CN113298954B

CN113298954B - Method and device for determining and navigating movement track of object in multi-dimensional variable-granularity grid

Info

Publication number: CN113298954B
Application number: CN202110394515.4A
Authority: CN
Inventors: 童晓冲; 雷毅; 张永生; 李贺; 邱春平; 赖广陵; 王大力; 孙月坤; 唐佳怡
Original assignee: Information Engineering University of PLA Strategic Support Force
Current assignee: Information Engineering University of PLA Strategic Support Force
Priority date: 2021-04-13
Filing date: 2021-04-13
Publication date: 2022-11-22
Anticipated expiration: 2041-04-13
Also published as: CN113298954A

Abstract

The invention discloses a method and a device for determining and navigating an object movement track in a multi-dimensional variable-granularity grid, which are used for solving the problem of low efficiency of identification and calculation of the object movement track in a multi-dimensional space. This scheme includes: determining an N-dimensional grid containing the position of a target object; acquiring unit granularity and moving distance of the target object moving in each dimension corresponding to the N-dimensional grid; determining an encoding of a path mesh of the target object in the N-dimensional mesh; and determining the moving track of the target object according to the coding of the path mesh of the target object in the N-dimensional mesh. According to the scheme, the hierarchy of the grid is determined according to the granularity matched with the moving distance of the object in each dimension, so that a multi-dimensional variable-granularity grid structure and codes are formed, the moving track of the object is identified efficiently, data redundancy caused by the fact that the object moves at a high speed in certain dimensions is avoided, the number of codes used for determining the moving track is reduced, the coding calculation efficiency is improved, and meanwhile, the accuracy of the determined moving track is guaranteed.

Description

Method and device for determining and navigating movement track of object in multi-dimensional variable-granularity grid

Technical Field

The invention relates to the field of multidimensional data processing, in particular to a method and a device for determining and navigating an object moving track in a multidimensional variable-granularity grid.

Background

In production and life, different objects have different moving directions and moving speeds. For example, a person may walk an average of about 1 meter for about 1 second, while a satellite may be able to operate about 10 kilometers in 1 second. If the trajectory is generated in unit granularity of meters, more data redundancy exists when the movement trajectory of the satellite is generated, and the calculation efficiency is often low. However, if the trajectory is generated with kilometer as unit granularity, the error is large when the trajectory of the person walking is generated, and it is difficult to accurately mark the trajectory. Therefore, the moving speed difference between the human and the satellite is too large, and the moving tracks of the human and the satellite are often not on the same plane, so that the generated moving track is difficult to be matched with the target object. For the moving track of the object in the multi-dimensional space, the prior art has the problems of low calculation efficiency, low efficiency of identifying the moving track and inaccuracy.

How to efficiently and accurately identify and calculate the movement track of an object in a multidimensional space is a technical problem to be solved by the application.

Disclosure of Invention

The embodiment of the application aims to provide a method and a device for determining and navigating an object movement track in a multi-dimensional variable-granularity grid, which are used for solving the problem of low efficiency of identification and calculation of the object movement track in a multi-dimensional space.

In a first aspect, a method for determining an object movement trajectory in a multidimensional variable-granularity grid is provided, which includes:

acquiring unit granularity and moving distance of the target object moving in each dimension corresponding to the N-dimensional grid, wherein the unit granularity of the target object moving in each dimension corresponding to the N-dimensional grid is determined by the speed of the target object moving in each dimension;

determining the coding of a path grid of a target object in the N-dimensional grid, wherein the path grid comprises grids matched with unit granularity of movement of the target object in each dimension and movement distance, and the coding of the path grid is obtained by cross-positioning of multi-scale coding of each dimension corresponding to the N-dimensional grid;

and determining the movement track of the target object according to the coding of the path grid of the target object in the N-dimensional grid.

In a second aspect, an apparatus for determining a moving trajectory of an object in a multi-dimensional variable-granularity grid is provided, including:

the first determining module is used for determining an N-dimensional grid containing the position of a target object, wherein N is an integer larger than 1, and the dimension corresponding to the N-dimensional grid comprises the movable dimension of the target object;

the first acquisition module is used for acquiring unit granularity and movement distance of the target object moving in each dimension corresponding to the N-dimensional grid, and the unit granularity of the target object moving in each dimension corresponding to the N-dimensional grid is determined by the speed of the target object moving in each dimension;

the second determination module is used for determining the coding of a path grid of the target object in the N-dimensional grid, wherein the path grid comprises grids matched with unit granularity and moving distance of the target object in each dimension, and the coding of the path grid is obtained by cross-positioning of multi-scale coding of each dimension corresponding to the N-dimensional grid;

and the third determination module is used for determining the movement track of the target object according to the coding of the path mesh of the target object in the N-dimensional mesh.

In a third aspect, a method for navigating an object in a multidimensional variable-granularity grid is provided, which includes:

determining an N-dimensional grid containing the position of a target object and a navigation end position, wherein N is an integer greater than 1, and the corresponding dimension of the N-dimensional grid comprises the movable dimension of the target object;

determining the coding of a path grid of the target object in the N-dimensional grid, wherein the path grid comprises grids matched with unit granularity of movement and movement distance of the target object in each dimension, and the coding of the path grid is obtained by cross-positioning of multi-scale coding of each dimension corresponding to the N-dimensional grid;

determining the movement track of the target object according to the coding of the path mesh of the target object in the N-dimensional mesh;

and generating a navigation route according to the movement track and the navigation end point position.

In a fourth aspect, an apparatus for navigating an object in a multi-dimensional variable-granularity grid is provided, comprising:

the fourth determining module is used for determining an N-dimensional grid containing the position of the target object and the navigation end position, wherein N is an integer larger than 1, and the corresponding dimensionality of the N-dimensional grid comprises the movable dimensionality of the target object;

the second acquisition module is used for acquiring the unit granularity and the movement distance of the target object moving in each dimension corresponding to the N-dimensional grid, and the unit granularity of the target object moving in each dimension corresponding to the N-dimensional grid is determined by the speed of the target object moving in each dimension;

a fifth determining module, configured to determine a code of a path mesh of the target object in the N-dimensional mesh, where the path mesh includes a mesh with a unit granularity of movement of the target object in each dimension and a movement distance that are matched, and the code of the path mesh is obtained by cross-fetching of multi-scale codes of each dimension corresponding to the N-dimensional mesh;

a sixth determining module, configured to determine a movement trajectory of the target object according to a code of a path mesh of the target object in the N-dimensional mesh;

and the generating module is used for generating a navigation route according to the moving track and the navigation end position.

In a fifth aspect, there is provided an electronic device comprising a processor, a memory and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the method according to the first or third aspect.

A sixth aspect provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method as in the first or third aspect.

