Use of reference measurements to reduce geospatial uncertainty

Abstract

Systems and methods for minimizing the uncertainty of geospatial location measurements. First and second position data of a first reference marker are received, each including an uncertainty radius centered on a preliminary coordinate. A first translation vector is received that includes the displacement from a second reference marker to the first reference marker. A second uncertainty radius is translated by the first translation vector, and based on the intersection area of the translated second uncertainty radius and the first uncertainty radius, the first uncertainty radius is reduced to the intersection area.

Description

Technical Field

[0001] The present disclosure relates to a system for determining a geospatial location, and more particularly, to a system and related processes for iteratively reducing the uncertainty of geospatial uncertainty using the use of virtual reference measurements.

Background Art

[0002] The specific geospatial locations (e.g., longitude and latitude) received and returned by consumer devices are typically inherently inaccurate in the case of the Global Positioning System (GPS), with a resolution of several meters of the device's exact (e.g., true) geospatial location. Although a physical location can be very accurately described from the perspective of geospatial coordinates (e.g., longitude, latitude, altitude) on a map, due to the granularity of the measurement (e.g., meters), the exact location of the device or user with respect to the world and the map is uncertain. In many cases, locations are usually given preliminary coordinates due to uncertainty. Therefore, querying a device for its exact location, or what is within the device's field of view, with an appropriate resolution for the device is inherently inaccurate.

Summary of the Invention

Means for Solving the Problems

[0003] In light of the foregoing, the present disclosure provides a system and related method for minimizing the uncertainty of location measurements (e.g., GPS, ultra-wideband, GLONASS, Wi-Fi) by referring to and relying on reference measurements (e.g., measurements performed locally using algorithms such as distance and direction applications or simultaneous learning and mapping algorithms). Once the exact displacement between at least two reference markers is ascertained, the uncertainty of the geospatial coordinates can be iteratively reduced by excluding the areas where it is impossible for there to be candidates for the true location of the markers, which is achieved by translating either of the uncertainty radii to the other using the measured displacement between the two reference markers, as will be explained and illustrated in more detail below.

[0004] In a first approach, a method is provided for minimizing the uncertainty of geospatial location measurements. The method includes receiving first and second position data of a first fiducial marker, the first and second position data including a second uncertainty radius centered on second preliminary coordinates. For example, a user scans a fiducial marker (in this example, two fiducial markers, although 1+N are also possible), such as a QR code (registered trademark), on a user device or taps an NFC tag to receive a GPS location with an associated certainty radius for each fiducial marker. A first translation vector including the displacement from the second fiducial marker to the first fiducial marker can be received, calculated, or measured. For example, using an augmented reality measurement tool that utilizes the built-in SLAM functionality and accelerometer of the user device, the displacement amount (i.e., distance and direction) from the second fiducial marker to the first fiducial marker is measured or calculated and then received for further use in the method. By knowing the translation vector including the displacement between the fiducial markers, the second uncertainty radius, which is the minimum uncertainty radius, is translated by the first translation vector. In some embodiments, the translation is performed from any point within the second uncertainty radius. The intersection between the first uncertainty radius and the overlapping uncertainty radii of the translated second uncertainty radius replaces the first uncertainty radius, and thus the first uncertainty radius is reduced to the intersection area, reducing the uncertainty of the geospatial measurement. The intersection can be referred to as a reduced radius or equivalent, and the term "reduced radius" serves as a label for an arbitrary convex or substantially convex shape within this context.

[0005] In some embodiments, the method further includes iteratively repeating the translation and reduction of the uncertainty radius. For example, the newly reduced radius (which may be an irregular shape or volume in practice) can be translated to the second preliminary coordinates here until the uncertainty radii of both the first and second position data are minimized, and so on. In some embodiments, the method further includes stopping the iterative process when the first radius reaches a threshold value. In the general case (i.e., more than two measurements), the threshold value can be that before calculating all translations and intersections that are possible from N + 1 measurements for N intersections when a sufficient uncertainty radius has been achieved. Thus, in some embodiments, the threshold value may be based on a certain total number of iterations (e.g., one iteration per N measurements, or 10 iterations in total), after the expiration of a timer, and / or the ideal uncertainty radius size when the uncertainty resolution (e.g., uncertainty radius) is on the same scale as the user device. For example, the iterative process may be stopped after 20 iterations, after 5 seconds, or when the uncertainty radius becomes the size of the user device when the uncertainty radius is less than 10 mm. It should be understood that these embodiments are provided for illustration of the configuration of the threshold value of the iterative process. For a large sample size, e.g., for 100 measured values, after 99 intersections of the uncertainty radius, some of the measured values were inconsistent. Specifically, the uncertainty radius was only an indication, which was incorrect for one of the measured values, so that only the empty set was potentially left, and it should be noted that this invalidates the intersection. Thus, such incorrect samples can be identified by repeating different combinations of intersections less than N times and stopping the process when a suitable uncertainty radius (i.e., resolution) is achieved.

[0006] In some embodiments, the method further includes capturing, by a camera on the user device, first and second fiducial markers. The method may also include storing the first position data and the second position data in a temporary local coordinate space stored on the user device. The location of the fiducial markers transformed into a local coordinate system (e.g., a virtual coordinate space) for measuring the displacement amount (i.e., a 3D vector including both distance and direction) between two or more fiducial markers is often referred to herein as a new spatial coordinate system. The displacement between two fiducial markers and the translation vector between two fiducial markers are thus synonymous terms. In some embodiments, the method includes implementing a simultaneous localization and mapping (SLAM) algorithm on the user device to obtain the displacement amount (e.g., absolute distance and direction) between the first fiducial marker and the second marker within the local coordinate space.

[0007] In some embodiments, the method further includes receiving third position data of a third fiducial marker, the third position data including a third uncertainty radius centered at third preliminary coordinates. The method may also further include receiving, measuring, or calculating a second translation vector including the displacement from the first fiducial marker to the third fiducial marker. The method further includes translating the reduced first uncertainty radius by the second translation vector and reducing the third uncertainty radius to the intersection area based on the intersection area of the translated, reduced first uncertainty radius and the third uncertainty radius.

