CN114777793B

CN114777793B - BIM map extraction and path planning method for any navigation subject

Info

Publication number: CN114777793B
Application number: CN202210677392.XA
Authority: CN
Inventors: 周小平; 王家麟; 王佳; 齐彤华
Original assignee: Bim Winner Shanghai Technology Co ltd; Foshan Yingjia Smart Space Technology Co ltd; Jiaxing Wuzhen Yingjia Qianzhen Technology Co ltd; Shandong Jiaying Internet Technology Co ltd; Shenzhen Bim Winner Technology Co ltd; Shenzhen Qianhai Yingjia Data Service Co ltd; Yingjia Internet Beijing Smart Technology Co ltd; Bim Winner Beijing Technology Co ltd
Current assignee: Qingdao Saab Weitong Technology Co.,Ltd.
Priority date: 2022-06-16
Filing date: 2022-06-16
Publication date: 2022-09-20
Anticipated expiration: 2042-06-16
Also published as: CN114777793A

Abstract

The application provides a BIM map extraction and path planning method facing any navigation subject, which comprises the steps of obtaining multiple action constraint conditions of a target subject and a building information model of a target place to be entered by the target subject; constructing a continuous span region of the target subject; performing triangular surface division on at least one passable area in the continuous span area to obtain a target road network meeting the passing requirement of a target main body; starting from a target starting point, performing path search on a target road network by adopting a path search algorithm until a target end point is reached and stopping to obtain at least one path; screening a target path with the shortest travel distance of the target main body from at least one path; and optimizing the target path to obtain the indoor path of the target subject. Therefore, road network extraction is carried out based on the characteristics of the target main body and the building information model, the universality of the road network is improved, and the indoor path planning efficiency is improved through the path searching and optimizing method.

Description

BIM map extraction and path planning method for any navigation subject

Technical Field

The application relates to the technical field of indoor path planning, in particular to a BIM map extraction and path planning method facing any navigation subject.

Background

The route planning means planning an obstacle-free route from a start position to an end position through a road network. The path planning is the basis of the fields of unmanned driving, smart cities, smart buildings, emergency fire fighting and the like, is one of scientific research focuses of computers, automatic control, intellectualization, electronic information and the like, is one of core technologies for effective operation of intelligent bodies such as people, vehicles, robots and the like, and has become a research hotspot for the current industrialized development. Indoor path planning has become a popular research content in the field of current building automation science as a basis for guiding intelligent agents to reach target locations along a path in an indoor space.

The core technology of indoor path planning lies in the extraction of indoor road networks, most of the existing indoor path planning methods only aim at people or a special subject, and no path generation method capable of simultaneously facing multiple subjects exists, so that the existing methods are not applicable any more every time a new subject appears, and an algorithm needs to be redesigned, and therefore indoor road networks with universality are urgently needed.

Disclosure of Invention

In view of this, an object of the present application is to provide a BIM map extraction and path planning method for any navigation subject, which constructs a continuous span region map of a target location into which a target subject is to enter according to the size of a space occupied by the target subject and movement capability information of the target subject, and extracts a road network suitable for subject features according to the continuous span region map, so as to perform efficient indoor path planning based on the extracted road network, thereby greatly improving universality of the indoor road network and improving efficiency of the indoor path planning.

The embodiment of the application provides a BIM map extraction and path planning method facing any navigation subject, which comprises the following steps:

acquiring a plurality of action constraint conditions of a target subject and a building information model of a target place where the target subject is to enter; wherein the action constraint is selected according to the size of the space occupied by the target subject and the mobility of the target subject;

constructing a continuous span area corresponding to the target subject according to the multiple action constraint conditions of the target subject and a building information model of a target place to which the target subject is to enter; the continuous span area comprises at least one passable area and/or at least one impassable area through which the target body moves;

for the at least one passable area, performing triangular surface division on the passable area by adopting a triangular surface division method to obtain a target road network meeting the passing requirement of the target main body; the target road network is a road network consisting of a plurality of triangular surfaces;

starting from a target starting point, performing path search on the target road network by adopting a path search algorithm until a target end point is reached, and stopping to obtain at least one path; each path in the at least one path is a route formed by connecting center points of triangular surfaces through which the target main body starts to reach a target end point from a target start point;

screening a target path with the shortest travel distance of the target body from the at least one path;

and optimizing the target path to obtain an indoor path of the target main body moving in the target place.

Optionally, the action constraint includes at least one of a maximum passable slope, a minimum passable height, a maximum climbing height, and a minimum passable width.

Optionally, when the action constraint condition includes a maximum passable slope, a minimum passable height, a maximum climbing height, and a minimum passable width, the constructing a continuous span area corresponding to the target subject according to the multiple action constraint conditions of the target subject and a building information model of the target subject to enter the target site includes:

screening obstacles in the building information model under the constraint of the maximum passable gradient and the minimum passable height, and constructing an entity height three-dimensional model of the target site;

and under the constraint of the maximum climbing height and the minimum passing width, screening passable areas and impassable areas in the entity height three-dimensional model to construct a continuous span area of the target site.

Optionally, the screening the obstacles in the building information model under the constraints of the maximum passable slope and the minimum passable height to determine the three-dimensional model of the physical height of the target site includes:

carrying out voxelization processing on the building information model according to a preset spatial resolution, and determining a three-dimensional voxel model of the target site;

screening voxel units in the three-dimensional voxel model according to the maximum passable gradient and the minimum passable height, and determining voxel units which block the target body from moving in the target place;

and constructing a solid height three-dimensional model of the target place based on the determined voxel unit.

Optionally, the screening passable areas and impassable areas in the three-dimensional entity height model under the constraints of the maximum climbing height and the minimum passable width to construct a continuous span area corresponding to the target subject includes:

constructing an open height three-dimensional model of the target place according to the entity height three-dimensional model and the actual space height of the target place;

under the constraint of the maximum climbing height, determining the communication relation among neighborhoods and the span information among the neighborhoods based on the three-dimensional model of the open height;

creating a distance field of the target place according to the communication relation among the neighborhoods and the span information among the neighborhoods;

under the constraint of the minimum passable width, determining a continuous span region corresponding to the target subject based on the distance field.

Optionally, the triangular surface division is performed on the passable area by using a triangular surface division method for the at least one passable area to obtain a target road network meeting the passing requirement of the target subject, including:

identifying and processing the boundary contour of each region in the continuous span region to determine the target boundary contour line of each region in the target place;

for each passable area, determining the contour vertex of the passable area according to the target boundary contour line of the passable area;

connecting the contour vertexes of the passable area by adopting a triangular surface dividing method to determine an initial road network of the passable area;

for each initial road network, determining the initial road network of which the difference between the fitting height and the actual height does not meet the requirement of a preset threshold value as a road network to be optimized, and determining a passable area corresponding to the road network to be optimized as an area to be optimized;

determining at least one sample node influencing the fitting effect of the road network to be optimized according to the fitting height and the actual height corresponding to the road network to be optimized aiming at each road network to be optimized;

connecting the contour vertex of each region to be optimized and at least one corresponding sample node by adopting a triangular surface division method aiming at each region to be optimized, and determining an initial road network of the optimized region to be optimized;

and determining the initial road networks of all passable areas which are not optimized and the road network formed after the initial road networks of all areas to be optimized are combined into a target road network meeting the traffic requirements of the target subject.

