WO2020019162A1

WO2020019162A1 - Map data reconstruction method and apparatus thereof, and recording medium

Info

Publication number: WO2020019162A1
Application number: PCT/CN2018/096830
Authority: WO
Inventors: 吴博; 刘昂
Original assignee: 深圳市大疆创新科技有限公司
Priority date: 2018-07-24
Filing date: 2018-07-24
Publication date: 2020-01-30
Also published as: CN110869921A

Abstract

The present invention provides a map data reconstruction, query, and utilization method and an apparatus thereof, and a recording medium. The map data is multilevel map data constituted in a mode that at least one superior unit comprises multiple subordinate units. The map data reconstruction method comprises: from the multilevel map data, reading multiple map data units by taking the unit size of the subordinate unit as the size of the map data units; and generating single level map data constituted only by the multiple map data units according to the read map data units, the positions of the map data units in the multilevel map data being consistent with the positions in the single level map data.

Description

Map data reconstruction method, device and recording medium

Technical field

The present disclosure relates to a method, a device, and a recording medium for reconstructing, querying, and utilizing map data, and in particular, a method, a device, and a recording medium for reconstructing, querying, and utilizing map data.

Background technique

With the rapid development of robot (for example, self-propelled devices such as drones, self-driving cars, and self-propelled robots), the requirements for navigation technology, that is, map data processing, have become higher and higher.

Among them, for self-propelled devices such as drones, it is often necessary to quickly query map data to determine the current feasible area of the device and / or instruct the device to avoid obstacles. In this way, complex navigation tasks or complex navigation environments need to query the map data at a higher frequency, and it is important to be able to query the map data efficiently.

However, the existing map data is expressed in various forms. Among them, multi-level map data such as octomap, 2.5D elevation map, multi-level map, etc., although it is beneficial to save and / or update map data, The structure of multi-level map data is not conducive to querying the map data, and may even lead to a significant reduction in map query efficiency, such as limiting the use frequency of path planning.

Therefore, how to reconstruct the structure of the map data to improve the query speed and / or how to construct and use the map data to take into account both the data update and the data query in order to improve the user experience has become an urgent technical problem in this field.

Summary of the Invention

The present disclosure has been made to solve the above-mentioned technical problems.

An aspect of the present disclosure provides a method for reconstructing map data. The map data is multi-level map data composed of at least one upper unit including multiple lower units. The method is characterized by comprising: In the multi-level map data, each of the map data units is read by using the unit size of the lower-level unit as the size of the map data unit; according to each of the read map data units, only the map data unit is generated. In the formed single-level map data, the position of each map data unit in the multi-level map data is consistent with the position in the single-level map data.

Another aspect of the present disclosure provides a map data query method that uses the single-level map data generated in the map data reconstruction method of the one aspect to perform a query.

Another aspect of the present disclosure provides a map data utilization method, including: generating the multi-level map data in the map data reconstruction method of the one aspect; generating the single-level map data; using the multi-level map data; The hierarchical map data is used to save and / or update the map data; the single-level map data is used to query the map data, and the content of the multi-level map data and the single-level map data are always consistent.

Another aspect of the present disclosure provides a map data reconstruction device including a processor and a memory, and computer-executable instructions are stored in the memory, and when the instructions are executed by the processor, the processing is performed. The processor executes the map data reconstruction method of the one aspect.

Another aspect of the present disclosure provides a map data query device, including a processor and a memory, where computer-executable instructions are stored in the memory, and when the instructions are executed by the processor, the processor The map data query method of the another aspect is performed.

Another aspect of the present disclosure provides a map data utilization device including a processor and a memory, where computer-executable instructions are stored in the memory, and when the instructions are executed by the processor, the processor The map data utilization method of the another aspect is performed.