[0008] In some embodiments, the method further includes capturing, by a camera on the user device, the first and third reference markers; storing the first position data and the third position data in a temporary local coordinate system stored on the user device; implementing a simultaneous localization and mapping (SLAM) algorithm on the user device to obtain an absolute distance between the first marker and the third marker within the local coordinate system; and obtaining a displacement amount (e.g., a virtual coordinate space locally stored on the user device with a known orientation relative to the global coordinate system) from the first marker to the third marker using the known orientation. For example, a scanning device communicating with the first user device may be used to scan the reference marker or an additional reference marker, and such a device may be disposed on an automobile, a tricycle, a boat, a snowmobile, and an underwater device, as well as on a backpack carried on foot.

[0009] In some embodiments, the user device is a second user device different from the first user device. In some embodiments, the first and second markers are the same marker recorded at two different times by the same user device. Thus, the translation vector may be zero, but the intersection area between the two uncertainty radii measured at the first time T1 and the second time T2 can be intersected to reduce the uncertainty of the marker's location.

[0010] In another approach, a media device comprising a control module, a transceiver module, and a network module receives first position data of a first reference marker, the first position data including a first uncertainty radius centered on first preliminary coordinates, performs a step of receiving second position data of a second reference marker, the second position data including a second uncertainty radius centered on second preliminary coordinates, receives a first translation vector including a displacement from the second reference marker to the first reference marker, translates the second uncertainty radius by the first translation vector, and is configured to reduce the first uncertainty radius to the intersection area based on the intersection area of the translated second uncertainty radius and the first uncertainty radius. The media device is provided.

[0011] In another approach, a non-transitory computer-readable medium having instructions recorded thereon that, when executed, perform a method for minimizing uncertainty in location measurements, the method including receiving first position data of a first reference marker, the first position data including a first uncertainty radius centered on first preliminary coordinates, receiving second position data of a second reference marker, the second position data including a second uncertainty radius centered on second preliminary coordinates, receiving a first translation vector including a displacement from the second reference marker to the first reference marker, translating the second uncertainty radius by the first translation vector, and reducing the first uncertainty radius to the intersection area based on the intersection area of the translated second uncertainty radius and the first uncertainty radius. The non-transitory computer-readable medium is provided.

[0012] In another approach, a system for minimizing the uncertainty of location measurements, comprising means for receiving first position data of a first reference marker, the first position data including a first uncertainty radius centered on first preliminary coordinates; means for receiving second position data of a second reference marker, the second position data including a second uncertainty radius centered on second preliminary coordinates; means for receiving a first translation vector between the first reference marker and the second reference marker; means for translating the second uncertainty radius by the first translation vector; and means for reducing the first uncertainty radius to an intersection area based on an intersection area of the translated second uncertainty radius and the first uncertainty radius, is provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The above and other objects and advantages of the present disclosure will become apparent upon consideration of the following detailed description, taken in conjunction with the accompanying drawings.

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Mode for Carrying Out the Invention

[0023] Detailed Description As briefly described above, the geospatial uncertainty in current GPS technology can be minimized by receiving first and second position data of a first reference marker, each including an uncertainty radius centered on a preliminary coordinate. A first translation vector including the displacement from the second reference marker to the first reference marker is received. The second uncertainty radius is translated by the first translation vector, and based on the intersection area of the translated second uncertainty radius and the first uncertainty radius, the first uncertainty radius is reduced to the intersection area between the first uncertainty radius and the second uncertainty radius. Such a modality can be implemented, for example, on a GPS device.

[0024] GPS technology is becoming widely available and is currently commonly used by user devices such as smartphones and equivalents. For example, a GPS receiver inside a user device calculates its four-dimensional position in spacetime based on data received from multiple GPS satellites. Each satellite carries an accurate record of its position and time and transmits that data to the receiver. The satellites carry very stable atomic clocks that are synchronized with each other and with ground clocks. Any deviation from the time maintained on the ground is corrected daily. In the same manner, the location of the satellites is ascertained with great accuracy. GPS receivers located within user devices also have clocks, but they are less stable and less precise, introducing measurement uncertainty. Since the speed of radio waves is constant and independent of satellite speed, the time delay between when a satellite transmits a signal and when the receiver receives it is proportional to the distance from the satellite to the receiver. At a minimum, four satellites must be in the receiver's field of view for it to calculate the four unknown quantities (three position coordinates and the deviation of its own clock from satellite time). However, the uncertainty and resolution of GPS are limited by the capabilities of the user device. Therefore, in other ways, it is desirable to have a method to improve the uncertainty of GPS locations. GPS technology is not the only general geospatial location data that is or is becoming widely available; ultra-wideband (UWB), home mesh Wi-Fi, and equivalents can also be the basis for location measurements where the uncertainty is required to be improved based on them.

[0025] Figure 1 is an illustrative diagram of a mapping application that locates user 110 using GPS technology, according to some embodiments of the present disclosure. User 110 is located at the "X" on the map of the mapping application on a smartphone device (e.g., user device). User 110 activates the "My Location" or similar feature of the mapping application and locates that place on the map of the mapping application. The mapping application is returning preliminary geospatial coordinates 120 with an uncertainty radius 130. In some examples, the mapping application also returns the field of view 140 of user 110 or, rather, the user's device.

[0026] Geospatial data is information that describes an object, event, or other feature associated with a location on or near the surface of the Earth. Geospatial data typically combines location information (usually coordinates on the Earth), attribute information (characteristics of the associated object, event, or phenomenon), and time information (the time or lifespan during which the location and attributes exist). The locations provided may be static over a short period (e.g., the location of a device component, an earthquake event, a child living in poverty) or dynamic (e.g., a moving vehicle or pedestrian, the spread of an infectious disease). Geospatial data typically involves a large set of spatial data collected from many diverse sources in various formats and can include information such as census data, satellite imagery, weather data, mobile phone data, drawn images, and social media data. Geospatial data is most useful when it can be discovered, shared, analyzed, and used in combination with conventional business data. Geospatial data and / or geographical data and information are defined in the ISO / TC211 series of standards as data and information having an implied and explicit association with locations on the Earth (geographical places or geographical positions). This is also referred to as geospatial data and information, georeferenced data and information, and geographic data and geographic information. Approximately 90% of government procured data has a location component.

