CN111047683A

CN111047683A - Intelligent positioning method based on space collision detection

Info

Publication number: CN111047683A
Application number: CN201911255915.6A
Authority: CN
Inventors: 陈劲松
Original assignee: Dms Corp
Current assignee: Dms Corp
Priority date: 2019-12-06
Filing date: 2019-12-06
Publication date: 2020-04-21

Abstract

An intelligent positioning method based on space collision detection is characterized by at least comprising the following steps: automatically partitioning the three-dimensional space into at least one numbered cubic space; screening available cubic spaces based on the collision modes of the cubic spaces and the model objects, calculating the available positioning point positions obtained by screening positioning data in a data filtering mode and the available cubic spaces in a collision mode of space areas and space point positions, obtaining a collision result capable of determining the track point positions, and automatically connecting the track point positions based on the time attributes of the track point positions to form a moving track. The invention can completely simulate the real position in the three-dimensional space, and realizes the automatic generation and intelligent movement of the standard model.

Description

Intelligent positioning method based on space collision detection

Technical Field

The invention relates to the technical field of collision detection, in particular to an intelligent positioning method based on space collision detection.

Background

Collision detection is an indispensable component in the field of computer graphics and physical simulation, and is a problem that needs to be solved in the research process of the subject direction such as virtual simulation and robot path planning. In recent years, with the continuous development of computer technology, collision detection is widely applied in the fields of computer games, virtual reality and the like, and has become a hot issue of interest to researchers. In the virtual operation, the collision of the virtual surgical instrument with the human tissue is the basis of the deformation calculation and is also the precondition of the cutting operation. In the deformation calculation and model cutting processes, the requirement of an operator on collision detection is high, and the collision detection result not only reflects the basic situation of collision, but also provides detailed collision information for further deformation calculation.

However, the existing space collision detection method has high requirements on computer operation during partition calculation, and more algorithms are involved in the operation process, and may involve proprietary algorithms of infringing third parties, and even a calculation method needs to be created by the existing space collision detection method. Moreover, in the current spatial collision detection method, the partition calculation is performed by relying on a three-dimensional engine developed by the company, which has considerable difficulty for compatibility of the spatial collision detection method. Most of the spatial partitions in the market are two-dimensional positioning, such as map functions of hundredth google and the like, or the rest of three-dimensional companies relate to the application scene. The existing partition calculation also needs to acquire and preliminarily calculate the positioning coordinates by means of a UWB positioning technology, and is complex.

For example, chinese patent CN 107610231 a discloses a dynamic collision detection method for determining whether a polyhedron a and a polyhedron B collide with each other, which is characterized by comprising the following steps: decomposing a polyhedron a into N simple polyhedrons a1, a2, … …, AN, decomposing a polyhedron B into M simple polyhedrons B1, B2, … …, BM, and simultaneously judging whether a collision occurs between a simple polyhedron Ai, i ═ 1, 2, … …, N and a simple polyhedron Bk, k ═ 1, 2, … …, M by using a parallel machine of a Cluster structure or AN SMP structure, if so, a collision occurs between the polyhedron a and the polyhedron B, otherwise, no collision occurs, wherein the method for decomposing the polyhedron a into N simple polyhedrons a1, a2, … …, AN is the same as the method for decomposing the polyhedron B into M simple polyhedrons B1, B2, … …, BM, and comprises the following steps: step 1, obtaining vertex coordinate values of a polyhedron to be processed and vertex sequences of planes forming the polyhedron; step 2, generating a function according to a plane equation to obtain plane equations of all planes forming the polyhedron, wherein the normal vector of each plane points to the outside of the polyhedron; step 3, selecting convex vertexes from the vertex sequence to form a convex vertex sequence; step 4, selecting an unprocessed convex vertex from the convex vertex sequence, projecting an adjacent vertex of the unprocessed convex vertex onto a plane, and obtaining a convex space of the current convex vertex by using a Delaunay triangulation algorithm; step 5, sectioning the current convex vertex and the convex space thereof into independent tetrahedrons from the polyhedron; and 6, judging whether each convex vertex in the convex vertex sequence is read, if so, completing subdivision, and otherwise, returning to the step 4. The patent refers to the collision between a typical model object and a model object, and is applied to collision detection in a virtual environment on the basis of completing a subdivision algorithm of any multi-convex body, and a parallel technology is introduced to improve the real-time performance of the collision detection.

