U.S. patent application number 15/278879 was filed with the patent office on 2018-03-29 for method and apparatus for pipe imaging with chemical analysis.
The applicant listed for this patent is RedZone Robotics, Inc.. Invention is credited to Galin Konakchiev, Todd Kueny, John Lettman, Foster J. Salotti, Justin Starr.
Application Number | 20180088043 15/278879 |
Document ID | / |
Family ID | 61633199 |
Filed Date | 2018-03-29 |
United States Patent
Application |
20180088043 |
Kind Code |
A1 |
Starr; Justin ; et
al. |
March 29, 2018 |
METHOD AND APPARATUS FOR PIPE IMAGING WITH CHEMICAL ANALYSIS
Abstract
One embodiment provides a method for identifying a target object
of a pipe wall, including: positioning a pipe inspection robot
within a pipe; emitting, using a terahertz (THz) beam source of the
pipe inspection robot, a laser beam towards a target object;
receiving, using a THz receiver of the pipe inspection robot, THz
data related to the target object; analyzing, using a processor,
the THz data; and determining, based on the analyzing, an identity
of the object. Other aspects are described and claimed.
Inventors: |
Starr; Justin; (Baden,
PA) ; Lettman; John; (Pittsburgh, PA) ; Kueny;
Todd; (Tarentum, PA) ; Salotti; Foster J.;
(Verona, PA) ; Konakchiev; Galin; (Pittsburgh,
PA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
RedZone Robotics, Inc. |
Pittsburgh |
PA |
US |
|
|
Family ID: |
61633199 |
Appl. No.: |
15/278879 |
Filed: |
September 28, 2016 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01S 13/86 20130101;
G01S 13/88 20130101; G01N 21/954 20130101; G01N 21/3581 20130101;
G01N 2201/0216 20130101; G01S 17/88 20130101; G01N 21/94 20130101;
G01S 13/862 20130101; G01S 13/867 20130101; Y10S 901/01 20130101;
G01N 2021/945 20130101; G01N 2021/9548 20130101; Y10S 901/44
20130101; F16L 2101/30 20130101 |
International
Class: |
G01N 21/3581 20060101
G01N021/3581; G01N 21/954 20060101 G01N021/954; G01N 21/94 20060101
G01N021/94; B25J 5/00 20060101 B25J005/00; F16L 55/32 20060101
F16L055/32 |
Claims
1. A pipe inspection robot, comprising: a powered track system
providing movement to the pipe inspection robot to traverse through
the interior of a water or sewer pipe; a sensor component attached
to the powered track system; and a processor; said sensor component
comprising: a terahertz (THz) beam source a receiver; and a visual
camera; said processor configured to: operate the sensor component
to collect THz data and visual image data related to an interior
surface of the water or sewer pipe as the pipe inspection robot
traverses through the water or sewer pipe; associate the THz data
with visual image data; and communicate the THz data and the visual
image data collected over a network connection.
2. The pipe inspection robot of claim 1, wherein the THz data
comprises spectral data.
3. The pipe inspection robot of claim 1, wherein the spectral data
comprises one or more peaks.
4. The pipe inspection robot of claim 1, wherein the processor is
further configured to identify one or more peaks in the THz
data.
5. The pipe inspection robot of claim 4, wherein the processor is
further configured to compare the one or more peaks to one or more
known spectra for a predetermined set of water or sewer pipe
interior wall materials.
6. The pipe inspection robot of claim 5, wherein the processor is
further configured to compare the one or more peaks to one or more
known spectral peaks using a neural network.
7. The pipe inspection robot of claim 5, wherein: the THz beam
source directs a THz beam to a target object of the pipe wall; and
the processor is further configured to identify the target
object.
8. The pipe inspection robot of claim 1, wherein the THz source
comprises a laser.
9. (canceled)
10. The pipe inspection robot of claim 1, wherein the receiver
comprises a charge-coupled device.
