The disclosure generally relates to magnetometer systems, and more particularly, to diamond nitrogen-vacancy (DNV) magnetometer systems utilizing human infrastructure with characteristic magnetic signatures and broad geographical distribution, such as power lines and cellular communications networks, for magnetic navigation.
Small unmanned aircraft systems (UASs) typically navigate using GPS and fly at a nominal altitude to avoid obstructions on the earth surface. When GPS is not available or intentionally denied, a UAS may not be able to accurately navigate to its destination as its inertial navigation system (INS) may drift. Visual flight references can sometimes be used to remove INS errors. However, there are several deficiencies. For example, the fact that a UAS has to fly at relatively high altitudes to provide a visual sample space of sufficient geographic coverage to locate its position makes the UAS more vulnerable to detection. Further, a large image database has to be either carried on-board, which impacts platform endurance, or a data-link is required to reach back to an off-board processor. Accessing an off-board processor may not be practical in contested environments. Visual flight references can also be impacted by varied lighting conditions, and are ineffective in degraded visibility environments.
Sometimes synthetic aperture radar (SAR) and passive coherent location (PCL) may be utilized and can provide non real-time data such that the system can build an image of the terrain to its side after it has flown by the area of interest. SAR, nonetheless, requires the sensor to operate at a higher altitude that exposes it to detection. Further, SAR may require substantial on-board computing resources and emits RF energy that may unintentionally reveal the location of the UAS. Passive measurements of RF emissions (e.g., TV and FM radio transmitters) can be used to measure location when RF transmitters are operating and their location(s) are known. PCL requires multiple known RF emitters to triangulate position, and position accuracy may be limited by the type and number of transmitters detected, and by multi-path errors.
Methods and systems are described for exploiting magnetic signature characteristics of electrical power transmission, distribution lines, communication networks and other magnetic sources for navigation. In the following description, reference is made to the accompanying attachments that form a part thereof, and in which are shown by way of illustration, specific embodiments in which the technology may be practiced. It is to be understood that other embodiments may be utilized and changes may be made without departing from the scope of the disclosure. For example, the same principals disclosed apply to ground autonomous vehicles that can follow the same overhead and buried power lines, and to undersea autonomous vehicles that can follow submerged power cables and other infrastructure, or other networks generating magnetic fields. In addition, groups of unmanned systems may improve the scope, accuracy and types of features represented in the magnetic database described below. Magnetic metadata for way-point determination and other applications such as homing can be collected with the system and method described. Metadata can be compiled in a central database and/or shared in real-time with other platforms and sensors for navigation and homing. In addition, platforms may coordinate their information with other platforms to allow more distant platforms, with or without a magnetic sensor, to more accurately locate position.
The foregoing and other features of this disclosure will become more fully apparent from the following description and appended claims, taken in conjunction with the accompanying drawings. Understanding that these drawings depict only several implementations in accordance with the disclosure and are, therefore, not to be considered limiting of its scope, the disclosure will be described with additional specificity and detail through use of the accompanying drawings.
In some embodiments, methods and configurations are disclosed for diamond nitrogen-vacancy (DNV) magnetic navigation via power transmission and distribution lines. The characteristic magnetic signature of human infrastructure provides context for navigation. For example, power lines, which have characteristic magnetic signatures, can serve as roads and highways for mobile platforms (e.g., UASs). Travel in relatively close proximity to power lines may allow stealthy transit, may provide the potential for powering the mobile platform itself, and may permit point-to-point navigation both over long distances and local routes.
Some implementations can include one or more magnetic sensors, a magnetic navigation database, and a feedback loop that controls the UAS position and orientation. DNV magnetic sensors and related systems and methods may provide high sensitivity magnetic field measurements. The DNV magnetic systems and methods can also be low cost, space, weight, and power (C-SWAP) and benefit from a fast settling time. The DNV magnetic field measurements may allow UASs to align themselves with the power lines, and to rapidly move along the power-line infrastructure routes. The subject solution can enable navigation in poor visibility conditions and/or in GPS-denied environments. Such magnetic navigation allows for UAS operation in close proximity to power lines facilitating stealthy transit. DNV-based magnetic systems and methods can be approximately 100 times smaller than conventional systems and can have a reaction time that that is approximately 100,000 times faster than other systems.