In the embodiment of the application, an N-dimensional grid containing the position of a target object is determined; acquiring unit granularity and moving distance of the target object moving in each dimension corresponding to the N-dimensional grid; determining an encoding of a path mesh of the target object in the N-dimensional mesh; and determining the moving track of the target object according to the coding of the path mesh of the target object in the N-dimensional mesh. According to the scheme, the hierarchy of the grid is determined according to the granularity matched with the moving distance of the target object in each dimension, so that a multi-dimensional variable-granularity grid structure and codes are formed to identify the moving track of the target object, data redundancy caused by the fact that the target object moves at a high speed in certain dimensions is avoided, the number of codes used for determining the moving track is reduced, the coding calculation efficiency is improved, and meanwhile the accuracy of the determined track is ensured.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and not to limit the invention. In the drawings:

FIG. 1a is a schematic diagram of rectangular grid positions in an intersecting relationship in two-dimensional space;

FIG. 1b is a flowchart of a method for determining a moving trajectory of an object in a multidimensional variable-granularity grid according to an embodiment of the present invention;

FIG. 1c is a schematic diagram of a two-dimensional grid constructed in accordance with an embodiment of the present invention;

FIG. 1d is a schematic diagram of a two-dimensional grid hierarchy based on FIG. 1 c;

FIG. 2 is a second flowchart of a method for determining a moving trajectory of an object in a multi-dimensional variable-granularity grid according to an embodiment of the present invention;

FIG. 3a is a flow chart of a third method for determining a moving trajectory of an object in a multi-dimensional variable-granularity grid according to an embodiment of the present invention;

FIG. 3b is a schematic diagram of two-dimensional trellis encoding after cross-encoding based on FIG. 1 c;

FIG. 4 is a flowchart illustrating a method for determining a moving trajectory of an object in a multidimensional variable-granularity grid according to an embodiment of the present invention;

FIG. 5 is a flow chart of a method for determining a moving trajectory of an object in a multidimensional variable-granularity grid according to an embodiment of the present invention;

FIG. 6a is a flowchart illustrating a method for determining a moving trajectory of an object in a multi-dimensional variable-granularity grid according to an embodiment of the present invention;

FIG. 6b is a flow diagram illustrating an exemplary trellis encoding implementation of binary cross-coding according to the present invention;

FIG. 6c is a diagram illustrating two-dimensional trellis encoded results according to an embodiment of the present invention;

FIG. 6d is a schematic diagram of grid positions of possible paths for a target object in accordance with an embodiment of the present invention;

FIG. 7a is a seventh flowchart of a method for determining a moving trajectory of an object in a multi-dimensional variable-granularity grid according to an embodiment of the present invention;

FIG. 7b is a schematic diagram of a two-dimensional grid position relationship associated with one embodiment of the present invention;

FIG. 8 is a flowchart illustrating the process of creating an index based on the mapping relationship between trellis codes and data identifiers according to an embodiment of the present invention;

FIG. 9 is a structural diagram of an apparatus for determining a moving trajectory of an object in a multi-dimensional variable-granularity grid according to an embodiment of the present invention;

FIG. 10a is a flowchart of a method for object navigation in a multi-dimensional variable-granularity grid of an object according to an embodiment of the present invention;

FIG. 10b is a flowchart illustrating a second method for object navigation in a multi-dimensional variable-granularity grid of an object according to an embodiment of the present invention;

FIG. 11 is a structural diagram of an object navigation device in a multi-dimensional variable-granularity grid according to an embodiment of the invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. The reference numbers in the present application are only used for distinguishing the steps in the scheme, and are not used for limiting the execution sequence of the steps, and the specific execution sequence is subject to the description in the specification.

In daily life, different objects move at different speeds and in different spatial dimensions. For example, the moving speed of a person is much lower than that of a satellite, and it is difficult to efficiently represent the moving trajectories of the person and the satellite in a multidimensional grid of the same size. In addition, the moving speeds of the same object in different dimensions can be greatly different. For example, during take-off, flight, landing, the movement track of the passenger aircraft relates to the longitudinal direction, the latitudinal direction and the elevation direction, but the movement speed in the longitudinal direction and the latitudinal direction is much greater than the movement speed in the elevation direction. If a grid with the same three-dimensional length is used to represent the moving track of a passenger plane, data redundancy in the longitudinal direction and the latitudinal direction or low accuracy in the elevation direction often occurs.

For the same object, when the moving speed difference of different dimensions is large, the moving track of the object can be represented by using a non-grid. The non-grid may refer to a grid having different unit lengths in different dimensions. Taking a two-dimensional space as an example, as shown in fig. 1a, the grid includes squares and non-squares. Such non-square grids may have overlapping and containing relationships due to different unit lengths in different dimensions, for example, a rectangular grid shown by oblique lines on the right side in fig. 1a is compared with a rectangular grid shown by oblique lines on the lower side in comparison with a square grid shown by oblique lines. This intersecting relationship makes it difficult to uniquely mark each grid in the non-grid and to efficiently and accurately characterize the movement trajectory of the object in the multidimensional space.

In order to solve the problems in the prior art, the embodiment of the application provides a method for determining an object movement track in a multi-dimensional variable-granularity grid, and relates to the fields of grid coding, spatial index, space-time index and the like. As shown in fig. 1b, the method comprises the following steps:

s11: and determining an N-dimensional grid containing the position of the target object, wherein N is an integer greater than 1, and the dimension corresponding to the N-dimensional grid comprises the movable dimension of the target object.

Each dimension of the N-dimensional grid may be used to represent different meanings, for example, a four-dimensional grid including a longitude dimension, a latitude dimension, an elevation dimension, and a time dimension. Additionally, dimensions for characterizing the state of the target object may also be included, such as a temperature dimension, a volume dimension, a density dimension, etc. of the target object. The dimension corresponding to the N-dimensional grid includes the dimension in which the target object is movable. For example, cruise ships tend to travel on the surface of water, and their movable dimensions may include longitude and latitude dimensions. In contrast, a satellite may move not only in a horizontal plane but also in an elevation dimension, and the movable dimension may include not only a longitude dimension and a latitude dimension but also an elevation dimension.

S12: and acquiring the unit granularity and the movement distance of the target object moving in each dimension corresponding to the N-dimensional grid, wherein the unit granularity of the target object moving in each dimension corresponding to the N-dimensional grid is determined by the speed of the target object moving in each dimension.

The speed of the target object moving in each dimension is often different, and the unit granularity may be the moving speed of the target object in a certain dimension, such as 1 meter per second or 1000 meters per minute. The above example is a unit particle size in units of time, and the unit particle size may have an attribute other than time as a unit, for example, 10 seconds per meter, 5 seconds per degree celsius, or the like. The units of the unit granularity are related to the meaning of the dimension characterization.

The moving distance includes a moving distance of the target object in a dimension, for example, in an elevation dimension, the moving distance may refer to a moving distance of the target object in an altitude direction. In the time dimension, the moving distance may refer to the time consumed by the target object in the moving process.

S13: determining the coding of a path grid of a target object in the N-dimensional grid, wherein the path grid comprises grids matched with unit granularity of movement and movement distance of the target object in each dimension, and the coding of the path grid is obtained by cross-fetching of multi-scale coding of each dimension corresponding to the N-dimensional grid.