11. (canceled)
12. A method for identifying a target object of a pipe wall,
comprising: positioning a pipe inspection robot within a water or
sewer pipe to traverse through the interior of the water or sewer
pipe; receiving, using a visual camera of the pipe inspection
robot, visual image data related to an interior surface of the
water or sewer pipe as the pipe inspection robot traverses through
the water or sewer pipe; emitting, using a terahertz (THz) beam
source of the pipe inspection robot, a laser beam towards a target
object of the interior surface of the water or sewer pipe;
receiving, using a THz receiver of the pipe inspection robot, THz
data related to the target object as the pipe inspection robot
traverses through the water or sewer pipe; associating, using a
processor, the THz data with the visual image data and pipe network
mapping data; analyzing, using a processor, the THz data;
determining, based on the analyzing, an identity of the object and
providing the identity of the object in a visual display comprising
one or more of the pipe network data, a visual image, and a THz
image.
13. The method of claim 12, wherein the THz data comprises spectral
data.
14. The method of claim 12, wherein the spectral data comprises one
or more peaks.
15. The method of claim 12, wherein the determining comprises using
the one or more peaks in the THz data.
16. The method of claim 15, wherein the one or more peaks are
compared to one or more known spectra for a predetermined set of
water or sewer pipe interior wall materials.
17. The method of claim 16, wherein the one or more peaks are
compared to one or more known spectral peaks using a neural
network.
18. The method of claim 16, wherein the emitting comprises
directing the laser beam toward the target object of the pipe
wall.
19. The method of claim 12, further comprising obtaining, using a
sensor component of the pipe inspection robot, additional
inspection data.
20. The method of claim 19, further comprising combining, using a
processor, the additional inspection data with the THz data.
21. A method, comprising: traversing, with a pipe inspection robot,
through an interior of a water or sewer pipe; receiving, using a
visual camera of the pipe inspection robot, visual image data
related to a target object of an interior surface of the water or
sewer pipe; receiving, using a THz receiver of the pipe inspection
robot, THz data related to the target object; associating, using a
processor, the THz data with the visual image data; analyzing,
using a processor, the THz data; determining, based on the
analyzing, an identity of the target object; providing the identity
of the object in a visual display comprising the visual image data
and the THz data.
22. The method of claim 21, comprising overlaying the THz data with
visual image data in a combined image, wherein the combined image
comprises THz data aligned with visual data of the target object in
the combined image.
Description
BACKGROUND
[0001] Pipes that carry water, other fluids and gases are an
important type of infrastructure. Pipes are often inspected as a
matter of routine upkeep or in response to a noticed issue. A great
deal of pipe data is captured in still images or video, e.g., using
cameras to record information from the visible spectrum of light.
However, other data can provide additional information beyond what
is visible to the naked eye. For example, acoustic, ultraviolet
(UV) and infrared (IR) imaging have been utilized to identify
details related to pipe topology or condition.
[0002] When inspecting pipes, experienced inspectors may observe a
certain type of buildup, inflow of material, or defect and be able
to produce a logical guess as to its composition or source, e.g.,
based upon the visual characteristics of that build-up. However,
these guesses are not always accurate and are even more difficult
to make if the substance to be identified is a liquid.
BRIEF SUMMARY
[0003] In summary, one aspect provides a pipe inspection robot,
comprising: a powered track system providing movement to the pipe
inspection robot; a sensor component; and a processor; said sensor
component comprising a terahertz (THz) beam source and a receiver;
said processor configured to: operate the sensor component to
collect THz data related to a pipe wall; and communicate the THz
data collected over a network connection.
[0004] Another aspect provides a system, comprising: a computing
system; a pipe inspection robot operatively coupled to the
computing system and comprising: a sensor portion; and a processor;
said sensor component comprising a terahertz (THz) beam source and
a receiver; said processor configured to: operate the sensor
component to collect THz data related to a pipe wall; and
communicate the THz data collected over a network connection to the
computing system.
[0005] A further aspect provides a method for identifying a target
object of a pipe wall, comprising: positioning a pipe inspection
robot within a pipe; emitting, using a terahertz (THz) beam source
of the pipe inspection robot, a laser beam towards a target object;
receiving, using a THz receiver of the pipe inspection robot, THz
data related to the target object; analyzing, using a processor,
the THz data; and determining, based on the analyzing, an identity
of the object.
[0006] The foregoing is a summary and thus may contain
simplifications, generalizations, and omissions of detail;
consequently, those skilled in the art will appreciate that the
summary is illustrative only and is not intended to be in any way
limiting.
[0007] For a better understanding of the embodiments, together with
other and further features and advantages thereof, reference is
made to the following description, taken in conjunction with the
accompanying drawings. The scope of the invention will be pointed
out in the appended claims.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
[0008] FIG. 1 illustrates an example pipe inspection robot.