Another aspect of the present disclosure provides a recording medium storing executable instructions that, when executed by a processor, cause the processor to execute the map data reconstruction method of the one aspect, or the map of the other aspect A data query method, or a map data utilization method according to the other aspect.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the disclosure and its advantages, reference will now be made to the following description in conjunction with the accompanying drawings, in which:

FIG. 1 schematically illustrates a structure diagram of multiple secondary map data according to an embodiment of the present disclosure.

FIG. 2 schematically illustrates a schematic flowchart of a map data reconstruction method according to an embodiment of the present disclosure.

FIG. 3 schematically illustrates a brief flowchart of reading steps of multi-level map data in a map data reconstruction method according to an embodiment of the present disclosure.

FIG. 4 schematically illustrates a brief flowchart of a reconstruction process of a single-level map data in a map data reconstruction method according to an embodiment of the present disclosure.

FIG. 5 schematically illustrates a schematic flowchart of a map data query method according to another embodiment of the present disclosure.

FIG. 6 schematically illustrates a structure diagram of a map data reconstruction / query / utilization apparatus according to another embodiment of the present disclosure.

detailed description

With the development of robot technology, the detection of the surrounding environment by the robot is more and more important. The robot needs to save the detected map data to provide it to other functional modules, such as obstacle avoidance module, navigation module, and perception module. Wait, the robots here include: drones, self-driving cars, self-propelled robots, and other equipment that need to be mapped. They are not limited here. We will use drones as an example.

Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

Here, in order to facilitate understanding, as an example, only a common structure of three-dimensional three-level map data is shown. The map represents the position and size of the map data stored in the drone in three dimensions.

As shown in FIG. 1, the multi-level map data in the embodiment of the present disclosure may include a grid Grid level, a cell Cell level included in the grid Grid level, and a block Level included in the cell Cell level.

Among them, the grid Grid level, for example, may have a three-dimensional structure of 16m * 16m * 16m, which may include multiple cells Cell as its lower level unit (ie, second level). A cell Cell, and each of the plurality of cells Cell may have a size of, for example, 1m * 1m * 1m, that is, the resolution of the grid Grid level may be considered to be 1m * 1m * 1m (low resolution). In addition, for example, in the grid Grid hierarchy of the memory, a plurality of cells Cells are continuously arranged in a predetermined order (a first order, for example, a predetermined order in which the plurality of Cells are arranged in the grid Grid hierarchy).

In the cell Cell level, the overall size of the cell Cell may be 1m * 1m * 1m as described above. Among them, the cell Cell can be divided into two types. One type of cell Cell is shown in the cell Cell-1 of FIG. 1, which can include multiple block blocks as its lower-level unit (ie, the third level). Here, for example, 8 * 8 * 8 block blocks, and the size of each of the plurality of block blocks can be, for example, 0.125m * 0.125m * 0.125m, that is, the resolution of the cell cell level can be considered to be 0.125m * 0.125m * 0.125m (high resolution) . In addition, for example, in the cell Cell level of the memory, a plurality of block Blocks are also continuously arranged in a predetermined order (a second order, for example, a predetermined order in which the plurality of block blocks are arranged in the cell Cell level). Another type of cell Cell is shown in the cell Cell-2 of FIG. 1, which does not include a lower-level cell, but as a unit of 1m * 1m * 1m Cell is included in the Grid hierarchy as a whole. The reason for the existence of these two types of cells Cell can be considered, for example, in the process of saving or updating multi-level map data, in order to improve the efficiency of saving or updating, high resolution is usually adopted for areas with obstacles (considering the need for refinement) High-level multi-level data structures such as Cell-1, and only low-resolution even single-level data structures such as Cell-2 are used for areas such as no obstacles or areas with the same obstacle as a whole.

Here, as a method of tree storage based on the first order and the second order, it may be considered as follows: For example, first, in a grid Grid level, a first cell Cell is found in the first order Then, in the first cell Cell, all data in the first cell Cell are continuously stored in the second order, and then, in the grid Grid level, the second cell Cell is found in the first order, And so on, until all cells Cell are found in the grid Grid level and all data is continuously stored in all cells Cell.