Optionally, the identifying and processing the boundary contour of each region in the continuous span region to determine the target boundary contour line of each region in the target location includes:

identifying the boundary contour of each region in the continuous span region, and determining the contour line of the equivalent region of each region; wherein, partial boundary contour lines of adjacent regions are mutually overlapped and share a section of contour line of the equivalent region;

carrying out zigzag line identification on contour lines of the equivalent regions of each region, and simplifying the identified zigzag lines to obtain simplified boundary contour lines of each region; the simplification processing is to simplify the zigzag line into at least one straight line;

for each region, the simplified boundary contour of the region is determined as the target boundary contour of the region.

Optionally, the performing, from a target starting point, a path search algorithm on the target road network until a target end point is reached and a path is cut off to obtain at least one path includes:

a, determining a triangular surface where a target starting point is located, determining the triangular surface as a starting triangular surface, and storing the starting triangular surface into a passable triangular mesh list; wherein, only the starting triangle surface is included in the passable triangular mesh list at this time;

b, determining a passable triangular surface with an adjacent edge to the starting triangular surface, and storing the passable triangular surface into a passable triangular mesh list;

c, determining whether the passable triangular surface comprises the target end point, if not, executing a step D, and if so, executing a step E;

d, determining a target passable triangular surface with the shortest distance to the end point from the passable triangular surfaces, determining the target passable triangular surface as a starting triangular surface, and returning to execute the step B;

e, according to the adjacent relation of the passable triangular surfaces in the passable triangular mesh list, traversing the center point of each passable triangular surface from the target starting point to the target end point, and determining at least one path from the target starting point to the target end point.

Optionally, the optimizing the target path to obtain the indoor path of the target location includes:

determining whether straight lines from a target starting point to a target end point are all located in a triangular surface mesh through which the target path passes;

if yes, determining a straight line from a target starting point to a target end point as the indoor path;

if not, selecting at least one target node from the candidate end points, so that the target node and the start point are sequentially connected from the target start point to the target end point until the target node and the start point are connected to the target end point according to the sequence from near to far, the shortest driving path is obtained, and the shortest driving path is determined to be the indoor path; the candidate end point is an end point of a common edge of adjacent triangular faces in the triangular face mesh through which the target path passes.

The embodiment of the present application further provides a BIM map extraction and path planning device facing any navigation subject, the device includes:

the system comprises an acquisition module, a storage module and a display module, wherein the acquisition module is used for acquiring a plurality of action constraint conditions of a target subject and a building information model of a target place where the target subject is to enter; wherein the action constraint is selected according to the size of the space occupied by the target subject and the mobility of the target subject;

the construction module is used for constructing a continuous span area corresponding to the target subject according to the multiple action constraint conditions of the target subject and a building information model of a target place where the target subject enters; the continuous span area comprises at least one passable area and/or at least one impassable area through which the target body moves;

the dividing module is used for performing triangular surface division on the passable area by adopting a triangular surface dividing method aiming at the at least one passable area so as to obtain a target road network meeting the passing requirement of the target main body; the target road network is a road network consisting of a plurality of triangular surfaces;

the searching module is used for searching a path of the target road network by adopting a path searching algorithm from a target starting point until a target end point is reached, so as to obtain at least one path; each path in the at least one path is a route formed by connecting center points of triangular surfaces through which the target main body starts to reach a target end point from a target start point;

the screening module is used for screening the target path with the shortest driving distance of the target main body from the at least one path;

and the optimization module is used for optimizing the target path to obtain an indoor path of the target main body moving in the target place.

Optionally, when the action constraint conditions include a maximum passable slope, a minimum passable height, a maximum climbing height, and a minimum passable width, the building module is configured to, when the building module is configured to build a continuous span area corresponding to the target subject according to the multiple action constraint conditions of the target subject and a building information model of the target subject about to enter the target site,:

and under the constraint of the maximum climbing height and the minimum passing width, screening a passable area and a non-passable area in the entity height three-dimensional model, and constructing a continuous span area corresponding to the target subject.

Optionally, the building module is configured to, when the building module is configured to screen obstacles in the building information model under the constraints of the maximum passable slope and the minimum passable height, and determine a physical height three-dimensional model of the target site, the building module is configured to:

Optionally, when the building module is configured to screen the passable region and the non-passable region in the three-dimensional entity height model under the constraints of the maximum climbing height and the minimum passable width, and build the continuous span region corresponding to the target subject, the building module is configured to:

Optionally, when the dividing module is configured to perform triangular surface division on the passable area by using a triangular surface dividing method for the at least one passable area so as to obtain a target road network meeting the passing requirement of the target subject, the dividing module is configured to:

and determining the initial road networks of all passable areas which are not required to be optimized and the road networks formed by the initial road networks of all areas to be optimized after the initial road networks are combined to be a target road network meeting the traffic requirements of the target subject.

Optionally, when the dividing module is configured to identify and process the boundary contour of each region in the continuous span region, and determine the target boundary contour of each region in the target location, the dividing module is configured to:

Optionally, the search module is configured to, starting from a target starting point, perform a path search on the target road network by using a path search algorithm until a target end point is reached, so as to obtain at least one path, where the search module is configured to:

determining a triangular surface where a target starting point is located, determining the triangular surface as a starting triangular surface, and storing the starting triangular surface into a passable triangular mesh list; wherein, only the starting triangle surface is included in the passable triangular mesh list at this time;

determining a passable triangular surface with an adjacent edge with the starting triangular surface, and storing the passable triangular surface into a passable triangular mesh list;

determining whether the passable triangular surface comprises the target end point, if not, determining a target passable triangular surface with the shortest distance from the end point from the passable triangular surfaces, determining the target passable triangular surface as a starting triangular surface, returning to execute the determination of the passable triangular surface with an adjacent edge to the starting triangular surface, and storing the passable triangular surface into a passable triangular grid list;

if so, traversing the center point of each passable triangular surface from the target starting point to the target end point according to the adjacent relation of the passable triangular surfaces in the passable triangular mesh list, and determining at least one path from the target starting point to the target end point.

Optionally, when the optimization module is configured to optimize the target path to obtain an indoor path along which the target subject moves in the target site, the optimization module is configured to:

when the indoor path is the straight line, determining a straight line from the target starting point to the target end point as the indoor path;

An embodiment of the present application further provides an electronic device, including: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when the electronic device is operating, the machine-readable instructions when executed by the processor performing the steps of the method as described above.

Embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by a processor to perform the steps of the method as described above.

Thus, the present application first considers the capability characteristics of the target subject. Secondly, providing a building information model road network extraction method facing to main body capability characteristics, and constructing an entity height field by limiting the maximum passable gradient and the minimum passable height; then establishing a continuous span area by limiting the maximum climbing height and the minimum width of the same row; then generating a simple polygon outline fitting the outline of the continuous span area based on the continuous span area; and finally, further screening and adding the heights of the small areas to construct a triangular road network which is more appropriate to the model. For path planning, firstly, screening pairwise connected shortest triangular surface mesh paths from a starting point to an end point by a diffusion principle; and then further optimizing to obtain the shortest path from the starting point to the end point based on the connected triangular surface grids. Therefore, through the technical scheme provided by the application, the universality of the indoor road network can be greatly improved, and the efficiency of path planning is further improved.

