MOOS-DAWG'11

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* The Yellowfin UUV

* Unmanned Underwater Vehicles (UUVs) / Autonomous Underwater Vehicles (AUVs)

* UUVs/AUVs
* Underwater SLAM
* Acoustic Communications

!! Talk-06: ''Autonomy and Collaboration Research using MOOS with the Yellowfin UUV at the Georgia Tech Research Institute''

Georgia Tech Research Institute's Yellowfin is a low-cost, lightweight AUV designed for use in mutli-vehicle collaborative missions. It utilizes the MOOS middleware in addition to IvP-Helm to enable rapid development of the platform as well as autonomous behavior research. MOOS plays a large component in continuing research. IvP-Helm is a key component in developing methods of recognizing behaviors in multi-vehicle missions should there be a loss of communications or vehicle malfunction. Identifying and compensating for behavior changes due to such events will lead to more robust collaboration in multi-AUV missions. Additionally, the research also focuses on passivity based controls over acoustic communications with an unknown discrete time-varying delay in order to improve the stability of vehicle control. Finally, underwater navigation through the use of a high frequency imaging sonar underwater SLAM is also currently being researched on the Yellowfin platform.

Use of the MOOS-IvP package in addition to pAcommsHandler provides a large backbone of the vehicle's software programming. This presentation will briefly overview our research and discuss how MOOS influences both the hardware and software development of the Yellowfin AUV. Roadblocks encountered using MOOS in the process of our research will be discussed as well as suggestions for improvements.

!! Talk-06: ''Autonomy and Collaboration Research using MOOS with the Yellofin UUV at the Georgia Tech Research Institute''

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!! Talk-01: ''Autonomy and Collaboration Research using MOOS with the Yellofin UUV at the Georgia Tech Research Institute''

!!!!%color=#449944% '''Andrew Melim, Michael Novitzky, Paul Varnell, Kevin DeMarco, Tom Collins, Mick West, Georgia Tech Research Institute'''

Georgia Tech Research Institute's Yellow􏰁n is a low-cost, lightweight AUV designed for use in mutli-vehicle collaborative missions. It utilizes the MOOS middleware in addition to IvP-Helm to enable rapid development of the plat- form as well as autonomous behavior research. MOOS plays a large component in continuing research. IvP-Helm is a key component in developing methods of recognizing behaviors in multi-vehicle missions should there be a loss of com- munications or vehicle malfunction. Identifying and compensating for behavior changes due to such events will lead to more robust collaboration in multi-AUV missions. Additionally, the research also focuses on passivity based controls over acoustic communications with an unknown discrete time-varying delay in order to improve the stability of vehicle control. Finally, underwater navigation through the use of a high frequency imaging sonar underwater SLAM is also currently being researched on the Yellow􏰁n platform.

Use of the MOOS-IvP package in addition to pAcommsHandler provides a large backbone of the vehicle's software programming. This presentation will brie􏰂y overview our research and discuss how MOOS in􏰂uences both the hard- ware and software development of the Yellow􏰁n AUV. Roadblocks encountered using MOOS in the process of our research will be discussed as well as sugges- tions for improvements.

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!! Talk-01: ''Behaviour Development for Anti-Submarine Warfare: The Design of a MOOS-IvP Behavior Based on Maximizing the Doppler of Autonomous Assets Operating Within a Bistatic Sonar System''

!!!!%color=#449944% '''Kevin LePage, NATO Undersea Research Centre'''

The NATO Undersea Research Centre is currently exploring system concepts for collaborative ASW using AUVs.  As part of this effort the design of autonomy algorithms (behaviours) which are adaptive on Doppler-sensitive sonar signals is being pursued.  MOOS-IvP is currently used onboard two Ocean Explorer AUVs which each have horizontal line arrays and accompanying CW signal processing software capable of converting acoustic signals into time-bearing-Doppler contacts.  These contacts are fused with FM contacts within NURC's DMHT tracker.  The fused CW-FM tracks are acted on by the behaviours implemented within the MOOS-IvP software architecture.  In this talk we explore the performance of a behaviour which seeks to maximize the future Doppler on contacts of interest. The collaborative use of this behaviour with a second vehicle performing traditional FM processing is also considered.

* MOOS-IvP
* Anti-Submarine Warfare
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!! Talk-01: ''MOOS Then, Now and Next''

I will provide a perspective about where MOOS came from, why I designed it as I did, where I think its
strengths lie and where I think there is room for improvement. I will describe of the range of
platforms and projects MOOS has been, is and will be used on. I won't restrict attention to the marine domain - indeed some of the most challenging deployments have been on land in particular large scale infrastructure free navigation. As I conclude I'll look ahead to the planned next substantial release of MOOS  and describe the new functionality therein.

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!! Talk-01: ''MOOS Updates (PLACEHOLDER)''

!!!!%color=#449944% '''Paul Newman, Oxford'''

No Abstract Yet.