[0009] FIG. 2 illustrates an example method of using terahertz
(THz) data to identify target objects.
[0010] FIG. 3 illustrates an example of device electronics in the
form of a computer.
DETAILED DESCRIPTION
[0011] It will be readily understood that the components of the
embodiments, as generally described and illustrated in the figures
herein, may be arranged and designed in a wide variety of different
configurations in addition to the described example embodiments.
Thus, the following more detailed description of the example
embodiments, as represented in the figures, is not intended to
limit the scope of the embodiments, as claimed, but is merely
representative of example embodiments.
[0012] Reference throughout this specification to "embodiment(s)"
(or the like) means that a particular feature, structure, or
characteristic described in connection with the embodiment is
included in at least one embodiment. Thus, appearances of the
phrases "according to embodiments" or "an embodiment" (or the like)
in various places throughout this specification are not necessarily
all referring to the same embodiment.
[0013] Furthermore, the described features, structures, or
characteristics may be combined in any suitable manner in one or
more embodiments. In the following description, numerous specific
details are provided to give a thorough understanding of
embodiments. One skilled in the relevant art will recognize,
however, that the various embodiments can be practiced without one
or more of the specific details, or with other methods, components,
materials, et cetera. In other instances, well known structures,
materials, or operations are not shown or described in detail to
avoid obfuscation.
[0014] Over time, issues may arise in various pipe segments. For
example, different types of sediment deposits may accumulate in
pipes, which may impede the flow of the materials. Additionally,
the pipes may experience various other forms of damage such as
cracks or corrosion, unauthorized inflows, etc. For these reasons,
the pipes need to be routinely inspected and properly
maintained.
[0015] One current inspection method involves inspectors visually
identifying a deposit, for example by reviewing video captured by a
pipe inspection robot or CCTV system. Through years of experience,
inspectors are able to differentiate between different types of
caustic substances (e.g., grease, calcium, iron oxide deposits,
etc.). In this way, an experienced inspector may be able to
distinguish between various types of inflows, various types of
deposits or buildups, etc. However, this is more of an art than a
science, with no metrics or rules except in the case of obvious
substances, e.g., iron deposits tend to be red in color. An
alternate solution is to take a sample of the deposit and bring it
to a lab where tests can be conducted to determine the identity of
the substance, e.g. with a spectrophotometer. However, this takes
time and may not be ideal when a situation is time-sensitive. These
technical issues present problems for users in that accurately
identifying damage or deposits, if possible, may be difficult,
time-consuming and expensive.
[0016] Accordingly, an embodiment provides a method for providing
real-time chemical analysis of deposits found in pipelines using
image based spectroscopy. Using this method, physical inspection
and analysis of samples is no longer necessary. Rather, an
embodiment may provide a non-contact identification technique that
includes emitting a beam of terahertz (THz) radiation onto an
object and receiving not only visual and topographic information,
but also information related to the chemical composition of the
object. Additionally, the THz radiation is slightly penetrative, so
an embodiment may also provide depth information, e.g., image based
information about an object in a first layer and an object in a
second, deeper layer.
[0017] In an embodiment, other spectral imaging techniques may be
utilized alone or in combination with a THz based technique. For
example, an embodiment may couple THz spectral data with other
spectral data, such as IR spectral data and/or UV spectral data, in
addition to THz spectral data, for chemical analysis. Appropriate
transmission and receiving components may therefore be included
on-board a pipe inspection robot.
[0018] The description now turns to the figures. The illustrated
example embodiments will be best understood by reference to the
figures. The following description is intended only by way of
example, and simply illustrates certain example embodiments.
[0019] FIG. 1 illustrates an example pipe inspection robot 10 that
may be utilized for capturing pipe inspection data, including THz
imaging data. For purposes of clarity, a partially exploded view of
the pipe inspection robot 10 is shown in FIG. 1. As explained in
more detail hereinafter, the device may be utilized to navigate,
explore, map, etc., various environments (e.g., water pipes, sewer
pipes, etc.). In an embodiment, the pipe inspection robot 10 may be
implemented as an autonomous mobile robot 10 utilized for pipe
inspection (e.g., a sewer pipe). However, it will be appreciated
that the pipe inspection robot 10 may be embodied in any number of
different types of inspection platforms, including non-autonomous
devices and platforms, and may be utilized in a plurality of other
environments.