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

Fig. 1 is a flowchart of a BIM map extraction and path planning method for any navigation subject provided in the embodiment of the present application;

FIG. 2 is a schematic structural diagram of a portion of a solid height three-dimensional model provided herein;

FIG. 3 is a schematic diagram of a neighborhood search method provided herein;

FIG. 4 is a schematic diagram of a partial distance field provided herein;

FIG. 5 is a schematic illustration of a portion of a continuous span region of a target site provided herein;

FIG. 6 is a schematic diagram of the determined edge structure of the area provided in the present application;

FIG. 7 is a schematic illustration of an iso-contour of a portion of a continuous span region as provided herein;

FIG. 8 is a schematic flow diagram of a meander line reduction process provided herein;

FIG. 9 is a schematic diagram of a simplified boundary contour for a portion of a continuous span region as provided herein;

FIG. 10 is a schematic flow chart illustrating the determination of an initial road network according to the present application;

FIG. 11 is a schematic flow chart of an initial road network optimization process provided herein;

FIG. 12 is a schematic diagram of a road network fitting effect provided by the present application;

FIG. 13 is a schematic illustration of a local target road network provided herein;

FIG. 14 is a schematic diagram of a passable triangular mesh determined after a path search is performed according to the present application;

fig. 15 is a schematic flow chart illustrating an implementation of a path optimization rule provided in the present application;

FIG. 16 is a schematic structural diagram of a building information model used in the experimental process of the present application;

FIG. 17 is a schematic illustration of an indoor path determined during an experiment of the present application;

fig. 18 is a schematic structural diagram of a BIM map extraction and path planning device facing any navigation subject according to an embodiment of the present disclosure;

fig. 19 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. Every other embodiment that can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present application falls within the protection scope of the present application.

Based on this, the present application aims to provide a BIM map extraction and path planning method for any navigation subject, which constructs a continuous span regional map of a target place into which a target subject enters according to the size of a space occupied by the target subject and the mobility information of the target subject, and extracts a road network suitable for subject characteristics according to the continuous span regional map, thereby performing efficient indoor path planning based on the extracted road network, and further greatly improving the universality of the indoor road network and the efficiency of indoor path planning.

Referring to fig. 1, fig. 1 is a flowchart of a BIM map extraction and path planning method for any navigation subject according to an embodiment of the present disclosure. As shown in fig. 1, a method provided in an embodiment of the present application includes:

s101, acquiring a plurality of action constraint conditions of a target subject and a building information model of a target place where the target subject is to enter.

Here, the target subject refers to an object that enters a target site and moves in the target site; wherein the target subject may include a normal adult, a wheelchair-bound disabled person, a robot, a vehicle, and the like.

The action constraint is selected based on the amount of space occupied by the target subject and the ability of the target subject to move. Wherein the action constraint conditions are at least one of maximum passable slope, minimum passable height, maximum climbing height and minimum passable width.

The action constraints determined according to the size of the space occupied by the target subject include a minimum passable height and a minimum passable width. The action constraints determined according to the movement capacity of the target subject include a maximum passable gradient and a maximum climbing height.

The lowest passable height is chosen as an action constraint because each subject has a different height, limiting the subject's action to some extent. For example, the sweeping robot can shuttle to short areas such as a table bottom, a bed bottom and the like, and people are inconvenient to pass through the excessively short areas, so that the lowest passable height is defined in the text

。

The minimum passable width is chosen as an action constraint because each body has a different width. For example, for cars, the width allowed to pass is more strict than for humans, and for smaller robots, the width allowed to pass is less strict. For example, some subjects are inherently dangerous and require a certain amount of safety space around them. For this purpose, the minimum passable width is defined herein

. Wherein, if the main body has a longer length and needs to change a larger angle to move, at this time

It is required to be set according to the relevant requirements.

The maximum passable slope is selected as a constraint for the action because different subjects have different climbing abilities, for example, a disabled person using a wheelchair can move only on a slope with a gentle slope. The car can run on a steep slope, so the maximum passable gradient is defined in the text

. Wherein the maximum passable gradient

This can be determined by the following equation:

wherein the content of the first and second substances,ain order to be the height of the slope,bis the horizontal distance of the slope.

The maximum climbing height is chosen as a constraint because the climbing capabilities of different subjects are different, e.g., a normal person, a part of a robot, etc., have the ability to climb a certain height. Disabled persons, most sweeping robots, cars and the like do not have the ability to climb stairs. Thus, the maximum climbing height is defined herein

。

For example, please refer to table 1, where table 1 is a specific value table under different subject action constraints.

Table 1:

the Building Information Model (BIM) is the basis of digital transformation in the Building, engineering and Architecture (AEC) industry, and three-dimensional geometric Information and semantic Information of a Building are stored in the BIM.

S102, constructing a continuous span area corresponding to the target subject according to the multiple action constraint conditions of the target subject and a building information model of a target place where the target subject enters.

Here, the continuity area defines a passable area and/or a non-passable area when the target subject moves in the target place. The passable area comprises at least one area, and the impassable area also comprises at least one area.

In one embodiment provided by the present application, when the action constraint condition includes a maximum passable slope, a minimum passable height, a maximum climbing height, and a minimum passable width, the constructing a continuous span area corresponding to the target subject according to the plurality of action constraint conditions of the target subject and a building information model of the target subject to enter a target site includes: screening obstacles in the modeling information model under the constraint of the maximum passable gradient and the minimum passable height, and constructing a three-dimensional model of the entity height of the target place; and under the constraint of the maximum climbing height and the minimum passing width, screening a passable area and a non-passable area in the entity height three-dimensional model, and constructing a continuous span area corresponding to the target subject.

Here, in constructing the continuous span region of the target site, the continuous span region is constructed under the constraint of the behavior constraint condition selected from the characteristics of the target subject. In the construction process, barrier screening is carried out according to the maximum passable gradient and the minimum passable height in the behavior constraint conditions, an entity height three-dimensional model of a target site is constructed, then region screening and region type determination are carried out based on the constraints of the rated maximum climbing height and the rated minimum passable width in the behavior constraint conditions, and a continuous span region of the target site is constructed according to the screening result. Wherein the area types include a passable area and a non-passable area.

In another embodiment provided by the present application, the screening obstacles in the building information model under the constraint of the maximum passable slope and the minimum passable height to determine a three-dimensional model of the physical height of the target site includes: carrying out voxelization processing on the building information model according to a preset spatial resolution, and determining a three-dimensional voxel model of the target site; screening voxel units in the three-dimensional voxel model according to the maximum passable gradient and the minimum passable height, and determining voxel units which block the target body from moving in the target place; and constructing a solid height three-dimensional model of the target place based on the determined voxel unit.

It should be noted that, in order to implement multi-agent adaptive indoor path planning, an indoor navigation grid needs to be established, and for the building information model, an entity height three-dimensional model needs to be established first, so the building information model is used as input, and the building information model is discretized into a three-dimensional voxel grid to establish the entity height three-dimensional model.

Here, the voxelization process is to convert a geometric representation of an object into a voxel representation closest to the object and generate a voxel data set. The method comprises the steps of firstly calculating an AABB bounding box of the building information model, then dividing the AABB bounding box according to the spatial resolution to obtain a voxel list with each size being a fixed size.