* Academia

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!! Talk-29: ''Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm''

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!!!!%color=#449944% '''Matthew J. Bays, Jean-François Kamath and Signe A. Redfield, NSWC-PCD'''

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!!!!%color=#449944% '''Matthew J. Bays, Jean- François Kamath and Signe A. Redfield, NSWC-PCD'''

!! Talk-04: ''Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm''

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!! ''Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm''

%color=#449944% '''Matthew J. Bays, Jean- François Kamath and Signe A. Redfield, NSWC-PCD'''

We address the integration and field testing of a novel reacquire/identify(RID) pattern generation algorithm.  This algorithm, known as Probabilistic Reacquire/ID Optimal Path Selection (PROPS), is designed to plan a path for a sidescan sonar equipped underwater vehicle in order to produce multiple views of a cluster of discrete targets.  The desired pattern minimizes the total number of turns and time required, while attaining appropriate coverage of the targets. Initial tests of the pattern generation algorithm suggest that it requires between 35% and 95% of the time required by the standard “star” RID pattern.  Following a brief description of the algorithm itself, we present the integration of the algorithm, both as a stand-alone MOOS module and as a library using a standard RID pattern generator created from the MOOS-IvP Helm autonomy toolkit.  Simulation and field test results of the algorithm on a REMUS 100 autonomous underwater vehicle are included.

* MCM

!! ''MOOS-Enabled Semi-Autonomous Remote USV Operations''

%color=#449944% '''Signe Redfield, NSWC-PCD'''

A multi-vehicle mission involving simultaneous identification (by UUVs) and neutralization (by a USV) of targets is complicated by the need to keep the neutralization efforts distant from the
identification vehicles.  As targets are identified by the UUVs, they are relayed to the USV for imaging (proxy for neutralization).  The USV plans a sequence of neutralization efforts based on desired efficiency (prosecuting targets in close proximity in the same sequence), neutralization capacity (number of targets that can be prosecuted without reloading), the location of the reloading depot, and distance from other vehicles.  We present a solution to this variation of the capacitated vehicle routing problem, implemented on a semi-autonomous USV.  MOOS performed the autonomous portion of the mission running on a remote laptop while a human operator ran a teleoperated underwater vehicle launched and retrieved from the USV as a proxy for the neutralization system as each target was reached. Together the system demonstrated semi-autonomous remote USV operations, with the human operator working smoothly with the autonomous system.

This talk addresses the challenge of autonomously and adaptively tracking features of the underwater environment using AUVs running the MOOS-IvP autonomy software.  This problem is addressed from concept to implementation in the field on various AUV platforms, developing specifically the example of thermocline tracking.  Some recent research involving methods for feature tracking on board multiple AUVs operating simultaneously and collaboratively to detect an underwater feature will also be discussed briefly.

* Environmental Sampling

* Autonomy
* MOOS-IvP
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%color=#449944% '''Stephanie Petillo, MIT (LAMSS)'''

!! ''Autonomous Adaptive Environmental Feature Tracking on Board AUVs: Tracking the Thermocline''

%color=#449944% '''Stephanie Petillo, MIT (LAMSS)''

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* Acoustic Communications,
* Multi-Vehicle Autonomy
* Autonomy%%

%color=#BD614A% '''Topics:''' Acoustic Communications, Multi-Vehicle Autonomy, Autonomy%%

One of the greatest challenges of working in the underwater regime is the severe limitations of acoustic communications. This problem becomes even more evident in multi-vehicle autonomy, when vehicles must continually update each other with their state and intentions to achieve cooperative goals. In order to support tests of a multi-vehicle arbiter framework, an optimization scheme was created and implemented as a MOOS module to enable sufficient message passing between vehicles. Using this tool, vehicle state and destination, shared map updates, updated algorithm parameters, target information, and decision reconciliation can be effectively shared between vehicles using the published Compact Control Language (CCL) standard for acoustic messages.

''Topics:'' Acoustic Communications, Multi-Vehicle Autonomy, Autonomy

%color=#449944% '''Andrew Bouchard, NSWC-PCD'''

%color=#449944% '''Andrew Bouchard, NSWC PCD'''

%color=#449944% '''Andrew Bouchard, NSWC PCD'''%

%color=#449944% !!! '''Andrew Bouchard, NSWC PCD'''%

!!! '''Andrew Bouchard, NSWC PCD'''

!! ''Unmanned Robot Message Optimization Method (URMOM)''

!! Title: ''Unmanned Robot Message Optimization Method (URMOM)''

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Title: ''Unmanned Robot Message Optimization Method (URMOM)''

'''Andrew Bouchard, NSWC PCD'''

One of the greatest challenges of working in the underwater regime is the severe limitations of acoustic communications. This problem becomes even more evident in multi-vehicle autonomy, when vehicles must continually update each other with their state and intentions to achieve cooperative goals. In order to support tests of a multi-vehicle arbiter framework, an optimization scheme was created and implemented as a MOOS module to enable sufficient message passing between vehicles. Using this tool, vehicle state and destination, shared map updates, updated algorithm parameters, target information, and decision reconciliation can be effectively shared between vehicles using the published Compact Control Language (CCL) standard for acoustic messages.

     One of the greatest challenges of working in the underwater regime is the
severe limitations of acoustic communications. This problem becomes even more evident in multi-vehicle autonomy, when vehicles must continually update each other with their state and intentions to achieve cooperative goals. In order to support tests of a multi-vehicle arbiter framework, an optimization scheme was created and implemented as a MOOS module to enable sufficient message passing between vehicles. Using this tool, vehicle state and destination, shared map updates, updated algorithm parameters, target information, and decision reconciliation can be effectively shared between vehicles using the published Compact Control Language (CCL) standard for acoustic messages.