[0027] As shown in FIG. 1, the preliminary coordinates 120 do not coincide with the actual user's location at 110. This is due to the lack of accuracy of user devices that utilize geospatial location technology. The GPS coordinates received and returned by consumer devices are inherently inaccurate, and typically, it is only possible to place the device within a few meters of the exact geospatial location. The physical location can be accurately described from the perspective of geospatial coordinates (e.g., longitude, latitude, altitude) on a map, but the location of the user device relative to the world and the map remains uncertain. The present disclosure includes details regarding the step of querying the exact location of the device or the reference markers scanned by the device and reducing the uncertainty of the returned query. Also, as shown in FIG. 1, the device returns preliminary coordinates and an uncertainty radius, and the exact location is found somewhere within the circle represented by the product of the uncertainty radius and the preliminary coordinates.

[0028] FIG. 2 is an illustrative diagram of reference markers within a certain area according to some embodiments of the present disclosure. What is shown in FIG. 2 are two reference markers, namely, reference marker A and reference marker B. Each reference marker displays unique encoded information that can be acquired (e.g., machine-detectable or machine-readable). For example, the reference marker may be regarded as a machine-readable label or the like. For example, the machine-readable label may be a two-dimensional code such as a QR code (registered trademark). In some examples, the reference marker may be a near-field communication (NFC) tag that the user device can query to receive reference marker data.

[0029] The reference marker also triggers the user device to determine the current geospatial location of the user device (e.g., the current position and orientation of the user device). For example, in a scenario where two markers (A and B as shown in Figure 2) are installed at two locations, these markers will have geospatial coordinates with various degrees of uncertainty when read by the user device. The user device is configured to acquire the known physical dimensions and appearance of the reference object. It should be understood that the term "known" in "known physical dimensions and appearance" means that the physical dimensions and appearance of the reference marker have been pre-determined. In other words, the reference object has physical dimensions and an appearance that are pre-known so that they can be compared with the apparent dimensions and appearance of the reference object in which it is imaged.

[0030] Figure 3 is an illustrative diagram of the user's geospatial uncertainty when scanning a reference marker according to some embodiments of the present disclosure. Shown in Figure 3 are the geospatial locations and uncertainties of markers A and B. Each marker has a geospatial location represented as a tuple of preliminary coordinates (pn) and uncertainty radius (rn), where n is either A or B in this example. After the step of scanning the marker, all that is known is that each marker is somewhere within the area generated by using the uncertainty radius and the preliminary coordinates. For example, marker A is inside area oA generated by preliminary coordinates pA and uncertainty radius rA.

[0031] Figures 4A and 4B are illustrative diagrams of ways in which position vectors and translation vectors between reference points in a new spatial environment can be generated according to some embodiments of the present disclosure. Shown in Figures 4A and 4B are the origin 100, reference point A, reference point B, reference point C, and a plurality of position vectors.

[0032] In geometry, a position vector, also known as a location vector or radius vector, is a Euclidean vector that represents the position of a point P in space relative to an arbitrary reference origin O100. It is usually denoted by x, r, or s and corresponds to the straight-line segment from O to P. In other words, it is a displacement or translation that maps the origin to P as follows.

Chem.

[0033] Referring to FIG. 4A, the vector

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[0034] Generally, the well-known Cartesian coordinate system is used as follows, or sometimes spherical polar coordinates or cylindrical coordinates are used. [Chemical] In the formula, t is a parameter due to its rectangular or circular symmetry. These different coordinates and corresponding base vectors represent the same position vector r. The selection of the coordinate system is mainly determined by the required level of resolution. For example, if millimeter accuracy of geospatial certainty is required, a volume approach using spherical polar coordinates may be most appropriate. Another element in the selection of the coordinate system can be the computational output of the system where the measurement is made. In the first case and for the remaining embodiments, a Cartesian coordinate system will be used due to its bias. The selected coordinate system is local to the user device and may be used to temporarily store the location of the reference markers where the displacement vector between them can be calculated.

[0035] Cartesian coordinates are simple for many applications, but for some types of motion of the object of interest, it may be necessary or more efficient to work in one of the non - linear coordinate systems such as polar or cylindrical coordinates. For example, if an avatar or user is constantly moving around the environment, this motion involves circular interpolation around multiple reference points, and thus polar coordinates may be more convenient to work in than Cartesian coordinates. Spherical polar coordinates use a combination of linear and angular units to define a position in 2 - D or 3 - D space. Using spherical polar coordinates, a point is defined by the straight - line distance from a reference point (typically the origin 100 or the center of the user's viewpoints 110, 120) and one or two angles from a reference direction. These are referred to as the radius and angular coordinates (r, θ) or (r, θ, φ) in 2 - D and 3 - D respectively.

[0036] The cylindrical coordinate system is a three-dimensional coordinate system that defines a point position by the distance from a selected reference axis such as an axis (not shown) at the origin 100, the direction from the axis to a selected reference direction (typically the positive X direction), and the distance from a selected reference plane perpendicular to the axis. The latter distance is given as a positive or negative number depending on the side of the reference plane facing the point. The exponents of the cylindrical coordinate system, in fact, the origin is the point where all three coordinates can be given as zero. This is the intersection between the reference plane and the axis.

[0037] From the above, it is important to recall that when using Cartesian coordinates, any point in space can be defined by only one set of coordinates. The difference that becomes important when using polar coordinates is that the polar coordinate system allows theoretically an infinite number of coordinate sets to describe any point. Thus, in summary, spherical polar coordinates are likely to be a preferred option for reducing geospatial uncertainty to a minimum using minimization of uncertainty or reaching its threshold volume. However, the simplicity of Cartesian coordinates can be utilized on hardware with processing limitations such as mobile devices or equivalents, and cylindrical coordinates can be utilized in relation to objects having a certain degree of rotational symmetry about a longitudinal axis (e.g., mapping of an arena using a reference marker at the center of the arena).

