Talk
• The EvoLogics modem has the ability to operate in different modes, which should remain available.
No Abstract Yet.
[[Talk.04-Redfield|Prev-Talk]] | [[Talk.04-Redfield|Next-Talk]]
* Multi-Vehicle Autonomy
* USVs
* Environmental Sampling
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.
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.
02-Schmidt
Talk.02-Schmidt History
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!! Talk-02: ''Collaborative Marine Sensing with MOOS-IvP''
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!! Talk-02: ''Physics-based Simulation Environment for Adaptive and Collaborative Marine Sensing with MOOS-IvP''
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!! Talk-19: ''Collaborative Marine Sensing with MOOS-IvP''
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!! Talk-02: ''Collaborative Marine Sensing with MOOS-IvP''
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* Collaborative Autonomy
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* Autonomy / Collaborative Autonomy
* Mine Countermeasures
* Anti-Submarine Warfare
* Mine Countermeasures
* Anti-Submarine Warfare
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* Anti-Submarine Warfare
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* Simulation
* Ocean Modeling
* Collaborative Autonomy
* Ocean Modeling
* Collaborative Autonomy
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!! Talk-18: ''The EvoLogics Acoustic Modem Integration into NURC’s MOOS Environment''
!!!!%color=#449944% '''Arjan Vermeij, NATO Undersea Research Centre'''
The NATO Undersea Research Centre (NURC) recently acquired acoustic modems from EvoLogics. These modems, of type S2C R 8/16, are to be used in an upcoming sea trial on board our two Ocean Explorer (OEX) autonomous underwater vehicles (AUVs). They should provide the ability to communicate at longer ranges and possibly with a higher data throughput, than currently achievable with our WHOI (Woods Hole Oceanographic Institute) Micro-Modems.
As part of the Collaborative Anti-Submarine Warfare programme, NURC researches communications and networks in the maritime environment. This project aims to evolve underwater communications from point-to-point underwater messaging into true net- working, taking into account the limitations imposed by the underwater acoustic channel, such as high latency and bandwidth constraints. This involves the development of an underwater communications stack.
There are some requirements on the integration ofthe EvoLogics modem into NURC’s MOOS environment:
* The EvoLogics modem hasthe ability to operate in different modes, which should remain available.
* The MAC layer, already available in the EvoLogics modem, should be usable.
* The integration should allow for potential replacement and addition of components developed within the communications and networking task.
* If possible, the EvoLogics modem should be able to work in parallel to the WHOI Micro-Modem.
This presentation discusses the design and developed applications as part of this inte- gration process. Furthermore, initial results obtained during the June engineering trial are presented.
A reprint of this presentation, including the source code of the developed processes, will be made available through NURC, after the conference.
!!!!%color=#449944% '''
The NATO Undersea Research Centre (NURC) recently acquired acoustic modems from EvoLogics. These modems,
As part of
There are some requirements on the integration of
* The EvoLogics modem has
* The MAC layer, already available in the EvoLogics modem, should be usable.
* The integration should allow for potential replacement
* If possible, the EvoLogics modem should be able to work in parallel to the WHOI Micro-Modem.
This presentation discusses the design and developed applications as part of this inte- gration process. Furthermore, initial results obtained during the June engineering trial are presented.
A reprint of this presentation, including the source code of the developed processes, will be made available through NURC, after the conference
to:
!! Talk-19: ''Collaborative Marine Sensing with MOOS-IvP''
!!!!%color=#449944% '''Henrik Schmidt, MIT, Laboratory for Autonomous Marine Sensing Systems, Center for Ocean Engineering'''
One of the main obstacles to the development of adaptive and collaborative autonomy is the unpredictability of the platform actions when the underwater vehicles are released to autonomous control based on real-time sensory input. The most efficient and cost-effective approach to mitigating the risk is the extensive use of a simulation environment which accurately mimics the actual system, not only in regard to the onboard autonomy and platform dynamics, but even more critical, accurately reproduces the performance of the sensor systems. For adaptive and collaborative acoustic sensing, a particular challenge in this regard is the real-time generation of acoustic sensor data that accurately represents the complex environmental acoustics of the ocean environment. With its modular structure, MOOS-IvP is ideal for establishing a multi-platform simulation infrastructure, where the actual autonomy configuration can be operated in a virtual environment which accurately mimics the real ocean. The Laboratory for Autonomous Marine Sensing Systems has developed a suite of sensor simulations of various levels of fidelity that allow the execution of highly realistic, adaptive and collaborative acoustic and non-acoustic sensing missions. The extensive use of virtual experiments in this simulation environment has been a key to a string of successful field deployments of distributed sensing systems over the last decade [Work supported by ONR, and the NATO Undersea Research Centre].
