CN116359942A - Point cloud data acquisition method, equipment, storage medium and program product - Google Patents
Point cloud data acquisition method, equipment, storage medium and program product Download PDFInfo
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Abstract
The embodiment of the application provides a method, equipment, a storage medium and a program product for acquiring point cloud data, wherein the method comprises the steps of acquiring engineering data respectively corresponding to a plurality of engineering tasks corresponding to a target acquisition area, acquiring the engineering data by carrying out data acquisition on the target acquisition area based on the corresponding engineering tasks, and carrying out fusion processing on laser point clouds in the engineering data respectively corresponding to the engineering tasks to acquire target laser point cloud data of the target acquisition area. According to the method, the point cloud map data of the target acquisition area are acquired by dividing the acquisition of the point cloud map data into a plurality of projects, the projects are enabled to completely cover the target acquisition area, after the acquisition of the projects is completed, the point cloud data acquired by the projects are fused, so that the complete point cloud data of the ground object in the target acquisition area can be obtained, and compared with the acquisition of a single project of the target acquisition area, redundant data can be greatly reduced, the acquisition efficiency is improved, and the acquisition cost is reduced.
Description
Technical Field
The embodiment of the application relates to the technical field of high-precision maps, in particular to a method, equipment, a storage medium and a program product for acquiring point cloud data.
Background
The high-precision point cloud map data of the target acquisition area is generally acquired by adopting a single project, so that the complete acquisition of ground objects in the target acquisition area is facilitated.
However, in the above manner, in order to complete collection of the point cloud map data of the ground object in the target area in one project, the method is limited by traffic rules, and many redundant collection routes exist, and in addition, urban roads are congested, so that the collection efficiency is extremely low, and the collection cost is high.
Disclosure of Invention
The embodiment of the application provides a method, equipment, a storage medium and a program product for acquiring point cloud data, so as to improve acquisition efficiency and reduce acquisition cost.
In a first aspect, an embodiment of the present application provides a method for collecting point cloud data, including:
acquiring engineering data respectively corresponding to a plurality of engineering tasks corresponding to a target acquisition area; the engineering data are obtained by carrying out data acquisition on the target acquisition area based on the corresponding engineering task;
and carrying out fusion processing on the laser point clouds in the engineering data corresponding to the engineering tasks respectively to obtain target laser point cloud data of a target acquisition area.
In one possible design, the fusing processing is performed on the laser point clouds in the engineering data corresponding to the engineering tasks respectively to obtain target laser point cloud data of the target acquisition area, including:
carrying out partition processing on laser point clouds in engineering data corresponding to a plurality of engineering tasks respectively to obtain a plurality of laser partitions which are not overlapped with each other;
performing point cloud consistency alignment treatment on the plurality of laser partitions to obtain aligned laser partitions;
and performing edge splicing processing on the plurality of aligned laser partitions to obtain target laser point cloud data of a target acquisition area.
In one possible design, the partitioning processing is performed on the laser point clouds in the engineering data corresponding to the engineering tasks respectively to obtain a plurality of laser partitions without overlapping each other, including:
dividing laser point clouds in engineering data into laser point cloud segments corresponding to a plurality of time periods respectively aiming at engineering data corresponding to each engineering task;
partitioning a plurality of laser point cloud segments of the engineering data to obtain a plurality of laser partitions which are not overlapped with each other.
In one possible design, the dividing the laser point cloud in the engineering data into laser point cloud segments corresponding to a plurality of time periods respectively includes:
dividing the POS track in the engineering data into a plurality of track segments according to the length;
and dividing the laser point cloud in the engineering data based on the time corresponding relation between the POS track and the laser point cloud data to obtain a plurality of laser point cloud segments respectively corresponding to the track segments.
In one possible design, the partitioning the plurality of laser point cloud segments of the engineering data to obtain a plurality of laser partitions without overlapping each other includes:
determining a minimum wrapping range of each laser point cloud segment in a plurality of laser point cloud segments of the engineering data;
and dividing the laser point cloud segments with the overlapping areas in the minimum outsourcing ranges in the multiple laser point cloud segments of the engineering data into the same partition, and obtaining multiple laser partitions which are not overlapped with each other.