[0038] Referring back to Figure 4A, the vector

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[0039] In classical physics, translational motion is, in contrast to rotation, a movement that changes the position of an object. For example, translation is an operation that changes the positions of all points (x, y, z) of an object according to the following formula. (x,y,z)→(x+Δx,y+Δy,z+Δz) Wherein, (Δx, Δy, Δz) is the same displacement for each point of the object. The translational vector (Δx, Δy, Δz) common to all points of the object is usually called a linear displacement to distinguish it from a displacement with rotation, which is usually called an angular displacement. In some scenarios, the translational vector may be sufficient alone to determine a way to correct position information. However, in some embodiments, especially with respect to reference markers in a real-world environment, the translational vector is likely to be accompanied by a rotation or a rotation vector, which will be described in more detail below.

[0040] Therefore, for example, after determining the position vectors for a plurality of reference points with respect to the origin, the translational vectors from each reference point to another can also be determined. In this way, a shape such as that shown in FIG. 4B can be defined. In FIG. 4B, a triangle is selected. However, a translational vector between two points (for example, defining a line) or actually any other shape is sufficient for the disclosure of this specification. The shape of FIG. 4B will be used throughout the following embodiments and will be referred to as triangle ABC, or ΔABC. ΔABC has a fixed shape. In this embodiment, the three translational vectors between point A, B, and C

Chemical formula

[0041] Furthermore, the corresponding locations of the reference markers are also created within a virtual space (referred to as the new space location) along with the temporary local coordinates, and the local coordinate system has a known orientation with respect to the global coordinate system. Thus, the geographical space and the new space location of the reference markers are grasped. Also, what is grasped at the time of scanning (i.e., reading / interacting with it / imaging) is the reference marker, which is the position and orientation of the user device with respect to the reference marker. The step of obtaining the known physical dimensions and appearance of the reference marker may include the step of accessing the virtual space layer, which includes the known physical dimensions and the appearance of the reference object.

[0042] Measurements between markers can be performed using, for example, an augmented reality measurement app (e.g., "AR ruler" (RTM) manufactured by Auki Labs) that utilizes the built-in SLAM functionality and accelerometer of the device to find the exact distance between the markers, and using the known orientation, the displacement amount between the markers can then be acquired or calculated. Thus, each marker is given 3D coordinates within the new space coordinate system that is temporarily generated and stored on the device. The new space coordinates of each marker are exact, while the geographical space coordinates remain uncertain. Thus, the displacement between two or more markers, for example, between A and B in FIG. 3,

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[0043] The local coordinate system may be a coordinate system within the virtual space, i.e., the new space system, which can be part of a partially virtual world such as an augmented reality world with a known orientation. Alternatively, the virtual space may be part of a fully virtual world such as a virtual reality world. The virtual space may have a coordinate system different from the preliminary coordinates of the first and second position data. For example, the preliminary coordinates, which are geospatial, are likely to be configured with the origin at the center of the earth, as in the case of using GPS. The virtual space, including the local coordinate system, has a known orientation with respect to the global coordinate system.

[0044] Figures 5 and 6 are illustrative diagrams showing the translation of the error radius according to some embodiments of the present disclosure. With respect to Figure 5, the minimum error radius, in this case the error radius area 520oB, is

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[0045] In mathematics, the intersection of two or more sets is the set of elements that are common to each of the sets. An element is in the intersection if it belongs to all of the sets. The symbol for intersection is "∩", and the term "and" is associated with it because A ∩ B is the set of elements that are in both A and B. To find the intersection of two (or more) sets, only those elements that are listed in both (or all) of the sets are considered. In a Venn diagram, the intersection of two sets A and B can be shown as the shaded region inside the middle of two overlapping circles, and in a similar way, the intersection between oA and oB is also in the middle of two overlapping regions. In mathematical notation, the intersection of A and B is written as A ∩ B = {x: x ∈ A and x ∈ B}.

[0046] In Figure 6, for example, by moving to the leftmost possible coordinates enabled by the uncertainty oB, while maintaining the new spatial coherence, taking the coordinates further to the left would leave marker B outside the acceptable geospatial range provided by the GPS. Thus, it can be inferred that marker A likely cannot exist further to the left. In particular, it is shown that oB can be translated by a vector

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[0047] In the embodiments of FIGS. 2, 3, 5, and 6, only two markers and translation vectors are shown. However, it should be understood that multiple markers can be used and the term "translation vector" is sometimes used herein as a label to describe not only translations in the x, y, and / or z directions of the second error radius, but also associated rotations and / or additional rotation vectors. In particular, as the user scans two or more reference markers, the translation vector may include a series of translations and rotations that are similar to the path taken by the user's device within the local coordinate system between the two reference markers. However, in some embodiments, the translation of the shortest path can be calculated between two or more reference markers regardless of the path taken by the user's device within the local coordinate system.

[0048] In another use case, if the user was communicating with multiple transmitters at a location and the exact locations of the transmitters were known to the user device, the relative locations from the user device to the transmitters could be determined, the uncertainty radius could be reduced, and then the actual location of the user device could be determined. In other words, when the user device communicates with multiple transmitters, it would be possible to determine, for each transmitter, the direction, distance, and radius of uncertainty that could be minimized by the method of this specification. By knowing the actual locations of the transmitters and the relative locations of the user device, the actual location of the user device can be determined. The transmitters may be, for example, UWB transmitters, Wi-Fi mesh transmitters, or the like within the user's home, workplace space, train station, bus stop, stadium, or the like.

[0049] In addition, the imaging of the reference marker may depend on the individual field of view of the user device. In some embodiments, after observing a reference marker within the field of view of the user device, the current location is requested (e.g., via GPS or the like), and a SLAM algorithm that maps the area to the next reference marker is utilized. The next reference marker may be located behind the user relative to the user's initial field of view. Thus, when applying the translation vector, a rotation vector may be required. In addition, in another embodiment, the user may be able to record one or more reference markers by rotating the field of view of the user device rather than moving the user device. Thus, in some scenarios, the translation vector may also likely include a rotation element or rotation vector. In some embodiments, the translation vector and the rotation vector are applied separately or in parallel to arrive at a combined translation vector.

[0050] To be complete, in mathematics, the axis-angle representation of rotation parameterizes a rotation in three-dimensional Euclidean space by two quantities, namely, a unit vector e indicating the direction of the axis of rotation and an angle θ describing the magnitude of the rotation about the axis. In this embodiment, the unit vector e, i.e., the axis of rotation, is parallel to the conventional z-direction (e.g., upward), which is typically approximately perpendicular to the field of view of the user or the user's device. However, other axes of rotation may be selected, e.g., the axis of rotation may be parallel to the translation vector. In this way, the rotation vector can be directly applied to the translation vector to result in a single vector.