Here, the screening, according to the constraint of the maximum passable slope and the minimum passable height, voxel units in the three-dimensional voxel model to determine voxel units that hinder the target subject from moving in the target site may specifically be: for each polygon for which a modeling information model is constructed, the following process is performed, wherein for each face of each polygon, the actual slope height of the polygon is determined according to the size of each voxel in the three-dimensional voxel model and the voxel grid spanned by each face, and if the actual slope height of the polygon is lower than a slope set value (namely, the maximum passable slope), all voxel units in the corresponding area of the polygon are deleted (namely, the area is ignored when the height field is established). And simultaneously, determining the span distance of adjacent polygons, overlapping two span regions corresponding to the adjacent polygons when the span distance of the adjacent polygons does not meet the constraint of the lowest passable height, and respectively establishing a height three-dimensional model according to voxel units included in the region corresponding to each polygon if the span distance of the adjacent polygons meets the constraint of the lowest passable height.

In this way, a solid-height three-dimensional model of the target site may be constructed based on the determined voxel units. For example, please refer to fig. 2, fig. 2 is a schematic structural diagram of a part of the solid height three-dimensional model provided in the present application.

In another embodiment provided by the present application, the screening passable areas and impassable areas in the three-dimensional model of entity height under the constraints of the maximum climbing height and the minimum passable width to construct a continuous span area corresponding to the target subject includes: constructing an open height three-dimensional model of the target place according to the entity height three-dimensional model and the actual space height of the target place; under the constraint of the maximum climbing height, determining the communication relation among the neighborhoods and the span information among the neighborhoods based on the open height three-dimensional model; creating a distance field of the target place according to the communication relation among the neighborhoods and the span information among the neighborhoods; under the constraint of the minimum passable width, determining a continuous span region corresponding to the target subject based on the distance field.

Here, the objective of this partial technical solution is to further construct a traversable surface area (i.e. the continuous span area) representing the original geometry based on the solid height three-dimensional model and under the constraints of the maximum climbing height and the minimum passing width. The steps of constructing the continuous span region mainly comprise: the method comprises the steps of constructing an open height three-dimensional model, determining a neighborhood connection relation in the second step, creating a distance field in the third step, and finally creating a continuous span region capable of being traversed based on the operations of the previous three steps.

Here, the open-height three-dimensional model represents the area above the span of the solid-height three-dimensional model, and if the span is marked traversable, the open space between its maximum value and the minimum value of the next higher span in its column is determined, these values constituting the new open span, such as the floor and the ceiling, respectively. Thus, on the premise that the physical height three-dimensional model and the actual space height of the target place are known, the construction of the open height three-dimensional model can be completed.

Here, when determining the connectivity between neighborhoods and the span information between neighborhoods, it is also possible to find out which span regions form the surface of the continuous span by creating the axis neighborhood connection. A stair step surface may be considered an effective connection when the constraint between two span areas is less than the maximum climbing height, for example, when the upper and lower steps between floors are less than the maximum climbing height.

For example, please refer to fig. 3, fig. 3 is a schematic diagram of a neighborhood search method provided in the present application. Where a column of cells has a neighborhood, and likewise a span has a neighborhood, but for a span, a span neighborhood is considered to be joinable only if its height is close enough to the reference span. The full neighborhood of the span consists of an axis neighborhood and a diagonal neighborhood. The axis neighborhoods are four adjacent axes offset along the Y-axis: (-1,0),(0,1),(1,0),(0, -1). For all height fields in the open height three-dimensional model, performing an axis-adjacent search starting from (-1, 0) in all clockwise directions, as shown in (a) of fig. 3; the diagonal neighborhood is the corresponding diagonal neighborhood from the (-1, 1) clockwise search axis neighborhood; as shown in fig. 3 (b); the full neighborhood is shown in fig. 3 (c).

Here, in constructing the distance field, span information between the neighbors includes a boundary span distance from each sample point in the region to the boundary, where the boundary span distance may be based according to a euclidean distance calculation formula. Thus, the distance field of the target site can be created based on the connectivity between neighborhoods and span information between neighborhoods. Where the boundary generally refers to the edge of the original geometry that can traverse a curved surface and an obstacle (e.g., a wall) or a falling space (e.g., a balcony).

Wherein, can be held by a formula Fd ₁ ,d ₂ ,…，d _n }=

Constructing a distance field, in which formula F refers to the distance field; d _i Refers to the distance between each span and its nearest boundary span;Ix _a finger spanIMiddle pointaThe abscissa of (a);Ex _b points in the nearest boundary span EbThe abscissa of (a);Iy _a finger spanIMiddle pointaThe ordinate of (a);Ey _b points in the nearest boundary span EbThe ordinate of (c).

For example, referring to fig. 4, fig. 4 is a schematic diagram of a partial distance field as provided herein. As shown in fig. 4, darker places indicate closer distances from the boundary, and lighter places indicate farther distances from the boundary.

And finally, under the constraint of the minimum passable width, based on the distance field, adopting a classical watershed algorithm to determine a continuous span region of the target place. The continuous span region represents a group of continuous spans that can traverse the surface region, and a simple polygon is formed after the continuous span region is subjected to designated plane projection.

For example, referring to fig. 5, fig. 5 is a schematic diagram of a portion of a continuous span region of a target site provided herein. As shown in fig. 5, the black areas represent the non-accessible areas, and the other different gray areas each represent the accessible areas, and it is possible to determine which areas are connected and which areas are not connected by the determined continuous span areas.

S103, aiming at the at least one passable area, carrying out triangular surface division on the passable area by adopting a triangular surface division method so as to obtain a target road network meeting the passing requirement of the target main body; the target road network is a road network consisting of a plurality of triangular surfaces.

When the target road network is generated, passable regions are screened based on the constructed continuous span regions, and at least one passable region is determined. Then, aiming at each determined passable area in the at least one passable area, carrying out triangular division on the passable area by adopting a triangular surface division method to obtain a road network of the passable area, and arranging the road networks of all the passable areas according to the position information of the corresponding passable area to obtain a target road network meeting the passing requirement of the target subject. The target road network is a road network consisting of a plurality of triangular surfaces.

In an embodiment provided by the present application, the triangle-surface dividing, by using a triangle-surface dividing method, the passable area for the at least one passable area to obtain a target road network meeting the target subject passage requirement includes: identifying and processing the boundary contour of each region in the continuous span region to determine the target boundary contour line of each region in the target place; for each passable area, determining the contour vertex of the passable area according to the target boundary contour line of the passable area; connecting the contour vertexes of the passable area by adopting a triangular surface dividing method to determine an initial road network of the passable area; for each initial road network, determining the initial road network of which the difference between the fitting height and the actual height does not meet the requirement of a preset threshold value as a road network to be optimized, and determining a passable area corresponding to the road network to be optimized as an area to be optimized; determining at least one sample node influencing the fitting effect of the road network to be optimized according to the fitting height and the actual height corresponding to the road network to be optimized aiming at each road network to be optimized; connecting the contour vertex of each region to be optimized and at least one corresponding sample node by adopting a triangular surface division method aiming at each region to be optimized, and determining an initial road network of the optimized region to be optimized; and determining the initial road networks of all passable areas which are not optimized and the initial road networks of all areas to be optimized which are optimized to form a road network after being combined as a target road network meeting the traffic requirements of the target subject.