At least one dimension grid of the N-dimension grid may include a plurality of levels, and in this embodiment, a two-dimension grid is taken as an example for description. Fig. 1c shows a two-dimensional grid, and the lower side of the grid and the right side of the grid show the coding results of coding the two-dimensional grid with different granularities. Fig. 1d shows the trellis encoding levels of any dimension, which is illustrated by taking 5 levels as an example in this example, and in practical applications, the number of levels may be more or less, and the 5 levels L are respectively represented by 0 to 4. Coding spans of different levels are different, and referring to fig. 1c, in a level of L =4, the lengths of the grids are all 1 unit length, and in a level of L =0, the lengths of the grids are all 16 unit lengths.

The approach mesh of the target object in the N-dimensional mesh determined in this step includes a mesh of a corresponding hierarchy that matches the unit granularity of movement of the target object. For example, for a target object with a slow moving speed, the mesh of the target object path may be determined according to the mesh in the L =4 level, and then the corresponding code of the path mesh may be determined. For the target object with a fast moving speed, the grid of the target object path can be determined according to the grid in the L =0 level. For a target object moving at varying speeds, the grid of the target object's path may also be determined based on the speed of the target object and from the grids in the multiple levels.

Optionally, in this embodiment, a corresponding level of the approach mesh in the target dimension, that is, a corresponding level matched with the unit granularity, is determined according to the unit granularity of the movement of the target object in the target dimension. And determining the code of the path mesh of the target object in the target dimension according to the moving distance of the target object in the target dimension.

S14: and determining the movement track of the target object according to the coding of the path grid of the target object in the N-dimensional grid.

In this embodiment, the movement trajectory of the target object may be characterized using one or more meshes. When the number of meshes of the target object path is plural, the path meshes may be sequentially connected according to the encoding of the target object path mesh to characterize the movement trajectory of the target object.

The embodiment of the application provides a coding method applied to a multi-dimensional variable-granularity grid, which can realize simultaneous coding of squares and non-squares so as to meet the requirement that the granularity of the grid is inconsistent in different dimensions. The method can be applied to longitude and latitude + elevation three-dimensional grids, can also be applied to scenes such as space-time integrated four-dimensional grids and the like, and is used for efficiently and accurately determining the moving track of the target object. The moving track can be used for recording the moving route of the moving object, such as a vehicle running track, an unmanned aerial vehicle flying track and the like. The method can also be applied to the field of machine learning, such as recording the moving track of the robot to compare the error of the planned route with the actual route. Or the method can be used for planning the air route of the airplane, ensuring the safe distance between different airplanes, avoiding the congestion of the air channel and the like.

According to the scheme provided by the embodiment of the application, the N-dimensional grid required by the position and the moving track of the target object is determined; determining a moving track of a target object in an N-dimensional grid space, decomposing the moving track into unit granularity and distance of movement in N dimensions, wherein the unit granularity and the distance can be used for identifying information of the target object in directions such as longitude, latitude, elevation and the like; matching unit granularity of the target object moving in each dimension with grids with proper granularity respectively, and accordingly determining grid levels with proper and different dimensions; establishing one-dimensional multi-scale codes of the target object on each dimension, and crossing the codes of the N dimensions to form N-dimensional variable-granularity grid codes, thereby determining the moving track of the target object according to the codes of the target object approach N-dimensional variable-granularity grid; and realizing the space navigation of the target object based on the identification and calculation of the N-dimensional variable-granularity grid code. According to the scheme, the hierarchy of the grid is determined according to the granularity matched with the moving distance of the target object in each dimension, so that a multi-dimensional variable-granularity grid structure and codes are formed to identify the moving track of the target object, data redundancy caused by the fact that the target object moves at a high speed in certain dimensions is avoided, the number of codes used for determining the moving track is reduced, the coding calculation efficiency is improved, and meanwhile the accuracy of the determined track is guaranteed.

Based on the solution provided by the foregoing embodiment, optionally, step S13, as shown in fig. 2, includes:

s21: and determining grids matched with the unit granularity and the movement distance of the target object moving in each dimension corresponding to the N-dimensional grids.

S22: and performing cross bit extraction on the multi-scale codes of all dimensions corresponding to the N-dimensional grids to obtain the N-dimensional variable-granularity grid codes.

S23: and determining the coding of the path grid of the target object in the N-dimensional grid according to the N-dimensional variable granularity grid coding.

Through the scheme provided by the embodiment of the application, the target object path grid can be represented by the multi-dimensional variable-granularity grid code, and the moving track of the target object can be further represented

Based on the solution provided by the foregoing embodiment, optionally, as shown in fig. 3a, step S22 includes:

s31: performing multi-scale coding on each dimension grid corresponding to the N dimension grids to obtain multi-scale codes of N single dimension grids, wherein the nth dimension grid in the N dimension grids is coded as a Code ⁿ (L ⁿ ，C ⁿ ) N is a positive integer not greater than N, L ⁿ For the level of the grid in the dimension to which it belongs, C ⁿ The grid coordinate of the grid in the dimension to which the grid belongs.

S32: and performing cross bit fetching on the multi-scale codes of the N single-dimension grids to obtain the N-dimension variable-granularity grid codes.

In the step of establishing the N-dimensional mesh, multi-scale encoding is performed on the mesh of each dimension. For example, an N-dimensional grid at eachGrid coordinate in dimension C ⁿ The corresponding level is L ⁿ . Wherein, the multi-scale coding on each dimension is expressed by adopting M bit unsigned integer.

According to the scheme provided by the embodiment of the application, each dimension grid in the N-dimension grid is formed by multi-scale codes, and in the moving process of the target object in the N-dimension grid, the moving track of the target object can be represented by the grid codes of corresponding levels matched with the moving unit granularity in any dimension, so that the moving track of the target object can be effectively expressed, the problem that the determined moving track is inaccurate due to overlarge granularity is avoided, the problem that data redundancy is caused due to undersize granularity is also avoided, and the moving track of the target object can be efficiently determined.

For the step S31, taking a two-dimensional grid as an example, the encoding result is shown in fig. 1c. Wherein, the multi-scale coding result of one dimension grid is shown below the grid, and the multi-scale coding result of the other dimension grid is shown on the right side of the grid.

Based on the coding rule shown in FIG. 1d, item L ⁿ The minimum trellis coding of the hierarchy is:

Code ⁿ (L ⁿ ，0)＝(1＜＜(M-1-L ⁿ ))-1

in the embodiment of this specification, < is a left shift operator, which is used to shift each binary bit of a number all to the left by a number of bits, the number of shifted bits being specified by the right operand, the left free bit being padded with 0.

L th ⁿ The adjacent trellis coding interval of the hierarchy is:

for a hierarchy and coordinates of (L) in the nth dimension ⁿ ，C ⁿ ) The corresponding multi-scale code of (a) is:

the formula is expressed in a binary form, and the following can be obtained:

Code ⁿ (L ⁿ ，C ⁿ )＝C ⁿ ＜＜(M-L ⁿ )+(1＜＜(M-1-L ⁿ ))-1 (1)

as to the above step S32, after encoding is performed on each dimension grid, cross encoding may be performed on the encoded two-dimension grids by using Mordon cross method, the cross encoding result based on fig. 1c is shown in fig. 3b, and fig. 3b shows the multi-scale encoding result for a plurality of grids shown by hatching with oblique lines.