[0051] Rather than three, only two numbers are required to define the direction of the unit vector e rooted at the origin, since the magnitude of e is constrained. For example, the elevation and azimuth angles of e are sufficient to locate this in any particular Cartesian coordinate frame. The angles and axes determine a transformation that rotates a three-dimensional vector (e.g., the position vectors of the first and second users). The axis-angle representation is equivalent to a more concise rotation vector, also called an Euler vector. In this case, both the rotation axis and the angle are represented by a vector in the same direction as the rotation axis, whose length is the rotation angle θ, as follows.

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[0052] Many rotation vectors correspond to the same rotation. In particular, a rotation vector of length θ + 2πM for any integer M encodes the same rotation as a rotation vector of length θ. Thus, there exist at least a countably infinite number of rotation vectors corresponding to any rotation. Furthermore, all rotations by 2πM are not identical to any rotation, so that for a given integer M, all rotation vectors of length 2πM form an uncountably infinite set of 2-parameter rotation vectors that encode the same rotation as the zero vector in all directions. These relationships are considered when inverting the exponential map, i.e., when applying the present disclosure using matrices rather than vectors, to find the rotation vector corresponding to a given rotation matrix.

[0053] Figures 7 - 12 are exemplary schematic diagrams of the steps of determining an error radius, translating the error radius, and repeating the process to reach a minimized geospatial uncertainty, according to some embodiments of the present disclosure. Figures 7 - 12 have an error radius shown as a rectangle for simplicity. Referring to Figure 7, three rectangles (sA, sB, sC) represent three error radii centered on reference markers A, B, and C, respectively. Additionally, the new spatial relationships between points A, B, and C, and thus the displacements, have already been measured and are demonstrated by ΔABC in Figures 7 - 12. In particular, ΔABC consists of three translation vectors that describe the displacements between each of the reference markers A, B, and C, respectively.

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[0054] Regarding Figure 8, in the first case, error rectangle sB is the smallest of the error rectangles and is thus selected to be translated first. The coordinates of the left - most corner of sB are selected as the translation starting point because this is the closest to sA.

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[0055] Regarding Figure 9, the next iteration begins. In this example, sB is

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[0056] Regarding FIG. 10, the intersection of sC and sB is now the smallest error rectangle. Therefore, the next step in the iterative process is to take the currently reduced error rectangle sC

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[0057] FIG. 12 enables the iterative process to be performed again because the new error rectangle sB* has an intersection with the updated error rectangle centered on the reference marker B, which further reduces uncertainty, etc. Again, further geospatial uncertainty can be introduced, as demonstrated by subsequent measurements of the reference marker, for example, reference marker B, by the user device. In this way, the iterative process can continue until the process reaches a threshold. In some embodiments, the threshold may be based on the total number of iterations, the expiration of a timer, and / or the ideal uncertainty radius size when the uncertainty resolution (e.g., uncertainty radius) is on the same scale as the user device. For example, the iterative process may stop after a certain number of iterations, such as 100 iterations, after an iterative process over a time period such as 5 seconds, or when the size of one or more errors becomes the size of the user device, when the radius of uncertainty of each reference marker is less than a specific size such as less than 10 mm. It should be understood that these embodiments are provided for the illustration of the configuration of the threshold of the iterative process.

[0058] FIG. 13 is an illustrative flowchart of a process for minimizing the geospatial uncertainty of a location according to some embodiments of the present disclosure. Note that process 1300 or any of its steps may be implemented on or provided by any of the devices shown in FIGS. 14 and 15 below. Additionally, one or more steps of process 1300 may be incorporated into or combined with one or more steps of any other process or embodiment described herein.

[0059] In step 1302, the system receives first position data of a first reference marker, the first position data including a first uncertainty radius centered on first preliminary coordinates. In step 1304, the system receives second position data of a second reference marker, the second position data including a second uncertainty radius centered on second preliminary coordinates. The reception may be performed by a transceiver such as that described with reference to FIG. 15.

[0060] In step 1306, the system receives a first translation vector between the first reference marker and the second reference marker. In some examples, the first translation vector includes the displacement from the second reference marker to the first reference marker, or alternatively, the first translation vector may include the displacement from the first reference marker to the second reference marker. In some examples, the translation vector may be calculated, i.e., the translation vector may already be received, and step 1306 may be replaced by a step in which the system calculates the first translation vector from the second reference marker to the first reference marker, or vice versa. For example, with respect to an origin (e.g., origin 400 of FIG. 4), the location and distance of the reference markers are determined. In practice, this is done by determining the coordinates of the reference markers with respect to the origin at (x 1 , y 1 , z 1 ), e.g., the center of the earth, and the position vectors are thus

Chemical formula

[0061] In step 1308, the system translates the second uncertainty radius by the first translation vector, as will be described in detail with reference to FIGS. 5-12. For example, the first and second position data may include information such as direction, distance, elevation, or other information that describes the user's current position and / or the imaged (or scanned / measured, etc.) specific location of the reference marker relative to the field of view. Using the translation vector, the position information may be corrected so that the direction, distance, elevation, or other information describes the true location where it should be used instead within the local coordinate system.

[0062] In step 1310, based on the intersection area of the translated second uncertainty radius and the first uncertainty radius, the system reduces the first uncertainty radius to the intersection area.

[0063] Process 1300 may also include optional steps (not shown). For example, a step of starting a repeating loop between steps 1308 and 1310 may be included. Additionally, process 1300 may also include a pause for the loop between steps 1308 and 1310 after a certain condition, such as a threshold, as discussed with reference to FIG. 12, is satisfied. Further, process 1300 may also include a waiting period (not shown) between steps 1304 and 1306, allowing the user sufficient time to scan a plurality of reference markers. The waiting period may include a manual action button to force process 1300 to proceed to step 1306.