[0020] The autonomous mobile robot 10 used by way of example for
descriptive purposes includes a sensor component 12 and a chassis
portion 14. The sensor component 12 is electrically and
mechanically connected to the chassis portion 14. As shown in FIG.
1, the autonomous mobile robot 10 may also include a riser portion
16 which is positioned between the sensor component 12 and the
chassis portion 14, and is electrically and mechanically connected
to each. The riser portion 16 operates to increase the distance the
sensor component 12 is situated above the lowest portion of the
pipe, and may be utilized in large pipe applications to provide a
desired vantage point for various sensing devices of the sensor
component 12. Additionally, riser portion 16 and sensor component
12 are modular, i.e., they may be coupled/decoupled to and from the
autonomous mobile robot 10. For example, according to other
embodiments, the autonomous mobile robot 10 does not include the
above-described riser portion 16. Functionality of the autonomous
mobile robot 10 may be implemented by a computing device and/or a
computer program stored on a computer-readable medium, as further
described herein.
[0021] According to an embodiment, the sensor component 12 includes
a plurality of sensing devices (e.g., a THz source, a camera, a
radar device, a sonar device, an infrared device, a laser device,
etc.) for sensing the conditions within the environment, a
computing device communicably connected to the sensing devices and
having a processor for processing raw information captured by the
sensing devices, a memory device communicably connected to a
computing device for storing the raw and/or processed information,
and control circuitry communicably connected to the computing
device for controlling various components of the autonomous mobile
robot 10. The memory device may also be utilized to store software
which is utilized by the autonomous mobile robot 10 to navigate,
explore, map, etc., the environment.
[0022] The THz source of the sensor component 12 may be implemented
using a variety of techniques. For example, an antenna or laser
(beam pump) may act to produce a THz source that is directed to a
pipe wall. In an embodiment, sensor component 12 includes an
antenna or sensor such as a charged coupled device (CCD)/camera may
receive reflections and/or transmissions of a THz source. The
sensor component 12 is therefore capable of performing THz imaging
data collection using an active transmission technique to paint an
object such as a wall area of a pipe segment. In another
embodiment, the sensor portion 12 may include a passive THz imaging
element, which views the naturally occurring radiation of an
object.
[0023] As further shown in FIG. 1, the chassis portion 14 includes
a first track 18, and a second track 20. In an embodiment, the
first track 18 is identical to the second track 20. The first and
second tracks 18, 20 may be fabricated from any suitable material
or combination of materials. The first and second tracks 18, 20
each define a plurality of openings 22 there-through. The openings
22 may be of any suitable shape and size, and may be arranged in
any suitable configuration. Although only two rows of the openings
22 are shown in FIG. 1 for each track, it is understood that the
openings 22 may be arranged in any number of rows. The first track
18 is positioned adjacent the second track 20. Collectively, the
first and second tracks 18, 20 define a spacing there-between, and
cover substantially the entire width of the chassis portion 14. For
example, according to an embodiment, the width of the chassis
portion is approximately 100 millimeters, and the first and second
tracks 18, 20 collectively cover approximately 92 of the 100
millimeters.
[0024] The first track 18 defines a first surface 18a and a second
surface (not shown in FIG. 1) opposite the first surface 18a.
According an embodiment, the first surface 18a is the surface which
comes in contact with an interior surface of a pipe when the
autonomous mobile robot 10 is being utilized for a pipe
application. The first surface 18a of the first track 18 is
substantially smooth. Similarly, the second track 20 defines a
first surface 20a and a second surface (not shown in FIG. 1)
opposite the first surface 20a. The first surface 20a is the
surface which comes in contact with an interior surface of a pipe
when the autonomous mobile robot 10 is being utilized for a pipe
application. Again, the first surface 20a of the first track 20 may
be substantially smooth. The respective first surfaces 18a, 20a of
the first and second tracks 18, 20 have a relatively high static
coefficient of friction.