Chinese patent CN 110047143A discloses a continuous collision detection method based on space subdivision and dynamic bounding boxes, which is characterized by comprising the following steps: step 1: constructing a virtual soft tissue model and a virtual instrument model used for collision detection; step 2: calculating the space occupied by the moving path of the detected object, if the moving path of the object to be detected shares the same space, executing the next step, otherwise, quitting the detection; and step 3: constructing dynamic bounding boxes for the moving paths of the objects in the same space, and performing intersection tests on the bounding boxes; if the intersection exists, executing the next step, otherwise, quitting the detection; and 4, step 4: determining the position where collision is possible by bisection, and returning the object to be detected to the position where the primary collision occurs from the actual position by a backtracking technology; and 5: constructing a hierarchical bounding box for the object set which is likely to be contacted and executing bounding box intersection detection; if the intersection of the child node bounding boxes is detected, executing the next step, otherwise, quitting the detection; step 6: accurately detecting whether the characteristics contained in the child nodes in the step 5 collide; if collision is detected, recalculating the position of the object to be detected; otherwise, the position of the object to be measured is unchanged. The method can solve the problems of penetration and missing detection of the discrete collision detection method in virtual operation application, and can greatly improve the calculation efficiency on the premise of ensuring the accuracy. However, this patent still cannot accurately calculate the positioning data of the spatial collision detection.

Furthermore, on the one hand, due to the differences in understanding to the person skilled in the art; on the other hand, since the inventor has studied a lot of documents and patents when making the present invention, but the space is not limited to the details and contents listed in the above, however, the present invention is by no means free of the features of the prior art, but the present invention has been provided with all the features of the prior art, and the applicant reserves the right to increase the related prior art in the background.

Disclosure of Invention

Aiming at the defects of the prior art, the invention provides an intelligent positioning method based on space collision detection, which is characterized by at least comprising the following steps:

automatically partitioning the three-dimensional space into at least one numbered cubic space;

screening available cubic spaces based on the collision patterns of the cubic spaces with model objects,

calculating the collision mode of the available positioning point locations obtained by screening the positioning data in a data filtering manner and the available cubic space with the space regions and the space point locations and obtaining a collision result capable of determining the locus location,

and automatically connecting the track point positions to form a moving track based on the time attribute of the track point positions.

According to a preferred embodiment, the method for screening available cubic spaces based on the collision mode of the cubic spaces and the model objects comprises the following steps:

calculating a collision result of the cube space and the model object based on a collision mode algorithm of the space region and the space region,

selecting and marking the cubic space with spatial overlapping characteristics with the model object as an available cubic space;

the cubic space that has no spatial overlap features with the model object is selected and marked as unavailable cubic space.

According to a preferred embodiment, the method for calculating the collision mode of the space region and the space point location and obtaining the collision result capable of determining the track point location comprises the following steps:

carrying out spatial position overlapping calculation on the collected positioning point location and the point location of the cubic space to obtain a collision result of the positioning point location in the cubic space, or,

and obtaining a collision result that the positioning point is not in the cubic space.

According to a preferred embodiment, the method for calculating the collision mode between the spatial region and the spatial point location and obtaining the collision result capable of determining the trajectory point location further comprises:

automatically saving the available location points and connecting into a line when the available location points are within the available cubic space,

and forming the locus points by dynamically connecting the positioning points with the available cubes.

and when the available positioning point is not in the available cubic space, deleting the available positioning point and selecting the available positioning point again in a space spreading mode.

According to a preferred embodiment, the method of reselecting an available localization point in a spatially-extended manner when said available localization point is not within an available cubic space comprises:

and when the available positioning point is not in the available cubic space, spreading to the available cubic space around the unqualified available positioning point and selecting at least one new available positioning point in the available cubic space, so as to connect the new available positioning point to form a track point not in the space model.

