11-Murphy
Talk.11-Murphy History
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- UUVs/AUVs
- Unmanned Underwater Vehicles (UUVs) / Autonomous Underwater Vehicles (AUVs)
- MOOS-IvP
- Anti-Submarine Warfare
- UUVs/AUVs
- Acoustic Communications
- Image Compression
Chris Murphy, Woods Hole Oceanographic Institute
Chris Murphy, Woods Hole Oceanographic Institute (WHOI)
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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
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Talk-11: Fully Embedded Wavelet Compression for Low Bandwidth Image Telemetry
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.
Chris Murphy, Woods Hole Oceanographic Institute
AUVs typically communicate with scientists on the surface over an unreliable acoustic channel, resulting in very low data throughput. While there are several examples of scientific data, even imagery, being successfully transmitted over high rate acoustic links, channel coding methods with high rates of error-correction are often employed that limit data throughput to tens or a few hundred bits per second. Little research exists into appropriate methods for image and data compression for acoustic links at these very low rates.
We recently have experienced success using compression techniques based upon the Set Partitioning in Hierarchical Trees (SPIHT) embedded coding method, and feel they are particularly suited to underwater data. In this paper we describe how these methods can be applied to compress scalar environmental data and imagery for communication over acoustic links. We also present initial results of sea trials performed near Rota in the Commonwealth of Northern Marianas Islands, during which images were captured, compressed and transmitted in-situ.
Talk-01: MOOS Then, Now and Next
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.
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
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 Core
- Academia
- MOOS-IvP
- Anti-Submarine Warfare
Talk-01: MOOS Updates (PLACEHOLDER)
Talk-01: MOOS Then, Now and Next
No Abstract Yet.
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
Talk-29: Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm
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.
Talk-01: MOOS Updates (PLACEHOLDER)
Paul Newman, Oxford
No Abstract Yet.
- Autonomy
- MOOS-IvP
- MCM
- UUVs
- Navy Labs
- Academia
Talk-04: Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm
Talk-29: Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm
Matthew J. Bays, Jean- François Kamath and Signe A. Redfield, NSWC-PCD
Matthew J. Bays, Jean-François Kamath and Signe A. Redfield, NSWC-PCD
Matthew J. Bays, Jean- François Kamath and Signe A. Redfield, NSWC-PCD
Matthew J. Bays, Jean- François Kamath and Signe A. Redfield, NSWC-PCD
Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm
Talk-04: Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm
MOOS-Enabled Semi-Autonomous Remote USV Operations
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.
Integration and Testing of a Novel Reacquire/Identify Pattern Generation Algorithm
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.
- Multi-Vehicle Autonomy
- Neutralization
- MCM
- USVs
Autonomous Adaptive Environmental Feature Tracking on Board AUVs: Tracking the Thermocline
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.
MOOS-Enabled Semi-Autonomous Remote USV Operations
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.
- Environmental Sampling
- Neutralization
- USVs
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.
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.
- Acoustic Communications,
- Environmental Sampling
- Autonomy
- Autonomy
- MOOS-IvP
'Stephanie Petillo, MIT (LAMSS)
Stephanie Petillo, MIT (LAMSS)
Unmanned Robot Message Optimization Method (URMOM)
Andrew Bouchard, NSWC-PCD
Autonomous Adaptive Environmental Feature Tracking on Board AUVs: Tracking the Thermocline
'Stephanie Petillo, MIT (LAMSS)
Topics: Acoustic Communications, Multi-Vehicle Autonomy, Autonomy
Topics:
- Acoustic Communications,
- Multi-Vehicle Autonomy
- Autonomy
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.
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
Andrew Bouchard, NSWC PCD
Andrew Bouchard, NSWC-PCD
Andrew Bouchard, NSWC PCD%
Andrew Bouchard, NSWC PCD
!!! Andrew Bouchard, NSWC PCD%
Andrew Bouchard, NSWC PCD%
Andrew Bouchard, NSWC PCD
!!! Andrew Bouchard, NSWC PCD%
Andrew Bouchard, NSWC PCD
Andrew Bouchard, NSWC PCD
Title: Unmanned Robot Message Optimization Method (URMOM)
Unmanned Robot Message Optimization Method (URMOM)
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
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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.
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.
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.