[0064] FIG. 14 shows an illustrative block diagram of a computing configuration 1400 that may include a media device, system, and / or method disclosed herein. The computing configuration 1400 includes a user device 1402. The user device 1402 may be a portable electronic device such as a smartphone, tablet, laptop, smartwatch, smart glasses, augmented reality (AR) glasses, AR lens, or any other suitable device. In some embodiments, the user device 1402 may include a control circuitry 1404 and an input / output (I / O) path 1406. The control circuitry 1404 may include a processing circuitry 1408 and a storage device 1410 (e.g., RAM, ROM, hard disk, removable disk, etc.), and the storage device 1410 may be provided with instructions for executing the methods herein, such as process 1300. Additionally, the storage device 1410 may temporarily store a local coordinate system for making measurements between two or more fiducial markers. For example, the fiducial markers may be transformed to positions within the local coordinate system, and a SLAM algorithm on the user device may be used to measure the displacement amount between the fiducial markers. The I / O path 1406 may provide device information or other data and / or other content and data to the control circuitry 1404 via a local area network (LAN) or wide area network (WAN). The control circuitry 1404 may use the I / O path 1406 to transmit and receive commands, requests, signals (digital and analog), and other suitable data. The I / O path 1406 may connect the control circuitry 1404 (specifically, the processing circuitry 1408) to one or more communication paths.

[0065] The user device 1402 may include a head-up display 1412 and a speaker 1414 for visually and audibly presenting content. Additionally, for interacting with the user, the user device 1402 includes a user interface 1416. The user interface 1416 may include a scroll wheel, physical buttons, switches, touch pads, direct drive motors, triggers, or touch screens. The user interface 1416 is connected to the I / O path 1406 and the control circuitry 1404.

[0066] The control circuitry 1404 may be based on any suitable processing circuitry such as the processing circuitry 1408. As referred to herein, processing circuitry is to be understood to mean circuitry based on one or more microprocessors, microcontrollers, digital signal processors, programmable logic devices, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), etc., and may include multi-core processors (e.g., dual-core, quad-core, hexa-core, or any suitable number of cores), cloud-based computing units, or even supercomputers. In some embodiments, the processing circuitry may be distributed across multiple distinct processors or processing units, e.g., multiple ones of the same type of processing unit (e.g., two Intel Core i7 processors) or multiple different processors (e.g., an Intel Core i5 processor and an Intel Core i9 processor).

[0067] The memory may be an electronic memory device provided as a storage device 1410 that is part of the control circuitry 1404. The storage device 1410 may store instructions that, when executed by the processing circuitry 1408, implement the processes described herein. As referred to herein, the phrases "electronic memory device" or "memory device" are to be understood to mean any device for storing electronic data, computer software, or firmware, such as random access memory, read-only memory, hard drives, solid state devices, quantum memory devices, or any other suitable fixed or removable storage device, and / or any combination thereof. Non-volatile memory may also be used (e.g., to boot up the routine and other instructions). The user device 1402 may be a smartphone, tablet, e-book reader, laptop, etc., that includes a camera (not shown) for recording an image of the reference marker.

[0068] The computing configuration 1400 may also include a communication network 1418 and a server device 1420. The user device 1402 may be coupled to the communication network 1418 to communicate with the server device 1420. The communication network 1418 may be one or more networks including the Internet, a mobile phone network, a mobile voice or data network (e.g., other wireless transmissions as described by BLUETOOTH®, Wi-Fi, WiMAX, Zigbee®, GSM®, UTMS, CDMA, TDMA, 3G, 4G, 4G LTE, 5G, or related 802.11 wireless communication protocols), a mesh network, a peer-to-peer network, a cable network, or other type of communication network, or a combination of communication networks. Additionally, additional user devices (not shown) may also communicate with the communication network 1418.

[0069] In some embodiments, the server device 1420 may include a control circuitry 1422 and an input / output (I / O) path 1424. The control circuitry 1404 may include a processing circuitry 1426, similar to what has already been discussed in relation to the user device 1402, and a storage device 1428. The server device 1420 may be a content provider for the user device 1402, such as SLAM algorithm data, new space data information, geospatial data information, user profile data, or the like.

[0070] It should be understood that the user device 1402 is not limited to the embodiments and methods shown and described herein. In non-limiting examples, the user device 1402 may be a digital storage device, a digital media receiver, a digital media adapter, a streaming media device, a personal computer (PC), a laptop computer, a tablet computer, a PC media server, a PC media center, a handheld computer, a personal digital assistant (PDA), a mobile phone, a portable gaming machine, a smartphone, a virtual reality headset, an augmented reality headset, a mixed reality headset, or any other device, client device, or wireless device, and / or a combination of things capable of implementing the methods as described with reference to the claims.

[0071] FIG. 15 illustrates an exemplary media device 1500 according to some embodiments of the present disclosure. The media device 1500 includes a transceiver module 1510, a control module 1520, and a network module 5130. The media transmission system may communicate with additional user devices 1535 such as a gateway, a smartphone, a camera system (e.g., a 3D camera), a mono Internet of Things (IoT) device, or other devices as described with reference to FIG. 14. In some examples, the additional user device 1535 is the user's primary device for interacting with the reference marker, and the media device 1500 includes components for performing processing, particularly when the additional user device has limited processing capabilities.

[0072] In some examples, the transceiver module communicates with a second user device 1535 via a communication link 1518. The communication link 1518 between the transceiver module 1510 and the second user device 1535 may comprise a physical connection facilitated by an input port such as a 3.5 mm jack, an RCA jack, a USB port, an Ethernet® port, or any other suitable connection for communicating via a wired connection, or a wireless connection via other wireless transmissions as described by the BLUETOOTH®, Wi-Fi, WiMAX, Zigbee®, GSM®, UTMS, CDMA, TDMA, 3G, 4G, 4G LTE, 5G, or related 802.11 wireless communication protocols.

[0073] In some embodiments, the second user device 1535 may receive an image data input (e.g., an image of a QR code (registered trademark) representing a fiducial marker as described above), and then transmit the image data to the media device 1500. However, these embodiments are to be considered non-limiting, and other combinations of the features herein are also considered to be within the scope of the present disclosure to be spread across two or more devices. For example, the transceiver module, network module, and control module may each be separate Internet of Things (IoT) devices, each performing a part of the method herein. Collectively, these devices may be referred to as a system. In some embodiments, the image data may be stored on a server such as the server device 1420 of FIG. 14.

