Nested Auton
459
Part B | 20
20. Nested Autonomy for Distributed Ocean Sensing
Henrik Schmidt, Michael R. Benjamin, Stephanie M. Petillo, Raymond Lum
Nested autonomy is a new control paradigm
for distributed undersea surveillance, specifically designed for the layered communication
infrastructure provided by the low-bandwidth
underwater acoustic communication and the intermittent RF connectivity. Implemented using
the open-source MOOS-IvP behavior-based, autonomous command and control architecture, it
provides the fully integrated sensing, modeling,
and controlling that allows each platform to autonomously detect, classify, localize, and track an
episodic event in the ocean, without depending
on any operator command and control. The prosecution of an event, such as the detection and
tracking of a subsea volcanic plume or an oceanographic feature, may be initiated by the operators
or entirely autonomously by an onboard detection capability. The event information collected
by each node in the network is reported back to
the operators by transmitting an event report, using a dedicated command and control language.
Collaborative processing and control is exploited
when the communication channel allows, for example, collaborative tracking of a coastal front,
or the tracking of manmade sources or marine
mammals.
20.1 Nested Autonomy ................................ 460
20.2 Concept of Operations (CONOPS) ............ 461
20.2.1 Field Level ................................ 461
20.2.2 Cluster Level.............................. 462
20.2.3 Node Level................................ 462
20.3 Autonomy ........................................... 463
20.3.1 MOOS-IvP Autonomy
Architecture and System............. 463
20.3.2 The Payload Autonomy Paradigm 463
20.3.3 The MOOS-IvP Autonomy
Architecture .............................. 464
20.4 Acoustic Communication Infrastructure . 466
20.5 On-Board, Real-Time
Signal Processing ................................. 467
20.6 Application Examples........................... 467
20.6.1 Unified Command,
Communication,
and Control Infrastructure .......... 467
20.6.2 Adaptive Thermocline
and Acousticline Tracking ........... 469
20.6.3 Bistatic Target Tracking (GLINT’10) 474
20.7 Conclusion........................................... 478
References................................................... 479
The primary motivation for designing a distributed
command and control architecture for undersea monitoring and observation is to achieve the ability to deploy
a fleet of autonomous mobile marine platforms over
a wide area of the ocean environment and over a long
period of time with little or no human supervision. Concerns over effective coverage, communication range,
and safe operation of the platforms are all primary motivations of an effective form of autonomous control.
The long duration of missions and unpredictable nature
of the environment require the vehicles to adapt their
missions and behave autonomously as events unfold.
Conversely, practical concerns of marine operations
over large areas require an element of operator intervention over the course of time. These two characteristics
can be at odds with each other in practice, but can be
tempered by effective periodic communication through
a network of fixed and mobile nodes co-deployed in
a coordinated manner designed to balance individual
platform and network objectives. The connectivity with
and between the submerged assets of such networks is
almost entirely dependent on underwater acoustic communication, except for rare and time-limited surfacings.
Consequently, the undersea network nodes must operate with a communication infrastructure with severely
limited bandwidth. Current underwater communication technology can robustly provide a point-to-point
channel capacity in shallow water of less than a few
hundred byte km=min, close to ten orders of magnitude
smaller than modern electromagnetic communication
459
Part B | 20
20. Nested Autonomy for Distributed Ocean Sensing
Henrik Schmidt, Michael R. Benjamin, Stephanie M. Petillo, Raymond Lum
Nested autonomy is a new control paradigm
for distributed undersea surveillance, specifically designed for the layered communication
infrastructure provided by the low-bandwidth
underwater acoustic communication and the intermittent RF connectivity. Implemented using
the open-source MOOS-IvP behavior-based, autonomous command and control architecture, it
provides the fully integrated sensing, modeling,
and controlling that allows each platform to autonomously detect, classify, localize, and track an
episodic event in the ocean, without depending
on any operator command and control. The prosecution of an event, such as the detection and
tracking of a subsea volcanic plume or an oceanographic feature, may be initiated by the operators
or entirely autonomously by an onboard detection capability. The event information collected
by each node in the network is reported back to
the operators by transmitting an event report, using a dedicated command and control language.
Collaborative processing and control is exploited
when the communication channel allows, for example, collaborative tracking of a coastal front,
or the tracking of manmade sources or marine
mammals.
20.1 Nested Autonomy ................................ 460
20.2 Concept of Operations (CONOPS) ............ 461
20.2.1 Field Level ................................ 461
20.2.2 Cluster Level.............................. 462
20.2.3 Node Level................................ 462
20.3 Autonomy ........................................... 463
20.3.1 MOOS-IvP Autonomy
Architecture and System............. 463
20.3.2 The Payload Autonomy Paradigm 463
20.3.3 The MOOS-IvP Autonomy
Architecture .............................. 464
20.4 Acoustic Communication Infrastructure . 466
20.5 On-Board, Real-Time
Signal Processing ................................. 467
20.6 Application Examples........................... 467
20.6.1 Unified Command,
Communication,
and Control Infrastructure .......... 467
20.6.2 Adaptive Thermocline
and Acousticline Tracking ........... 469
20.6.3 Bistatic Target Tracking (GLINT’10) 474
20.7 Conclusion........................................... 478
References................................................... 479
The primary motivation for designing a distributed
command and control architecture for undersea monitoring and observation is to achieve the ability to deploy
a fleet of autonomous mobile marine platforms over
a wide area of the ocean environment and over a long
period of time with little or no human supervision. Concerns over effective coverage, communication range,
and safe operation of the platforms are all primary motivations of an effective form of autonomous control.
The long duration of missions and unpredictable nature
of the environment require the vehicles to adapt their
missions and behave autonomously as events unfold.
Conversely, practical concerns of marine operations
over large areas require an element of operator intervention over the course of time. These two characteristics
can be at odds with each other in practice, but can be
tempered by effective periodic communication through
a network of fixed and mobile nodes co-deployed in
a coordinated manner designed to balance individual
platform and network objectives. The connectivity with
and between the submerged assets of such networks is
almost entirely dependent on underwater acoustic communication, except for rare and time-limited surfacings.
Consequently, the undersea network nodes must operate with a communication infrastructure with severely
limited bandwidth. Current underwater communication technology can robustly provide a point-to-point
channel capacity in shallow water of less than a few
hundred byte km=min, close to ten orders of magnitude
smaller than modern electromagnetic communication