[0025] The first and second tracks 18, 20 may be referred to as
full coverage/wide tracks. Due to the collective width of the first
and second tracks 18, 20 relative to the width of the chassis
portion 14, the first and second tracks 18, 20 collectively form
nearly the entire "front," "bottom" and "rear" surfaces of the
chassis portion 14. Thus, when the autonomous mobile robot 10
encounters any debris or feature within the sewer pipe, the first
surfaces 18a, 20a of the first and second tracks 18, 20 come in
contact with the debris or feature. In contrast to wheeled robots
and narrow track robots, the full coverage/wide tracks 18, 20 are
configured to enable the autonomous mobile robot 10 to climb over
the debris or feature and continue performing the inspection,
navigation, mapping, etc. Additionally, nearly all of the weight of
the autonomous mobile robot 10 passes through the moving full
coverage/wide tracks 18, 20 to the encountered debris or feature.
Therefore, the autonomous mobile robot 10 is configured to always
continue driving as the full coverage tracks 18, 20 cannot rotate
without contacting something to react with and continue
driving.
[0026] Referring now to FIG. 2, at 201 an embodiment may operate a
THz source to emit a THz beam to paint a target, e.g., wall of a
pipe segment. This permits the collection of return radiation (THz
beam) at 202. The return beam collected at 202 may comprise
absorption and/or emission data related to chemical bonds of a
target object, which may be resolved for example utilizing
spectroscopy processing techniques.
[0027] The return data may comprise one or more characteristic
absorption peaks, as sensed for example by sensor component 12 of
FIG. 1, which permits analysis of the chemical composition of the
pipe wall segment, as illustrated at 203. For example, THz
spectroscopy utilizes wavelengths of radiation in the terahertz
band, which ranges from about 1 mm to about 0.1 mm, to distinguish
between various chemicals contained in an object according to their
spectral characteristics. For example, a THz sensor may be used to
emit a THz beam (that may be focused on a target object using a
mirror or other optical structure) and sense return radiation that
is influence by chemical(s) in a target object. The return
radiation may therefore include information related to absorption
spectra. In turn, various materials may be distinguished on the
basis of their chemical compositions, e.g., in terms of classifying
the materials based on dominant features contained within the
spectral data related to certain chemical bonds of known materials.
For example, in an embodiment, classification of the absorption
spectra of a target object may be achieved by using a minimum
distance classifier and neural network methods. By way of specific
example, spectral data for a known material may be utilized as a
reference for identifying a target object by comparison of one or
more peaks in the target object's THz return data. THz images of a
target object may be formed by integrating the peak data around one
or more known frequencies in the THz band, e.g., 0.82 THz.
[0028] In an embodiment, a variety of THz laser sensing chips may
be utilized for sensing or receiving the return radiation, e.g.,
provided within sensor component 12. Different chips have different
strengths and weaknesses in terms of the environments they work in.
In an embodiment, chips that are sensitive to different chemicals
(e.g., bond vibrations) can be interchanged with chips in existing
THz sensors to suit desired applications. For example, some chips
may not work well when detecting reflections off of fabrics because
there is a greater signal to noise ratio. However, those same chips
may work very well with objects that are dark colored, e.g., an
asbestos lined pipe that is pitch black may require a very
different sensor than a sensor used in a typical pipe. In an
embodiment, the THz beam generator and THz sensor may be utilized
in air-filled pipes as well as pipes that are submerged with
water.
[0029] THz imagery provides distinct advantages over other types of
visual imagery, particularly in a pipe inspection implementation.
For example, when a wave of visible light is directed onto an
object, the light is reflected or refracted back and information
relating to color, shape, and topography is received. When a beam
of THz radiation is emitted, not only is return information about
shape and topography received, but because each type of chemical
bond has a unique vibrational frequency, THz spectroscopy leverages
these differences in order to determine the chemical composition of
an object based on the identification of its chemical bonds.
[0030] For example, as outlined at 203 and 204 of FIG. 2, an
embodiment may analyze return radiation to produce peak data, e.g.,
in the form of an absorption/emission spectra, for a particular
target, as shown at 203. The absorption/emission spectra may be
used to identify one or more predetermined spectra, e.g., known
spectra of cement, metal or metal alloys, rust, soil or organic
material of varying types, etc., as shown at 204.
[0031] If a match is determined at 205, e.g., return radiation
produces a spectra having one or more peaks matching (classified to
a predetermined confidence level) to iron oxide, an embodiment may
output an indication that a match for a particular chemical
composition has been identified at 206. Otherwise, an embodiment
may output an indication that no match has been found. In an
embodiment, visual image data or additional imaging data may be
collected by at least one camera or other sensing device mounted to
autonomous mobile robot 10, e.g., including in sensor component 12.