Multi-scale encoding of Code in each dimension based on the N-dimensional mesh obtained in step S32 ⁿ (L ⁿ ，C ⁿ ) And n is a positive integer. Wherein, the special description is that: n levels of dimensional trellis coding L ¹ ，...，L ⁿ ，...，L ^N The level values of each dimension can be equal or unequal, namely the ratio between the granularities of the N dimension grids is not fixed and is variable, which is the core and the basis for constructing the N dimension variable-granularity grid coding.

Based on the solution provided by the foregoing embodiment, optionally, step S31, as shown in fig. 4, includes:

s41: performing multi-scale coding on the nth dimension grid in the N dimension grids, wherein the length of the multi-scale coding of the nth dimension is M, and the level L of the multi-scale coding of the nth dimension is ⁿ Is an integer, said L ⁿ Has a value range of [0, M-1 ]]The multi-scale coding of the nth dimension is in L ⁿ Grid coordinate C of the hierarchy ⁿ Is an integer, said C ⁿ Has a value range of

Multi-scale encoding of nth dimension to binary encoding

Wherein the content of the first and second substances,

or i is more than or equal to 1,1 and less than or equal to M.

In the single-dimension multi-scale coding method, the length of the n-dimension multi-scale coding is M bits, wherein 1bit is used for describing the level L where the one-dimensional grid coding is positioned ⁿ Thus, L ⁿ Has a value range of [0, M-1 ]]That is, the mesh with the largest granularity is located at the level 0, and the mesh with the smallest granularity is located at the level (M-1). For example, referring to fig. 1c and fig. 1d, the mesh with the largest granularity is the encoding 15 mesh, and is located at the level 0; the mesh with the largest granularity is the

encoding

0, 2 and 4. Grid coordinate C ⁿ Is an integer having a value range of

According to the scheme provided by the embodiment of the application, the grid is coded by the binary code, so that the grid code can be efficiently calculated and processed through the electronic equipment, and the efficiency of determining the moving track is improved.

Based on the solution provided by the foregoing embodiment, optionally, as shown in fig. 5, step S21 includes:

s51: determining the level { L) of the multi-scale code of each dimension corresponding to the target object approach grid according to the unit granularity and the moving distance of the target object moving in each dimension corresponding to the N-dimensional grid ¹ ，L ² ，...，L ^N }；

S52: the level { L) of the multi-scale coding according to each dimension of the path grid of the target object ¹ ，L ² ，...，L ^N And determining grids matched with the unit granularity and the moving distance of the target object moving in each dimension corresponding to the N-dimensional grids.

Optionally, based on the solution provided by the foregoing embodiment, as shown in fig. 6, the foregoing step S22 includes:

s61: the binary system of each dimension corresponding to the N-dimensional gridEncoding and executing Mordon intersection to obtain the Mordon intersection result of the N-dimensional variable-granularity grid after multi-scale encoding

Wherein the content of the first and second substances,

characterizing bit-wise cross coding;

s62: determining the multi-scale coded N-dimensional variable granularity grid coding according to the Mordon intersection result of the N-dimensional grid:

specifically, the multi-scale coding of the nth dimension is represented by a binary code with a length of M bits, and the high bits thereof are filled with 0, as shown in fig. 6b, the following expression can be obtained:

wherein, the first and the second end of the pipe are connected with each other,

or i is more than or equal to 1,1 and less than or equal to M.

Then, morton crossing is performed on the N binary one-dimensional multi-scale codes, and referring to fig. 6b, an N-dimensional variable-granularity trellis code (L) can be obtained ¹ ，L ² ，...，L ^N ；C ¹ ，C ² ，...，C ^N ) As shown in the following formula:

in the above formula

Representing bitwise cross coding, obtained in combination with equation (2) above:

finally, a binary unsigned integer with the length of N multiplied by M bits is obtained and used for representing N-dimensional grid coding, and the coding not only comprises grid coordinate information of an N-dimensional space, but also comprises coding level information on each dimension. This coding hierarchy can be used in subsequent steps to determine a corresponding hierarchy that matches the unit granularity of movement of the target object, and thus determine the trellis coding of the target object's path.

In addition, based on the encoding process, the process may be inverse transformed to obtain a decoding process corresponding to the encoding.

By using the scheme provided by the embodiment of the present application, taking M =4 as an example, the encoding result is shown in fig. 6 c. The result of the encoding of the different hierarchical meshes in the two-dimensional mesh is shown in fig. 6 c. Wherein the first row and the first column (upper left in fig. 6 c) illustrate the coding results for the lateral dimension and the longitudinal dimension L =3, the first row and the second column illustrate the coding results for the lateral dimension L =3 and the longitudinal dimension L =2, the first row and the third column illustrate the coding results for the lateral dimension L =3 and the longitudinal dimension L =1, the first row and the fourth column (upper right in fig. 6 c) illustrate the coding results for the lateral dimension L =3 and the longitudinal dimension L =0, and so on.

The embodiment of the application takes a two-dimensional plane space variable-granularity rectangular grid as an example, and elaborates the variable-granularity grid coding and decoding process and the coding calculation method in detail. The two-dimensional variable-granularity grid is identified by adopting an unsigned integer of 2M bits, and the number of grid coding bits in each dimension is M.

Based on the result shown in fig. 6c, in the subsequent step S13, assuming that the unit granularity of movement of the target object in the transverse dimension is 1 and the unit granularity of movement of the target object in the longitudinal dimension is 2, then the grid of possible paths of the target object is as shown in fig. 6 d. Wherein, C ¹ The abscissa representing the grid, i.e. the grid coordinate of the transverse dimension, C ² A grid coordinate representing a vertical dimension of the grid; l is ¹ Represents the trellis code at C ¹ Hierarchical value of direction, L ² Representing trellis codes at C ² The hierarchy number of directions.

According to the scheme provided by the embodiment of the application, variable-granularity coding can be executed on the multi-dimensional grid, the moving track of the target object can be represented by corresponding hierarchical grid coding according to the unit granularity of the target object in different dimensions, the condition that the determined moving track is inaccurate or data redundancy is avoided due to overlarge granularity or undersize granularity is avoided, and the moving track of the target object can be determined efficiently and accurately.

To further illustrate the present solution, the following describes a process of trellis encoding and decoding, which can be used to improve the determination efficiency of the motion trajectory. The encoding and decoding calculation process provided by the embodiment is executed by adopting bit operation or addition and subtraction operation, so that the execution efficiency of the grid encoding and decoding is effectively improved.

(1) Encoding process

If a certain two-dimensional variable-granularity grid (L) is known ¹ ，L ² ；C ¹ ，C ² ) The two-dimensional variable-granularity trellis code value 2DCode corresponding to the trellis can be calculated according to the formulas (1), (2) and (3), and the code generation algorithm is shown in table 1. According to the code generation algorithm, the code values of all the two-dimensional variable-granularity grids in fig. 6c can be calculated.

TABLE 1 two-dimensional variable-granularity trellis code generation algorithm

(2) Decoding process

If a two-dimensional variable-granularity grid code 2Dcode is known, the horizontal and vertical coordinates and the level information corresponding to the grid can be calculated according to the inverse operation of the formulas (1), (2) and (3), and the decoding algorithm is shown in table 2.