In one possible design, after dividing the laser point cloud segments with the overlapping areas in the minimum outsourcing ranges in the multiple laser point cloud segments of the multiple engineering data into the same partition, obtaining multiple laser partitions without overlapping each other, the method further includes:
and adding an isolated laser point cloud segment, of which the minimum outsourcing range and other minimum outsourcing ranges are not overlapped, in the multiple laser point cloud segments of the engineering data into a laser partition with the shortest distance from the isolated laser point cloud segment.
In one possible design, the edge bonding process for the aligned laser partitions includes:
sequentially carrying out edge splicing treatment on the plurality of aligned laser partitions according to an adjacent relation;
and aiming at the current processed partition in the aligned laser partitions, determining the deviation between the current processed partition and the last processed partition and the edge connecting length of the edge connecting area of the current processed partition, and updating coordinates of laser points in the edge connecting area according to the deviation and the edge connecting length to finish edge connecting processing between the current processed partition and the last processed partition.
In a second aspect, an embodiment of the present application provides a device for collecting point cloud data, including:
the acquisition module is used for acquiring engineering data corresponding to a plurality of engineering tasks corresponding to the target acquisition area respectively; the engineering data are obtained by carrying out data acquisition on the target acquisition area based on the corresponding engineering task;
and the fusion module is used for carrying out fusion processing on the laser point clouds in the engineering data corresponding to the engineering tasks respectively to obtain target laser point cloud data of the target acquisition area.
In a third aspect, an embodiment of the present application provides a device for collecting point cloud data, including: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executes the computer-executable instructions stored by the memory such that the at least one processor performs the method as described above in the first aspect and the various possible designs of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored therein computer-executable instructions which, when executed by a processor, implement the method as described in the first aspect and the various possible designs of the first aspect.
In a fifth aspect, embodiments of the present application provide a computer program product comprising a computer program which, when executed by a processor, implements the method as described above for the first aspect and the various possible designs of the first aspect.
The method includes acquiring engineering data corresponding to a plurality of engineering tasks corresponding to a target acquisition area, wherein the engineering data is obtained by acquiring data of the target acquisition area based on the corresponding engineering tasks, and performing fusion processing on laser point clouds in the engineering data corresponding to the engineering tasks to obtain target laser point cloud data of the target acquisition area. According to the method, the point cloud map data of the target acquisition area are acquired by dividing the acquisition of the point cloud map data into a plurality of projects, the projects are enabled to completely cover the target acquisition area, after the acquisition of the projects is completed, the point cloud data acquired by the projects are fused, so that the complete point cloud data of the ground object in the target acquisition area can be obtained, and compared with the acquisition of a single project of the target acquisition area, redundant data can be greatly reduced, the acquisition efficiency is improved, and the acquisition cost is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief description will be given below of the drawings that are needed in the embodiments or the prior art descriptions, it being obvious that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is an application scenario schematic diagram of a method for acquiring point cloud data according to an embodiment of the present application;
fig. 2 is a flow chart of a method for collecting point cloud data according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a device for collecting point cloud data according to an embodiment of the present application;
fig. 4 is a schematic hardware structure diagram of a point cloud data acquisition device according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of 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 apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
The high-precision point cloud map data of the target acquisition area is generally acquired by adopting a single project, so that the complete acquisition of ground objects in the target acquisition area is facilitated. Wherein, an engineering corresponds to a continuous collection of a collection vehicle. For example, the target acquisition area is a road segment AB (the starting point is a and the end point is B), and the road segment AB is acquired by a single project, that is, one acquisition vehicle is used for one continuous acquisition. If the road section AB includes branches, intersections, bidirectional lanes, etc., for these situations, for the sake of completeness of feature collection, it is generally necessary to make round trips on the bidirectional lanes and branches by the collection vehicle, and for complex road conditions such as intersections, it is also necessary to make multiple turns and round trips.