[0074] The media device 1500 and / or the user device 1535 system may collectively be a series of image capture devices that operate on a portable backpack, vehicle (e.g., an automobile or van), bicycle, or the like. Further, the media device 1500 may be a virtual reality, mixed reality, or augmented reality headset, and in such cases, may include an eye contact detection component that may be part of the control module 1520 and may be used to identify the user's point of gaze to determine whether the user is focused on a particular part of the environment and / or to determine the user's line of sight or field of view. For example, where the user's eye is focused may determine where the image data is captured and recorded.

[0075] In particular, the transceiver module 1510 and the network module 1530 may be configured to perform the step of receiving the first position data of the first reference marker, where the first position data includes a first uncertainty radius centered on the first preliminary coordinates, and the step of receiving the second position data of the second reference marker, where the second position data includes a second uncertainty radius centered on the second preliminary coordinates. Also, the control module 1520 may calculate a first translation vector between the first reference marker and the second reference marker, and use the first translation vector to translate the second uncertainty radius to the first preliminary coordinates, and be configured to reduce the first uncertainty radius to the intersection area based on the intersection area of the translated second uncertainty radius and the first uncertainty radius.

[0076] The systems and processes discussed above are intended to be illustrative, not limiting. Those skilled in the art will understand that the actions of the processes discussed herein may be omitted, modified, combined, and / or rearranged, and that any additional actions may be performed without departing from the scope of the invention. More generally, the above disclosure is meant to be illustrative, not limiting. Only the following claims set the boundaries of what the disclosure encompasses. Further, note that any features and limitations described in any one embodiment may be applied to any other embodiment herein, and that flowcharts or examples associated with one embodiment may be performed in a different order, appropriately combined with any other embodiment, or performed in parallel. Additionally, the systems and methods described herein may be implemented in real time. Also, note that the systems and / or methods described above may be applied to or used in accordance with other systems and / or methods. The following terms may be understood herein subject to the following explanations.

[0077] All features disclosed in this specification (including any accompanying claims, abstract, and drawings) and / or all steps of any method or process so disclosed may be combined in any combination except combinations in which at least some of such features and / or steps are mutually exclusive.

[0078] Each feature disclosed in this specification (including any accompanying claims, abstract, and drawings) may be replaced by an alternative feature serving the same, equivalent, or similar purpose, unless expressly stated otherwise. Thus, unless expressly stated otherwise, each feature disclosed is only an example of a general series of equivalent or similar features.

[0079] The present invention is not limited to the details of any of the foregoing embodiments. The present invention extends to any novel one or any novel combination of features disclosed in this specification (including any accompanying claims, abstract, and drawings) or to any novel one or any novel combination of steps of any method or process so disclosed. The claims should not be construed as merely reciting the foregoing embodiments, but should also be construed as covering any embodiment falling within the scope of the claims.

[0080] Throughout the description and claims of this specification, the words "comprise" and "contain" and their variants mean "including but not limited to", and they are not intended to (do not) exclude other parts, additives, components, integers, or steps. Throughout the description and claims of this specification, the singular form includes the plural unless the context otherwise requires. In particular, when an indefinite article is used, this specification is to be understood as including both the plural and the singular unless the context otherwise requires.

[0081] All of the features disclosed in this specification (including any accompanying claims, abstract, and drawings) and / or all of the steps of any method or process so disclosed may be combined in any combination, except combinations in which at least some of such features and / or steps are mutually exclusive. The invention is not limited to the details of any of the foregoing embodiments. The invention extends to any novel one or any novel combination of the features disclosed in this specification (including any accompanying claims, abstract, and drawings) or to any novel one or any novel combination of the steps of any method or process so disclosed.

[0082] The reader's attention is directed to all articles and documents related to this application that are filed contemporaneously with or prior to this application and that are open to public inspection together with this application, and the contents of all such articles and documents are incorporated herein by reference.

Claims

1. A method for minimizing the uncertainty of location measurement, the method comprising: Receiving first position data of a first reference marker, the first position data including a first uncertainty radius centered on first preliminary coordinates; Receiving second position data of a second reference marker, the second position data including a second uncertainty radius centered on second preliminary coordinates; Receiving a first translation vector including the displacement from the second reference marker to the first reference marker; Translating the second uncertainty radius by the first translation vector; Reducing the first uncertainty radius to the intersection area based on the intersection area of the translated second uncertainty radius and the first uncertainty radius A method comprising:

2. The method according to claim 1, further comprising repeatedly repeating the translation and reduction of the uncertainty radius.

3. The method according to claim 2, further comprising stopping the iterative process when the first radius reaches a threshold value.

4. The method according to claim 3, wherein the threshold value is based on an ideal uncertainty radius size, a total number of iterations, a timer expiration, and / or when the resolution of the uncertainty is on the same scale as the user device.

5. Capturing the first and second reference markers by a camera of a user device; Storing the first position data and the second position data in a temporary local coordinate system stored on the user device The method according to claim 1, further comprising:

6. The method according to claim 5, further comprising implementing a simultaneous localization and mapping (SLAM) algorithm to obtain a displacement amount between the first marker and the second marker in the local coordinate system on the user device.

7. Receiving third position data of a third reference marker, the third position data including a third uncertainty radius centered on third preliminary coordinates; Receiving a second translation vector including the displacement from the first reference marker to the third reference marker; Translating the reduced first uncertainty radius by the second translation vector; Reducing the third uncertainty radius to the intersection area based on the intersection area of the translated, reduced first uncertainty radius and the third uncertainty radius The method according to claim 1, further comprising.

8. Capturing the first and third reference markers on a camera of the user device; Storing the first position data and the third position data in a temporary local coordinate system stored on the user device; Performing a simultaneous localization and mapping (SLAM) algorithm on a second user device to obtain an absolute distance between the first marker and the third marker within the local coordinate system The method according to claim 7, further comprising.

9. The method according to claim 8, wherein the user device is a second user device different from the first user device.