According to a preferred embodiment, the method for screening available positioning points obtained by the positioning data in a data filtering manner comprises the following steps:

and filtering and removing at least one repeated point based on the distance between two adjacent points, so that an available positioning point location is formed based on the filtered positioning data.

According to a preferred embodiment, the method for automatically partitioning a three-dimensional space into at least one numbered cubic space comprises the following steps:

filtering any convex body to generate coordinate data of 8 vertexes of a standard body space based on the stored space coordinate data of the model object; and

the coordinate data of the standard body space are individually stored in groups of individuals to automatically divide and store the three-dimensional space into at least one corresponding standard body space and an overall space, wherein,

at least one of the standard body spaces is located within the overall space.

According to a preferred embodiment, the method for automatically connecting the locus point positions to form a moving locus based on the time attribute of the locus point positions comprises the following steps:

deviating the available positioning points in the available cubic space according to the set deviation direction principle,

grouping and storing the positioning point locations as trajectory point locations based on time attributes and automatically connecting the trajectory point locations into three-dimensional lines,

wherein, the deviation direction principle is as follows: and taking the normal vector direction of the cubic space surface closest to the positioning point and far away from the cubic space as a deviation direction.

According to a preferred embodiment, the coordinate data of the available positioning point locations are grouped and calculated and stored according to a preset time interval, so that a segmented moving track formed on the basis of each group of coordinate data is formed.

The invention also provides an intelligent positioning device based on space collision detection, which is characterized by at least comprising:

the partitioning module is used for automatically partitioning the three-dimensional space into at least one cubic space with a number;

a first collision module for screening available cubic spaces based on collision patterns of the cubic spaces with model objects,

the second collision module is used for calculating the collision mode of the available positioning point locations obtained by screening the positioning data in a data filtering mode and the available cubic space between the space area and the space point location and obtaining the collision result capable of determining the locus point location,

and the track module is used for automatically connecting the track point positions to form a moving track based on the time attribute of the track point positions.

The invention has the beneficial technical effects that:

in the prior art, most space collision detection generally stays in the collision between a model object and the model object, and in a three-dimensional space, the position coordinates of real personnel positioning have the problem of confusion in the three-dimensional space range of the model object; the positioning information is inaccurate and even disordered, and the technical effect of accurate positioning cannot be achieved. Moreover, the prior art has the following defects: firstly, the positioning process is complex, the objects to be collided must be established through a three-dimensional modeling model, and accurate size and spatial position information must be provided; secondly, the requirement on the environment is high, and the collision of a large batch of model objects with objects has higher operation requirements on hardware and a calculation engine, so that the collision inspection of the large batch cannot be simultaneously carried out, or hardware crash, operation errors and the like are easily caused; thirdly, the real-time performance is not realized, and response can not be timely carried out on some dynamic collisions to obtain results; fourthly, the method is not special, is carried out on the market, has no new content and is not strong in ductility. According to the invention, through performing collision calculation between the cubic space and the model object in the three-dimensional space, the problem that the position coordinates of real personnel positioning are mixed in the three-dimensional space range of the model object can be avoided, so that the positioning is more real and accurate. The invention can overcome the defects of the prior art: the position coordinates of the personnel can be obtained in real time, and the collision calculation of the invention can obtain the calculation result in real time and optimize the personnel path; the invention can also correct the deviation in time, and correct guidance can be obtained in time through collision calculation after the personnel coordinates collide with the model object, so that the personnel coordinates can be closer to the real situation when displayed in the three-dimensional engine.

In the prior art, the spatial point location coordinates are acquired by external hardware, for example, positioning coordinate acquisition and preliminary calculation are performed by means of UWB positioning technology, and the adverse effect of the spatial point location coordinates acquired by the external hardware is as follows: data is easy to damage or lose in the transmission process due to the network environment, and field hardware such as a base station in the UWB technology is easy to be influenced by the environment and sends error data; the algorithm of a positioning engine (a calculation engine of the UWB technology) is not intelligent enough, and the data has no deviation rectifying algorithm. The spatial point position coordinate is determined by the collision calculation of the spatial point position and the spatial region, is dynamically generated, avoids the technical problem of inaccurate moving track caused by spatial point position error, and has high positioning accuracy.