The step is a specific implementation process for constructing a target road network, and is implemented by firstly identifying a boundary contour of each region according to the determined continuous span region, and then processing the identified boundary contour to determine a target boundary contour of each region, namely determining a boundary line of each region.

In another embodiment provided by the present application, the identifying and processing the boundary contour of each region in the continuous span region to determine the target boundary contour of each region in the target location includes: identifying the boundary contour of each region in the continuous span region, and determining the contour line of the equivalent region of each region; wherein, partial boundary contour lines of adjacent regions are mutually overlapped and share a section of contour line of the equivalent region; carrying out zigzag line identification on contour lines of the equivalent regions of each region, and simplifying the identified zigzag lines to obtain simplified boundary contour lines of each region; the simplification processing is to simplify the zigzag line into at least one straight line; for each region, the simplified boundary contour of the region is determined as the target boundary contour of the region.

This step illustrates how the continuous span area surface is converted into an iso-area contour and the contour is optimized to produce a simplified boundary contour.

Here, in determining the contour lines of the iso-regions of the respective regions, the search may be performed by: first, the region edge is searched. For each span, it needs to search its complete neighborhood, as shown in fig. 3 (c), and if the neighborhood is not in the same region as the current span, please refer to fig. 6, where fig. 6 is a schematic diagram of the determined region edge structure provided by the present application. As shown in fig. 6, at this time, the edge is marked as an area edge, such as a black edge in (a) in fig. 6, and the area divided by the area edge is stored. If the adjacent elements are located in the same area, the edge will be marked as an inner edge, such as a white edge in (a) of FIG. 6.

Next, a continuous contour line is generated from the intermittent region side, as shown by the black line (b) in fig. 6. Firstly, adding a region edge of a certain region to the contour, taking one point of the edge as the vertex of the next region edge to be searched, judging which of the four edges connected by the vertex is the region edge of the region to be searched currently, adding the edge into the contour line of the region, and repeating the operation until the first region edge is returned. In this way, the iso-regional contours for each region are determined.

By way of example, referring to fig. 7, fig. 7 is a schematic diagram of an iso-contour of a portion of a continuous span region as provided herein. The contour line of the contour region circled in fig. 7 is a contour line that needs to be simplified, and it should be noted that the contour line circled here is only a part of the contour line that needs to be simplified.

Firstly, it can be seen from fig. 7 that the contour lines encircled by the circles are not flat and influence the appearance, so that vertexes which do not represent the change of the area connection need to be reduced; secondly, the final requirement for determining the contour line of the region is to triangulate the road network, and as more vertices are triangulated, the more complex the data size is, and therefore, unnecessary vertices need to be simplified.

The important idea is to select a point set K capable of reflecting the integral trend and layout of the curve from the point sets K forming the contour line of the equivalent region'Form a simplified curve L'。

Optionally selecting a section of contour line of the isovolumetric region, and assuming that a point set K forming the contour line of the isovolumetric region is: k = { K ₁ ,k ₂ ,……k _n Get the point set K of the contour line after simplification processing'Comprises the following steps: k'={k _c1 ,k _c2 ,……k _cn According to the simplified point set K'A simplified boundary contour of the contour line of the equivalence region can be obtainedAnd obtaining the target boundary contour line.

For example, when simplifying the contour line of the equal-value region, please refer to fig. 8, and fig. 8 is a schematic flow chart of the zigzag line simplification process provided in the present application. As shown in fig. 8, the implementation steps of the simplified process specifically include:

the method comprises the following steps: connecting a straight line AB in an end-to-end manner between the points A and B, wherein the green straight line AB is a chord of a broken line, and 32 points are shared in the K set, as shown in (a) in FIG. 8;

step two: taking the point where the distance from the straight line AB to the broken line is the largest, and recording as a point C, as shown in (a) of fig. 8;

step three: comparing the distance with a set threshold value, if the distance is smaller than the set threshold value, taking the straight line segment as the approximation of a broken line, and finishing the processing of the curve segment;

step four: if the distance is greater than the set threshold, dividing the curve into two segments of AC and BC by using a point C, and repeating the steps from the first step to the third step as shown in (b) in FIG. 8;

step five: when all the curves are processed, the broken lines formed by the respective dividing points are connected in sequence, i.e., the simplified boundary contour line of the broken line is used, as shown in (d) of fig. 8, K'Set as K'={k ₁ ，k ₁₀ ，k ₂₂ ，k ₂₇ ，k ₃₂ }。

Thus, a simplified boundary contour for each region is obtained, thereby determining a target boundary contour for each region. For example, referring to fig. 9, fig. 9 is a schematic diagram of a simplified boundary contour line of a partial continuous span region provided in the present application. Here, fig. 9 is obtained by simplifying the processing of fig. 7.

And after the target boundary contour line of each region is determined, the target road network extraction operation can be carried out. Firstly, determining the contour vertex of each passable area; then, for each passable area, connecting the contour vertexes of the passable area by adopting a triangular surface division method, and determining an initial road network of the passable area.

Here, please refer to fig. 10, where fig. 10 is a schematic flow chart of determining an initial road network provided in the present application, and as shown in fig. 10, a line segment firstly encloses three adjacent vertices into a triangle, and the line segment is an effective partition line inside the polygon, otherwise, the line segment is an ineffective partition line, as shown in fig. 10; secondly, selecting the shortest effective partition line, and completing triangle division by the triangle surrounded by the line segment. Excluding vertices no longer connected to the polygon at the time of next partitioning, as in (b) of fig. 10; then, the first two steps are repeated with the remaining vertices continued until the triangulation is completed, as shown in (d) of fig. 10.

This allows the initial road network for each passable area to be determined. And then, judging whether the initial road network is the road network needing to be optimized or not according to the height information for each initial road network. Here, the initial road network in which the difference between the fitted height and the actual height does not satisfy the requirement of the preset threshold is determined as the road network to be optimized.

When determining whether the initial road network is the road network to be optimized, determining whether a difference value between the fitting height and the actual height of each triangular surface in the initial road network is a preset threshold requirement or not, and when determining that the height after any triangular surface is fitted does not meet the preset threshold requirement, determining the initial road network as the road network to be optimized. Wherein the actual height may be determined by a solid height three-dimensional model. When determining the initial road network, it is necessary to determine the height of each triangular surface in the initial road network.

After the road network to be optimized is determined, determining the sample nodes influencing the fitting effect, and determining at least one sample node corresponding to the road network to be optimized. Then, aiming at the area to be optimized corresponding to each road network to be optimized, connecting the contour vertex of the area to be optimized and at least one corresponding sample node by adopting a triangular surface division method, and re-determining the initial road network corresponding to the area to be optimized.

For example, please refer to fig. 11, where fig. 11 is a schematic flowchart of an initial road network optimization process provided in the present application. Excellence inBefore the change, select the sample node that influences the fitting effect, the screening process specifically includes the following steps: first, a sample vertex mesh is constructed within the bounding region AABB of the XZ plane of the triangular mesh, as in (a) of fig. 11. The coordinates of the sample vertex in the XZ projection are expressed as P (XZ), and the value of the Y axis of the vertex is expressed as P (Y); next, the sample vertices outside the mesh are discarded as in (b) of FIG. 11, and in the remaining n height sample nodes Pn, the matching formula H (Y (V) is filtered _k ）-HF（V _k ））=|Y（V _k ）-HF（V _k ) Node P of |iForming a node list, (where Y (V) _k ) To fit height, HF (V) _k ) As a real height). And then screening out at least one sample node influencing the fitting effect of the road network to be optimized according to the following sample node screening formula. The screened sample nodes are shown as square dots in (b) in fig. 11.

