Patent Publication Number: US-2022237822-A1

Title: Vehicle pose determination systems and methods

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application relates to and claims priority benefits from U.S. Provisional Patent Application No. 63/142,008, entitled “Vehicle Pose Determination Systems and Methods,” filed Jan. 27, 2021, which is hereby incorporated by reference in its entirety. 
    
    
     FIELD OF THE DISCLOSURE 
     Embodiments of the present disclosure generally relate to vehicle pose determination systems and methods, such as may be used with aircraft during an in-flight refueling or rendezvous process. 
     BACKGROUND OF THE DISCLOSURE 
     During a flight, an aircraft may need to be refueled. Certain aircraft are configured as fuel tankers that are configured to refuel another aircraft during a flight. For example, a fuel tanker may include a boom or drogue that is extended behind the fuel tanker during a flight. The boom is coupled to a fuel line. A trailing aircraft is maneuvered to the end of the boom, which is then attached to a fuel inlet of a probe of the trailing aircraft. After the boom of the fuel tanker is connected to the fuel inlet of the trailing aircraft, an in-flight refueling of the trailing aircraft occurs. 
     Typically, a pilot of the trailing aircraft maneuvers the trailing aircraft in relation to the fuel tanker. The pilot manually operates the control devices of the trailing aircraft to guide the probe to the boom (engagement), and ensure a connection therebetween. Once the fuel inlet is connected to the boom, the pilot continues to manually operate the control devices of the trailing aircraft to ensure that the fuel inlet remains coupled to the boom as the trailing aircraft is refueled. Typically, as the trailing aircraft is being refueled, the pilot ensures that the trailing aircraft maintains position in relation to the fuel tanker, which is known as station-keeping. Station-keeping also occurs while the trailing aircraft is queuing to be refueled, and various forms of formation flight. After the refueling process, the connection between the probe of the trailing aircraft is disconnected from the boom of the fuel tanker (disengagement), and the refueled aircraft continues flight, such as according to a particular mission. 
     As can be appreciated, the process of maneuvering a trailing aircraft in relation to the fuel tanker, and manually controlling the trailing aircraft (as well as the boom of the fuel tanker) during the refueling process requires a high level of skill and experience. In certain situations, such as during periods of turbulence, a pilot may have difficulty maneuvering the trailing aircraft in relation to the fuel tanker before and after the connection between the boom and the fuel inlet is attained (engagement and disengagement). Further, the advent of autonomous aircraft without human pilots typically utilizes fully autonomous maneuvering. 
     SUMMARY OF THE DISCLOSURE 
     A need exists for a system and a method for automatically determining a pose of a first vehicle relative to a second vehicle. Also, a need exists for a system and a method for automatically controlling positioning (including position/location and/or orientation) of a vehicle, such an aircraft during an in-flight refueling process. Further, a need exists for a system and a method for automatically maintaining a relative position between two different vehicles. Moreover, a need exists for a low cost, effective, and efficient automatic vehicle pose determination and positioning. 
     With those needs in mind, certain embodiments of the present disclosure provide a system including an imaging device configured to capture one or more images of a first vehicle. A control unit is in communication with the imaging device. A model database is in communication with the control unit. The model database stores a three-dimensional (3D) model of the first vehicle. The control unit is configured to receive image data regarding the one or more images of the first vehicle from the imaging device and analyze the image data with respect to the 3D model of the first vehicle to determine a pose of the first vehicle. 
     In at least one embodiment, the system also includes a second vehicle. For example, the second vehicle includes the imaging device, the control unit, and the model database. 
     As an example, the first vehicle is a first aircraft and the second vehicle is a second aircraft. As a further example, the second vehicle trails the first vehicle. As another example, the first vehicle trails the second vehicle. 
     In at least one embodiment, the second vehicle further includes one or more control devices in communication with the control unit. The control unit is configured to operate the one or more control devices based on the pose of the first vehicle. 
     In at least one embodiment, the control unit is configured to move and manipulate the 3D model of the first vehicle to match the image data of the first vehicle and determine the pose of the first vehicle. 
     As an example, the control unit includes a renderer that dynamically generates an expected image as anticipated to be captured by the imaging device. 
     As an example, the control unit is configured to employ Maximum Mutual Information Correlator (MMIC) matching followed by a Fitts correlator. 