10. A non-transitory computer-readable medium having instructions recorded thereon, which when executed perform a method for minimizing the uncertainty of location measurements, the method comprising: Receiving first position data of a first reference marker, the first position data including a first uncertainty radius centered on first preliminary coordinates; Receiving second position data of a second reference marker, the second position data including a second uncertainty radius centered on second preliminary coordinates; Receiving a first translation vector including a displacement from the second reference marker to the first reference marker; Translating the second uncertainty radius by the first translation vector; Reducing the first uncertainty radius to the intersection area based on the intersection area of the translated second uncertainty radius and the first uncertainty radius A non-transitory computer-readable medium comprising.

11. The computer-readable medium according to claim 10, further comprising repeatedly iterating the translation and reduction of the uncertainty radius.

12. The computer-readable medium according to claim 11, further comprising stopping the iterative process when the first radius reaches a threshold value.

13. The computer-readable medium according to claim 12, wherein the threshold value is based on an ideal uncertainty radius size, a total number of iterations, a timer expiration, and / or when the uncertainty resolution is on the same scale as the user device.

14. capturing the first and second reference markers by a camera on the user device; storing the first position data and the second position data in a temporary local coordinate system stored on the user device; The computer-readable medium according to claim 10, further comprising the above.

15. The computer-readable medium according to claim 14, further comprising implementing a simultaneous localization and mapping (SLAM) algorithm on the user device to obtain a displacement amount between the first marker and the second marker in the local coordinate system.

16. receiving third position data of a third reference marker, the third position data including a third uncertainty radius centered on third preliminary coordinates; receiving a second translation vector including the displacement from the first reference marker to the third reference marker; translating the reduced first uncertainty radius by the second translation vector; reducing the third uncertainty radius to the intersection area based on an intersection area between the translated reduced first uncertainty radius and the third uncertainty radius; The computer-readable medium according to claim 10, further comprising the above.

17. capturing the first and third reference markers by a camera on the user device; storing the first position data and the third position data in a temporary local coordinate system stored on the user device; implementing a simultaneous localization and mapping (SLAM) algorithm on the user device to obtain a displacement amount between the first marker and the third marker in the local coordinate system; The computer-readable medium according to claim 16, further comprising the above.

18. The computer-readable medium according to claim 17, wherein the user device is a second user device different from the first user device.

19. A media device comprising a control module for minimizing the uncertainty of location measurement, a transceiver module, and a network module, wherein the media device receives first position data of a first reference marker, the first position data including a first uncertainty radius centered on first preliminary coordinates, receives second position data of a second reference marker, the second position data including a second uncertainty radius centered on second preliminary coordinates, receives a first translation vector including the displacement from the second reference marker to the first reference marker, translates the second uncertainty radius by the first translation vector, reduces the first uncertainty radius to the intersection area based on the intersection area of the translated second uncertainty radius and the first uncertainty radius is configured to perform.

20. The media device according to claim 19, further configured to repeatedly iterate the translation and reduction of the uncertainty radius.

21. The media device according to claim 20, further configured to stop the iterative process when the first radius reaches a threshold value.

22. The media device according to claim 21, wherein the threshold value is based on an ideal uncertainty radius size, a total number of iterations, a timer expiration, and / or when the resolution of the uncertainty is on the same scale as the user device.

23. further configured to capture the first and second reference markers by a camera, store the first position data and the second position data in a temporary local coordinate system stored on the user device The media device according to claim 19, which is configured to perform.

24. The media device according to claim 23, further configured to implement a simultaneous localization and mapping (SLAM) algorithm to obtain a displacement amount between the first marker and the second marker in the local coordinate system on the user device.

25. receives third position data of a third reference marker, the third position data including a third uncertainty radius centered on third preliminary coordinates, Receiving a second translation vector including the displacement from the first reference marker to the third reference marker; Translating the reduced first uncertainty radius by the second translation vector; Reducing the third uncertainty radius to the intersection area based on the intersection area of the translated, reduced first uncertainty radius and the third uncertainty radius The media device according to claim 19, further configured to perform.

26. Capturing the first and third reference markers by a camera on a second user device; Storing the first position data and the third position data in a temporary local coordinate system stored on the user device; Performing a simultaneous localization and mapping (SLAM) algorithm on the user device to obtain an absolute distance between the first marker and the third marker in the local coordinate system The media device according to claim 25, further configured to perform.

27. The media device according to claim 26, wherein the user device is a second user device different from the first user device.

28. A system for minimizing the uncertainty of location measurements, the system comprising: Means for receiving first position data of a first reference marker, the first position data including a first uncertainty radius centered on a first preliminary coordinate; Means for receiving second position data of a second reference marker, the second position data including a second uncertainty radius centered on a second preliminary coordinate; Means for receiving a first translation vector including the displacement from the second reference marker to the first reference marker; Means for translating the second uncertainty radius by the first translation vector; Means for reducing the first uncertainty radius to the intersection area based on the intersection area of the translated second uncertainty radius and the first uncertainty radius A system comprising.

29. The system according to claim 28, further comprising means for repeatedly repeating the translation and reduction of the uncertainty radius.

30. The system according to claim 29, further comprising means for stopping the iterative process when the first radius reaches a threshold.

31. The system according to claim 30, wherein the threshold value is based on an ideal uncertainty radius size and / or the number of iterations.

32. Means for capturing the first and second reference markers by a camera on the user device, and Means for storing the first position data and the second position data in a temporary local coordinate system stored on the user device The system according to claim 28, further comprising.

33. The system according to claim 32, further comprising means for implementing a simultaneous localization and mapping (SLAM) algorithm to obtain a displacement amount between the first marker and the second marker in the local coordinate system on the user device.

34. Means for receiving third position data of a third reference marker, the third position data including a third uncertainty radius centered on third preliminary coordinates, and Means for receiving a second translation vector including the displacement from the first reference marker to the third reference marker, and Means for translating the reduced first uncertainty radius by the second translation vector, and Means for reducing the third uncertainty radius to the intersection area based on an intersection area of the translated and reduced first uncertainty radius and the third uncertainty radius The system according to claim 28, further comprising.

35. Means for capturing the first and third reference markers by a camera on a second user device, and Means for storing the first position data and the third position data in a temporary local coordinate system stored on the user device, and Means for implementing a simultaneous localization and mapping (SLAM) algorithm to obtain an absolute distance between the first marker and the third marker in the local coordinate system on the user device The system according to claim 34, further comprising.

36. The system according to claim 35, wherein the user device is a second user device different from the first user device.

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