TABLE 2 decoding algorithm for two-dimensional variable granularity trellis coding

Wherein Algorithm 3 represents a one-dimensional spatial multi-scale trellis-coded Code ⁿ The hierarchy of (2) is obtained as shown in the table.

TABLE 3 hierarchical acquisition algorithm for one-dimensional space multi-scale trellis coding

Based on the solution provided by the foregoing embodiment, optionally, as shown in fig. 7a, before the foregoing step S14, the method further includes:

s71: determining an encoding of a mesh associated with the pathway mesh, wherein the mesh associated with the pathway mesh comprises at least one of: a parent cell mesh of the pathway mesh, a child cell mesh of the pathway mesh, a neighborhood cell mesh of the pathway mesh, an intersecting cell mesh of the pathway mesh;

wherein, the step S14 includes:

s72: and determining the movement track of the target object according to the coding of the path grid of the target object in the N-dimensional grid and the coding of the grid associated with the path grid.

Parent-child grids and adjacent grids in the scheme provided by the embodiment of the application can be used for assisting in determining the track, so that the precision of the moving track is improved, and the track can be more coherent. In addition, the relationship between the trajectory and the trajectory, the relationship between the trajectory and the area, the relationship between the trajectory and the point, and the like may also be determined using the grids associated with the above-described approach grids. The parent cell grid, the child cell grid, the neighborhood cell grid, and the intersecting cell grid are explained below.

(1) Parent cell trellis coded computation

If the two-dimensional variable-granularity trellis coding 2DCode is known, the algorithm 2 (decoding algorithm) in the above embodiment can be used to obtain the corresponding trellis coordinate and level information (L) ¹ ，L ² ；C ¹ ，C ² ). Let the desired parent cell trellis code be Fa2DCode, which corresponds to the hierarchy information

Wherein

And is

The parent cell trellis encoding calculation includes:

performing reverse Morton crossover on the 2DCode by using an algorithm 2 to obtain multi-scale codes on each dimension, namely codes ¹ And Code ² ；

Calculating the parent code of the multi-scale code on each dimension according to the following formula, and respectively marking as FaCode ¹ And FaCode ² N =1,2 in the following formula;

as shown in the following equation, the parent codes in each dimension are Morton interleaved to obtain Fa2DCode.

(2) Sub-cell trellis coded computation

If two-dimensional variable-granularity grid is knownThe encoding 2DCode uses the algorithm 2 to obtain the corresponding level information and grid coordinate (L) ¹ ，L ² ；C ¹ ，C ² ). Setting the desired sub-unit trellis code set as Son2DCodeset at the level

Wherein

And is

The step of calculating the sub-unit grid coding comprises the following steps:

performing reverse Morton crossing on the 2DCode by using an algorithm 2 to obtain multi-scale codes on each dimension, namely the codes ¹ And Code ² ；

Calculating the sub-coding set of multi-scale coding on each dimension by using the following formula, and respectively recording the sub-coding set as SonSet ¹ And SonSet ² Corresponding to the number of subcodes of Q ¹ And Q ² N =1,2 in the following formula;

as shown in the following formula, monton crossing is performed on the sub-codes in the two sub-code sets to obtain Son2DCodeSet.

(3) Neighborhood cell trellis coded computation

The computation involves four/eight neighborhood cells at the same level as the known coded 2DCode, whose steps of trellis-coded computation include:

by usingAlgorithm 2 decodes 2DCode to obtain corresponding hierarchical information and grid coordinates (L) ¹ ，L ² ；C ¹ ，C ² )；

The grid coordinate set of the four neighborhood units is { (C) ¹ (i)，C ² (i))，1≤i≤4}＝{(C ¹ ，C ² +1)，(C ¹ +1，C ² )，(C ¹ ，C ² -1)，(C ¹ -1，C ² )}；

The grid coordinate set of the eight neighborhood units is { (C) ¹ (i)，C ² (i))，1≤i≤8}＝{(C ¹ -1，C ² +1)，(C ¹ ，C ² +1)，(C ¹ +1，C ² +1)，(C ¹ +1，C ² )，(C ¹ +1，C ² -1)，(C ¹ ，C ² -1)，(C ¹ -1，C ² -1)，(C ¹ -1，C ² )}；

Grid coordinates which do not accord with the following conditions in the grid coordinate set of the four/eight neighborhood units are removed;

and (3) obtaining a four/eight neighborhood unit grid coding set by utilizing the remaining four/eight neighborhood unit grid coordinates and an algorithm 1 (a two-dimensional variable granularity grid coding algorithm).

(4) Cross cell trellis coding computation

If the two-dimensional variable-granularity grid code 2DCode is known, the corresponding grid coordinate and level information can be obtained as (L) by using the algorithm 2 ¹ ，L ² ；C ¹ ，C ² ). Setting the intersected unit grid coding set with 2DCode as an IntersectSet, wherein the calculation step comprises the following steps:

Computing Code using parent cell trellis Code computation method ⁿ (n =1, 2) of a mesh of all parent cells constituting a set of codes of the parent cells ofFaSet ⁿ (n =1,2); if L is ⁿ Set Faset > 0 ⁿ Containing a code number of

Parent coding level range of [0, L ⁿ -1](ii) a If L is ⁿ ＝0，

And is

Computing Code using a subcell trellis Code computation method ⁿ (n =1, 2) and the sub-unit encoding set is SonSet ⁿ (n =1,2); if L is ⁿ < (M-1), set SonSet ⁿ Containing a code number of

Coding level range of [ L ] ⁿ +1，M-1](ii) a If L is ⁿ ＝(M-1)，

And is provided with

And as shown in the following formula, performing Morton intersection on the child code of one dimension and the parent code of the other dimension, and finally obtaining a union set to obtain the IntersectSet.

In addition to the grids associated by the approach grids provided in the above embodiments, the movement trajectory may also be assisted to be generated according to the grid spatial relationship. Or, the method is used for judging the spatial position relation between the moving track and the specific area.

(5) Grid spatial relationship determination

The grid space relation judging method can be used for judging the space relation between two grids corresponding to the codes. In a two-dimensional multi-granularity grid space, the spatial relationship between every two grids is mainly divided into 6 types: separated, adjacent, contained, equal, and intersecting as shown in fig. 7 b.

In the one-dimensional multi-scale grid space, the spatial relationship between every two grids is mainly divided into 5 types: separated, adjacent, containing, contained, and equal. In the nth dimension space, let the known multi-scale coding of two one-dimensional grids be

And

spatial relationship between two corresponding grids

Denotes, rel ⁿ Values may be taken as 0, 1,2, 3, and 4, indicating separated, adjacent, included, and equal, respectively. Rel ⁿ The calculation steps of (2) are as follows:

if it is

Then Rel ⁿ =4, and go to step (7); if not, turning to the step (2);

calculation by Algorithm 3

Hierarchy of (1)

If it is

Turning to the step (3); if not, turning to the step (4);

if it is

Then Rel ⁿ =1, otherwise Rel ⁿ =0, andturning to the step (7);

computing

And calculating using equation (4)

In that

Hierarchical parent cell coding

If it is

Turning to the step (5); if not, turning to the step (6);

if it is

Then Rel ⁿ =2, otherwise Rel ⁿ =3, and go to step (7);

when in use

When the method is used: calculating using equation (5)

In that

Sub-intervals of a hierarchy

If it is

Then Rel ⁿ =1, otherwise Rel ⁿ =0, and go to step (7); when in use

The method comprises the following steps: calculation by equation (5)

In that

Sub-intervals of a hierarchy

If it is

Then Rel ⁿ =1, otherwise Rel ⁿ =0, and go to step (7);

output of

The value of (c).