An embodiment may thus additionally capture visual data (images,
video) such that a THz analysis may be improved (e.g., in terms of
confidence) or omitted, e.g., if THz data is unresolvable, in favor
of other or additional sensed data.
[0032] In addition to providing chemical information, THz radiation
is also slightly penetrative. Some frequencies of THz radiation can
penetrate several millimeters below the surface of a targeted
object. This aspect of the radiation not only provides chemical
information about the targeted object, but it also provides
chemical information about what the targeted object may be laying
on top of or layered over. For example, if part of a pipe appears
to be corroded with rust, lime or other deposit, THz imaging may
reveal that the corroded segment is composed of the components of
cement, e.g., lime, carbonate, iron oxide, etc. If the THz imaging
produces readings of chemical signatures that are suggestive of
soil, because the original beam was directed at the pipe wall, this
provides a strong indication that the pipe wall has become very
thin and is in danger of failing or has in fact failed.
[0033] In an embodiment, a THz beam generator and a THz sensor
(e.g., CCD/camera, crystal, etc.) may be mounted to autonomous
mobile robot 10. In an embodiment, a THz beam generator and a THz
sensor may be mounted to any type of robot that is able to capably
traverse through a pipeline. In an embodiment, the THz beam
generator and sensor may be mounted at different locations on the
mobile inspection robot. For example, in order to attain 360-degree
scanning ability, THz-related units may be positioned in an array,
e.g., at the 3, 6, 9, and 12 o'clock locations of the sensor
component 12. In an embodiment, power supplied to the THz units may
be supplied by the autonomous mobile robot 10, may be supplied by a
separate, dedicated battery, or may be supplied by a commercial
power source (e.g., a wireline provided from the surface to the
robot). In an embodiment, THz imaging may be conducted at-will,
e.g., by a user-generated command, or may be set to scan
continuously or intermittently, e.g., according to a program or a
policy.
[0034] The processing at 203 and/or 204 may take place locally on
the autonomous mobile robot 10 or may take place off-site on
another information handling device (PC computer, laptop, tablet,
etc.). In an embodiment, the processing may be completed in
real-time or near real-time. For example, if THz imaging is being
continuously run, the processing of each subsequent scan may lag
behind by a few seconds because the previous scans need to be
completed first.
[0035] An analysis of the collected THz data at 203 may be combined
with other techniques. For example, a THz scan of an object may be
conducted that collects chemical composition data for a
pattern-matching algorithm that analyses spectral peak data to
determine what the object actually is, e.g., based on comparison
matching, as indicated at 204. In addition, a visual camera (or
other imaging device) may be used to collect visual image data of
the same target. Thus, in addition to comparing THz data to a
database of known materials, an embodiment may couple this to a
visual light analysis of the target object in order to refine or
rank various possibilities of object identifications. For example,
a suggested list of the top three most likely candidates of what
the targeted object might be may be included in the output
indication at 206.
[0036] Accordingly, images produced by THz imaging data (or data
derived therefrom) may be overlaid or combined with traditional
visual images or other data (e.g., pipe map data) using standard
image alignment techniques. The benefits of this overlay are that a
user not only obtains a visual of the internals of a pipe, but they
also receive a metric as to what they are visualizing
chemically.
[0037] An embodiment may relate the THz imaging data to various
parts of a pipe network using pipe mapping data. For example, if a
detailed mapping is available for a pipe network, the THz imaging
data may be associated with the various parts of the pipe network.
This permits a user to review visual inspection data for a
particular part of the pipe network as well as related THz imaging
data for the particular part of the pipe network.
[0038] It will be readily understood that certain embodiments can
be implemented using any of a wide variety of devices or
combinations of devices. Referring to FIG. 3, an example device
that may be used in implementing one or more embodiments includes a
computing device (computer) 310. In this regard, a computing device
310 may be operatively coupled to autonomous mobile robot 10 and
provide hosted services (data storage, data analysis, data summary
and querying, and the like). For example, computing device 310 may
provide network based access to autonomous mobile robot 10 for
reporting THz data, receiving data such as autonomous mission
protocols, etc. Additionally or alternatively, autonomous mobile
robot 10 may incorporate a computing device such as outlined in
FIG. 3, e.g., included on board in sensor component 12.