However, in the above manner, in order to complete collection of the point cloud map data of the ground object in the target area in one project, the method is limited by traffic rules, and many redundant collection routes exist, and in addition, urban roads are congested, so that the collection efficiency is extremely low, and the collection cost is high. And the redundant acquisition travel causes data redundancy, occupies storage resources and also causes interference to subsequent data processing. In addition, a single project is too large to process in parallel, resulting in low data processing efficiency.
In order to solve the technical problems, the inventor of the application researches and discovers that the point cloud data acquired by a plurality of projects can be fused after the acquisition of the projects is completed by dividing the acquisition of the point cloud map data of the target acquisition region into the projects, so that the complete point cloud data of the ground object in the target acquisition region can be obtained. Based on the above, the embodiment of the application provides a method for acquiring point cloud data.
Fig. 1 is an application scenario schematic diagram of a method for acquiring point cloud data according to an embodiment of the present application. As shown in fig. 1, the target acquisition area is an intersection, and both of the two paths intersecting the intersection are bidirectional lanes.
In a specific implementation process, the acquisition task of the target acquisition area can be divided into 1 to 8 and eight projects, then the acquisition vehicle is used for carrying out data acquisition on the target acquisition area based on a plurality of engineering tasks to obtain engineering data corresponding to the engineering tasks respectively, terminal equipment or a server is used for obtaining the engineering data corresponding to the engineering tasks respectively, and fusion processing is carried out on laser point clouds in the engineering data corresponding to the engineering tasks respectively to obtain target laser point cloud data of the target acquisition area. According to the point cloud data acquisition method, the point cloud map data of the target acquisition area are acquired by dividing the acquisition of the point cloud map data into a plurality of projects, the projects are enabled to completely cover the target acquisition area, after the acquisition of the projects is completed, the point cloud data acquired by the projects are fused, so that the complete point cloud data of the ground object in the target acquisition area can be obtained, compared with the acquisition of a single project of the target acquisition area, redundant data can be greatly reduced, the acquisition efficiency is improved, and the acquisition cost is reduced.
It should be noted that, the schematic view of the scenario shown in fig. 1 is only an example, and the method and the scenario for acquiring point cloud data described in the embodiments of the present application are for more clearly describing the technical solution of the embodiments of the present application, and do not constitute a limitation on the technical solution provided in the embodiments of the present application, and as one of ordinary skill in the art can know, along with the evolution of the system and the appearance of a new service scenario, the technical solution provided in the embodiments of the present application is also applicable to similar technical problems.
The technical scheme of the present application is described in detail below with specific examples. The following embodiments may be combined with each other, and some embodiments may not be repeated for the same or similar concepts or processes.
Fig. 2 is a flow chart of a method for collecting point cloud data according to an embodiment of the present application. As shown in fig. 2, the method includes:
201. acquiring engineering data respectively corresponding to a plurality of engineering tasks corresponding to a target acquisition area; the engineering data is obtained by data acquisition of the target acquisition area based on the corresponding engineering task.
The execution body of the embodiment may be a terminal device or a server.
In this embodiment, the engineering task, i.e., engineering, refers to one continuous collection performed by one collection vehicle. The target acquisition area may be a road segment, a location, etc. The plurality of engineering tasks can be executed in parallel by adopting different collection vehicles, and can be executed for a plurality of times by adopting the same collection vehicle, and the engineering tasks can be determined according to actual needs, and the embodiment is not limited to the above.
Specifically, a plurality of projects are collected by a plurality of collecting vehicles in a target collecting area, wherein the collecting vehicles comprise sensors such as GNSS, INS, laser radar and the like. The whole coverage of the acquisition area is ensured to be complete, the complete acquisition of ground features in a single project is not required, the redundant acquisition stroke is reduced, and the acquisition efficiency is improved. For example, assuming that there is an intersection as shown in fig. 1 in the target collection area, 8 projects (8 collection vehicles are only illustrative, and 2, 3, 4, etc. are also used) may be collected by 8 collection vehicles, each project includes a route of the intersection, and finally the 8 projects completely cover the intersection.