!!!!%color=#449944% '''Henrik Schmidt, MIT, Laboratory for Autonomous Marine Sensing Systems, Center for Ocean Engineering'''
One of the main obstacles to the development of adaptive and collaborative autonomy is the unpredictability of the platform actions when the underwater vehicles are released to autonomous control based on real-time sensory input. The most efficient and cost-effective approach to mitigating the risk is the extensive use of a simulation environment which accurately mimics the actual system, not only in regard to the onboard autonomy and platform dynamics, but even more critical, accurately reproduces the performance of the sensor systems. For adaptive and collaborative acoustic sensing, a particular challenge in this regard is the real-time generation of acoustic sensor data that accurately represents the complex environmental acoustics of the ocean environment. With its modular structure, MOOS-IvP is ideal for establishing a multi-platform simulation infrastructure, where the actual autonomy configuration can be operated in a virtual environment which accurately mimics the real ocean. The Laboratory for Autonomous Marine Sensing Systems has developed a suite of sensor simulations of various levels of fidelity that allow the execution of highly realistic, adaptive and collaborative acoustic and non-acoustic sensing missions. The extensive use of virtual experiments in this simulation environment has been a key to a string of successful field deployments of distributed sensing systems over the last decade [Work supported by ONR, and the NATO Undersea Research Centre].
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* The EvoLogics modem has the ability to operate in different modes, which should remain available.
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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.
!!!!%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
to:
!! Talk-18: ''The EvoLogics Acoustic Modem Integration into NURC’s MOOS Environment''
!!!!%color=#449944% '''Arjan Vermeij, NATO Undersea Research Centre'''
The NATO Undersea Research Centre (NURC) recently acquired acoustic modems from EvoLogics. These modems, of type S2C R 8/16, are to be used in an upcoming sea trial on board our two Ocean Explorer (OEX) autonomous underwater vehicles (AUVs). They should provide the ability to communicate at longer ranges and possibly with a higher data throughput, than currently achievable with our WHOI (Woods Hole Oceanographic Institute) Micro-Modems.
As part of the Collaborative Anti-Submarine Warfare programme, NURC researches communications and networks in the maritime environment. This project aims to evolve underwater communications from point-to-point underwater messaging into true net- working, taking into account the limitations imposed by the underwater acoustic channel, such as high latency and bandwidth constraints. This involves the development of an underwater communications stack.
There are some requirements on the integration of the EvoLogics modem into NURC’s MOOS environment:
• The EvoLogics modem has the ability to operate in different modes, which should remain available.
* The MAC layer, already available in the EvoLogics modem, should be usable.
* The integration should allow for potential replacement and addition of components developed within the communications and networking task.
* If possible, the EvoLogics modem should be able to work in parallel to the WHOI Micro-Modem.
This presentation discusses the design and developed applications as part of this inte- gration process. Furthermore, initial results obtained during the June engineering trial are presented.
A reprint of this presentation, including the source code of the developed processes, will be made available through NURC, after the conference.
!!!!%color=#449944% '''Arjan Vermeij, NATO Undersea Research Centre'''
The NATO Undersea Research Centre (NURC) recently acquired acoustic modems from EvoLogics. These modems, of type S2C R 8/16, are to be used in an upcoming sea trial on board our two Ocean Explorer (OEX) autonomous underwater vehicles (AUVs). They should provide the ability to communicate at longer ranges and possibly with a higher data throughput, than currently achievable with our WHOI (Woods Hole Oceanographic Institute) Micro-Modems.
As part of the Collaborative Anti-Submarine Warfare programme, NURC researches communications and networks in the maritime environment. This project aims to evolve underwater communications from point-to-point underwater messaging into true net- working, taking into account the limitations imposed by the underwater acoustic channel, such as high latency and bandwidth constraints. This involves the development of an underwater communications stack.
There are some requirements on the integration of the EvoLogics modem into NURC’s MOOS environment:
• The EvoLogics modem has the ability to operate in different modes, which should remain available.
* The MAC layer, already available in the EvoLogics modem, should be usable.
* The integration should allow for potential replacement and addition of components developed within the communications and networking task.
* If possible, the EvoLogics modem should be able to work in parallel to the WHOI Micro-Modem.
This presentation discusses the design and developed applications as part of this inte- gration process. Furthermore, initial results obtained during the June engineering trial are presented.
A reprint of this presentation, including the source code of the developed processes, will be made available through NURC, after the conference.
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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.
!!!!%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
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
to:
!! 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.
!!!!%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.