     Certain embodiments of the present disclosure provide a method including capturing, by an imaging device, one or more images of a first vehicle; storing, in a model database, a three-dimensional (3D) model of the first vehicle; communicatively coupling a control unit with the imaging device; communicatively coupling the model database with the control unit; receiving, by the control unit, image data regarding the one or more images of the first vehicle from the imaging device; and analyzing, by the control unit, the image data with respect to the 3D model of the first vehicle to determine a pose of the first vehicle. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  illustrates a schematic block diagram of a system for determining a pose of a first vehicle in relation to a second vehicle, according to an embodiment of the present disclosure. 
         FIG. 2  illustrates a perspective view of a first aircraft refueling a second aircraft, according to an embodiment of the present disclosure. 
         FIG. 3  illustrates a schematic block diagram for architecture of the system of  FIG. 1 , according to an embodiment of the present disclosure. 
         FIG. 4  illustrates a flow chart of a method for determining a pose of a first vehicle in relation to a second vehicle, according to an embodiment of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION OF THE DISCLOSURE 
     The foregoing summary, as well as the following detailed description of certain embodiments will be better understood when read in conjunction with the appended drawings. As used herein, an element or step recited in the singular and preceded by the word “a” or “an” should be understood as not necessarily excluding the plural of the elements or steps. Further, references to “one embodiment” are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features. Moreover, unless explicitly stated to the contrary, embodiments “comprising” or “having” an element or a plurality of elements having a particular condition can include additional elements not having that condition. 
     Certain embodiments of the present disclosure provide vehicle pose determination systems and methods that use computer vision to measure a relative pose between two vehicles, such as two aircraft. Embodiments of the present disclosure can be used to facilitate rendezvous, station-keeping and/or docking, such as between two aircraft. The systems and methods provide vision-based guidance and alignment using one or more imaging devices. The systems and methods provide true three-dimensional (3D) tracking of relative pose, rather than simple two-dimensional tracking of position. Further, the systems and methods provide a passive measurement approach, which operate independently of other infrastructure. In at least one embodiment, the systems and methods estimate relative pose (attitude and position) between two vehicles using passive computer vision techniques, such as to allow for rendezvous and station-keeping between the vehicles. 
     Embodiments of the present disclosure provide systems and methods that are configured to calculate a relative position and attitude (pose) between two vehicles, such as aircraft, to support autonomous operations that will allow the vehicles to rendezvous, maintain relative position (station-keeping), transfer fuel and cargo, and/or the like. In at least one embodiment, the term pose relates to a six degree of freedom vector of position (x, y, z) and angular orientation (yaw, pitch, roll). 
     The term “pose” refers to the six-degree of freedom position and attitude of an object, such as a first vehicle, with respect to a second object, such as a second vehicle. 
       FIG. 1  illustrates a schematic block diagram of a system  100  for determining a pose of a first vehicle  102  in relation to a second vehicle  104 , according to an embodiment of the present disclosure. In at least one embodiment, the first vehicle  102  is a first aircraft and the second vehicle  104  is a second aircraft. In at least one embodiment, the first aircraft  102  leads (for example, in front) the second aircraft  104 , which trails (that is, behind) that first aircraft  102 . Optionally, the first aircraft  102  trails the second aircraft  104 . In at least one other embodiment, the first vehicle  102  and/or the second vehicle  104  is a ground based vehicle, such as an automobile, bus, locomotive, military vehicle (such as a tank), and/or the like. In at least one embodiment, the first vehicle  102  and/or the second vehicle  104  is a spacecraft, watercraft, or the like. In at least one embodiment, the first vehicle  102  is an aeronautical or aerospace vehicle, and the second vehicle  104  is a land-based or water-based vehicle. 
     In at least one embodiment, the first vehicle  102  is a fuel tanker, such as a KC-46, manufactured by The Boeing Company, and the second vehicle  104  is a military fighter jet, such as an F-15, manufactured by The Boeing Company. Optionally, as another example, the first vehicle  102  is a military fighter jet, and the second vehicle  104  is a fuel tanker. As another example, one or both of the first vehicle  102  or the second vehicle  104  is/are an unmanned aircraft, such as an unmanned aerial vehicle, drone, or the like. 
     The second vehicle  104  includes an imaging device  106  in communication with a control unit  108 , such as through one or more wired or wireless connections. The control unit  108  is further in communication with a model database  110 , such as through one or more wired or wireless connections. The model database  110  stores vehicle model data  112  related to one or more vehicle models, such as computer aided design (CAD) models of the first vehicle  102  and/or the second vehicle  104 . 