In some embodiments, obtaining engineering data corresponding to a plurality of engineering tasks corresponding to the target acquisition area may include: engineering division is carried out on the target acquisition area, and a plurality of engineering tasks are obtained; and acquiring engineering data respectively corresponding to a plurality of engineering tasks, which are acquired by the acquisition vehicle for acquiring data of the target acquisition area based on the engineering tasks.
Specifically, the engineering task design may be performed on the target acquisition area by the terminal device or the server, and the engineering task design may be divided into a plurality of engineering tasks, for example, 8 engineering tasks in fig. 1. The principle of division can be that a plurality of engineering tasks can be designed to completely cover a target acquisition area, namely engineering data obtained by completing acquisition of the engineering tasks comprises complete point cloud data of the target acquisition area, so that the integrity of the acquired data can be ensured. In addition, the round trip acquisition is not performed in the execution process of the acquisition vehicle, so that redundant data can be avoided to the greatest extent.
202. And carrying out fusion processing on laser point clouds in engineering data corresponding to the engineering tasks respectively to obtain target laser point cloud data of a target acquisition area.
Specifically, the engineering data corresponding to the engineering tasks may have a certain deviation, so that the engineering data can be fused, the deviation is eliminated, and finally the target laser point cloud data of the target acquisition area is obtained.
In some embodiments, performing fusion processing on laser point clouds in engineering data corresponding to a plurality of engineering tasks respectively to obtain target laser point cloud data of a target acquisition area may include: in response to touch operation of a user, the terminal equipment or the server carries out deviation correction, de-duplication and other operations on the laser point clouds in each engineering data, so that fusion processing of the laser point clouds in each engineering data is realized, and target laser point cloud data of a target acquisition area are obtained.
In some embodiments, performing fusion processing on laser point clouds in engineering data corresponding to a plurality of engineering tasks respectively to obtain target laser point cloud data of a target acquisition area may include: carrying out partition processing on laser point clouds in engineering data corresponding to a plurality of engineering tasks respectively to obtain a plurality of laser partitions which are not overlapped with each other; performing point cloud consistency alignment treatment on the plurality of laser partitions to obtain aligned laser partitions; and performing edge splicing processing on the plurality of aligned laser partitions to obtain target laser point cloud data of a target acquisition area.
Specifically, during laser point cloud data fusion processing, firstly, carrying out data partition processing on laser point clouds in a plurality of engineering data in an acquisition area; then carrying out consistency alignment processing on laser point cloud data in each partition; and finally, carrying out inter-partition edge connection processing.
In some embodiments, performing partition processing on laser point clouds in engineering data corresponding to a plurality of engineering tasks respectively to obtain a plurality of laser partitions without overlapping each other may include: dividing laser point clouds in engineering data into laser point cloud segments corresponding to a plurality of time periods respectively aiming at engineering data corresponding to each engineering task; and partitioning a plurality of laser point cloud segments of the engineering data to obtain a plurality of laser partitions which are not overlapped with each other.
Specifically, in the process of data partitioning, the laser point clouds in each engineering data can be divided into a plurality of time periods according to a preset rule, so as to obtain laser point cloud segments corresponding to the time periods respectively. The duration of the different time periods may be the same or may be different. For example, the road segments where the collection vehicle travels at a constant speed may be divided according to a first time period, and the road segments where the collection vehicle is suspended may be divided according to a second time period. The second time period is longer than the first time period.
In some embodiments, dividing the laser point cloud in the engineering data into laser point cloud segments corresponding to a plurality of time periods respectively may include: dividing a POS track in engineering data into a plurality of track segments according to the length; and dividing the laser point cloud in the engineering data based on the time corresponding relation between the POS track and the laser point cloud data to obtain laser point cloud segments corresponding to the track segments respectively. The Positioning and Orientation System (POS) is an airborne reference sensor in the aerial photogrammetry equipment, and is composed of a satellite navigation System and a POS System computer, so that information such as carrier speed, attitude and Position can be obtained in real time. The POS track is track data collected by a positioning and orientation system POS.