Furthermore, the current market basically stays in dynamic movement on a two-dimensional interface, such as generating a point on a plane and moving through pixel point positions. The negative effects of movement on a two-dimensional interface are: the positioning is relatively unilateral, the position and the moving track of the third dimension cannot be positioned, the actual position scene of real personnel is not close enough, and the deviation of the display effect is large. Wherein the two-dimensional model shows a relatively solid, less accurate, e.g. a positioning datum actually moves to a side of the device, but cannot be represented on the two-dimensional map; moreover, the two-dimensional graph has no zooming effect, because two dimensions are basically converted, positioned and displayed through picture pixel points, for a large-scale positioning area, if one point is positioned, the two-dimensional graph cannot be accurately and correctly expressed on the two-dimensional graph. The invention can zoom in the three-dimensional space through the data acquisition of the three-dimensional space and the data calculation of the three-dimensional space; the three-dimensional scene is an accurate model, the relative spatial position and the size of a model object are accurate, and any spatial point position can be rapidly and accurately displayed and simulated; the personnel positioning system can accurately acquire and position, and the three-dimensional scene display effect is close to the actual position scene of real personnel as much as possible.

Drawings

FIG. 1 is a simplified logic block diagram of the present invention;

FIG. 2 is a diagram of a person positioning trajectory in three-dimensional space of the present invention; and

FIG. 3 is a schematic diagram of an avatar walk in a three-dimensional model.

List of reference numerals

A is an available cube; b: an unavailable cube; d: calculating points intelligently; RT: a real route; RI: and (4) intelligent routes.

Detailed Description

The following detailed description is made with reference to the accompanying drawings.

The problem that coordinates for positioning personnel are mixed in the space range of a model object is solved; the invention also discloses an intelligent positioning method and device based on space collision detection, and aims to solve the technical problem that the three-dimensional scene display effect cannot be close to a real scene when people are inaccurately positioned. The invention also relates to a three-dimensional object generation method and a system, and a three-dimensional environment generation method and a system based on the three-dimensional object.

Example 1

An intelligent positioning method based on space collision detection is characterized by at least comprising the following steps: automatically partitioning the three-dimensional space into at least one numbered cubic space; screening available cubic spaces based on the collision modes of the cubic spaces and the model objects, calculating the available positioning point positions obtained by screening positioning data in a data filtering mode and the available cubic spaces in a collision mode of space areas and space point positions, obtaining a collision result capable of determining the track point positions, and automatically connecting the track point positions based on the time attributes of the track point positions to form a moving track.

Compared with a positioning method for space collision detection of a two-dimensional section, the positioning method for the three-dimensional space can be closer to a real scene in actual life, so that the defects of large deviation and inaccuracy of two-dimensional data relative to the real scene are overcome, and a more real and accurate moving track is displayed.

Preferably, the method for screening available cubic space based on the collision mode of the cubic space and the model object comprises the following steps:

calculating a collision result of the cube space and the model object based on a collision mode algorithm of the space region and the space region;

Compared with the traditional collision calculation method using the collision between the model object and the model object, the cubic space obtained by the collision between the space region and the model object can filter out irrelevant space data in advance, and the calculation amount and the error rate of subsequent data are reduced. Furthermore, the collision between the space region and the model object enables the dynamic screening result of the available cube space to be accurately exchanged, and the delay time of the space data is reduced. The invention also stores and calculates the data through the setting of the database, not only calculates in the three-dimensional scene, but also can fully reduce the high requirements on hardware configuration, and has real-time performance and historical performance.

Preferably, the method for calculating the collision mode between the spatial region and the spatial point location and obtaining the collision result capable of determining the locus point location comprises the following steps:

and carrying out spatial position overlapping calculation on the collected positioning point location and the point location of the cubic space to obtain a collision result of the positioning point location in the cubic space, or obtain a collision result of the positioning point location not in the cubic space.