Let known two-dimensional variable-granularity trellis codes be 2DCode respectively _A And 2DCode _B Rel (2 DCode) for spatial relationship between the two corresponding grids _A ，2DCode _B ) By which Rel may take the

values

0, 1,2, 3, 4, and 5, which are respectively meant separated, adjacent, contained, equal, and intersecting. Rel was calculated as follows:

if 2DCode _A ＝2DCode _B If Rel =4, and the step (8) is carried out; if not, executing the steps (2) to (7);

utilizing Algorithm 2-to-2 DCode _A And 2DCode _B Performing reverse Morton crossing to obtain multi-scale codes on each dimension, wherein the codes are respectively

And

and

using Rel as described above ⁿ Method of calculating, respectively calculating

A value of (d);

when Rel ¹ Or Rel ² If =0, rel =0, and go to step (8);

when Rel ¹ =1 and Rel ² Not equal to 0, or Rel ¹ Not equal to 0 and Rel ² If =1, rel =1, and go to step (8);

when Rel ¹ ＝Rel ² =2, or Rel ¹ =2 and Rel ² =4, or Rel ¹ =4 and Rel ² If =2, rel =2, and go to step (8);

when Rel ¹ ＝Rel ² =3, or Rel ¹ =3 and Rel ² =4, or Rel ¹ =4 and Rel ² If =3, rel =3, and go to step (8);

when Rel ¹ =2 and Rel ² =3, or Rel ¹ =3 and Rel ² If =2, rel =5, and go to step (8);

output Rel (2 DCode) _A ，2DCode _B ) The value of (c).

Based on the solutions provided in the foregoing embodiments, the present application further provides an index and query method for trellis coding in any of the foregoing embodiments. For convenience of illustration, the present embodiment is still illustrated by taking two-dimensional trellis coding as an example.

The following explains the indexing method of trellis coding:

firstly, data with the same space/space-time dimension are associated by using multi-dimensional variable-granularity grid codes, a mapping relation between data identification and codes is established, then the codes are combined with common one-dimensional indexes (such as a B + tree, a red-black tree, a hash table, a skip table and the like) to establish a code index of the data, and finally the multi-dimensional space/space-time index of the data can be converted into the one-dimensional code index, so that the index efficiency of the data is improved.

It should be noted that, in the same code index, the managed data objects have the same spatial/spatiotemporal dimension. When the dimension N =2, for example, two-dimensional space or latitude and longitude space points, lines, planar data; when the dimension N =3, for example, true three-dimensional spatial data, spatial data of longitude and latitude + elevation dimension, and spatiotemporal data of longitude and latitude + time dimension; when dimension N =4, for example, spatio-temporal data of three-dimensional space + time dimension.

Let a known set of data be DataSet, with its corresponding dimension being N, and the multi-scale coding in each dimension being represented by M-bit unsigned integers. The step of establishing the code index comprises the following steps:

(1) A mapping relationship between the data identifier and the code is established, as shown in (a) of fig. 8. This step is used to associate each data object DataSet (i) in the DataSet with multidimensional variable-granularity trellis coding, and is implemented as follows:

determining the lth dimension of DataSet (i) in the nth (N =1,2 ⁿ (0≤L ⁿ Grid coordinate range less than or equal to M-1) level

Calculated using equation (1)

And

corresponding multi-scale coding

And

if it is

Then get

Otherwise, calculate the sum using equation (4)

And

first common parent cell encoding

I.e. the parent cell encoding level

And L ⁿ The difference of (a) is minimal;

obtaining a grid coding set corresponding to the coverage range of the DataSet (i) on each dimension

And counting the minimum and maximum values of the levels where all DataSet (i) associated codes are positioned

And (3) calculating to obtain an N-dimensional variable-granularity grid code (NDcode) by using a formula (3), and identifying the range covered by the DataSet (i) in the N-dimensional space/time air, so that the association between the data identification ID (i) of the DataSet (i) and the NDcode is realized.

(2) Constructing a coding index table, wherein a first column of the coding index table is a multidimensional variable-granularity grid coding NDcode, and a second column of the coding index table is an ID set formed by a plurality of IDs (i) corresponding to the same NDcode, as shown in (b) in FIG. 8; secondly, combining the NDcode coding column with common one-dimensional indexes (such as a B + tree, a red-black tree, a hash table and a skip table) to establish a one-dimensional coding index, thereby realizing the index of the N-dimensional space/space-time data.

The following sets forth a trellis-coded query method:

firstly, gridding a query area to obtain a corresponding multi-dimensional variable-granularity grid code set S, then querying and extracting codes which are intersected with S and have mutual inclusion relation and corresponding data identifications in a code index table established by the scheme by using the code calculation method and a common one-dimensional index searching method, and finally obtaining a data query result in a query area range. The query method is realized by the following steps:

(1) The query region is gridded. Specifically, a step-by-step recursive division method can be adopted to grid the N-dimensional space/space-time query region, so that a grid result of the query region in the N-dimensional space/space-time is obtained, and a corresponding multi-dimensional variable-granularity grid coding set is set as S.

(2) And calculating codes which have intersection and mutual inclusion relation with S. According to the statistical result in the process of coding index establishment

By utilizing the multi-dimensional variable-granularity grid coding calculation method of the scheme, all codes in the set S are calculated

And (4) carrying out grid coding on the parent unit, the child unit and the intersected unit in the hierarchy range, wherein the coding set formed by the calculation result is SA.

(3) And querying in the coding index table to obtain a data query result. Based on a search method of a common one-dimensional index (e.g., a B + tree, a red-black tree, a hash table, a skip table, etc.), in the NDCode code column shown in (B) of fig. 8, all codes belonging to an SA set are searched, and a set formed by the codes is SOutCode; in the query process, all data identifiers corresponding to all codes in SOutCode are extracted from the ID set column shown in (b) in fig. 8 at the same time, and the set formed by the data identifiers is set as SOutID, so that a data query result in the query area range is obtained.

In addition, on the basis of the N-dimensional space/space-time query result, the more complex data comprehensive query function can be realized by combining various attribute query operations of the data.

By the scheme provided by the embodiment of the application, multi-dimensional variable-granularity grid coding can be realized, and the moving track of the target object can be efficiently and accurately determined. In addition, encoding and decoding can be performed on the trellis codes, and indexing and querying can also be performed on the trellis codes. In addition, the accuracy of the determined movement track can be further improved by using the target object approach grid association grid.