In some embodiments, partitioning a plurality of laser point cloud segments of a plurality of engineering data to obtain a plurality of laser partitions that do not overlap each other may include: determining a minimum outsourcing range of the laser point cloud segment for each of a plurality of laser point cloud segments of the plurality of engineering data; and dividing the laser point cloud segments with the overlapping areas in the minimum outsourcing ranges in the laser point cloud segments of the engineering data into the same partition to obtain a plurality of laser partitions which are not overlapped with each other.
In some embodiments, dividing the laser point cloud segment with the overlapping area in the minimum wrapping range in the multiple laser point cloud segments of the multiple engineering data into the same partition, and after obtaining multiple laser partitions without overlapping each other, further includes: and adding the isolated laser point cloud segments, of which the minimum outsourcing ranges and other minimum outsourcing ranges are not overlapped, in the plurality of laser point cloud segments of the engineering data into the laser partition with the shortest distance from the isolated laser point cloud segments.
In some embodiments, dividing the POS track in the engineering data into a plurality of track segments by length may include: based on the preset length, the POS track in the engineering data is divided into a plurality of track segments with equal length.
Specifically, data partitioning is performed. The single engineering data includes POS trajectory and laser point cloud data. The POS track includes the coordinates of the INS origin of coordinates and the acquisition time (x, y, z, t). The laser point cloud data includes feature point coordinates and acquisition time (x i ，y i ，z i ，t i ). The above coordinates may be coordinates in the world coordinate system.
First, POS track segmentation and laser point cloud data segmentation can be performed for each engineering data. In the process of segmentation, the POS track can be segmented based on the distance (the POS track has a time t field and the laser point cloud also has a time t field), and then the time period obtained by segmenting the POS track is utilized to segment the laser point cloud data based on the time, so that a segmented laser point cloud segment corresponding to the segmented POS track segment is obtained. In the process of segmenting the POS track, the mileage of the POS track point can be calculated, and the POS track is segmented at equal intervals, for example, 15 meters. The distance setting range can be between 10 meters and 40 meters, and specific data can be set according to actual needs.
And secondly, partition clustering can be performed. For a plurality of laser point cloud segments of all projects, an overlapping laser point cloud segment of each laser point cloud segment is calculated. Specifically, the outer bounding box of each laser point cloud segment, namely the minimum outer bounding range, can be calculated first, wherein each laser point cloud segment comprises a plurality of points, each point has a corresponding coordinate value xyz, and the maximum and minimum values of xyz in all directions are counted to obtain the outer bounding box of the point cloud; if the outer bounding boxes of two laser point cloud segments intersect, i.e., it is stated that the two laser point cloud segments overlap. The outer bounding box has all laser point cloud segments that intersect, i.e., overlap, to form one laser partition.
Furthermore, there may be isolated laser point cloud segments for which the outer bounding box does not intersect the outer bounding box of any other laser point cloud segments, which may be merged into an adjacent partition (e.g., the distance between the outer bounding boxes is the shortest). So far, overlapping laser point cloud segments are not existed between the partitions, and the laser point cloud segments are mutually independent.
Further, the consistency alignment processing of the laser point cloud data can be performed inside each laser section. The overlapping laser point cloud segments in each laser partition may employ an iterative closest point (Iterative Closest Point, ICP) point cloud matching algorithm to achieve consistent alignment of the overlapping laser point cloud segments.
In some embodiments, performing edge splicing on the plurality of aligned laser partitions may include: sequentially carrying out edge splicing treatment on the plurality of aligned laser partitions according to the adjacent relation; and aiming at the current processed partition in the plurality of aligned laser partitions, determining the deviation between the current processed partition and the last processed partition, and the edge connecting length of the edge connecting area of the current processed partition, and updating coordinates of laser points in the edge connecting area according to the deviation and the edge connecting length to finish the edge connecting process between the current processed partition and the last processed partition.