     In at least one embodiment, the control unit  108  is further in communication with one or more control devices  114  of the second vehicle  104 , such as through one or more wired or wireless connections. The control devices  114  are operatively coupled to various components of the second vehicle  104 , such as engines, control surfaces on wings, stabilizers, etc., and the like. The control devices  114  can include one or more of a yoke, stick, joystick, pedals, buttons, switches, keyboards, touchscreens, and/or the like that are configured to control the various components of the second vehicle  104 . The control devices  114  can be onboard the second vehicle  104  (such as within a cockpit or flight deck), or remotely located from the second vehicle  104 , such as if the second vehicle  104  is an unmanned aerial vehicle. Optionally, the control unit  108  is not in communication with the control device(s)  114 . Optionally, the first vehicle  102  includes the imaging device  106 , the control unit  108 , the model database  110 , and/or the control device(s)  114 . For example, the first vehicle  102  can be a tanker aircraft that maneuvers a boom to engage the second vehicle  104 , such as an aircraft that is to be refueled. The imaging operations described herein can be used to automatically operate and guide the tanker in relation to the other aircraft to couple the boom to the other aircraft for refueling. Certain embodiments of the present disclosure a system that is configured to determine relative pose between two different aircraft to facilitate station-keeping and maintain safe zones. 
     In at least one embodiment, the imaging device  106  is a camera, such as a video camera, still image camera, and/or the like. As another example, the imaging device  106  is an infrared imaging device. As another example, the imaging device  106  is an ultrasonic imaging device. As another example, the image device  106  is a Laser Detection and Ranging (LADAR) sensor. As another example, the imaging device  106  is a radio detection and ranging (RADAR) sensor. The imaging device  106  is configured to capture one or more images  116  of the first vehicle  102  within a field of view  118 . In at least one embodiment, one or more imaging devices  106  are configured to utilize multiple image bands in order to extend the envelope of operational conditions to exploit the viewing benefits of each band. 
     As an example, and as shown on  FIG. 1 , the second vehicle  104  is a trailing aircraft that is to be refueled in flight by the first vehicle  102 , such as a tanker aircraft. The second vehicle  104  includes the imaging device  106 , the control unit  108 , the model database  110 , the control devices  114 , and the positioning activator  121 , as shown in  FIG. 1 . Continuing with this example, in operation, the imaging device  106  of the second vehicle  104  images the first vehicle  102  and acquires the one or more images  116  of the first vehicle  102 . The imaging device  106  outputs image data  120 , which can include raw image data and/or reconstructed images  116  to the control unit  108 . 
     The control unit  108  analyzes the image data  120  in relation to the vehicle model data  112 , which includes a 3D model  113  of the first vehicle  102 . In particular, the control unit  108  compares the image data  120  to the vehicle model data  112 . The control unit  108  moves and manipulates (for example, virtually moves and manipulates) the 3D model  113  of the first vehicle  102 , as stored in the vehicle model data  112 , to match the image data  120  of the first vehicle  102 . When the image data  120  matches the 3D model  113 , the control unit  108  determines the pose of the first vehicle  102  relative to the second vehicle  104 . In this manner, the control unit  108  determines the pose (including position and angular orientation) of the first vehicle  102  relative to the second vehicle  104 . 
     In at least one embodiment, the control unit  108  automatically operates the second vehicle  104  based on the determined pose of the first vehicle  102  relative to the second vehicle  104 . For example, the control unit  108  operates the control devices  114  of the second vehicle  104  to automatically control the second vehicle  104  relative to the first vehicle  102 . In particular, by determining the pose of the first vehicle  102  relative to the second vehicle  104 , the control unit  108 , such as when commanded by a pilot or operator (such as a land-based operator on an unmanned aerial vehicle), automatically operates the control device  114  of the second vehicle  104  to maintain a predetermined distance and orientation between the first vehicle  102  and the second vehicle  104 . 