According to the invention, a collision calculation mode of the space point location and the space area is used, a batch of positioning point locations can be dynamically obtained, and the screening accuracy of available positioning point locations is improved. And for unavailable positioning points, deletion is facilitated in advance, and the processing amount of subsequent spatial data is reduced. The method not only realizes a better technical effect that the three-dimensional scene is close to a real scene, but also can improve the calculation speed of data.

Preferably, the method for calculating the collision mode between the spatial region and the spatial point location and obtaining the collision result capable of determining the trajectory point location further includes:

and when the available positioning point is in the available cubic space, automatically storing the available positioning point and connecting the available positioning point with a line, and forming a track point by dynamically connecting the positioning point with the available cubic space. And the final personnel walking track point location is formed by comprehensively and intelligently connecting the available positioning point location with the available cubic space.

According to the invention, through dynamic collision between the space region and dynamic collision between the space region and the positioning point location, the space point location which is orderly, regular and reasonably distributed in the three-dimensional space can be automatically generated, and the real position of the object can be completely simulated.

And when the available positioning point is not in the available cubic space, deleting the available positioning point and selecting the available positioning point again in a space spreading mode. When the available positioning point location is not in the available cubic space, the method for reselecting the available positioning point location in a space spreading mode comprises the following steps: and when the available positioning point is not in the available cubic space, spreading to the available cubic space around the unqualified available positioning point and selecting at least one new available positioning point in the available cubic space, so as to connect the new available positioning point to form a track point not in the space model.

When the available positioning point is not in the available cube space, the method has no simple deletion solution, and partial data is lost by the simple deletion mode, so that the moving track is partially lost and inaccurate. According to the invention, through a spatial spreading mode, the nearest available positioning point location capable of being used is used for supplementing the position of point location loss, so that the final trajectory of personnel movement is always not in the spatial model and is always closer to the actual route.

Preferably, the method for screening the available positioning points obtained by the positioning data in a data filtering manner comprises the following steps: and filtering and removing at least one repeated point based on the distance between two adjacent points, so that an available positioning point location is formed based on the filtered positioning data. The invention can repeatedly filter the data without being limited to one time so as to eliminate unnecessary repeated data as much as possible, thereby obtaining accurate available positioning point positions, reducing subsequent data processing amount and improving the accuracy of the formation of the moving track. Preferably, the data filtering method for positioning data according to the present invention further includes: and point positions in two adjacent time points are filtered and supplemented, so that the data consistency is ensured.

Preferably, the data filtering method for positioning data according to the present invention further includes: repeated data is filtered, for example, a plurality of same data exist at a time point, and the number of the same data is filtered to 1.

Preferably, the data filtering method for positioning data according to the present invention further includes: the fixed interval is filtered, and redundant point positions in the same small interval can be filtered. Preferably, the fixed interval represents a difference between a point and a point.

Preferably, the method for automatically partitioning the three-dimensional space into at least one cubic space with numbers comprises the following steps:

filtering any convex body space to generate coordinate data of 8 vertexes of a standard body space based on the stored space coordinate data of the model object; and the coordinate data of the standard body space are independently stored by taking an individual as a group so as to automatically divide and store the three-dimensional space into at least one corresponding standard body space and an integral space. Wherein at least one of the standard body spaces is located within the overall space. The standard body space is a cubic space. The three-dimensional model is generated in a data configuration driving mode.

The automatic partitioning method has the advantages that any convex body space is simplified into the standard body space, so that the model is prevented from being complicated, the data calculation is simplified, the standard body space can be closer to the real convex body space, and the accuracy of the moving track in the three-dimensional space is improved.

Preferably, the method for automatically connecting the locus point positions to form the moving locus based on the time attribute of the locus point positions includes:

deviating the available positioning point locations in the available cubic space according to a set deviation direction principle, grouping and storing the positioning point locations as track point locations based on time attributes, and automatically connecting the track point locations into three-dimensional lines, wherein the deviation direction principle is as follows: and taking the normal vector direction of the cubic space surface closest to the positioning point and far away from the cubic space as a deviation direction. And the deviated positioning points still have time attributes, so that point ordering and line forming are facilitated. The advantage of setting the deviation calculation is that firstly, the correctness of the point position after the deviation calculation can be ensured; secondly, the calculation result can be ensured to accord with the calculation principle of a space three-dimensional engine, and the concept of a space coordinate system is provided; thirdly, deviation calculation accords with the real walking logic of the site, and the calculated and simulated point position can meet the requirement of simulated playback display of the position of the person.