Specifically, after the internal consistency alignment processing of the laser subareas, the connection point clouds among the laser subareas are deviated (the method for determining the deviation can comprise the steps of leading the connection point clouds into a point cloud rendering tool and visually measuring whether the deviation occurs or not), so that the adjacent laser subareas are required to be subjected to edge connection processing, and the deviation of the connection positions is eliminated. For example, when the laser division a and the laser division B are subjected to the edge bonding process, the laser division a may be fixed, the laser division B may be subjected to the deviation adjustment, the laser division B needs to be adjusted so that the laser point at the start of the laser division a is the start point, and the cloud deviation at the connection point between the laser division a and the laser division B is Δ= (Δ) x ,Δ y ,Δ z ) The joint length (the total length of the laser point cloud from the starting point, which is required to be offset-adjusted) is s, and the joint point cloud coordinates of the partition B are corrected according to the following formula
Wherein, (x) i ,y i ,z i ) Is t i Time correction front coordinates, (x) i ′,y i ′,z i ') is t i Coordinates after time correction, l i Is t i And the distance from the track point corresponding to the moment to the track point corresponding to the cloud starting point of the partition connection point.
According to the point cloud data acquisition method, the point cloud map data of the target acquisition area is acquired by dividing the acquisition of the point cloud map data into a plurality of projects, the projects are enabled to completely cover the target acquisition area, after the acquisition of the projects is completed, the point cloud data acquired by the projects are fused, and then the complete point cloud data of the ground object in the target acquisition area can be obtained.
Fig. 3 is a schematic structural diagram of a device for collecting point cloud data according to an embodiment of the present application. As shown in fig. 3, the point cloud data acquisition apparatus 30 includes: an acquisition module 301 and a fusion module 302.
The acquiring module 301 is configured to acquire engineering data corresponding to a plurality of engineering tasks corresponding to a target acquisition area; the engineering data is obtained by data acquisition of the target acquisition area based on the corresponding engineering task.
And the fusion module 302 is configured to fuse laser point clouds in engineering data corresponding to a plurality of engineering tasks, and obtain target laser point cloud data of a target acquisition area.
According to the point cloud data acquisition equipment provided by the embodiment of the application, the point cloud map data of the target acquisition area is acquired by dividing the acquisition of the point cloud map data into a plurality of projects, the projects are enabled to completely cover the target acquisition area, after the acquisition of the projects is completed, the point cloud data acquired by the projects are fused, so that the complete point cloud data of the ground object in the target acquisition area can be obtained, compared with the acquisition of a single project of the target acquisition area, the redundant data can be greatly reduced, the acquisition efficiency is improved, and the acquisition cost is reduced.
In some embodiments, the fusion module 302 is specifically configured to perform partition processing on laser point clouds in the engineering data corresponding to the multiple engineering tasks, so as to obtain multiple laser partitions that do not overlap with each other; performing point cloud consistency alignment treatment on the plurality of laser partitions to obtain aligned laser partitions; and performing edge splicing processing on the plurality of aligned laser partitions to obtain target laser point cloud data of a target acquisition area.
In some embodiments, the fusion module 302 is specifically configured to divide, for the engineering data corresponding to each engineering task, a laser point cloud in the engineering data into laser point cloud segments corresponding to a plurality of time periods respectively; and partitioning a plurality of laser point cloud segments of the engineering data to obtain a plurality of laser partitions which are not overlapped with each other.
In some embodiments, the fusion module 302 is specifically configured to divide the POS track in the engineering data into a plurality of track segments according to the length; and dividing the laser point cloud in the engineering data based on the time corresponding relation between the POS track and the laser point cloud data to obtain laser point cloud segments corresponding to the track segments respectively.
In some embodiments, the fusion module 302 is specifically configured to determine, for each of a plurality of laser point cloud segments of a plurality of engineering data, a minimum outsourcing range of the laser point cloud segments; and dividing the laser point cloud segments with the overlapping areas in the minimum outsourcing ranges in the laser point cloud segments of the engineering data into the same partition to obtain a plurality of laser partitions which are not overlapped with each other.
In some embodiments, the fusion module 302 is specifically configured to add an isolated laser point cloud segment that has no overlapping between a minimum wrapping range and other minimum wrapping ranges in a plurality of laser point cloud segments of a plurality of engineering data, into a laser partition with a shortest distance from the isolated laser point cloud segment.