     In at least one embodiment, the second vehicle  104  includes a positioning activator  121  in communication with the control unit  108 , such as through one or more wired or wireless connections. The second vehicle  104  can be activated into an automatic positioning mode by the positioning activator  121 . For example, before and/or during a refueling process, a pilot may engage the positioning activator  121  to allow the control unit  108  to automatically control and position the second vehicle  104  relative to the first vehicle  102 . In general, the positioning activator  121  is configured to be selectively engaged to selectively transition the second vehicle  104  between a manual control mode (in which a pilot controls operation of the second vehicle  104 ) to the automatic positioning mode (in which the control unit  108  automatically controls the second vehicle  104  based on the determined pose of the first vehicle  102  relative to the second vehicle  104 , as described herein). In at least one embodiment, determination of the pose allow the control unit  108  to operate the second vehicle  104 . As another example, the automatic positioning mode may occur when the first vehicle  102  and the second vehicle  104  are on the ground (or in the air) to ensure that the first vehicle  102  and the second vehicle  104  remain a predetermined distance from one another, such as to avoid collisions or other inadvertent encounters. In at least one embodiment, the control unit  108  operates the control devices  114  to automatically maneuver the second vehicle  104  in relation to the first vehicle  102  to connect a fuel inlet of a probe of the second vehicle  104  to a boom of the first vehicle  102 , which may be a fuel tanker, for example. 
     Optionally, the second vehicle  104  may not include the positioning activator  121 . Instead, the second vehicle  104  may automatically transition to the automatic positioning mode, such as when the first vehicle  102  is determined to be within a predetermined distance (such as within  500  meters or less) of the second vehicle  104 , such as determined by the control unit  108  determining the pose of the first vehicle  102  relative to the second vehicle  104 . In at least one embodiment, the second vehicle  104  includes a manual override mechanism (such as a physical or virtual button, lever, switch, key, slide, or the like) that allows a pilot to manually override the automatic positioning mode. 
     As described herein, the system  100  includes the imaging device  106 , which is configured to capture one or more images  116  of the first vehicle  102 . The control unit  108  is in communication with the imaging device  106 . The model database  110  is in communication with the control unit  108 . The model database  110  stores the 3D model  113  of the first vehicle  102 . The control unit  108  is configured to receive the image data  120  regarding the one or more images  116  of the first vehicle  102  from the imaging device  106  and analyze the image data  120  with respect to the 3D model  113  of the first vehicle  102  to determine a pose of the first vehicle  102 , such as in relation to the second vehicle  104 . 
     In at least one embodiment, the second vehicle  104  includes the imaging device  106 , the control unit  108 , and the model database  110 . In at least one other embodiment, another component can include one or more of the imaging device  106 , the control unit  108 , and the model database  110 . For example, a land based monitoring station, a satellite, a different vehicle, or the like can include one or more of the imaging device  106 , the control unit  108 , and/or the model database  110 . As an example, the imaging device  106  on a satellite or land-based structure can be used to determine a pose of an approaching aircraft, spacecraft, or the like. 
     As used herein, the term “control unit,” “central processing unit,” “unit,” “CPU,” “computer,” or the like can include any processor-based or microprocessor-based system including systems using microcontrollers, reduced instruction set computers (RISC), application specific integrated circuits (ASICs), logic circuits, and any other circuit or processor including hardware, software, or a combination thereof capable of executing the functions described herein. Such are exemplary only, and are thus not intended to limit in any way the definition and/or meaning of such terms. For example, the control unit  108  can be or include one or more processors that are configured to control operation thereof, as described herein. 
     The control unit  108  is configured to execute a set of instructions that are stored in one or more data storage units or elements (such as one or more memories), in order to process data. For example, the control unit  108  can include or be coupled to one or more memories. The data storage units can also store data or other information as desired or needed. The data storage units can be in the form of an information source or a physical memory element within a processing machine. The one or more data storage units or elements can comprise volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. As an example, the nonvolatile memory can comprise read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable PROM (EEPROM), and/or flash memory and volatile memory can include random access memory (RAM), which can act as external cache memory. The data stores of the disclosed systems and methods is intended to comprise, without being limited to, these and any other suitable types of memory. 
     The set of instructions can include various commands that instruct the control unit  108  as a processing machine to perform specific operations such as the methods and processes of the various embodiments of the subject matter described herein. The set of instructions can be in the form of a software program. The software can be in various forms such as system software or application software. Further, the software can be in the form of a collection of separate programs, a program subset within a larger program or a portion of a program. The software can also include modular programming in the form of object-oriented programming. The processing of input data by the processing machine can be in response to user commands, or in response to results of previous processing, or in response to a request made by another processing machine. 