Wherein D (P (XZ) -P (Y)) represents PiThe distance from the ZX plane where the point lies to the Y axis, Hignore, represents a negligible height. For example, please refer to fig. 12, fig. 12 is a schematic diagram of the fitting effect of the road network provided by the present application, in fig. 12, (a) the selection of Hignore is too small, which results in road network over-fitting, and the amplitude of each step is fitted; in fig. 12 (b), Hignore is too large, which results in the road network being under-fitted, the level of the intermediate platform disappears, and the road network does not conform to the actual road. Therefore, it is necessary to select a proper threshold value to obtain a normal fitting road network as shown in (c) of fig. 12, where the Hignore value is selected to be 0.5 m.

And continuing to refer to fig. 11, after determining the sample nodes influencing the fitting effect, adding the sample nodes into the polygon, and outputting the initial road network of which the region to be optimized is optimized through a triangular surface division method of the sample nodes which must pass through the inside of the polygon. The specific method includes the following main loop iteration, deleting the edges of the original triangular mesh close to the sample nodes to form polygons, sequencing the sample node values obtained in the sample node screening formula, connecting the maximum value point with all the vertexes of the polygons only as shown in (c) in fig. 11, and then deleting the maximum value point from the sample node set. And performing the above operation on the rest sample nodes until all the nodes in the list are traversed. The final division result is shown in (d) in fig. 11.

And finally, determining a target road network which meets the traffic requirement of the target main body according to all the determined initial road networks. Wherein, all road networks comprise an initial road network which is not optimized and/or an initial road network which is optimized.

For example, please refer to fig. 13, where fig. 13 is a schematic diagram of a local target road network provided in the present application.

S104, starting from a target starting point, performing path search on the target road network by adopting a path search algorithm until a target end point is reached, and stopping to obtain at least one path; each of the at least one path is a route formed by connecting center points of triangular surfaces through which the target body starts from a target start point to a target end point.

After the self-adaptive trafficable region of the target body is divided into a series of triangular surfaces, indoor path planning is needed. Here, a path search algorithm is first adopted to perform a path search on the target road network from the target starting point until reaching the target end point, so as to obtain at least one path. The path search algorithm employed is not limited to a particular algorithm.

In an embodiment provided by the present application, the performing, from a target starting point, a path search on the target road network by using a path search algorithm until reaching a target ending point to obtain at least one path includes: a, determining a triangular surface where a target starting point is located, determining the triangular surface as a starting triangular surface, and storing the starting triangular surface into a passable triangular mesh list; wherein, only the starting triangle surface is included in the passable triangular mesh list at this time; b, determining a passable triangular surface with an adjacent edge to the starting triangular surface, and storing the passable triangular surface into a passable triangular mesh list; c, determining whether the passable triangular surface comprises the target end point, if not, executing a step D, and if so, executing a step E; d, determining a target passable triangular surface with the shortest distance to the end point from the passable triangular surfaces, determining the target passable triangular surface as a starting triangular surface, and returning to execute the step B; e, traversing the central point of each passable triangular surface from the target starting point to the target end point according to the adjacent relation of the passable triangular surfaces in the passable triangular grid list, and determining at least one path from the target starting point to the target end point.

Here, the triangular surface mesh list is added with triangular surfaces with adjacent edges which can be reached next, and the triangular surfaces are called passable triangular surfaces, and the initial triangular surface is also a passable triangular surface. The triangular meshes in the list of passed paths are all meshes that do not need to be explored again at present.

When a target passable triangular surface with the shortest distance to the end point is determined from the passable triangular surfaces, the passable triangular surface corresponding to the shortest distance can be selected as the target triangular surface by calculating the distance between the center point of the triangular surface and the end point; the distance between any point of the triangular surface and the end point can be calculated, and the passable triangular surface with the shortest distance can be selected as the target triangular surface.

For example, referring to fig. 14, fig. 14 is a schematic diagram of a passable triangular surface mesh determined after performing a path search according to the present application. As shown in fig. 14, the five-pointed star position represents the target end point, the triangle position represents the target start point, the passable triangular surface determined by the above path search algorithm is as shown in fig. 14, and as can be seen from (a) in fig. 14, after the passable triangular surface is determined, at least one path from the target start point to the target end point can be determined.

And S105, screening the target path with the shortest travel distance of the target main body from the at least one path.

Here, after at least one route is determined, the travel distance of each route may also be determined, and the shortest travel distance is screened out as the target route according to the determined travel distance.

For example, as shown in fig. 14 (b), the route is the route in which the target subject travels the shortest distance from the starting point to the end point, that is, the target route.

S106, optimizing the target path to obtain an indoor path of the target main body moving in the target place.

Here, after the target path is determined, the obtained target path is not necessarily an optimal path required when the target subject moves in the target location, and therefore the target path needs to be optimized to determine an optimal path, that is, an indoor path when the target subject moves in the target location.

In an embodiment provided by the present application, the optimizing the target path to obtain an indoor path along which the target subject moves in the target location includes: determining whether straight lines from a target starting point to a target end point are all located in a triangular surface mesh through which the target path passes; when the indoor path is the straight line, determining a straight line from the target starting point to the target end point as the indoor path; if not, selecting at least one target node from the candidate end points, so that the target node and the start point are sequentially connected from the target start point to the target end point until the target node and the start point are connected to the target end point according to the sequence from near to far, the shortest driving path is obtained, and the shortest driving path is determined to be the indoor path; the candidate end point is an end point of a common edge of adjacent triangular faces in the triangular face mesh through which the target path passes.

Here, the determined indoor route is a route having the shortest distance from the target start point to the target end point.

For example, as shown in fig. 14, it can be seen from (b) in fig. 14 that the current path is very tortuous, inaccurate and beautiful, so that a path optimization process is required, which is performed based on the triangular surface through which the target path passes.

The method comprises the steps of optimizing a shortest navigation grid according to a set optimization rule, and obtaining a shortest path from an end point to a starting point, namely the indoor path.

For example, please refer to fig. 15, and fig. 15 is a schematic flow chart illustrating an implementation flow of a path optimization rule provided in the present application. Before actually starting the optimization path, two items of data need to be extracted: 1. extracting all edges adjacent to the two triangular meshes to be used as a moving line through which the starting point passes when the path is optimized, such as a dotted line in fig. 15; 2. and starting to judge the left vertex and the right vertex by the action line of the mesh where the target starting point is located (the types of the left endpoint and the right endpoint on each action line are opposite to each other), and traversing until the action line of the mesh where the target end point is located, wherein the vertex is a mobile node. When the route searching starts, the target starting point is used as the starting node of the optimized path, and the starting point is connected with the left-right moving end point of the nearest moving line to form an included angle

As shown in (a) of fig. 15, optimization of the shortest navigation grid needs to be sequentially performed according to the proposed optimization rule until the shortest navigation grid is connected to the target end point, and finally the shortest path from the target end point to the target start point is obtained, as shown in (j) of fig. 15.