A composite magnetic field (B-field) 206 from all (3) wires shown in
As an example of some implementations, a vehicle, such as a UAS, can include one or more navigation sensors, such as DNV sensors. The vehicle's mission could be to travel to an initial destination and possibly return to a final destination. Known navigation systems can be used to navigate the vehicle to an intermediate location. For example, a UAS can fly using GPS and/or human controlled navigation to the intermediate location. The UAS can then begin looking for the magnetic signature of a power source, such as power lines. To find a power line, the UAS can continually take measurements using the DNV sensors. The UAS can fly in a circle, straight line, curved pattern, etc. and monitor the recorded magnetic field. The magnetic field can be compared to known characteristics of power lines to identify if a power line is in the vicinity of the UAS. For example, the measured magnetic field can be compared with known magnetic field characteristics of power lines to identify the power line that is generating the measured magnetic field. In addition, information regarding the electrical infrastructure can be used in combination with the measured magnetic field to identify the current source. For example, a database regarding magnetic measurements from the area that were previously taken and recorded can be used to compare the current readings to help determine the UAS's location.
In some implementations, once the UAS identifies a power line the UAS positions itself at a known elevation and position relative to the power line. For example, as the UAS flies over a power line, the magnetic field will reach a maximum value and then begin to decrease as the UAS moves away from the power line. After one sweep of a known distance, the UAS can return to where the magnetic field was the strongest. Based upon known characteristics of power lines and the magnetic readings, the UAS can determine the type of power line.
Once the current source has been identified, the UAS can change its elevation until the magnetic field is a known value that corresponds with an elevation above the identified power line. For example, as shown in
The UAS can be programmed, via a computer 306, with a flight path. In some implementations, once the UAS establishes its position, the UAS can use a flight path to reach its destination. In some implementations, the magnetic field generated by the transmission line is perpendicular to the transmission line. In some implementations, the vehicle will fly perpendicular to the detected magnetic field. In one example, the UAS can follow the detected power line to its destination. In this example, the UAS will attempt to keep the detected magnetic field to be close to the original magnetic field value. To do this, the UAS can change elevation or move laterally to stay in its position relative to the power line. For example, a power line that is rising in elevation would cause the detected magnetic field to increase in strength as the distance between the UAS and power line decreased. The navigation system of the UAS can detect this increased magnetic strength and increase the elevation of the UAS. In addition, on board instruments can provide an indication of the elevation of the UAS. The navigation system can also move the UAS laterally to the keep the UAS in the proper position relative to the power lines.
The magnetic field can become weaker or stronger, as the UAS drifts from its position of the transmission line. As the change in the magnetic field is detected, the navigation system can make the appropriate correction. For a UAS that only has a single DNV sensor, when the magnetic field had decreased by more than a predetermined amount the navigation system can make corrections. For example, the UAS can have an error budget such that the UAS will attempt to correct its course if the measured error is greater than the error budget. If the magnetic field has decreased, the navigation system can instruct the UAS to move to the left. The navigation system can continually monitor the magnetic field to see if moving to the left corrected the error. If the magnetic field further decreased, the navigation system can instruct the UAS to fly to the right to its original position relative to the current source and then move further to the right. If the magnetic field decreased in strength, the navigation system can deduce that the UAS needs to decrease its altitude to increase the magnetic field. In this example, the UAS would originally be flying directly over the current source, but the distance between the current source and the UAS has increased due to the current source being at a lower elevation. Using this feedback loop of the magnetic field, the navigation system can keep the UAS centered or at an offset of the current source. The same analysis can be done when the magnetic field increases in strength. The navigation can maneuver until the measured magnetic field is within the proper range such that the UAS in within the flight path.
The UAS can also use the vector measurements from one or more DNV sensors to determine course corrections. The readings from the DNV sensor are vectors that indicate the direction of the sensed magnetic field. Once the UAS knows the location of the power line, as the magnitude of the sensed magnetic field decreases, the vector can provide an indication of the direction the UAS should move to correct its course. For example, the strength of the magnetic field can be reduced by a threshold amount from its ideal location. The magnetic vector of this field can be used to indicate the direction the UAS should correct to increase the strength of the magnetic field. In other words, the magnetic field indicates the direction of the field and the UAS can use this direction to determine the correct direction needed to increase the strength of the magnetic field, which could correct the UAS flight path to be back over the transmission wire.