According to the scheme provided by the embodiment of the application, the grids of the target object path are represented by the grids of the corresponding levels matched with the unit granularity of the movement of the target object, and then the codes of the grids of the target object path are determined, so that the problem of inaccuracy or easiness in data caused by overlarge or undersize granularity can be solved, the movement track can be represented by squares and non-squares at the same time, and the requirement difference of the granularity of the grids in different dimensions can be met.

In addition, in the step of encoding and decoding the grids, only integer addition and subtraction and binary bit operation are needed, and the execution efficiency can be effectively improved. Moreover, the scheme is suitable for various multi-dimensional application scenes, can be widely applied to high-dimensional grids such as longitude and latitude + elevation three-dimensional grids, space-time integrated four-dimensional grids and the like,

in order to solve the problems in the prior art, an embodiment of the present application further provides an apparatus 90 for determining a moving trajectory of an object in a multidimensional variable-granularity grid, as shown in fig. 9, including:

the first determining module 91 determines an N-dimensional grid including a position of a target object, where N is an integer greater than 1, and a dimension corresponding to the N-dimensional grid includes a dimension in which the target object is movable;

a first obtaining module 92, configured to obtain a unit granularity and a moving distance of the target object moving in each dimension corresponding to the N-dimensional grid, where the unit granularity of the target object moving in each dimension corresponding to the N-dimensional grid is determined by a speed at which the target object moves in each dimension;

a second determining module 93, configured to determine a code of a path mesh of the target object in the N-dimensional mesh, where the path mesh includes a mesh with a unit granularity of movement of the target object in each dimension and a movement distance that are matched, and the code of the path mesh is obtained by cross-fetching a multi-scale code of each dimension corresponding to the N-dimensional mesh;

and a third determining module 94 for determining the moving track of the target object according to the coding of the path mesh of the target object in the N-dimensional mesh.

According to the scheme provided by the embodiment of the application, an N-dimensional grid containing the position of a target object is determined; acquiring unit granularity and moving distance of the target object moving in each dimension corresponding to the N-dimensional grid; determining an encoding of a path mesh of the target object in the N-dimensional mesh; and determining the movement track of the target object according to the coding of the path mesh of the target object in the N-dimensional mesh. According to the scheme, the hierarchy of the grid is determined according to the granularity matched with the moving distance of the target object in each dimension, so that a multi-dimensional variable-granularity grid structure and codes are formed to identify the moving track of the target object, data redundancy caused by the fact that the target object moves at a high speed in certain dimensions is avoided, the number of codes used for determining the moving track is reduced, the coding calculation efficiency is improved, and meanwhile the accuracy of the determined track is guaranteed.

By the device provided by the scheme, the N-dimensional grid required by the position and the moving track of the target object is determined; determining a moving track of a target object in an N-dimensional grid space, decomposing the moving track into unit granularity and distance of movement in N dimensions, wherein the unit granularity and the distance can be used for identifying information of the target object in directions such as longitude, latitude, elevation and the like; matching unit granularity of the target object moving in each dimension with grids with proper granularity respectively, and accordingly determining grid levels with proper and different dimensions; establishing one-dimensional multi-scale codes of the target object on each dimension, and crossing the codes of the N dimensions to form N-dimensional variable-granularity grid codes, thereby determining the moving track of the target object according to the codes of the target object passing through the N-dimensional variable-granularity grid; and realizing the space navigation of the target object based on the identification and calculation of the N-dimensional variable-granularity grid code. According to the scheme, the hierarchy of the grid is determined according to the granularity matched with the moving distance of the target object in each dimension, so that a multi-dimensional variable-granularity grid structure and codes are formed to identify the moving track of the target object, data redundancy caused by the fact that the target object moves at a high speed in certain dimensions is avoided, the number of codes used for determining the moving track is reduced, the coding calculation efficiency is improved, and meanwhile the accuracy of the determined track is ensured.

In order to solve the problems in the prior art, an embodiment of the present application further provides a method for navigating an object in a multidimensional variable-granularity grid, as shown in fig. 10a, including:

s101: determining an N-dimensional grid containing the position of a target object and a navigation end position, wherein N is an integer greater than 1, and the corresponding dimension of the N-dimensional grid comprises the movable dimension of the target object;

s102: acquiring unit granularity and moving distance of the target object moving in each dimension corresponding to the N-dimensional grid, wherein the unit granularity of the target object moving in each dimension corresponding to the N-dimensional grid is determined by the speed of the target object moving in each dimension;

s103: determining the coding of a path grid of the target object in the N-dimensional grid, wherein the path grid comprises grids matched with unit granularity of movement and movement distance of the target object in each dimension, and the coding of the path grid is obtained by cross-positioning of multi-scale coding of each dimension corresponding to the N-dimensional grid;

s104: determining the movement track of the target object according to the coding of the path mesh of the target object in the N-dimensional mesh;

s105: and generating a navigation route according to the movement track and the navigation end point position.

In the solution provided in the embodiment of the present application, the specific implementation of steps S101 to S104 may be as described in steps S11 to S14 of the above embodiment. In step S101, the navigation end point position may be specifically a coordinate point or may be an area. After the movement track of the target object is determined in step S104, the relative position relationship between the position of the target object and the end point position may be determined according to the movement track of the target object, and an optimal navigation route moving from the position of the target object to the navigation end point position may be generated based on the movement track of the target object. In the step of generating the navigation route, the navigation route may be generated based on a moving direction in the moving trajectory of the target object to improve quality of generating the navigation route.

According to the scheme, the moving track of the target object is determined according to the hierarchical grid matched with the unit granularity of the moving of the target object, so that data redundancy caused by high moving speed of the target object is avoided, and the efficiency is improved. Meanwhile, the accuracy of the determined movement track is ensured, and errors are reduced.

Based on the solution provided by the foregoing embodiment, optionally, as shown in fig. 10b, before step S105, the method further includes:

s106: and acquiring the movement track of an obstacle object except the target object, wherein the movement track of the obstacle object is determined according to the code of the path grid of the obstacle object in the N-dimensional grid.

Wherein, the step S105 includes:

s107: and generating a navigation route according to the moving track of the target object, the moving track of the obstacle object and the navigation end position.

In some application scenes, the target object is often influenced by obstacles in the moving process, and the obstacles need to be avoided to reach the navigation end position. In the embodiment, the movement track of the obstacle is determined according to the codes of the grids of the obstacle path, so that the movement track of the target object for avoiding the obstacle can be planned and determined according to the movement track of the obstacle, the target object is prevented from colliding with the obstacle in the process of moving to the navigation end point position, and the generated navigation route is optimized.