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* MOOS Core
* Academia
%%
* Academia
%%
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* MOOS-IvP
* Anti-Submarine Warfare
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* Anti-Submarine Warfare
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!! Talk-01: ''MOOS Updates (PLACEHOLDER)''
to:
!! Talk-01: ''MOOS Then, Now and Next''
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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.
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-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.
!!!!%color=#449944% '''
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
to:
!! Talk-01: ''MOOS Updates (PLACEHOLDER)''
!!!!%color=#449944% '''Paul Newman, Oxford'''
No Abstract Yet.
!!!!%color=#449944% '''Paul Newman, Oxford'''
No Abstract Yet.
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* Autonomy
* MOOS-IvP
* MCM
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* Navy Labs
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* MCM
* UUVs
* Navy Labs
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* Academia
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!!!!%color=#4444BB% '''Categories:''' \
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!! Talk-04: ''Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm''
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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'''
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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'''
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!! ''Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm''
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!! Talk-04: ''Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm''
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!! ''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 plansa 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.
%color=#449944% '''
A multi-vehicle mission involving simultaneous identification (by UUVs) and neutralization (by a USV)
identification vehicles. As targets are identified by the UUVs, they are relayed to the USV for imaging (proxy for neutralization). The USV plans
to:
!! ''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.
%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.
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* Neutralization
to:
* MCM
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!! ''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.
%color=#449944% '''
to:
!! ''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.
%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.
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* Neutralization
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* USVs
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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.
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* Acoustic Communications,
to:
* Environmental Sampling
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* Autonomy%%
to:
* Autonomy
* MOOS-IvP
%%
* MOOS-IvP
%%
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%color=#449944% '''Stephanie Petillo, MIT (LAMSS)''
to:
%color=#449944% '''Stephanie Petillo, MIT (LAMSS)'''
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!! ''Unmanned Robot Message Optimization Method (URMOM)''
%color=#449944% '''Andrew Bouchard, NSWC-PCD'''
%color=#449944% '''
to:
!! ''Autonomous Adaptive Environmental Feature Tracking on Board AUVs: Tracking the Thermocline''
%color=#449944% '''Stephanie Petillo, MIT (LAMSS)''
%color=#449944% '''Stephanie Petillo, MIT (LAMSS)''
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%color=#BD614A% '''Topics:''' Acoustic Communications, Multi-Vehicle Autonomy, Autonomy%%
to:
%color=#BD614A% '''Topics:''' \
* Acoustic Communications,
* Multi-Vehicle Autonomy
* Autonomy%%
* Acoustic Communications,
* Multi-Vehicle Autonomy
* Autonomy%%
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''Topics:'' Acoustic Communications, Multi-Vehicle Autonomy, Autonomy
to:
%color=#BD614A% '''Topics:''' Acoustic Communications, Multi-Vehicle Autonomy, Autonomy%%
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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.
to:
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
''Topics:'' Acoustic Communications, Multi-Vehicle Autonomy, Autonomy
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%color=#449944% '''Andrew Bouchard, NSWC PCD'''
to:
%color=#449944% '''Andrew Bouchard, NSWC-PCD'''
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%color=#449944% '''Andrew Bouchard, NSWC PCD'''%
to:
%color=#449944% '''Andrew Bouchard, NSWC PCD'''
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%color=#449944% !!! '''Andrew Bouchard, NSWC PCD'''%
to:
%color=#449944% '''Andrew Bouchard, NSWC PCD'''%
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!!! '''Andrew Bouchard, NSWC PCD'''
to:
%color=#449944% !!! '''Andrew Bouchard, NSWC PCD'''%
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'''Andrew Bouchard, NSWC PCD'''
to:
!!! '''Andrew Bouchard, NSWC PCD'''
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!! Title: ''Unmanned Robot Message Optimization Method (URMOM)''
to:
!! ''Unmanned Robot Message Optimization Method (URMOM)''
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Title: ''Unmanned Robot Message Optimization Method (URMOM)''
to:
!! Title: ''Unmanned Robot Message Optimization Method (URMOM)''
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(:notitle:)
(:notitlegroup:)
(:nofooter:)
Title: ''Unmanned Robot Message Optimization Method (URMOM)''
'''Andrew Bouchard, NSWC PCD'''
(:notitlegroup:)
(:nofooter:)
Title: ''Unmanned Robot Message Optimization Method (URMOM)''
'''Andrew Bouchard, NSWC PCD'''
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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.
to:
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.
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One of the greatest challenges of working in the underwater regime is the \
severe limitations of acoustic communications. This problem becomes even moree\
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.
severe limitations of acoustic communications. This problem becomes even more
vident
her
upport
reated
tween
tes
ion
rol
to:
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.
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.
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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 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.
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 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.