Using multiple sensors on a single vehicle can reduce the amount of maneuvering that is needed or eliminate the maneuvering all together. Using the measured magnetic field from each of the multiple sensors, the navigation system can determine if the UAS needs to correct its course by moving left, right, up, or down. For example, if both DNV sensors are reading a stronger field, the navigation system can direct the UAS to increase its altitude. As another example if the left sensor is stronger than expected but the right sensor is weaker than expected, the navigation system can move the UAS to the left.
In addition to the current readings from the one or more sensors, a recent history of readings can also be used by the navigation system to identify how to correct the UAS course. For example, if the right sensor had a brief increase in strength and then a decrease, while the left sensor had a decrease, the navigation system can determine that the UAS has moved to far to the left of the flight path and could correct the position of the UAS accordingly.
In various other implementations, a vehicle can also be used to inspect power transmission lines, power lines, and power utility equipment. For example, a vehicle can include one or more magnetic sensors, a magnetic waypoint database, and an interface to UAS flight control. The subject technology may leverage high sensitivity to magnetic fields of DNV magnetic sensors for magnetic field measurements. The DNV magnetic sensor can also be low cost, space, weight, and power (C-SWAP) and benefit from a fast settling time. The DNV magnetic field measurements allow UASs to align themselves with the power lines, and to rapidly move along power-line routes and navigate in poor visibility conditions and/or in GPS-denied environments. It is understood that DNV-based magnetic sensors are approximately 100 times smaller than conventional magnetic sensors and have a reaction time that that is approximately 100,000 times faster than sensors with similar sensitivity such as the EMDEX LLC Snap handheld magnetic field survey meter.
The fast settling time and low C-SWAP of the DNV sensor enables rapid measurement of detailed power line characteristics from low-C-SWAP UASs. In one or more implementations, power lines can be efficiently surveyed via small unmanned aerial vehicles (UAVs) on a routine basis over long distance, which can identify emerging problems and issues through automated field anomaly identification. In other implementations, a land based vehicle or submersible can be used to inspect power lines. Human inspectors are not required to perform the initial inspections. The inspections of the subject technology are quantitative, and thus are not subject to human interpretation as remote video solutions may be.
In some implementations, a vehicle may need to avoid objects that are in their navigation path. For example, a ground vehicle may need to maneuver around people or objects, or a flying vehicle may need to avoid a building or power line equipment. In these implementations, the vehicle can be equipment with sensors that are used to locate the obstacles that are to be avoided. Systems such as a camera system, focal point array, radar, acoustic sensors, etc., can be used to identify obstacles in the vehicles path. The navigation system can then identify a course correction to avoid the identified obstacles.
The processing system 1002 may be implemented using software, hardware, or a combination of both. By way of example, the processing system 1002 may be implemented with one or more processors. A processor may be a general-purpose microprocessor, a microcontroller, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a state machine, gated logic, discrete hardware components, or any other suitable device that can perform calculations or other manipulations of information.
A machine-readable medium can be one or more machine-readable media. Software shall be construed broadly to mean instructions, data, or any combination thereof, whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise. Instructions may include code (e.g., in source code format, binary code format, executable code format, or any other suitable format of code).
Machine-readable media (e.g., 1019) may include storage integrated into a processing system such as might be the case with an ASIC. Machine-readable media (e.g., 1010) may also include storage external to a processing system, such as a Random Access Memory (RAM), a flash memory, a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable PROM (EPROM), registers, a hard disk, a removable disk, a CD-ROM, a DVD, or any other suitable storage device. Those skilled in the art will recognize how best to implement the described functionality for the processing system 1002. According to one aspect of the disclosure, a machine-readable medium is a computer-readable medium encoded or stored with instructions and is a computing element, which defines structural and functional interrelationships between the instructions and the rest of the system, which permit the instructions' functionality to be realized. Instructions may be executable, for example, by the processing system 1002 or one or more processors. Instructions can be, for example, a computer program including code for performing methods of the subject technology.