Preferably, the coordinate data of the available positioning point locations are grouped and calculated and stored according to a preset time interval, so that a segmented moving track formed based on each group of coordinate data is formed. That is, after all the point locations are generated and arranged, the point locations are stored in groups according to time sequence,

the moving track of the invention is shown in a three-dimensional space model, and the line is automatically generated in a section along with the movement of time, and the position and the time of the line are reasonable.

Example 2

This example is a practical implementation of example 1.

As shown in fig. 1, the intelligent positioning method based on spatial collision detection of the present invention at least includes the following steps:

s1: and acquiring positioning data and loading the three-dimensional model so as to form a three-dimensional scene model.

Preferably, the acquisition mode of the positioning data comprises dynamic acquisition and static acquisition.

Dynamic collection: the dynamic data has a point location (xyz) for each second, and the point locations are collected one by one as time goes by.

Static collection: the static data is obtained from all historical point location data within a period of time at a time, and is a batch of data. The data contents are basically consistent and are all point locations (xyz), and the coordinate system of the point locations and the coordinate system of the three-dimensional model are unified.

The data point location will have a point in time. When points are connected into a line, the connection sequence is fixed, and the line trend is consistent with the actual line trend, so that the accuracy of the direction of the subsequent optimal route is ensured conveniently.

S2: and automatically partitioning the divided cube space and marking the category.

Dividing a three-dimensional space range where a model in a three-dimensional scene is located into a plurality of three-dimensional space regions such as N-N squares or cubes, and automatically numbering each cube space. Wherein the degree of fineness of the three-dimensional space region cutting is not limited to 30cm, and can be adjusted according to the fineness of personnel positioning, for example, N can be 50cm, 30cm, 20cm and 10 cm.

The method for automatically partitioning the cubic space comprises the following steps:

s21: and guiding the three-dimensional model into a three-dimensional engine processor after the three-dimensional model is lightened.

S22: a display coupled to the three-dimensional engine processor displays all of the model objects. Wherein each model object is a space occupied by one.

S23: the spatial coordinates (xyz) of each model object are received and stored within a database of the three-dimensional engine.

S24: after receiving the spatial coordinates of the model object, any complex convex body is taken as a standard body to consider the subsequent application. For example, based on the spatial coordinate values of the model object, 8 vertex coordinates that generate a standard volume may be filtered.

S25: each standard body is a set of data within the database. The data for each standard body is stored individually in groups within the database. Namely, a plurality of corresponding cubic spaces, namely, regions are generated, so that the whole three-dimensional space is divided into a plurality of independent scattered standard body spaces and a whole large space, and the standard body spaces are in the whole large space.

S3: the cubic space is marked by a dynamic collision result of the spatial region with the spatial region based on the collision mode.

Specifically, whether the cube space overlaps with the model object is calculated by an algorithm of the collision mode. Preferably, the algorithm of the collision mode may be a comparison and calculation of coordinates of the cube space and the model object, calculating whether it is in the overlapped three-dimensional space.

S31: the cube space is marked as available cube space in the case where the cube space overlaps with the model object.

S32: in the case where the cube space does not overlap with the model object, the cube space is marked as an unavailable cube space.

S4: and after the positioning data is collected, the collected positioning data is processed in a data filtering mode.

The data is filtered in a mode that repeated point filtering removal is carried out according to the distance between two adjacent points, so that available positioning point positions are formed.

S5: the anchor points are marked by the dynamic collision result of the anchor points with the spatial region based on the collision mode. And the positioning point location is collided with the three-dimensional model generated by the data configuration.

Preferably, currently in actual operation, the collision mode is to collect 8 point positions in the standard body space for calculation, and obtain a result:

the result is as follows: the point is located in the standard body, namely the available locating point is located in the available cube; or

And a second result: the points are not within the standard volume, i.e., the available locating points are not within the available cube, and the available locating points are within the unavailable cube.

