ivp Autonomy Softwarementioning

confidence: 99%

Advances in integrating autonomy with acoustic communications for intelligent networks of marine robots

Schneider¹

2013

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Autonomous marine vehicles are increasingly used in clusters for an array of oceanographic tasks. The effectiveness of this collaboration is often limited by communications: throughput, latency, and ease of reconfiguration. This thesis argues that improved communication on intelligent marine robotic agents can be gained from acting on knowledge gained by improved awareness of the physical acoustic link and higher network layers by the AUV's decision making software.This thesis presents a modular acoustic networking framework, realized through a C++ library called goby-acomms, to provide collaborating underwater vehicles with an efficient short-range single-hop network. goby-acomms is comprised of four components that provide: 1) losslessly compressed encoding of short messages; 2) a set of message queues that dynamically prioritize messages based both on overall importance and time sensitivity; 3) Time Division Multiple Access (TDMA) Medium Access Control (MAC) with automatic discovery; and 4) an abstract acoustic modem driver.Building on this networking framework, two approaches that use the vehicle's "intelligence" to improve communications are presented. The first is a "non-disruptive" approach which is a novel technique for using state observers in conjunction with an entropy source encoder to enable highly compressed telemetry of autonomous underwater vehicle (AUV) position vectors. This system was analyzed on experimental data and implemented on a fielded vehicle. Using an adaptive probability distribution in combination with either of two state observer models, greater than 90% compression, relative to a 32-bit integer baseline, was achieved.The second approach is "disruptive," as it changes the vehicle's course to effect an improvement in the communications channel. A hybrid data-and model-based autonomous environmental adaptation framework is presented which allows autonomous underwater vehicles (AUVs) with acoustic sensors to follow a path which optimizes their ability to maintain connectivity with an acoustic contact for optimal sensing or communication.

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“…The behavior, demonstrated successfully in the GLINT09 [18] at-sea experiment, used only contacts. In an Oceans 2010 accompanying paper [4], tracker-based approaches are detailed that use measurement-error models [19,20] and autonomous behavior algorithms based on information theory [3,21] rather than the 'keep-target-inbroadside' behavior employed during GLINT09.…”

Section: Autonomous Auv Behaviormentioning

confidence: 99%

“…Some aspects of this latter research area are covered in an accompanying paper [4]. In this paper, however, we will discuss options for ASW sensing and the NURC design.…”

Section: Introductionmentioning

confidence: 99%

Cooperative anti-submarine warfare at NURC moving towards a net-centric capability

Been

Hughes

Potter

et al. 2010

Oceans'10 Ieee Sydney

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The NATO Undersea Research Centre (NURC) conducts research on off-board Low Frequency Active (LFA) sensors for use in Cooperative distributed ASW (CASW). The objective is to create a scalable and autonomous system that removes vulnerable personnel from the vicinity of high risk, is cheaper than conventional ship-based sonar and that potentially leverages the benefits of multi-static operations by creating an increased diversity of assets and spatial distribution. Such systems would also release personnel to perform tasks elsewhere. The NURC intends to prototype an open-architecture system with a high degree of interoperability in a concept demonstration in 2012.

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Sensible behaviour strategies for AUVs in ASW scenarios

Cited by 11 publications

References 9 publications

Model-Based Adaptive Behavior Framework for Optimal Acoustic Communication and Sensing by Marine Robots

Model-Based Adaptive Behavior Framework for Optimal Acoustic Communication and Sensing by Marine Robots

Advances in integrating autonomy with acoustic communications for intelligent networks of marine robots

Cooperative anti-submarine warfare at NURC moving towards a net-centric capability

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