     The diagrams of embodiments herein illustrate one or more control or processing units, such as the control unit  108 . It is to be understood that the processing or control units can represent circuits, circuitry, or portions thereof that can be implemented as hardware with associated instructions (e.g., software stored on a tangible and non-transitory computer readable storage medium, such as a computer hard drive, ROM, RAM, or the like) that perform the operations described herein. The hardware can include state machine circuitry hardwired to perform the functions described herein. Optionally, the hardware can include electronic circuits that include and/or are connected to one or more logic-based devices, such as microprocessors, processors, controllers, or the like. Optionally, the control unit  108  can represent processing circuitry such as one or more of a field programmable gate array (FPGA), application specific integrated circuit (ASIC), microprocessor(s), and/or the like. The circuits in various embodiments can be configured to execute one or more algorithms to perform functions described herein. The one or more algorithms can include aspects of embodiments disclosed herein, whether or not expressly identified in a flowchart or a method. 
     As used herein, the terms “software” and “firmware” are interchangeable, and include any computer program stored in a data storage unit (for example, one or more memories) for execution by a computer, including RAM memory, ROM memory, EPROM memory, EEPROM memory, and non-volatile RAM (NVRAM) memory. The above data storage unit types are exemplary only, and are thus not limiting as to the types of memory usable for storage of a computer program. 
     In at least one embodiment, components of the system  100 , such as the control unit  108 , provide and/or enable a computer system to operate as a special computer system for automatic pose determination and/or positioning processes. 
       FIG. 2  illustrates a perspective view of a first aircraft  102 ′ refueling a second aircraft  104 ′, according to an embodiment of the present disclosure. The first aircraft  102 ′ is an example of the first vehicle  102  (shown in  FIG. 1 ), and the second aircraft  104 ′ is an example of the second vehicle  104  (also shown in  FIG. 1 ). The first aircraft  102 ′ includes a propulsion system  130  that includes one or more engines  132 , for example. The engines  132  are carried by wings  134  of the first aircraft  102 ′. In other embodiments, the engines  132  may be carried by a fuselage  136  and/or an empennage  138 . The empennage  138  may also support horizontal stabilizers  140  and a vertical stabilizer  142 . The second aircraft  104 ′ includes a propulsion system  160  that may include one or more engines  162 , for example. The engines  162  are carried by wings  164  and/or a fuselage  166  of the second aircraft  104 ′. In other embodiments, the engines  162  may be carried by the fuselage  166  and/or an empennage, which may also support horizontal stabilizers  170  and vertical stabilizers  172 . In at least one embodiment, the first aircraft  102 ′ is a fuel tanker that extends a boom  180  having a fuel line. The second aircraft  104 ′ includes a probe  182  having a fuel inlet. 
     Referring to  FIGS. 1 and 2 , embodiments of the present disclosure provide systems and methods for automatic station-keeping of the second aircraft  104 ′ during in-flight refueling. Further, the imaging device  106  and the model database  110  provides low-cost components that can be quickly and easily added to the second aircraft  104 ′, in contrast to more expensive and complex light detection and ranging (LIDAR) systems, laser-based systems, or the like. Accordingly, embodiments of the present disclosure provide low-cost and effective systems and methods for automatically determining a pose of the first aircraft  102 ′ relative to the second aircraft  104 ′ (or vice versa), and optionally controlling the second aircraft  104 ′ relative to the first aircraft  102 ′ (or vice versa). The first aircraft  102 ′ and the second aircraft  104 ′ may be manufactured having the components described herein, or existing aircraft can be quickly and easily retrofit at a relatively low cost. 
       FIG. 3  illustrates a schematic block diagram for architecture of the system of  FIG. 1 , according to an embodiment of the present disclosure. Referring to  FIGS. 1 and 3 , in at least one embodiment, the system  100  analyzes the 3D model  113  of the first vehicle  102 , such as with respect to a synthetic or virtual viewpoint. Positions of one or more components of the first vehicle  102  are determined through one or more images  116 , as captured by the imaging device  106 . In at least one embodiment, the control unit  108  renders portions of a 3D terrain database, rather than 3D object models, at various possible poses, which are then compared to actual measurements (such as the image(s)  116 ) to determine a pose of the first vehicle  102  relative to the second vehicle  104  or even a surrounding setting, such as a runway. The systems and methods described herein can be used to implement station-keeping with respect to ground or maritime vehicles and/or objects, for example, in addition to aerial vehicles. 
