MOOS-DAWG'11

* Collaborative Autonomy

* USVs/ASCs
* UUVs/AUVs

* The Iver2 UUV

* Iver2

An autonomous surface craft (ASC) is used as a communications and navigations aid to support collaborative autonomous underwater vehicles performing surveys.  The ASC is enabled with a backseat computer that implements MOOS-IVP as the middleware for the AUV control architecture.  A MOOS process optimizes the ASC path-planning so the ASC stays within communications range of the two (or more) submerged AUVs.  The ASC has access to DGPS and passes its position and range from the submerged AUVs to the submerged AUVs to aid in their navigations.  This system is realized with IVER2 AUVs for the submerged AUVs and either another IVER2 or a robotic catamaran for the ASC. The ASC path-planner consists of a MOOS process that works in pre-deployment or underway mode. In pre-deployment mode the optimized ASC path is calculated based on a priori knowledge of the AUVs' missions.  In underway mode, the MOOs process optimizes the ASC path on-the-fly as it receives the AUVs' mission updates(position, heading, and speed). The work to date will be described including the MOOS implementation.

* Anti-Submarine Warfare

!!!!%color=#449944% '''Jonathan Hudson, Mae Seto, Defense Research and Development Canada'''

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!!!!%color=#449944% '''Jonathan Hudson, Mae Seto, 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.

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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'''

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!! Talk-01: ''MOOS Then, Now and Next''

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

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.

* MOOS Core
* Academia
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!! Talk-01: ''MOOS Updates (PLACEHOLDER)''

No Abstract Yet.

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!! Talk-29: ''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.

* Autonomy
* MOOS-IvP
* MCM
* UUVs
* Navy Labs

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!! Talk-04: ''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'''

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

%color=#BD614A% '''Topics:''' \

!! ''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.

* Neutralization

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

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

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.

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.

* Acoustic Communications,

* Autonomy%%

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

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

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

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

''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.

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

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

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

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

'''Andrew Bouchard, NSWC PCD'''

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

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

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 e\
vident in multi-vehicle autonomy, when vehicles must continually update each ot\
her with their state and intentions to achieve cooperative goals. In order to s\
upport tests of a multi-vehicle arbiter framework, an optimization scheme was c\
reated and implemented as a MOOS module to enable sufficient message passing be\
tween vehicles. Using this tool, vehicle state and destination, shared map upda\
tes, updated algorithm parameters, target information, and decision reconciliat\
ion can be effectively shared between vehicles using the published Compact Cont\
rol Language (CCL) standard for acoustic messages.