S51: when the available location points are within the available cube, the available location points are automatically saved and connected into a line.

S52: and when the available point location is in the unavailable cube, the locating point location is not stored and deleted. Directly and automatically extending into the peripheral available cube to form an available point position in the available cube, so that the final personnel movement track is always not in the space model and is always relatively close to an actual route;

s6: and forming a final track point location through comprehensive intelligent connection of the saved available positioning point location and the available cubic space, namely generating an available route.

S61: when the available location point is within the available cube, the location point is deviated.

Wherein, the principle of deviation direction is as follows: and the normal vector of the standard body surface closest to the positioning point, namely the direction of the positioning point far away from the standard body. The deviated positioning point positions still have time attributes, so that point position sequencing and line forming are facilitated.

S62: and after all point locations are generated and sorted, grouping and storing according to time sequence.

Preferably, in the calculation in the case of real-time walking, the point locations are delayed with respect to the true position, preferably in groups of 5s, and are calculated and stored, each group forming a walking route.

S63: according to the time attribute of the point locations, each group of point locations are automatically connected into a line, and the line is a three-dimensional line.

S64: the final effect seen by the user is that the line is automatically generated in a section along with the movement of time, the position and the time of the line are reasonable, and the line is reapplied later

Preferably, in the case of the acquisition point location loss, the three-dimensional engine executes a static standing command to wait for the entry of a newly acquired point location.

If the three-dimensional engine can support each collected point location, one point location can be received and the avatar walking is carried out, and the calculation and the storage of the set time are not carried out on the point location data. For example, the points are not computed and saved in groups of 5 s. In the present invention, as shown in fig. 3, the alvanta walk means: a human model is generated in the three-dimensional scene through point position data to move, which is equivalent to converting the data into a dynamic three-dimensional model object to be played in a virtual environment.

S7: available routes are shown.

The display diagram of the person positioning trajectory in the three-dimensional space shown in fig. 2 is shown, in which a represents an available cubic space and B represents an unavailable cubic space. The solid line RT represents the real route, and the broken line RI represents the positioning trajectory route. The circle D symbol represents the smart computation point. Compared with a real route, the broken-line intelligently-planned positioning track route is formed by connecting available positioning points in an available cube space, so that the positioning is more accurate, the recommended route is simpler and quicker, and the path is obviously shorter.

Example 3

This example is a further modification of example 1 or example 2,

the embodiment discloses an intelligent positioning system based on space collision detection, which can also be an intelligent positioning device based on space collision detection, and can also be an intelligent positioning module based on space collision detection. The apparatus/system/module of the present invention includes at least a processor and a database. The processor and the database are in data connection in a wired or wireless mode. The database can be various data processing hardware with a storage function, such as a memory, a memory chip, a storage server, a cloud server, and the like. The database is used for storing data with time attributes of a plurality of cube spaces and positioning point positions.

Preferably, the processor of the present invention is provided with a data processing program of a three-dimensional engine, and is capable of realizing a related data function. Preferably, the processor of the present invention is not limited to a single data processing chip, but may be a combination of several data processing chips. Alternatively, the processor may be a server, a server farm, or a collection of application specific integrated chips and their application specific integrated chips with associated data processing functionality.

Preferably, the present invention includes a display device, such as a display, in data connection with the processor for displaying the three-dimensional model and the movement trajectory, and a display interface of the display device is shown in fig. 2.

The processor is configured to:

the system comprises a three-dimensional space, a control unit and a display unit, wherein the three-dimensional space is automatically partitioned into at least one cubic space with numbers;

Preferably, the processor is further configured to:

Preferably, the method for the processor to calculate the collision mode between the spatial region and the spatial point location and obtain the collision result capable of determining the locus point location comprises the following steps:

Preferably, the processor is further configured to:

when the available location points are in the available cubic space, the database automatically stores the available location points and is connected into a line by the processor,

and the processor forms the locus points by dynamically connecting the positioning points with the available cubes.

Preferably, the processor is further configured to:

at least one of the standard body spaces is located within the overall space.