In some embodiments, the fusion module 302 is specifically configured to sequentially perform edge splicing processing on the plurality of aligned laser partitions according to an adjacent relationship; and aiming at the current processed partition in the plurality of aligned laser partitions, determining the deviation between the current processed partition and the last processed partition, and the edge connecting length of the edge connecting area of the current processed partition, and updating coordinates of laser points in the edge connecting area according to the deviation and the edge connecting length to finish the edge connecting process between the current processed partition and the last processed partition.
The point cloud data acquisition device provided in the embodiment of the present application may be used to execute the above method embodiment, and its implementation principle and technical effects are similar, and this embodiment is not repeated here.
Fig. 4 is a schematic hardware structure diagram of a device for collecting point cloud data, where the device may be a terminal device such as a computer, a messaging device, a tablet device, a medical device, or a server.
The device 40 may include one or more of the following components: a processing component 401, a memory 402, a power component 403, a multimedia component 404, an audio component 405, an input/output (I/O) interface 406, a sensor component 407, and a communication component 408.
The processing component 401 generally controls the overall operation of the device 40, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 401 may include one or more processors 409 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 401 may include one or more modules to facilitate interactions between the processing component 401 and other components. For example, the processing component 401 may include a multimedia module to facilitate interaction between the multimedia component 404 and the processing component 401.
The power supply component 403 provides power to the various components of the device 40. Power components 403 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for device 40.
The multimedia component 404 includes a screen between the device 40 and the user that provides an output interface. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or sliding action, but also the duration and pressure associated with the touch or sliding operation. In some embodiments, the multimedia component 404 includes a front-facing camera and/or a rear-facing camera. The front camera and/or the rear camera may receive external multimedia data when the device 40 is in an operational mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have focal length and optical zoom capabilities.
The audio component 405 is configured to output and/or input an audio signal. For example, the audio component 405 includes a Microphone (MIC) configured to receive external audio signals when the device 40 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 402 or transmitted via the communication component 408. In some embodiments, the audio component 405 also includes a speaker for outputting audio signals.
The I/O interface 406 provides an interface between the processing assembly 401 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: homepage button, volume button, start button, and lock button.
The sensor assembly 407 includes one or more sensors for providing status assessment of various aspects of the device 40. For example, the sensor assembly 407 may detect an on/off state of the device 40, a relative positioning of the components, such as a display and keypad of the device 40, the sensor assembly 407 may also detect a change in position of the device 40 or one of the components of the device 40, the presence or absence of user contact with the device 40, an orientation or acceleration/deceleration of the device 40, and a change in temperature of the device 40. The sensor assembly 407 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 407 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 407 may also include an acceleration sensor, a gyroscopic sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 408 is configured to facilitate communication between the device 40 and other devices, either wired or wireless. The device 40 may access a wireless network based on a communication standard, such as WiFi,2G or 3G, or a combination thereof. In one exemplary embodiment, the communication component 408 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component 408 further includes a Near Field Communication (NFC) module to facilitate short range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the device 40 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic elements for executing the methods described above.
In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, such as memory 402, including instructions executable by processor 409 of device 40 to perform the above-described method. For example, the non-transitory computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
The computer readable storage medium described above may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk. A readable storage medium can be any available medium that can be accessed by a general purpose or special purpose computer.
An exemplary readable storage medium is coupled to the processor such the processor can read information from, and write information to, the readable storage medium. In the alternative, the readable storage medium may be integral to the processor. The processor and the readable storage medium may reside in an application specific integrated circuit (Application Specific Integrated Circuits, ASIC for short). The processor and the readable storage medium may reside as discrete components in a device.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
The embodiment of the application also provides a computer program product, which comprises a computer program, and when the computer program is executed by a processor, the method for acquiring the point cloud data, which is executed by the point cloud data acquisition device, is realized.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. The method for collecting the point cloud data is characterized by comprising the following steps of:
acquiring engineering data respectively corresponding to a plurality of engineering tasks corresponding to a target acquisition area; the engineering data are obtained by carrying out data acquisition on the target acquisition area based on the corresponding engineering task;
and carrying out fusion processing on the laser point clouds in the engineering data corresponding to the engineering tasks respectively to obtain target laser point cloud data of a target acquisition area.