In addition, in FIG. 1, the upper left corner indicates the arrangement direction of the map data unit (for example, including Cell or Block). For example, the x-axis can represent the far and near direction, the y-axis can represent the left-right direction, and the z-axis can represent the high and low direction.

In addition, the above only shows the structure of common 3D three-level map data as an example. It goes without saying that the map data can also have a two-dimensional structure. At this time, it can be considered as: for example, on the basis of a two-dimensional xy coordinate plane, labeling binary values at each xy coordinate point, or directly labeling the binary height. Value to represent another dimension beyond 2 dimensions. In addition, it can also be a multi-level map data structure with more than three levels. For example, the block level can continue to include sub-block levels as subordinate units, and it can even be divided into micro-blocks and more. Small levels, that is, can be divided into the smallest level allowed by the resolution.

As mentioned above, although the multi-level map data shown in FIG. 1 is beneficial to the preservation and / or update of the map data, the structure of such multi-level map data is not conducive to querying the map data, and may even lead to maps. The query efficiency is greatly reduced, for example, the use frequency of path planning is limited.

To this end, the inventors of the present disclosure have studied a single-level map data reconstruction method based on multi-level map data in order to improve query efficiency for such multi-level map data.

Hereinafter, a map data reconstruction method according to an embodiment of the present disclosure will be described with reference to FIGS. 2 to 4.

As shown in FIG. 2, the map data reconstruction method according to the embodiment of the present disclosure may include reading of multi-level map data (step S1) and reconstruction of single-level map data (step S2). The structure of the map data is as described above, and it may be multi-level map data configured such that at least one upper unit includes a plurality of lower units. Here, the multiple lower-level cells may not only refer to a structure such as a grid Grid level including multiple cell Cell levels, and / or a cell Cell level further including multiple block Block levels, but also may refer to, for example, and / or block Block levels It further includes a sub-block Sub-Block hierarchy, and even a sub-block Sub-Block hierarchy further includes a structure such as a micro-block Micro-Block and a smaller hierarchy. In addition, here, the at least one higher-level cell is as shown in FIG. 1. In addition to the higher-level cell Cell-1 including a plurality of lower-level cells, it may be considered that there may be a cell-2 that does not include a lower-level cell.

In the reading of the multi-level map data (step S1), each of the map data units is read from the multi-level map data with the unit size of the lower-level unit as the size of the map data unit. For example, each map data unit may be read with the size of the block Block (i.e., 0.125m * 0.125m * 0.125m) as shown in FIG.

Next, in the reconstruction of the single-level map data (step S2), based on the map data unit read in the reading of the multi-level map data (step S1), only the respective map data units are generated. Single-level map data (for example, a structure of (16 * 8) * (16 * 8) * (16 * 8)) constituted by a map data unit (for example, a block block of 0.125m * 0.125m * 0.125m).

Moreover, the content of the single-level map data that is finally generated is consistent with the content of the multi-level map data, that is, the content of the single-level map data is a "snapshot" of the content of the multi-level map data. That is, the position of each map data unit in the multi-level map data is consistent with the position in the single-level map data.

Therefore, in the data query, the single-level map data can be used to perform an efficient and fast query directly, thereby avoiding the inefficient problem such as the hierarchical query in the multi-level map data query.

In addition, in a case where the structure of the multi-level map data is, for example, a block Block level further includes a sub-block Sub-Block level, and even a sub-block Sub-Block level further includes a smaller level such as a micro-block Micro-Block, The unit size (ie, the size of the map data unit) is preferably the unit size of the unit at the lowest level. For example, in the case where the lowest level is the sub-block Sub-Block level, it is preferable to use the size of the sub-block Sub-Block as the unit size, and when the lowest level is the micro-block Micro-Block level, it is preferable to use the micro-block level. The size of the block Micro-Block is taken as the unit size. As a result, the query efficiency of querying using single-level map data can be sufficiently improved.

Hereinafter, details of the map data reconstruction method according to the embodiment of the present disclosure will be further specifically described with reference to FIGS. 3 and 4.