A network interface 1016 may be any type of interface to a network (e.g., an Internet network interface), and may reside between any of the components shown in
A device interface 1018 may be any type of interface to a device and may reside between any of the components shown in
The foregoing description is provided to enable a person skilled in the art to practice the various configurations described herein. While the subject technology has been particularly described with reference to the various figures and configurations, it should be understood that these are for illustration purposes only and should not be taken as limiting the scope of the subject technology.
One or more of the above-described features and applications may be implemented as software processes that are specified as a set of instructions recorded on a computer readable storage medium (alternatively referred to as computer-readable media, machine-readable media, or machine-readable storage media). When these instructions are executed by one or more processing unit(s) (e.g., one or more processors, cores of processors, or other processing units), they cause the processing unit(s) to perform the actions indicated in the instructions. In one or more implementations, the computer readable media does not include carrier waves and electronic signals passing wirelessly or over wired connections, or any other ephemeral signals. For example, the computer readable media may be entirely restricted to tangible, physical objects that store information in a form that is readable by a computer. In one or more implementations, the computer readable media is non-transitory computer readable media, computer readable storage media, or non-transitory computer readable storage media.
In one or more implementations, a computer program product (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.
While the above discussion primarily refers to microprocessor or multi-core processors that execute software, one or more implementations are performed by one or more integrated circuits, such as application specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs). In one or more implementations, such integrated circuits execute instructions that are stored on the circuit itself.
In some aspects, the subject technology is directed to DNV application to magnetic navigation via power lines. In some aspects, the subject technology may be used in various markets, including for example and without limitation, advanced sensors and mobile space platforms.
The description of the subject technology is provided to enable any person skilled in the art to practice the various embodiments described herein. While the subject technology has been particularly described with reference to the various figures and embodiments, it should be understood that these are for illustration purposes only and should not be taken as limiting the scope of the subject technology.
There may be many other ways to implement the subject technology. Various functions and elements described herein may be partitioned differently from those shown without departing from the scope of the subject technology. Various modifications to these embodiments may be readily apparent to those skilled in the art, and generic principles defined herein may be applied to other embodiments. Thus, many changes and modifications may be made to the subject technology, by one having ordinary skill in the art, without departing from the scope of the subject technology.
Phrases such as an aspect, the aspect, another aspect, some aspects, one or more aspects, an implementation, the implementation, another implementation, some implementations, one or more implementations, an embodiment, the embodiment, another embodiment, some embodiments, one or more embodiments, a configuration, the configuration, another configuration, some configurations, one or more configurations, the subject technology, the disclosure, the present disclosure, other variations thereof and alike are for convenience and do not imply that a disclosure relating to such phrase(s) is essential to the subject technology or that such disclosure applies to all configurations of the subject technology. A disclosure relating to such phrase(s) may apply to all configurations, or one or more configurations. A disclosure relating to such phrase(s) may provide one or more examples. A phrase such as an aspect or some aspects may refer to one or more aspects and vice versa, and this applies similarly to other foregoing phrases
A reference to an element in the singular is not intended to mean “one and only one” unless specifically stated, but rather “one or more.” The term “some” refers to one or more. Underlined and/or italicized headings and subheadings are used for convenience only, do not limit the subject technology, and are not referred to in connection with the interpretation of the description of the subject technology. All structural and functional equivalents to the elements of the various embodiments described throughout this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and intended to be encompassed by the subject technology. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the above description.
The present application claims the benefit of U.S. Provisional Application Nos. 62/109,006, filed Jan. 28, 2015, and 62/109,551, filed Jan. 29, 2015, each of which is incorporated by reference herein in its entirety. The present application is related to co-pending U.S. application Ser. No. 15/003,193, filed Jan. 21, 2016, titled “RAPID HIGH-RESOLUTION MAGNETIC FIELD MEASUREMENTS FOR POWER LINE INSPECTION,” which is incorporated by reference herein in its entirety. The present application is also related to co-pending U.S. application Ser. No. 15/003,088, filed Jan. 21, 2016, titled “IN-SITU POWER CHARGING”, which is incorporated by reference herein in its entirety.
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Number | Date | Country | |
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20170110015 A1 | Apr 2017 | US |
Number | Date | Country | |
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62109006 | Jan 2015 | US | |
62109551 | Jan 2015 | US |