In order to solve the problems in the prior art, an embodiment of the present application further provides an object navigation apparatus 110 in a multidimensional variable-granularity grid, as shown in fig. 11, including:

a fourth determining module 111, configured to determine an N-dimensional grid including a position of a target object and a navigation end position, where N is an integer greater than 1, and a dimension corresponding to the N-dimensional grid includes a dimension in which the target object is movable;

a second obtaining module 112, configured to obtain a unit granularity and a moving distance of the target object moving in each dimension corresponding to the N-dimensional grid, where the unit granularity of the target object moving in each dimension corresponding to the N-dimensional grid is determined by a speed at which the target object moves in each dimension;

a fifth determining module 113, configured to determine an encoding of a path mesh of the target object in the N-dimensional mesh, where the path mesh includes a mesh with a unit granularity of movement of the target object in each dimension and a movement distance that are matched, and the encoding of the path mesh is obtained by cross-fetching multi-scale encoding of each dimension corresponding to the N-dimensional mesh;

a sixth determining module 114, configured to determine a moving trajectory of the target object according to the coding of the path mesh of the target object in the N-dimensional mesh;

and the generating module 115 generates a navigation route according to the movement track and the navigation end position.

By the device provided by the embodiment of the application, the N-dimensional grid containing the position of the target object is determined; acquiring unit granularity and moving distance of the target object moving in each dimension corresponding to the N-dimensional grid; determining an encoding of a path mesh of the target object in the N-dimensional mesh; and determining the movement track of the target object according to the coding of the path mesh of the target object in the N-dimensional mesh. According to the scheme, the hierarchy of the grid is determined according to the granularity matched with the moving distance of the target object in each dimension, so that a multi-dimensional variable-granularity grid structure and codes are formed to identify the moving track of the target object, data redundancy caused by the fact that the target object moves at a high speed in certain dimensions is avoided, the number of codes used for determining the moving track is reduced, the coding calculation efficiency is improved, and meanwhile the accuracy of the determined track is ensured.

In addition, when an obstacle exists in the space, the scheme provided by the embodiment can also avoid the collision between the target object and the obstacle, generate the navigation route for avoiding the obstacle, and further improve the quality of the navigation route

Preferably, an embodiment of the present invention further provides an electronic device, which includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, where the computer program is executed by the processor to implement the processes of the method for determining an object movement trajectory and navigating in a multi-dimensional variable-granularity grid, and can achieve the same technical effects, and in order to avoid repetition, the details are not repeated here.

An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the method for determining a moving track of an object and navigating in a multi-dimensional variable-granularity grid, and can achieve the same technical effect, and in order to avoid repetition, the details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a component of' 8230; \8230;" does not exclude the presence of another like element in a process, method, article, or apparatus that comprises the element.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.

While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims

1. A method for determining the moving track of an object in a multi-dimensional variable-granularity grid is characterized by comprising the following steps:

determining an N-dimensional grid containing the position of a target object, wherein N is an integer greater than 1, and the dimension corresponding to the N-dimensional grid comprises the movable dimension of the target object;

wherein determining the encoding of the pathway mesh of the target object in the N-dimensional mesh comprises:

determining grids matched with unit granularity and movement distance of the target object moving in each dimension corresponding to the N-dimensional grids;

performing cross bit extraction on the multi-scale codes of all dimensions corresponding to the N-dimensional grids to obtain N-dimensional variable-granularity grid codes;

determining the coding of a path grid of a target object in the N-dimensional grid according to the N-dimensional variable-granularity grid coding;

wherein, the performing cross bit extraction on the multi-scale codes of each dimension corresponding to the N-dimensional grid to obtain the N-dimensional variable granularity grid code comprises:

performing multi-scale coding on each dimension grid corresponding to the N dimension grids to obtain multi-scale codes of N single dimension grids, wherein the nth dimension grid in the N dimension grids is coded as a Code ⁿ (L ⁿ ,C ⁿ ) N is a positive integer not greater than N, L ⁿ For the level of the grid in the dimension to which it belongs, C ⁿ Grid coordinates of the grid in the dimension to which the grid belongs;

performing cross bit extraction on the multi-scale codes of the N single-dimensional grids to obtain N-dimensional variable-granularity grid codes;

wherein performing multi-scale encoding on each dimension grid corresponding to the N-dimension grid comprises:

performing multi-scale coding on the nth dimension grid in the N dimension grids, wherein the length of the multi-scale coding of the nth dimension is M, and the level L of the multi-scale coding of the nth dimension is located ⁿ Is an integer of L ⁿ Has a value range of [0, M-1 ]]The multi-scale coding of the nth dimension is in L ⁿ Grid coordinate C of the hierarchy ⁿ Is an integer of said C ⁿ Has a value range of

The n-th dimension of the integer, to binary coding

Wherein the content of the first and second substances,

or i is more than or equal to 1,1 and less than or equal to M;

determining a grid matched with the unit granularity and the movement distance of the target object moving in each dimension corresponding to the N-dimensional grid, wherein the determining comprises the following steps of:

determining the level { L) of the multi-scale code of each dimension corresponding to the target object approach grid according to the unit granularity and the moving distance of the target object moving in each dimension corresponding to the N-dimensional grid ¹ ,L ² ,…,L ^N } of whichOf (C) { L ] ¹ ,L ² ,…,L ^N Any element in the data is a level where the multi-scale coding of the target object in the nth dimension approach grid is located;

according to the level { L) of the multi-scale coding of each dimension corresponding to the target object approach grid ¹ ,L ² ,…,L ^N Determining grids matched with unit granularity and movement distance of the target object moving in each dimension corresponding to the N-dimensional grids;

wherein, the multi-scale coding of N single-dimension grids is executed with cross bit extraction to obtain N dimension variable-granularity grid coding, which comprises:

performing Mordon intersection on the binary codes of all dimensions corresponding to the N-dimensional grids to obtain Mordon intersection results of the N-dimensional variable-granularity grids subjected to multi-scale coding

Wherein the content of the first and second substances,

characterizing bit-wise cross coding;

determining the multi-scale coded N-dimensional variable granularity grid coding according to the Mordon intersection result of the N-dimensional grid:

2. the method of claim 1, further comprising, prior to determining the movement trajectory of the target object based on the encoding of the approach mesh of the target object in the N-dimensional mesh:

determining an encoding of a mesh associated with the pathway mesh, wherein the mesh associated with the pathway mesh comprises at least one of: a parent cell mesh of the pathway mesh, a child cell mesh of the pathway mesh, a neighborhood cell mesh of the pathway mesh, an intersecting cell mesh of the pathway mesh;

wherein determining the movement trajectory of the target object according to the encoding of the approach mesh of the target object in the N-dimensional mesh comprises:

and determining the movement track of the target object according to the coding of the path grid of the target object in the N-dimensional grid and the coding of the grid associated with the path grid.

3. A movement track determining apparatus based on the method for determining movement track of object in multi-dimensional variable-granularity grid according to claim 1, comprising:

and the third determining module is used for determining the movement track of the target object according to the coding of the path mesh of the target object in the N-dimensional mesh.

4. A method for object navigation based on the method for determining an object movement trajectory in a multi-dimensional variable-granularity grid according to claim 1, comprising:

5. The method of claim 4, further comprising, prior to generating a navigation route from the movement trajectory and the navigation end position:

obtaining the movement track of an obstacle object except the target object, wherein the movement track of the obstacle object is determined according to the coding of a path grid of the obstacle object in the N-dimensional grid;

generating a navigation route according to the movement track and the navigation end position, wherein the method comprises the following steps:

and generating a navigation route according to the moving track of the target object, the moving track of the obstacle object and the navigation end position.