As shown in FIG. 3, in the reading of the multi-level map data (step S1), it may further specifically include: reading for an upper unit including a lower unit (step S1-1) and Reading of the upper unit (step S1-2).

Specifically, in the reading (step S1-1) for the upper unit including the lower unit, for example, for the at least one upper unit (for example, in the grid Grid hierarchy shown in FIG. 1) Cell-1), according to the first predetermined order of the superior unit (that is, the first order, for example, a predetermined order in which a plurality of cells are arranged in a Grid hierarchy) and the superior unit includes A second predetermined order of the lower-level cells (that is, the second order, for example, a predetermined order in which a plurality of blocks are arranged in the cell Cell level) to read each of the map data units.

More specifically, a table preset with indexes of various levels may be stored in advance, for example, a grid Grid level table stores the indexes of each cell Cell included, and a cell Cell level table stores each index included The index of the block. In this way, the at least one higher-level unit (for example, the cell Cell-1 in the grid Grid level shown in FIG. 1) is included in the first predetermined order of the upper-level unit and the upper-level unit includes Reading each of the map data units in a second predetermined order of the lower-level units may specifically include: obtaining an upper-level unit index (for example, a network of the upper-level unit (for example, the cell Cell) according to the first predetermined order). The Grid hierarchy uses the index of each cell Cell included in the table); according to the second predetermined order of the lower cell included in the upper cell corresponding to the higher cell index, the lower cell is obtained (for example, Block ) A lower-level unit index (for example, the index of each block Block included in the table for the cell Cell hierarchy); read the map data unit according to the obtained lower-level unit index.

Next, in the reading (step S1-2) for a higher-level unit that does not include a lower-level unit, for the other higher-level units (for example, the one shown in FIG. 1) other than the at least one higher-level unit Cell-2), in accordance with the first predetermined order of the upper-level cells (that is, the first order, for example, a predetermined order in which a plurality of cells are arranged in a grid Grid level), using the map data The size of the unit (eg, the size of the block 0.125m * 0.125m * 0.125m) to read each of said map data units. That is, in the other upper-level units (for example, Cell-2 shown in FIG. 1), since there is no lower-level unit, the map data units can be sized in any order (for example, blocks The size of the block is 0.125m * 0.125m * 0.125m) to read each of said map data units.

In some embodiments, the same reading method as in Cell-1 may be selected for reading.

As shown in FIG. 4, in the reconstruction of the single-level map data (step S2), it may further specifically include: setting the data arrangement direction (step S2-1) and reconstructing the data according to the arrangement direction (step S2) -2).

Specifically, in the setting of the data arrangement direction (step S2-1), as shown in FIG. 1, for the entire map data, according to the arrangement direction of the map data unit, it can be divided into vertical directions. Multiple alignment directions. For example, the plurality of arrangement directions may include an X-axis direction representing a near-far direction, a Y-axis direction representing a left-right direction, and a Z-axis direction representing a high-low direction.

In the reconstruction data according to the arrangement direction (step S2-2), each of the plurality of arrangement directions (for example, the X-axis direction, the Y-axis direction, and the Z-axis can be arranged). Direction) to arrange each of the map data units to generate the single-level map data. In addition, it is also preferable to set priorities respectively for the plurality of arrangement directions; and to arrange the map data units according to the plurality of arrangement directions according to the priorities to generate the single-level map data. Taking FIG. 1 as an example, for example, the priority may be preferably set as: the Z-axis direction> the Y-axis direction> the X-axis direction. In this way, since the arrangement in the Z-axis direction is performed first, the content of the reconstructed single-level map data can be more easily made consistent with the content of the original single-level map data.

Therefore, the data query is performed by using the single-level map data generated by the map data reconstruction method of the embodiment of the present disclosure, which can avoid the inefficient problem such as separate hierarchical query when querying the multi-level map data. Using the single-level map data to perform efficient and fast query directly, the query speed and efficiency can be greatly improved, and the user experience can be improved.