     In at least one embodiment, the orientation and position of the imaging device(s)  106  with respect to a reference location on the second vehicle  104  is assumed to be known. Notably, the vehicle model data  112  is locally stored within the model database  110 , such as may be or include a  3 -D model library  202 , which includes models of vehicles expected to be engaged. In at least one embodiment, the control unit  108  includes a renderer  200 , which dynamically generates an expected image as anticipated to be captured by the imaging device  106 . The renderer  200  is configured to render the expected image from an arbitrary point of view, and arbitrary relative pose. 
     The renderer  200  of the control unit  108  renders views of the observed vehicle type from the 3D model library  202  (such as that of the model database  110 ) with a perspective. The renderer  200  generates a number of images, each corresponding to a particular relative pose, all of which are compared to the actual image  116  captured by the imaging device  106 . As an example, each expected image corresponds to a different postulated relative pose. 
     The type of aircraft in the field of view  118  of the imaging device  106  is assumed to be known. An initial pose estimate  204 , based on either image measurements or a priori probabilities, is used to set a nominal pose used by the renderer  200 . The renderer  200  then generates a view of the 3D model  113  of the first vehicle  102  (or portions thereof, such as when the first vehicle  102  is close enough to the second vehicle  104  in which at least portions of the first vehicle  102  are outside the field of view  118 ) at multiple pose values bracketing the nominal value. 
     Because the renderer  200  operates on the 3D model  113 , the renderer  200  is able to acquire views at any pose value. Each of the resulting rendered images is compared to the actual image (that is, the image  116 ) in an image match block  206 . Resulting match statistics are processed to select a best estimate of relative pose among tested values. 
     In at least one embodiment, the control unit  108  employs a Maximum Mutual Information Correlator (MMIC) matching (or registration) algorithm to make the comparisons and determine a best match. The relative viewing geometry that defines the selected match is then accepted as an estimate of the relative pose of the first vehicle  102  relative to the second vehicle  104 . In at least one embodiment, the control unit  108  achieves sub-pixel registration accuracy by following this step with a Fitts correlator, for example. 
     Once the first pose estimate is determined, further iterations allow the solution to become more precise as the distance between the first vehicle  102  and the second vehicle  104  decreases, and the diversity of rendered images can be restricted to reduce computational burdens. After at least two measurements, a predictive tracking filter, such as a Kalman filter  208 , can be used to predict the expected location of the first vehicle  102  in the next image frame, and the expected pose is updated to adjust the rendering engine accordingly. 
     In at least one embodiment, when the first vehicle  102  being imaged by the imaging device  106  occupies only a portion of a camera frame, for example, the renderer  200  can be configured to generate multiple renderings of the entire vehicle as an input to the matching process. The pose of the rendered image that has the best match score can be selected as the best estimate of relative pose among the values tested. 
     As the same vehicle moves closer, the renderer  200  can render and match a multitude of smaller image sections for each pose value, each containing sufficient information (such as predetermined and known features) to support a match computation. Such a process may be used when the range between the first vehicle  102  and the second vehicle  104  is relatively small (such as within  30  meters or less) and the first vehicle  102  occupies a large portion of the image  116 . In this case, algorithms can be applied to estimate relative pose using the locations of feature matches in the image plus the knowledge of how the feature points are geometrically related in 3D. 
     In at least one embodiment, the MMIC algorithm is sensitive to the information content in the scene to be matched, rather than a particular ordering of gray levels or colors. Hence, the control unit  108  can employ the MMIC algorithm to match scenes from an arbitrary model database to the output of various imaging sensors (for example, monochrome or color visible, MWIR, LWIR, SWIR, RADAR and LADAR). 
     As described herein, the control unit  108  is configured to dynamically generate scenes with respect to the first vehicle  102 . For example, the renderer  200  generates reference images in real-time with arbitrary pose values (such as through manipulation of the 3D model  113 ), in contrast to the use of rigid, pre-computed image libraries. Optionally and/or additionally, the renderer  200  generates reference images from and/or in relation to pre-computed, fixed pose data. In at least one embodiment, the control unit  108  uses the MMIC, instead of traditional correlators, to match images or features, combined with use of a Fitts correlator for sub-pixel registration accuracy. Further, in at least one embodiment, the control unit  108  uses the MMIC algorithm to match multiple object images and then infer pose. Additionally, in at least one embodiment, the control unit  108  uses the MMIC algorithm to match predetermined object feature points which are then used with a pose estimation algorithm. 
