Part B | 19.3
450 Part B Autonomous Ocean Vehicles, Subsystems and Control
Data were collected during the experiment from
other sources as well as the gliders. These include
a Naval postgraduate school research aircraft, satellite
imagery, high-frequency radar, and several moorings,
drifters deployed by the Monterey Bay Aquarium Research Institute (MBARI) and other ships and vehicles outside the control volume. Three different highresolution ocean models regularly assimilated data: the
Harvard Ocean Prediction System (HOPS) [19.94], the
Jet Propulsion Laboratory implementation of the Regional Oceanic Modeling System (JPL/ROMS) [19.95]
and the Navy Coastal Ocean Model/Innovative Coastal
Ocean Observing Network (NCOM/ICON) [19.96].
Each model produced daily updated ocean predictions
of temperature, salinity, and velocity. A central data
server at MBARI was used to run a virtual control
room (VCR) and to make all observational data and
model outputs available in near real time. The VCR,
developed for the 2006 ASAP field experiment, made
it possible for participants to remain at their home institutions throughout the experiment but still be fully
informed and connected team members [19.97]. There
were a number of different panels on the VCR including
those for team decision making and voting.
Virtual pilot experiments were run in advance of
the field experiment to get experience with the coordinated control and adaptive sampling implementation.
The virtual experiments were run as if they were real
field experiments except for the replacement of real vehicles in the real ocean with simulated vehicles moving
in the currents of a virtual ocean defined by a HOPS
re-analysis of Monterey Bay in 2003. The simulation
mode of the GCCS was designed to allow for virtual
experiments with control of gliders, communication
paths, and data flow exactly the same as what was used
in the 2006 field experiment [19.90, 98].
For the ASAP experiment, the Slocum gliders were
allocated to mapping the interior volume using automated coordinated sampling defined by motion patterns
on a finite set of closed curves, with properties between
measured paths inferred using interpolation. The automated feedback control laws for the Slocums were
implemented with the GCCS. The Spray gliders were
allocated to mapping the periphery of the volume. The
boundary was divided up into segments and each Spray
glider was assigned to move in an oscillatory manner
along a segment of the boundary. A separate control law
was implemented for this oscillatory behavior so the
gliders were well distributed. The experiment started
with a default coordinated motion pattern, and as the
environment and operating conditions changed, the coordinated motion pattern was re-designed and updated.
The input file to the GCCS that defines a coordinated motion pattern is called a glider coordinated
trajectory (GCT). As an example, GCT #2 used for the
Slocum gliders in the ASAP experiment is illustrated
in Fig. 19.3a. A GCT defines the curves that serve as
tracks for the gliders as well as the synchronization of
the motion of the gliders on and across the different
curves. For example, the GCT #2 shown in Fig. 19.3a
defines a pattern in which a pair of gliders, denoted with
red circles, moves around the red curve with maximal
intervehicle spacing and is synchronized with another
pair of gliders, denoted with green circles, that moves
around the green curve with maximal intervehicle spacing. The glider planner status panel of the VCR on July
30 at 23:10 GMT, when GCT #2 was active, is shown
in Fig. 19.3b. The glider planner panel for OA mapping
error at roughly the same time is shown in Fig. 19.4.
Pseudoelliptical curves were selected for the
Slocums since they had nearly straight long sides. The
curves were oriented to ensure that the gliders would repeatedly cross over the shelf break, each time sampling
a cross-section of the dynamic ocean processes that
propagate parallel to the shelf break. The shelf break
refers to the end of the continental shelf characterized
by a markedly increased slope toward the deep ocean
bottom [19.3]:
By constructing a time sequence of cross-section
plots, it would then be possible to reconstruct,
identify and monitor ocean processes even before
assimilating the glider profile data into an advanced
ocean model.
The distribution (synchronization) of the gliders relative to one another around the curves, as well as the
dimensions and position of the curves, were selected to
maximize the sampling performance metric. An on-line
optimization tool was available for locally optimizing
any candidate motion pattern. Additionally, candidate
coordinated motion patterns were often pretested using
the GCCS in simulation mode using one or more of the
forecast ocean fields. Because the simulations of gliders
moving in the forecast ocean could be run in faster than
real time, it was possible to obtain predictions of glider
performance in the predicted real ocean.
To implement an adaptation to sampling plans,
a new GCT was prepared to replace the existing GCT.
This was initiated manually by briefly interrupting the
GCCS, swapping the new GCT file for the old one, and
then re-starting the GCCS. Over 24 days of the ASAP
experiment, 14 different GCTs were used to adapt the
Slocum glider plan (Fig. 19.4a). Some of the adaptations were made in response to changes in the ocean
involving strong and highly variable flow conditions.