Hereinafter, a map data query method according to another embodiment of the present disclosure will be described with reference to FIG. 5.

The map data query method is a map data query method that uses the single-layer map data generated by the map data reconstruction method according to the embodiment of the present disclosure to perform a query.

As shown in FIG. 5, in a case where the multi-level map data is updated, the map data query method may include: updating the multi-level map data (step S11), and generating the updated single-level map data ( Step S12) and query using single-level map data (Step S13).

Specifically, in the updating of the multi-level map data (step S11), the multi-level map data is updated; in the generating of the updated single-level map data (step S12), according to the updated The multi-level map data is generated by using the map data reconstruction method in the embodiment of the present disclosure to generate the updated single-level map data; in the query using the single-level map data (step S13) , Using the generated the updated single-level map data for query processing.

As a result, the query speed and efficiency can also be greatly improved, and the user experience can be improved.

In addition, as a map data utilization method according to another embodiment of the present disclosure, the multi-level map data and the single-level map data in the map data reconstruction method according to the embodiment of the present disclosure may be provided at the same time. The multiple secondary map data is used for saving and / or updating, and the single-level map data is used for querying.

Specifically, the map data utilization method may include: generating the multi-level map data in the map data reconstruction method according to the embodiment of the present disclosure; using the map data reconstruction method according to the embodiment of the present disclosure to generate The single-level map data; using the multi-level map data to save and / or update the map data; and using the single-level map data to query the map data, wherein the multi-level map data and The content of the single-level map data is always consistent, that is, the content of the single-level map data is a "snapshot" of the content of the multi-level map data.

In this way, it is possible to achieve a balance between facilitating data storage and / or updating and facilitating data query, so as to further improve the user experience.

The following uses FIG. 7 as an example to describe another apparatus that implements the map data reconstruction / query / utilization method in a hardware manner.

As shown in FIG. 6, the device 300 may include a processor 310 (for example, a CPU, etc.) and a memory 320 (for example, a hard disk HDD, a read-only memory ROM, etc.). In addition, a readable storage medium 321 (for example, a magnetic disk, an optical disc CD-ROM, USB, etc.) indicated by a dotted line may be included.

In addition, FIG. 6 is only an example, and does not limit the technical solution of the present disclosure. Each part of the apparatus 300 may be one or more. For example, the processor 310 may be one or multiple processors.

In this way, it goes without saying that the process described above with reference to the flowchart (FIGS. 2-5) of the map data reconstruction / query / utilization method of the embodiment of the present disclosure can be implemented as a computer software program. Here, the computer software program may be one or more.

Thus, for example, the computer software program is stored in the memory 320 of the device 300 as a storage device, and by executing the computer software program, one or more processors 310 of the device 300 execute the diagram of the present disclosure. 2- The method for reconstructing / querying / utilizing the map data shown in the flowcharts of FIG. 5 and the like, and a variant thereof.

Therefore, it is also possible to provide users with fast and efficient data query, and at the same time, it is beneficial to the preservation and / or update of data, thereby greatly improving the user experience.

In addition, it goes without saying that the map data reconstruction / inquiry / utilization method may also be stored as a computer program in a computer-readable storage medium (for example, the readable storage medium 521 shown in FIG. 6). The computer program It may include code / computer-executable instructions to cause a computer to execute the map data reconstruction / query / utilization method shown in the flowcharts of FIG. 2 to FIG. 5 and the like, and a modification thereof.

In addition, the computer-readable storage medium may be, for example, any medium capable of containing, storing, transmitting, propagating, or transmitting instructions. For example, a readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, device, or propagation medium. Specific examples of readable storage media include: magnetic storage devices such as magnetic tapes or hard disk drives (HDD); optical storage devices such as optical disks (CD-ROM); memories such as random access memory (RAM) or flash memory; and / or wired / Wireless communication link.