     Embodiments of the present disclosure are able to track a relative pose of the first vehicle  102  in six degrees of freedom. That is, the control unit  108  is configured to track position and attitude of the first vehicle  102 , in contrast to basis two-dimensional tracking. 
       FIG. 4  illustrates a flow chart of a method for determining a pose of a first vehicle in relation to a second vehicle, according to an embodiment of the present disclosure. The method includes capturing ( 300 ), by an imaging device, one or more images of a first vehicle; storing ( 302 ), in a model database, a three-dimensional (3D) model of the first vehicle; communicatively coupling ( 304 ) a control unit with the imaging device; communicatively coupling ( 306 ) the model database with the control unit; receiving ( 308 ), by the control unit, image data regarding the one or more images of the first vehicle from the imaging device; and analyzing ( 310 ), by the control unit, the image data with respect to the 3D model of the first vehicle to determine a pose of the first vehicle. 
     In at least one embodiment, the method also includes disposing the imaging device, the control unit, and the model database within a second vehicle. 
     In at least one example, the method also includes operating, by the control unit, one or more control devices of the second vehicle, based on the pose of the first vehicle. 
     In at least one embodiment, analyzing includes moving and manipulating, by the control unit, the 3D model of the first vehicle to match the image data of the first vehicle and determine the pose of the first vehicle. 
     In at least one embodiment, said analyzing includes dynamically generating, by a renderer of the control unit, an expected image as anticipated to be captured by the imaging device. 
     As an example, said analyzing includes employing, by the control unit, Maximum Mutual Information Correlator (MMIC) matching followed by a Fitts correlator. 
     As described herein, embodiments of the present disclosure provide systems and methods for automatically determining a pose of a first vehicle relative to a second vehicle. Further, embodiments of the present disclosure provide systems and method for automatically controlling positioning (including position/location and/or orientation) of a vehicle, such an aircraft during an in-flight refueling process. Further, embodiments of the present disclosure provide systems and methods for automatically maintaining a relative position between two different vehicles. Moreover, embodiments of the present disclosure provide systems and methods for low cost, effective, and efficient automatic vehicle pose determination and positioning. 
     Further, the disclosure comprises embodiments according to the following clauses: 
     Clause 1. A system comprising: 
     an imaging device configured to capture one or more images of a first vehicle; 
     a control unit in communication with the imaging device; and 
     a model database in communication with the control unit, wherein the model database stores a three-dimensional (3D) model of the first vehicle, wherein the control unit is configured to receive image data regarding the one or more images of the first vehicle from the imaging device and analyze the image data with respect to the 3D model of the first vehicle to determine a pose of the first vehicle. 
     Clause 2. The system of Clause 1, further comprising a second vehicle, wherein the second vehicle comprises the imaging device, the control unit, and the model database. 
     Clause 3. The system of Clause 2, wherein the first vehicle is a first aircraft and the second vehicle is a second aircraft. 
     Clause 4. The system of Clause 3, wherein the second vehicle trails the first vehicle. 
     Clause 5. The system of Clause 3, wherein the first vehicle trails the second vehicle. 
     Clause 6. The system of any of Clauses 2-5, wherein the second vehicle further comprises one or more control devices in communication with the control unit, wherein the control unit is configured to operate the one or more control devices based on the pose of the first vehicle. 
     Clause 7. The system of any of Clauses 1-6, wherein the control unit is configured to move and manipulate the 3D model of the first vehicle to match the image data of the first vehicle and determine the pose of the first vehicle. 
     Clause 8. The system of any of Clauses 1-7, wherein the control unit comprises a renderer that dynamically generates an expected image as anticipated to be captured by the imaging device. 
     Clause 9. The system of any of Clauses 1-8, wherein the control unit is configured to employ Maximum Mutual Information Correlator (MIMIC) matching followed by a Fitts correlator. 
     Clause 10. A method comprising: 
     capturing, by an imaging device, one or more images of a first vehicle; 
     storing, in a model database, a three-dimensional (3D) model of the first vehicle; 
     communicatively coupling a control unit with the imaging device; 
     communicatively coupling the model database with the control unit; 
     receiving, by the control unit, image data regarding the one or more images of the first vehicle from the imaging device; and 
     analyzing, by the control unit, the image data with respect to the 3D model of the first vehicle to determine a pose of the first vehicle. 