[0039] The computing device 310 may execute program instructions
configured to store an analyze pipe segment data and perform other
functionality of the embodiments, as described herein. Components
of the computing device 310 may include, but are not limited to, a
processing unit 320, a system memory 330, and a system bus 322 that
couples various system components including the system memory 330
to the processing unit 320. The computer 310 may include or have
access to a variety of computer readable media, for example for
storing infrastructure data indices. The system memory 330 may
include computer readable storage media in the form of volatile
and/or nonvolatile memory such as read only memory (ROM) and/or
random access memory (RAM). By way of example, and not limitation,
system memory 330 may also include an operating system, application
programs, other program modules, and program data.
[0040] A user can interface with (for example, enter commands and
information) the computing device 310 through input devices. A
monitor or other type of device can also be connected to the system
bus 322 via an interface, such as an output interface 350. In
addition to a monitor, computers may also include other peripheral
output devices. The computing device 310 may operate in a networked
or distributed environment using logical connections to one or more
other remote computers or databases, e.g., autonomous mobile robot
10. The logical connections may include a network, such local area
network (LAN) or a wide area network (WAN), but may also include
other networks/buses.
[0041] As will be appreciated by one skilled in the art, various
aspects may be embodied as a system, method or device program
product. Accordingly, aspects may take the form of an entirely
hardware embodiment or an embodiment including software that may
all generally be referred to herein as a "circuit," "module" or
"system." Furthermore, aspects may take the form of a device
program product embodied in one or more device readable medium(s)
having device readable program code embodied therewith.
[0042] It should be noted that the various functions described
herein may be implemented using instructions stored on a device
readable storage medium such as a non-signal storage device that
are executed by a processor. A storage device may be, for example,
an electronic, magnetic, optical, electromagnetic, infrared, or
semiconductor system, apparatus, or device, or any suitable
combination of the foregoing. More specific examples of a storage
medium would include the following: a portable computer diskette, a
hard disk, a random access memory (RAM), a read-only memory (ROM),
an erasable programmable read-only memory (EPROM or Flash memory),
an optical fiber, a portable compact disc read-only memory
(CD-ROM), an optical storage device, a magnetic storage device, or
any suitable combination of the foregoing. In the context of this
document, a storage device is not a signal and "non-transitory"
includes all media except signal media.
[0043] Program code embodied on a storage medium may be transmitted
using any appropriate medium, including but not limited to
wireless, wireline, optical fiber cable, RF, et cetera, or any
suitable combination of the foregoing.
[0044] Program code for carrying out operations may be written in
any combination of one or more programming languages. The program
code may execute entirely on a single device, partly on a single
device, as a stand-alone software package, partly on single device
and partly on another device, or entirely on the other device. In
some cases, the devices may be connected through any type of
connection or network, including a local area network (LAN) or a
wide area network (WAN), or the connection may be made through
other devices (for example, through the Internet using an Internet
Service Provider), through wireless connections, e.g., near-field
communication, or through a hard wire connection, such as over a
USB connection.
[0045] Example embodiments are described herein with reference to
the figures, which illustrate example methods, devices and program
products according to various example embodiments. It will be
understood that the actions and functionality may be implemented at
least in part by program instructions. These program instructions
may be provided to a processor of a device to produce a special
purpose machine, such that the instructions, which execute via a
processor of the device implement the functions/acts specified.
[0046] It is worth noting that while specific blocks are used in
the figures, and a particular ordering of blocks has been
illustrated, these are non-limiting examples. In certain contexts,
two or more blocks may be combined, a block may be split into two
or more blocks, or certain blocks may be re-ordered or re-organized
as appropriate, as the explicit illustrated examples are used only
for descriptive purposes and are not to be construed as
limiting.
[0047] As used herein, the singular "a" and "an" may be construed
as including the plural "one or more" unless clearly indicated
otherwise.
[0048] This disclosure has been presented for purposes of
illustration and description but is not intended to be exhaustive
or limiting. Many modifications and variations will be apparent to
those of ordinary skill in the art. The example embodiments were
chosen and described in order to explain principles and practical
application, and to enable others of ordinary skill in the art to
understand the disclosure for various embodiments with various
modifications as are suited to the particular use contemplated.
[0049] Thus, although illustrative example embodiments have been
described herein with reference to the accompanying figures, it is
to be understood that this description is not limiting and that
various other changes and modifications may be affected therein by
one skilled in the art without departing from the scope or spirit
of the disclosure.
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