The optimization path rule provided by the algorithm specifically comprises the following contents:

rule one is as follows: starting to pass through the action line from the starting node (the beginning is the target starting point), and finishing to the action line of the grid where the target end point is located by passing through the action line one time;

rule two: one of the left and right moving lines is updated through the moving line, if the new left and right moving line forms an included angle

When the moving line becomes smaller, the moving line is considered to pass through the moving line, as shown in fig. 15 (a) to 15 (f); the moving lines are respectively shown as a single-dot dashed line and a straight line connected with the initial node in fig. 15;

rule three: the left and right moving lines are updated alternately as shown in fig. 15 (a) to 15 (f);

rule four: if the updated moving line forms an included angle

Becomes larger, then returns to the state before updating, and then exchanges the moving right of the moving line as (f) in fig. 15 to (g) in fig. 15;

rule five: if the line is updated to make the two lines intersect, i.e. form an included angle

Produces (h) in change 15. The mobile node to which the previously updated mobile line is connected needs to be updated to (g) in the origination node 15 and then two origination nodes are connected as an optimized path. And constructs a left and right movement line from the start of the new start node, and restarts the optimization path as shown in (i) of fig. 15.

In another embodiment provided by the present application, the optimizing the target path to obtain an indoor path along which the target subject moves in the target site includes: extracting a common edge of an adjacent triangular surface in the triangular surface mesh through which the target path passes, taking the common edge as a moving line to be passed when the target path moves from the target starting point to the target end point during path optimization, and determining a target vertex to be traversed based on the moving line from the target starting point; the target vertex comprises a left vertex and a right vertex; according to the moving direction of the target path, alternately connecting the target starting point and the target vertex in sequence to determine a moving line corresponding to the moving line; the moving lines comprise a left moving line and a right moving line; after each moving line is determined, judging whether the moving line passes through all the moving lines before the moving line corresponding to the moving line; if not, determining the previous vertex on the same side as the moving line as the starting node, taking the starting node as a new target starting point, continuing path optimization from the new target starting point until the judgment on whether all the moving lines pass through the corresponding moving lines is completed, and determining at least one starting node; if so, judging whether the next moving line passes through all the moving lines before the moving line corresponding to the moving line until the judgment on the last moving line is finished; after judgment is finished, when at least one starting node exists, sequentially connecting the starting node and the target starting point until the target starting point is connected to the target end point according to the determined sequence of the starting node, and taking a path formed after connection as the indoor path of the target main body moving in the target place; and when the starting node does not exist, performing point connection according to a target starting point and a target end point, and taking a path formed after connection as the indoor path of the target main body moving in the target place.

In addition, the application also provides experimental data for indoor planning based on the method and other methods, so that the beneficial effects of universality, effectiveness and the like of the method are explained.

For example, referring to fig. 16, fig. 16 is a schematic structural diagram of a building information model used in an experimental process of the present application, and the experiment is performed based on the following two Building Information Models (BIMs): FIG. 16 (a) shows a floor area of 1483.32m ² The building information model I designs moving areas such as two sections of stairs, a section of short slope and a section of rotary slope. Fig. 16 (b) is a detailed view of the building information model I. FIG. 16 (c) shows a floor area exceeding 40000 m ² Large building information model II. This large model is mainly used to check the path planning efficiency of the proposed method.

In the building information model I, the experimental subjects are disabled persons who need wheelchairs and adults with normal walking ability. The specific parameters of the four action constraints proposed herein are determined for the amount of space occupied by the above subjects and the ability to move, see table 2.

Table 2:

by means of the building information model I, based on the target road network extraction method provided by the text and according to the parameters of the table 2, a road network which meets the requirements of disabled people needing wheelchairs and normal people is established. Referring to fig. 17, fig. 17 is a schematic view of an indoor path determined during the experiment of the present application, and comparing fig. 17 (a) with fig. 17 (b), it can be seen that in the road network of the handicapped person who needs a wheelchair, the stairs have been marked as a non-passable area and the slopes are marked as passable areas. Finally, based on the same starting and ending points, the shortest path conforming to the movement capability of the subject is queried through the indoor path planning algorithm proposed herein, as shown by the broken lines (a) in fig. 17 and (b) in fig. 17.

According to experimental results, for a given starting point and a given terminal point, the BIM map extraction and path planning method facing any navigation subject can plan the shortest paths based on different subjects, and the query result has high practical use value in indoor path planning.

In order to further test the efficiency of the path query and the practicability of the path, the building information model I and the floor area exceed 40000 m ² The random 8 sets of start and end points in the large building information model II are tested. Wherein the model I adopts a unit cell with the grid size of 15cm multiplied by 15 cm. In order to improve the query efficiency of the large model, the model II adopts a cell with the grid size of 45cm multiplied by 45 cm.

First, the efficiency of the BIM map extraction and path planning method for any navigation subject is evaluated, as shown in table 3. In the experiment, the path planning time used by the method is compared with the path planning time of applying the Bi-A algorithm to the grid road network and the path planning time of applying A + Dijkstra to the grid-based topological road network, and the path planning is carried out by taking a main body as a normal person.

Table 3:

from the experimental results, in the experiment of the model I, although the path planning algorithm based on the raster network is performed by adopting the bidirectional Bi-a algorithm, the path planning efficiency is still poor, and the average time is 8.64 s; the A + Dijkstra planning efficiency of the grid-based topological road network and the Dijkstra planning efficiency of the topological road network are better in performance, and the average time consumption is only 1.19s and 1.11s (the Dijkstra algorithm is slightly faster than the A + Dijkstra algorithm, because the A + Dijkstra algorithm needs to search the topological line closest to the start point and the end point through the diffusion principle, but the paths planned by the Dijkstra algorithm have the problems of wall penetration, detour and the like); based on the path planning efficiency performance provided by the method, the average time is only 0.30s, the planning efficiency is far higher than that of the former two methods, and compared with A + Dijkstra planning efficiency, the efficiency of the method provided by the application is improved by 2.5 times.

In the experiment of the model I, the bidirectional Bi-A algorithm based on the grid network has extremely poor performance in the aspect of path planning efficiency, and the average time length is 65.57 s. In the large model, the A + Dijkstra planning efficiency of the grid-based topological road network and the Dijkstra planning efficiency of the topological road network still perform well, and the average time consumption does not exceed 4 s. Based on the path planning efficiency provided by the method, the path planning efficiency is excellent, the average time is only 0.40s, and the method is not influenced by the size of the model body.

Experiments with different algorithms and models with different quantities prove that the method provided by the application has high efficiency compared with other algorithms, and can meet the requirements of users on planning efficiency.

In addition, the lengths of the routes planned by the respective laws and regulations are compared, and as shown in table 4, the routes are planned by taking the main body as a normal person. From experimental data, in the experiment of the model I, the path distance inquired by the path planning algorithm provided by the invention is shortest, and the average path length is 63.32 m; the average paths planned by the grid network-based Bi-A algorithm, the grid network-based A + Dijkstra algorithm and the topology network-based Dijkstra algorithm are about 2-4m more than those planned by the method. In the experiment of the model II, compared with the paths planned by the other three algorithms, the path distance inquired by the path planning algorithm provided by the invention is still shortest, and the path length difference is about 8m-12 m. The verification proves the effectiveness of the method provided by the invention, and the requirement of planning the shortest path for the main body can be met while the requirement of the main body is met.