     Clause 11. The method of Clause 10, further comprising disposing the imaging device, the control unit, and the model database within a second vehicle. 
     Clause 12. The method of Clause 11, further comprising operating, by the control unit, one or more control devices of the second vehicle, based on the pose of the first vehicle. 
     Clause 13. The method of any of Clauses 10-12, wherein said analyzing comprises moving and manipulating, by the control unit, the 3D model of the first vehicle to match the image data of the first vehicle and determine the pose of the first vehicle. 
     Clause 14. The method of any of Clauses 10-13, wherein said analyzing comprises dynamically generating, by a renderer of the control unit, an expected image as anticipated to be captured by the imaging device. 
     Clause 15. The method of any of Clauses 10-14, wherein said analyzing comprises employing, by the control unit, Maximum Mutual Information Correlator (MIMIC) matching followed by a Fitts correlator. 
     Clause 16. A system comprising: 
     a first vehicle; and 
     a second vehicle including: 
     an imaging device configured to capture one or more images of a first vehicle; 
     a control unit in communication with the imaging device; 
     a model database in communication with the control unit, wherein the model database stores a three-dimensional (3D) model of the first vehicle, wherein the control unit is configured to receive image data regarding the one or more images of the first vehicle from the imaging device and analyze the image data with respect to the 3D model of the first vehicle to determine a pose of the first vehicle; and 
     one or more control devices in communication with the control unit, wherein the control unit is configured to operate the one or more control devices based on the pose of the first vehicle. 
     Clause 17. The system of Clause 16, wherein the first vehicle is a first aircraft and the second vehicle is a second aircraft. 
     Clause 18. The system of Clause 17, wherein the second vehicle trails the first vehicle. 
     Clause 19. The system of Clause 17, wherein the first vehicle trails the second vehicle. 
     Clause 20. The system of any of Clauses 16-19, wherein the control unit is configured to move and manipulate the 3D model of the first vehicle to match the image data of the first vehicle and determine the pose of the first vehicle, wherein the control unit comprises a renderer that dynamically generates an expected image as anticipated to be captured by the imaging device, and wherein the control unit is configured to employ Maximum Mutual Information Correlator (MIMIC) matching followed by a Fitts correlator. 
     While various spatial and directional terms, such as top, bottom, lower, mid, lateral, horizontal, vertical, front and the like can be used to describe embodiments of the present disclosure, it is understood that such terms are merely used with respect to the orientations shown in the drawings. The orientations can be inverted, rotated, or otherwise changed, such that an upper portion is a lower portion, and vice versa, horizontal becomes vertical, and the like. 
     As used herein, a structure, limitation, or element that is “configured to” perform a task or operation is particularly structurally formed, constructed, or adapted in a manner corresponding to the task or operation. For purposes of clarity and the avoidance of doubt, an object that is merely capable of being modified to perform the task or operation is not “configured to” perform the task or operation as used herein. 
     It is to be understood that the above description is intended to be illustrative, and not restrictive. For example, the above-described embodiments (and/or aspects thereof) can be used in combination with each other. In addition, many modifications can be made to adapt a particular situation or material to the teachings of the various embodiments of the disclosure without departing from their scope. While the dimensions and types of materials described herein are intended to define the parameters of the various embodiments of the disclosure, the embodiments are by no means limiting and are exemplary embodiments. Many other embodiments will be apparent to those of skill in the art upon reviewing the above description. The scope of the various embodiments of the disclosure should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. In the appended claims and the detailed description herein, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Moreover, the terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to impose numerical requirements on their objects. Further, the limitations of the following claims are not written in means-plus-function format and are not intended to be interpreted based on 35 U.S.C. § 112(f), unless and until such claim limitations expressly use the phrase “means for” followed by a statement of function void of further structure. 
     This written description uses examples to disclose the various embodiments of the disclosure, including the best mode, and also to enable any person skilled in the art to practice the various embodiments of the disclosure, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the various embodiments of the disclosure is defined by the claims, and can include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if the examples have structural elements that do not differ from the literal language of the claims, or if the examples include equivalent structural elements with insubstantial differences from the literal language of the claims.