2. The method of claim 1, wherein the fusing the laser point clouds in the engineering data corresponding to the engineering tasks to obtain the target laser point cloud data of the target acquisition area includes:
carrying out partition processing on laser point clouds in engineering data corresponding to a plurality of engineering tasks respectively to obtain a plurality of laser partitions which are not overlapped with each other;
performing point cloud consistency alignment treatment on the plurality of laser partitions to obtain aligned laser partitions;
and performing edge splicing processing on the plurality of aligned laser partitions to obtain target laser point cloud data of a target acquisition area.
3. The method of claim 2, wherein the partitioning the laser point clouds in the engineering data corresponding to the engineering tasks to obtain a plurality of laser partitions without overlapping each other includes:
dividing laser point clouds in engineering data into laser point cloud segments corresponding to a plurality of time periods respectively aiming at engineering data corresponding to each engineering task;
partitioning a plurality of laser point cloud segments of the engineering data to obtain a plurality of laser partitions which are not overlapped with each other.
4. The method of claim 3, wherein the dividing the laser point cloud in the engineering data into laser point cloud segments corresponding to a plurality of time periods respectively comprises:
dividing the POS track in the engineering data into a plurality of track segments according to the length;
and dividing the laser point cloud in the engineering data based on the time corresponding relation between the POS track and the laser point cloud data to obtain a plurality of laser point cloud segments respectively corresponding to the track segments.
5. The method of claim 3, wherein the partitioning the plurality of laser point cloud segments of the plurality of engineering data to obtain a plurality of laser partitions that do not overlap each other comprises:
determining a minimum wrapping range of each laser point cloud segment in a plurality of laser point cloud segments of the engineering data;
and dividing the laser point cloud segments with the overlapping areas in the minimum outsourcing ranges in the multiple laser point cloud segments of the engineering data into the same partition, and obtaining multiple laser partitions which are not overlapped with each other.
6. The method of claim 5, wherein the dividing the laser point cloud segments with the overlapping areas in the minimum package ranges among the plurality of laser point cloud segments of the engineering data into the same partition, after obtaining the plurality of laser partitions without overlapping each other, further comprises:
and adding an isolated laser point cloud segment, of which the minimum outsourcing range and other minimum outsourcing ranges are not overlapped, in the multiple laser point cloud segments of the engineering data into a laser partition with the shortest distance from the isolated laser point cloud segment.
7. The method of any of claims 2-5, wherein the edging the plurality of aligned laser partitions comprises:
sequentially carrying out edge splicing treatment on the plurality of aligned laser partitions according to an adjacent relation;
and aiming at the current processed partition in the aligned laser partitions, determining the deviation between the current processed partition and the last processed partition and the edge connecting length of the edge connecting area of the current processed partition, and updating coordinates of laser points in the edge connecting area according to the deviation and the edge connecting length to finish edge connecting processing between the current processed partition and the last processed partition.
8. The utility model provides a collection equipment of point cloud data which characterized in that includes:
the acquisition module is used for acquiring engineering data corresponding to a plurality of engineering tasks corresponding to the target acquisition area respectively; the engineering data are obtained by carrying out data acquisition on the target acquisition area based on the corresponding engineering task;
and the fusion module is used for carrying out fusion processing on the laser point clouds in the engineering data corresponding to the engineering tasks respectively to obtain target laser point cloud data of the target acquisition area.
9. A computer-readable storage medium, wherein computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, the method for collecting point cloud data according to any one of claims 1 to 7 is implemented.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the method of collecting point cloud data according to any of claims 1 to 7.
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| CN117237557A (en) * | 2023-11-09 | 2023-12-15 | 武汉追月信息技术有限公司 | Urban mapping data processing method based on point cloud data |
| CN117237557B (en) * | 2023-11-09 | 2024-02-02 | 武汉追月信息技术有限公司 | Urban mapping data processing method based on point cloud data |
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