Table 4:

Referring to fig. 18, fig. 18 is a schematic structural diagram of a BIM map extraction and path planning apparatus for any navigation subject according to an embodiment of the present application, where the BIM map extraction and path planning apparatus 1800 includes:

an obtaining module 1810, configured to obtain multiple action constraints of a target subject and a building information model of a target site where the target subject is to enter; wherein the action constraint is selected according to the size of the space occupied by the target subject and the mobility of the target subject;

a constructing module 1820, configured to construct a continuous span area corresponding to the target subject according to multiple action constraints of the target subject and a building information model of a target site into which the target subject is to enter; the continuous span area comprises at least one passable area and/or at least one impassable area through which the target body moves;

the dividing module 1830 is configured to perform triangular surface division on the passable area by using a triangular surface dividing method for the at least one passable area, so as to obtain a target road network meeting the passing requirement of the target main body; the target road network is a road network consisting of a plurality of triangular surfaces;

a searching module 1840, configured to perform path search on the target road network by using a path search algorithm from a target starting point until a target end point is reached, so as to obtain at least one path; each path in the at least one path is a route formed by connecting center points of triangular surfaces through which the target main body starts to reach a target end point from a target start point;

a screening module 1850 for screening the target path having the shortest distance traveled by the target subject from the at least one path;

an optimizing module 1860, configured to optimize the target path to obtain an indoor path along which the target subject moves in the target location.

Optionally, when the action constraint conditions include a maximum passable slope, a minimum passable height, a maximum climbing height, and a minimum passable width, the constructing module 1820, when configured to construct a continuous span region corresponding to the target subject according to the plurality of action constraint conditions of the target subject and a building information model of the target subject to enter the target site, is configured to:

Optionally, when the building module 1820 is configured to screen obstacles in the building information model under the constraints of the maximum passable slope and the minimum passable height, and determine a physical height three-dimensional model of the target site, the building module 1820 is configured to:

Optionally, when the building module 1820 is configured to screen passable areas and non-passable areas in the three-dimensional model of the height of the entity under the constraints of the maximum climbing height and the minimum passable width, and build a continuous span area corresponding to the target subject, the building module 1820 is configured to:

Optionally, when the dividing module 1830 is configured to perform triangular surface division on the passable area by using a triangular surface dividing method for the at least one passable area to obtain a target road network meeting the target subject passage requirement, the dividing module 1830 is configured to:

Optionally, when the dividing module 1830 is configured to identify and process the boundary contour of each region in the continuous span region, and determine the target boundary contour line of each region in the target location, the dividing module 1830 is configured to:

Optionally, the search module 1840 is configured to, when the search module 1840 is configured to perform a path search on the target road network by using a path search algorithm from a target starting point until a target ending point is reached, so as to obtain at least one path, where the search module 1840 is configured to:

if yes, according to the adjacent relation of the passable triangular surfaces in the passable triangular grid list, traversing the central point of each passable triangular surface from the target starting point to the target end point, and determining at least one path from the target starting point to the target end point.

Optionally, when the optimization module 1860 is configured to optimize the target path to obtain an indoor path of the target subject moving in the target site, the optimization module 1860 is configured to:

Referring to fig. 19, fig. 19 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 19, the electronic device 1900 includes a processor 1910, a memory 1920, and a bus 1930.

The memory 1920 stores machine-readable instructions executable by the processor 1910, when the electronic device 1900 runs, the processor 1910 communicates with the memory 1920 through the bus 1930, and when the processor 1910 executes the machine-readable instructions, the steps in the method embodiments shown in fig. 1 to fig. 17 can be executed.

An embodiment of the present application 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 steps in the method embodiments shown in fig. 1 to 17 may be executed.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in software functional units and sold or used as a stand-alone product, may be stored in a non-transitory computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A BIM map extraction and path planning method for any navigation subject is characterized by comprising the following steps:

starting from a target starting point, performing path search on the target road network by adopting a path search algorithm until a target end point is reached and stopping to obtain at least one path; each path in the at least one path is a route formed by connecting center points of triangular surfaces through which the target main body starts to reach a target end point from a target starting point;

optimizing the target path to obtain an indoor path of the target subject moving in the target place;

the action constraints comprise at least one of a maximum passable slope, a minimum passable height, a maximum climbing height, and a minimum passable width;

when the action constraint condition comprises a maximum passable slope, a minimum passable height, a maximum climbing height and a minimum passable width, constructing a continuous span area corresponding to the target subject according to the plurality of action constraint conditions of the target subject and a building information model of a target site to be entered by the target subject, wherein the construction comprises:

2. The method of claim 1, wherein the screening obstacles in the building information model to determine a physical height three-dimensional model of the target site under the constraints of the maximum passable slope and the minimum passable height comprises:

carrying out voxelization processing on the building information model according to a preset spatial resolution, and determining a three-dimensional voxel model of the target place;

3. The method according to claim 1, wherein the screening passable areas and impassable areas in the three-dimensional model of the physical height under the constraints of the maximum climbing height and the minimum passable width to construct continuous span areas corresponding to the target subject comprises:

4. The method according to claim 1, wherein the triangle-surface dividing the passable area by the triangle-surface dividing method for the at least one passable area to obtain a target road network meeting the target main body passage requirement comprises:

connecting the contour vertexes of the passable area by adopting a triangular surface division method to determine an initial road network of the passable area;

for each region to be optimized, connecting the contour vertex of the region to be optimized and at least one corresponding sample node by adopting a triangular surface division method, and determining an initial road network of the optimized region to be optimized;

and determining the initial road networks of all passable areas which are not optimized and the initial road networks of all areas to be optimized which are optimized to form a road network after being combined as a target road network meeting the traffic requirements of the target subject.

5. The method of claim 4, wherein said identifying and processing the boundary contour of each of the regions in the continuous-span region to determine the target boundary contour of each of the regions in the target location comprises:

6. The method according to claim 1, wherein the starting from the target starting point, performing a path search on the target road network by using a path search algorithm until reaching the target end point, so as to obtain at least one path, comprises:

7. The method of claim 1, wherein optimizing the target path to obtain an indoor path for the target subject to move within the target site comprises:

8. A BIM map extraction and path planning device facing any navigation subject is characterized by comprising:

the searching module is used for searching a path of the target road network by adopting a path searching algorithm from a target starting point until a target end point is reached, so as to obtain at least one path; each path in the at least one path is a route formed by connecting center points of triangular surfaces through which the target main body starts to reach a target end point from a target starting point;

the optimization module is used for optimizing the target path to obtain an indoor path of the target main body moving in the target place;

when the action constraint conditions comprise a maximum passable slope, a minimum passable height, a maximum climbing height and a minimum passable width, the building module is used for building a continuous span area corresponding to the target subject according to a plurality of action constraint conditions of the target subject and a building information model of the target subject to enter a target site, and the building module is used for:

9. An electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when the electronic device is operated, the machine-readable instructions being executable by the processor to perform the steps of the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, performs the steps of the method according to any one of claims 1 to 7.