In addition, the computer program may be configured to have computer program code including, for example, a computer program module. It should be noted that the division manner and number of modules are not fixed, and those skilled in the art may use appropriate program modules or program module combinations according to actual conditions. When these program module combinations are executed by a computer (or processor), the computer For example, the process of the map data reconstruction / query / utilization method described above in conjunction with Figs. 2-5 and its variants can be performed.

Those skilled in the art can understand that the features described in the various embodiments and / or claims of the present disclosure can be combined or combined in various ways, even if such a combination or combination is not explicitly described in this disclosure. In particular, various features and / or combinations of features described in various embodiments and / or claims of the present disclosure may be made without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the disclosure.

Although the present disclosure has been shown and described with reference to specific exemplary embodiments thereof, those skilled in the art will understand that without departing from the spirit and scope of the present disclosure as defined by the appended claims and their equivalents, Various changes in form and detail have been made to the present disclosure. Therefore, the scope of the present disclosure should not be limited to the embodiments described, but should be determined not only by the appended claims, but also by the equivalents of the appended claims.

Claims

A method for reconstructing map data, which is characterized in that the map data is multi-level map data composed of at least one upper unit including a plurality of lower units, and the method is characterized in that it includes:

Reading each of the map data units from the multi-level map data with the unit size of the lower-level unit as the size of the map data unit;

Generating single-level map data composed of each of the map data units according to each of the read map data units,

The position of each map data unit in the multi-level map data is consistent with the position in the single-level map data.
The method for reconstructing map data according to claim 1, wherein:

The reading each map data unit from the multi-level map data with the unit size of the lower-level unit as the size of the map data unit includes:

For the at least one higher-level unit, each of the map data units is read according to a first predetermined order of the upper-level unit and a second predetermined order of the lower-level unit included in the higher-level unit.
The method for reconstructing map data according to claim 2, wherein:

For the at least one superior unit, reading each of the map data units according to a first predetermined order of the superior unit and a second predetermined order of the lower units included in the superior unit includes:

Obtaining an upper unit index of the upper unit according to the first predetermined sequence;

Obtaining the lower unit index of the lower unit according to the second predetermined order of the lower unit contained in the upper unit corresponding to the higher unit index;

Reading the map data unit according to the obtained lower-level unit index.
The method for reconstructing map data according to claim 2, wherein:

The reading each map data unit from the multi-level map data with the unit size of the lower-level unit as the size of the map data unit further includes:

For each of the higher-level units other than the at least one higher-level unit, each of the map data units is read in the size of the map data unit in the first predetermined order of the higher-level unit.
The method for reconstructing map data according to claim 1, wherein:

The generating single-level map data composed of only each of the map data units according to the read each of the map data units includes:

For the map data as a whole, it is divided into a plurality of mutually orthogonal arrangement directions according to the arrangement direction of the map data units;

Each of the map data units is arranged in each of the plurality of arrangement directions to generate the single-level map data.
The method for reconstructing map data according to claim 5, wherein:

Arranging each of the map data units according to each arrangement direction of the plurality of arrangement directions to generate the single-level map data includes:

Setting priorities for the plurality of arrangement directions respectively;

Arranging each of the map data units according to the priority in accordance with the plurality of arrangement directions to generate the single-level map data.
The method for reconstructing map data according to any one of claims 1-6, wherein:

The map data is 3-dimensional map data.
The method for reconstructing map data according to claim 7, wherein:

The plurality of alignment directions include an X-axis direction representing a near-far direction, a Y-axis direction representing a left-right direction, and a Z-axis direction representing a high-low direction.
The method for reconstructing map data according to claim 8, wherein:

The priority is: the Z-axis direction is greater than the Y-axis direction, and the Y-axis direction is greater than the X-axis direction.
The method for reconstructing map data according to any one of claims 1-6, wherein:

The unit size is a unit size of the lower-level unit.
A map data query method is characterized in that:

The query is performed using the single-level map data generated in the map data reconstruction method according to claims 1-10.
The method for querying map data according to claim 11, wherein:

In the case where the multi-level map data is updated,

Generating the updated single-level map data according to the updated multi-level map data,

The query is performed using the updated single-level map data.
A method for utilizing map data, comprising:

Generating the multi-level map data in the map data reconstruction method according to claims 1-10;

Generating the single-level map data;

Using the multi-level map data to save and / or update map data;

Querying map data by using the single-level map data,

The contents of the multi-level map data and the single-level map data are always consistent.
A map data reconstruction device, characterized in that the map data is multi-level map data constructed in such a manner that at least one upper unit includes a plurality of lower units,

The map data reconstruction device includes a processor and a memory,

Computer-executable instructions are stored in the memory, and when the instructions are executed by the processor, cause the processor to execute:

Reading each of the map data units from the multi-level map data with the unit size of the lower-level unit as the size of the map data unit;

Generating single-level map data composed of each of the map data units according to each of the read map data units,

The position of each map data unit in the multi-level map data is consistent with the position in the single-level map data.
The apparatus for reconstructing map data according to claim 14, wherein:

The reading each map data unit from the multi-level map data with the unit size of the lower-level unit as the size of the map data unit includes:

For the at least one higher-level unit, each of the map data units is read according to a first predetermined order of the upper-level unit and a second predetermined order of the lower-level unit included in the higher-level unit.
The map data reconstruction device according to claim 15, wherein:

For the at least one superior unit, reading each of the map data units according to a first predetermined order of the superior unit and a second predetermined order of the lower units included in the superior unit includes:

Obtaining an upper unit index of the upper unit according to the first predetermined sequence;

Obtaining the lower unit index of the lower unit according to the second predetermined order of the lower unit contained in the upper unit corresponding to the higher unit index;

Reading the map data unit according to the obtained lower-level unit index.
The map data reconstruction device according to claim 15, wherein:

The reading each map data unit from the multi-level map data with the unit size of the lower-level unit as the size of the map data unit further includes:

For each of the higher-level units other than the at least one higher-level unit, each of the map data units is read in the size of the map data unit in the first predetermined order of the higher-level unit.
The apparatus for reconstructing map data according to claim 14, wherein:

The generating single-level map data composed of only each of the map data units according to the read each of the map data units includes:

For the map data as a whole, it is divided into a plurality of mutually orthogonal arrangement directions according to the arrangement direction of the map data units;

Each of the map data units is arranged in each of the plurality of arrangement directions to generate the single-level map data.
The map data reconstruction device according to claim 18, wherein

Arranging each of the map data units according to each arrangement direction of the plurality of arrangement directions to generate the single-level map data includes:

Setting priorities for the plurality of arrangement directions respectively;

Arranging each of the map data units according to the priority in accordance with the plurality of arrangement directions to generate the single-level map data.
The map data reconstruction device according to any one of claims 14 to 19, wherein:

The map data is 3-dimensional map data.
The map data reconstruction device according to claim 20, wherein:

The plurality of alignment directions include an X-axis direction representing a near-far direction, a Y-axis direction representing a left-right direction, and a Z-axis direction representing a high-low direction.
The map data reconstruction device according to claim 21, wherein

The priority is: the Z-axis direction is greater than the Y-axis direction, and the Y-axis direction is greater than the X-axis direction.
The map data reconstruction device according to any one of claims 14 to 19, wherein:

The unit size is a unit size of the lower-level unit.
A map data query device, comprising a processor and a memory, wherein computer-executable instructions are stored in the memory, and when the instructions are executed by the processor, the processor executes claim 11 Or the map data query method described in 12.
A map data utilization device, comprising a processor and a memory, wherein computer-executable instructions are stored in the memory, and when the instructions are executed by the processor, the processor executes claim 13 The map data utilization method.
A computer-readable recording medium storing executable instructions that, when executed by a processor, cause the processor to execute the map data reconstruction method according to any one of claims 1-10, or claim 11 or The map data query method according to 12 or the map data use method according to claim 13.