Other adaptations were made in response to changes in
scientific objectives, for example, to add sampling over
the head of the canyon and to chase an eddy moving off-
450 Part B Autonomous Ocean Vehicles, Subsystems and Control
Data were collected during the experiment from
other sources as well as the gliders. These include
a Naval postgraduate school research aircraft, satellite
imagery, high-frequency radar, and several moorings,
drifters deployed by the Monterey Bay Aquarium Research Institute (MBARI) and other ships and vehicles outside the control volume. Three different highresolution ocean models regularly assimilated data: the
Harvard Ocean Prediction System (HOPS) [19.94], the
Jet Propulsion Laboratory implementation of the Regional Oceanic Modeling System (JPL/ROMS) [19.95]
and the Navy Coastal Ocean Model/Innovative Coastal
Ocean Observing Network (NCOM/ICON) [19.96].
Each model produced daily updated ocean predictions
of temperature, salinity, and velocity. A central data
server at MBARI was used to run a virtual control
room (VCR) and to make all observational data and
model outputs available in near real time. The VCR,
developed for the 2006 ASAP field experiment, made
it possible for participants to remain at their home institutions throughout the experiment but still be fully
informed and connected team members [19.97]. There
were a number of different panels on the VCR including
those for team decision making and voting.
Virtual pilot experiments were run in advance of
the field experiment to get experience with the coordinated control and adaptive sampling implementation.
The virtual experiments were run as if they were real
field experiments except for the replacement of real vehicles in the real ocean with simulated vehicles moving
in the currents of a virtual ocean defined by a HOPS
re-analysis of Monterey Bay in 2003. The simulation
mode of the GCCS was designed to allow for virtual
experiments with control of gliders, communication
paths, and data flow exactly the same as what was used
in the 2006 field experiment [19.90, 98].
For the ASAP experiment, the Slocum gliders were
allocated to mapping the interior volume using automated coordinated sampling defined by motion patterns
on a finite set of closed curves, with properties between
measured paths inferred using interpolation. The automated feedback control laws for the Slocums were
implemented with the GCCS. The Spray gliders were
allocated to mapping the periphery of the volume. The
boundary was divided up into segments and each Spray
glider was assigned to move in an oscillatory manner
along a segment of the boundary. A separate control law
was implemented for this oscillatory behavior so the
gliders were well distributed. The experiment started
with a default coordinated motion pattern, and as the
environment and operating conditions changed, the coordinated motion pattern was re-designed and updated.
The input file to the GCCS that defines a coordinated motion pattern is called a glider coordinated
trajectory (GCT). As an example, GCT #2 used for the
Slocum gliders in the ASAP experiment is illustrated
in Fig. 19.3a. A GCT defines the curves that serve as
tracks for the gliders as well as the synchronization of
the motion of the gliders on and across the different
curves. For example, the GCT #2 shown in Fig. 19.3a
defines a pattern in which a pair of gliders, denoted with
red circles, moves around the red curve with maximal
intervehicle spacing and is synchronized with another
pair of gliders, denoted with green circles, that moves
around the green curve with maximal intervehicle spacing. The glider planner status panel of the VCR on July
30 at 23:10 GMT, when GCT #2 was active, is shown
in Fig. 19.3b. The glider planner panel for OA mapping
error at roughly the same time is shown in Fig. 19.4.
Pseudoelliptical curves were selected for the
Slocums since they had nearly straight long sides. The
curves were oriented to ensure that the gliders would repeatedly cross over the shelf break, each time sampling
a cross-section of the dynamic ocean processes that
propagate parallel to the shelf break. The shelf break
refers to the end of the continental shelf characterized
by a markedly increased slope toward the deep ocean
bottom [19.3]:
By constructing a time sequence of cross-section
plots, it would then be possible to reconstruct,
identify and monitor ocean processes even before
assimilating the glider profile data into an advanced
ocean model.
The distribution (synchronization) of the gliders relative to one another around the curves, as well as the
dimensions and position of the curves, were selected to
maximize the sampling performance metric. An on-line
optimization tool was available for locally optimizing
any candidate motion pattern. Additionally, candidate
coordinated motion patterns were often pretested using
the GCCS in simulation mode using one or more of the
forecast ocean fields. Because the simulations of gliders
moving in the forecast ocean could be run in faster than
real time, it was possible to obtain predictions of glider
performance in the predicted real ocean.
To implement an adaptation to sampling plans,
a new GCT was prepared to replace the existing GCT.
This was initiated manually by briefly interrupting the
GCCS, swapping the new GCT file for the old one, and
then re-starting the GCCS. Over 24 days of the ASAP
experiment, 14 different GCTs were used to adapt the
Slocum glider plan (Fig. 19.4a). Some of the adaptations were made in response to changes in the ocean
involving strong and highly variable flow conditions.
Other adaptations were made in response to changes in
scientific objectives, for example, to add sampling over
the head of the canyon and to chase an eddy moving off-