Preferably, the processor is further configured to:

the database stores the positioning point locations in groups as track point locations based on time attributes, the processor automatically connects the track point locations into three-dimensional lines,

Preferably, the processor is further configured to:

and grouping the coordinate data of the available positioning point positions according to a preset time interval, calculating and storing the coordinate data into a database, and thus forming a sectional type moving track formed on the basis of each group of coordinate data.

The invention also provides an intelligent positioning device based on space collision detection, which at least comprises:

and the track module is used for automatically connecting the track point positions to form a moving track based on the time attribute of the track point positions. The partitioning module, the first collision module, the second collision module and the track module are in data connection with each other respectively. Preferably, the track module is connected with the display device. Preferably, the partitioning module is in data connection with a data input device or a data acquisition device. The data connection mode in the invention comprises wired data connection and wireless data connection. The wireless data connection comprises connection of a plurality of wireless communication modes such as WiFi communication connection, Bluetooth communication connection, ZigBee communication connection and the like.

Preferably, the method for screening the available cubic space by the first collision module based on the collision mode of the cubic space and the model object comprises the following steps:

Preferably, the method for calculating by the second collision module the collision mode between the spatial region and the spatial point location and obtaining the collision result capable of determining the locus point location includes:

Preferably, the method for calculating by the second collision module the collision mode between the spatial region and the spatial point location and obtaining the collision result capable of determining the locus point location further includes:

Preferably, the method for the second collision module to reselect the available location point in a spatially extended manner when the available location point is not within the available cubic space includes:

Preferably, the method for the first collision module to screen the available location points obtained by the location data in a data filtering manner includes:

Preferably, the method for automatically partitioning the three-dimensional space into at least one numbered cubic space by the partitioning module comprises the following steps:

at least one of the standard body spaces is located within the overall space.

Preferably, the method for the trajectory module to automatically connect the trajectory point locations to form the moving trajectory based on the time attribute of the trajectory point locations includes:

Preferably, the track module groups the coordinate data of the available positioning point locations according to a preset time interval and calculates and stores the coordinate data into the database, so that a segmented moving track formed based on each group of coordinate data is formed.

It should be noted that the above-mentioned embodiments are exemplary, and that those skilled in the art, having benefit of the present disclosure, may devise various arrangements that are within the scope of the present disclosure and that fall within the scope of the invention. It should be understood by those skilled in the art that the present specification and figures are illustrative only and are not limiting upon the claims. The scope of the invention is defined by the claims and their equivalents.

Claims

1. An intelligent positioning method based on space collision detection is characterized by at least comprising the following steps:

2. The intelligent positioning method based on spatial collision detection according to claim 1, wherein the method for screening available cubic space based on the collision mode of the cubic space and the model object comprises:

3. The intelligent positioning method based on the spatial collision detection as claimed in claim 2, wherein the method for calculating the collision mode between the spatial region and the spatial point location and obtaining the collision result capable of determining the locus point location comprises:

4. The intelligent positioning method based on spatial collision detection as claimed in one of the preceding claims, wherein the method for calculating the collision mode between the spatial region and the spatial point location and obtaining the collision result capable of determining the trajectory point location further comprises:

5. The intelligent positioning method based on spatial collision detection as claimed in one of the preceding claims, wherein the method for calculating the collision mode between the spatial region and the spatial point location and obtaining the collision result capable of determining the trajectory point location further comprises:

6. An intelligent positioning method based on spatial collision detection according to any one of the preceding claims, wherein when the available positioning point is not in the available cubic space, the method of reselecting the available positioning point in a spatially extended manner comprises:

7. An intelligent positioning method based on spatial collision detection according to any one of the preceding claims, wherein the method for screening available positioning point locations obtained by the positioning data in a data filtering manner comprises:

8. An intelligent positioning method based on spatial collision detection according to one of the preceding claims, wherein the method for automatically partitioning a three-dimensional space into at least one cubic space with numbers comprises:

at least one of the standard body spaces is located within the overall space.

9. The intelligent positioning method based on the spatial collision detection according to one of the preceding claims, wherein the method for automatically connecting the track point locations based on the time attributes of the track point locations to form a moving track comprises:

10. An intelligent positioning device based on spatial collision detection, the device comprising at least: