CN114925937A - Stage scene point cloud scanning site selection and path planning method - Google Patents
Stage scene point cloud scanning site selection and path planning method Download PDFInfo
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Abstract
The invention relates to a stage scene point cloud scanning site selection and path planning method and a calibration device. The method comprises the following steps: traversing a scene to be scanned through a mobile platform, obtaining a two-dimensional raster map of a stage, calculating to obtain an optimal site based on an SDF directed distance field, obtaining an optimal path based on a Dijkstra algorithm and an ant colony algorithm, controlling the mobile platform to move to the optimal site according to the optimal path, starting an elevator and a scanner body to scan, judging whether a scanning device traverses all the optimal sites, and if not, repeating the steps to obtain the optimal site and the optimal path. According to the invention, through completely and autonomously selecting the stations and planning the paths, the labor cost and the scanning time are greatly reduced, and the scanning efficiency and the reconstruction effect are improved.
Description
Technical Field
The invention relates to a stage scene point cloud scanning site selection and path planning method, and belongs to the technical field of measurement.
Background
Three-dimensional point cloud scanning and reconstruction are the main research directions in the field of computer vision at present. In the aspect of three-dimensional scanning of large scenes of a stage, scanning is mainly performed by a laser radar or a site type three-dimensional laser scanner at present, but the density of point cloud obtained by the laser radar is low. The site type three-dimensional laser scanner needs to select and scan sites manually, and labor cost and time cost are high.
Disclosure of Invention
The invention provides a stage scene point cloud scanning site selection and path planning method, and aims to at least solve one of the technical problems in the prior art.
The technical scheme is based on scanning equipment and a calibration device of a stage scene, wherein the scanning equipment comprises a scanner body, an elevator and a mobile platform, wherein the scanner body scans the stage scene to be detected and acquires point cloud of a single station; the elevator is used for adjusting the height of the scanner, so that a detected scene can be scanned better; the mobile platform is used for map building navigation and moving the scanner.
The technical scheme of the invention relates to a stage scene point cloud scanning site selection and path planning method which is applied to scanning equipment, wherein the scanning equipment comprises a scanner body, an elevator and a mobile platform. In this aspect, the method according to the invention comprises the steps of:
s100, traversing a scene to be scanned through a mobile platform to obtain a two-dimensional grid map of a stage;
s200, calculating to obtain an optimal site based on the SDF directed distance field, and obtaining an optimal path based on a Dijkstra algorithm and an ant colony algorithm;
s300, controlling the mobile platform to move to an optimal station according to an optimal path, and starting the elevator and the scanner body to scan; and judging whether the scanning equipment traverses all the optimal sites or not, and if not, repeating the step S200.
Further, the step S200 includes:
s210, initializing a subprogram to obtain an initial SDF;
s220, judging whether a feasible site exists or not;
s230, if yes, updating the SDF and the path;
s240, if not, solving a station traversal path.
Further, the step S210 includes:
s211, loading the two-dimensional grid map;
s212, cutting the two-dimensional grid map to reduce the size of the map;
s213, calculating a reachable area of the two-dimensional grid map;
s214, calculating the initial SDF of the two-dimensional grid map.
Further, the step S230 includes:
s231, creating a priority queue Q with (d, P) binary groups as elements, wherein the elements d are arranged in an ascending order, P represents an reachable place in the map, and S i Denotes a given site, d denotes S i The length of a certain path to P;
the initial value of S232 and Q is (0, S) i ) Wherein, except S i All reachable points except the reachable point are set as not accessed;
s233, if Q is not empty, taking out the head element (d, P); otherwise, skipping to execute step S225;
s234, loosening the neighbor N of the P, and skipping to execute the step S223;
and S235, ending the program.
Further, in step S230, the SDF is updated by the following algorithm:
where the absolute value of the directed distance field SDF is represented as the boundary between a given point x anddistance between themThe rejection coefficient is expressed as γ ∈ [0, 1 ]];Indicating site S i A scannable area; c represents such thatA continuous constant.
Further, the step S234 includes:
if the relaxed point N is an obstacle, the azimuth angle interval [ phi-delta phi, phi + delta phi]Joining collections
If the N azimuth phi of the relaxed point is in the set of the azimuth angles of the obstacleIf so, newly building a skip point N, and pressing the skip point N into a priority queue;
if the N azimuth angle phi of the relaxed point is not in the set of the azimuth angles of the obstacleAnd if so, utilizing the skip point H to relax N and pushing the skip point H into the priority queue.
Further, the step S240 includes:
s241, calculating the distance between the stations through a Floyd algorithm;
and S242, selecting a global optimal path through an ant colony algorithm, and solving a station traversal path.
Another aspect of the present invention also relates to a computer-readable storage medium having stored thereon program instructions, which when executed by a processor, implement the above-described method.
In another aspect, the present invention further relates to a stage scene scanning device, which includes a computer device that includes the computer readable storage medium.
The beneficial effects of the invention are as follows.
According to the stage scene point cloud scanning site selecting and path planning method and the calibration device, the point cloud scanning site selecting method based on the directed distance departure field (SDF) and the inter-site path planning method based on the improved Dijkstra algorithm and the ant colony algorithm are adopted, the site is selected and the path is planned completely and independently, the labor cost and the scanning time are greatly shortened, and the scanning efficiency and the reconstruction effect are improved. According to the method, a station scanning area is taken as a boundary to serve as a new SDF boundary, the advantage that a new station cannot appear in a certain station scanning area is achieved, the advantage that dead corners cannot be generated is achieved by taking the station as the new SDF boundary, and the advantages of the two strategies are absorbed by introducing rejection coefficients in the SDF updating process. In the path planning algorithm, the adjustment points and the obstacle azimuth angle set thereof are introduced to solve, so that the problem that the Dijkstra algorithm can only solve the shortest Manhattan distance between two points in a two-dimensional map is solved. In the invention, in the station traversal path planning, the Floyd algorithm is adopted for preprocessing, which is beneficial to ensuring that the station distance meets the measurement property, so that the total traversal length is shortened.
Drawings
Fig. 1 is a basic flow diagram of a method according to the invention.
Fig. 2 is a flow chart of an initialization sub-routine in an embodiment in accordance with the present invention.
Fig. 3 is a schematic diagram of an algorithm for updating SDFs and paths in an embodiment in accordance with the invention.
Fig. 4 is a schematic diagram of an algorithm for relaxing P-point neighbors in an embodiment of the invention.
Fig. 5 is a schematic diagram of a relaxed point N itself as an obstacle in an embodiment in accordance with the invention.
Fig. 6a and 6b are schematic diagrams comparing the update SDF algorithm and the update path algorithm in the embodiment of the present invention.
FIG. 7 is a schematic diagram of an algorithm for solving a site traversal path according to an embodiment of the present invention.
Fig. 8 is a schematic view of the structure of a scanning device according to the present invention.
Detailed Description
The conception, the specific structure and the technical effects of the present invention will be clearly and completely described in conjunction with the embodiments and the accompanying drawings to fully understand the objects, the schemes and the effects of the present invention.
It should be noted that, unless otherwise specified, when a feature is referred to as being "fixed" or "connected" to another feature, it may be directly fixed or connected to the other feature or indirectly fixed or connected to the other feature. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in the description herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any combination of one or more of the associated listed items.
It will be understood that, although the terms first, second, third, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element of the same type from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of the present disclosure. The use of any and all examples, or exemplary language ("e.g.," such as "etc.), provided herein is intended merely to better illuminate embodiments of the invention and does not pose a limitation on the scope of the invention unless otherwise claimed.
Referring to fig. 8, the technical scheme of the invention is based on scanning equipment of a stage scene, and the scanning equipment comprises a scanner body, an elevator and a mobile platform, wherein the scanner body scans the stage scene to be detected and acquires point cloud of a single station; the elevator is used for adjusting the height of the scanner, so that a detected scene can be scanned better; the mobile platform is used for map building navigation and moving the scanner.
Referring to fig. 1 to 7, in some embodiments, the stage scene point cloud scanning site selection and path planning method according to the present invention is applied to a scanning device, and at least includes the following steps:
s100, traversing a scene to be scanned through a mobile platform to obtain a two-dimensional grid map of a stage;
s200, calculating to obtain an optimal site based on the SDF directed distance field, and obtaining an optimal path based on a Dijkstra algorithm and an ant colony algorithm;
s300, controlling the mobile platform to move to an optimal station according to an optimal path, and starting the elevator and the scanner body to scan; and judging whether the scanning equipment traverses all the optimal sites or not, and if not, repeating the step S200.
Specifically, the input of the method in the invention is a two-dimensional grid map output by a Simultaneous Localization and Mapping (SLAM) module, and the output is coordinates of each station and path information traversing all stations, and the information is sent to a global path planning module of the chassis to control the motion of the chassis.
Detailed description of step S100
The moving platform is pushed manually or is controlled to move by a computer device, so that the scanning equipment traverses a stage scene to be scanned, and an SLAM module in the moving platform utilizes information returned by the laser sensor to build a scene map of the stage, so that a two-dimensional raster map of the stage is obtained.
Detailed description of step S200
S210, initializing a sub-program to obtain an initial SDF. Referring to fig. 2, the initialization sub-program includes four parts of loading a map, cutting the map, calculating a reachable area, and calculating an initial SDF.
Loading the map refers to loading a two-dimensional grid map built by reading information of the SLAM module. The two-dimensional grid map has three possibilities of unoccupied, occupied and unknown per pixel, and the occupied and unknown are regarded as the obstacle area.
The map cutting means cutting the two-dimensional grid map to reduce the size of the map, thereby reducing the calculation load degree and the memory occupation of subsequent operations. And marking the size of the cut map as n and m.
The process of calculating the reachable area refers to the process of acquiring the reachable area of the mobile platform by performing morphological operation on the two-dimensional grid map. The specific implementation process is as follows: 1) and (4) expanding the map according to the radius of the mobile platform, and regarding the expanded area as an inaccessible area. 2) The secondary connected region is treated as an unreachable region.
Calculating the initial SDF refers to solving the SDF of the binary image, and the method in the embodiment of the invention adopts the existing 8ssedt algorithm to solve.
Where a directed distance field is a technique for rapidly calculating the distance of a given pixel or voxel to the nearest boundary, the mathematical definition is as follows: for a directed distance field SDF in the metric space Ω, the absolute value is the boundary between a given point x anddistance between themThe sign of which depends on whether x is within Ω or not.
where d (x, y) represents the euclidean distance between x and y, and inf represents the infimum.
In the method of the present invention, the initial SDF is determined only by the two-dimensional grid map obstacle boundaries, consistent with the above definition. Whenever a program selects a new site S i The SDF needs to be updated to prevent the next selected site from being absent S i Nearby. There are two possible strategies for updating the SDF. One strategy is to use the boundary of a station scanning area as a new SDF boundary, and the method has the advantages that the information of the station scanning area is utilized, so that the new station cannot appear in a certain station scanning area, the station spacing is ensured not to be too dense, the defect is that dead corners which cannot be scanned possibly appear, theoretically, the dead corner areas can be scanned through reasonable station setting, but the position of the new station is located in the scanning areas of other stations, so that the dead corners cannot be scanned. The other strategy is to use the site itself as a new SDF boundary, and the method has the advantages of no dead angle and the disadvantages of unavailable utilization of the scanned information of the area, resulting in over-dense distribution of the sites and generation of large repeated scanning areas.
The method in the embodiment of the invention introduces a rejection coefficient gamma epsilon [0, 1]The advantages of both strategies are taken into account. Adopting Euclidean distance to the boundary; for site S i Distance defined by the formula:
wherein,indicating site S i Scannable area, C denotes such thatA continuous constant. A complete exclusion strategy when γ is 1, the same as the above strategy 1); the completely non-exclusive strategy when γ is 1, the same as the above strategy 2); when gamma is equal to (0, 1), the effect is between the two strategies, and the typical value is 0.9.
And S220, judging whether a feasible site exists.
S230, if yes, referring to fig. 3, updating the SDF and the path. Updating the SDF and the path subprogram essentially solves the single-source shortest path problem, and generally adopts Dijkstra algorithm. Given site S i The specific flow of the algorithm is as follows:
s231, creating a priority queue Q with (d, P) duplet as an element, arranging the elements d in ascending order, wherein P represents an reachable place in the map, and S i Denotes a given site, d denotes S i The length of a certain path to P.
The initial value of S232 and Q is (0, S) i ) Wherein, except S i All reachable points except those are set as not accessed.
S233, if Q is not null, taking out the head element (d, P); otherwise, the jump is performed to step S225.
and S235, ending the program.
The shortest Manhattan distance between two points in the two-dimensional map can only be solved by using a standard Dijkstra algorithm, but the Euclidean distance is generally adopted in practical application. The algorithm involved in the invention introduces the jumping point H and the obstacle azimuth angle set thereof to solve. Referring to fig. 4, the specific implementation process is as follows:
a. if the relaxed point N itself is an obstacle, the azimuth angle interval [ φ - δ φ, φ + δ φ is divided into intervals as shown in FIG. 5]Joining collections
b. If the N azimuth of the relaxed point is in the set of the azimuth of the obstacleWith internal, i.e. barrier between jump points H and NAnd (4) blocking by the obstacle, newly building a hop point N and pressing the hop point N into a priority queue.
c. If the N azimuth angle phi of the relaxed point is not in the set of the azimuth angles of the obstacleIf inner, i.e., hops H and N are straightforward, then hop H is used to relax N and push it into the priority queue.
Referring to fig. 6a and 6b, the SDF at update point P and the path at update point P are slightly different, the former being based on a metricThe latter is measured in terms of euclidean distance and cannot be calculated simultaneously.
And S240, if not, referring to FIG. 7, solving the station traversal path, wherein the distance between the stations is calculated through a Floyd algorithm, and the global optimal path is selected through an ant colony algorithm to solve the station traversal path. The specific implementation mode is as follows:
the site traversal path planning may be translated into a traveler Problem (TSP). Unlike the standard traveler problem, a site can be traversed repeatedly. Before solving the TSP problem, the method in the embodiment of the invention adopts the Floyd algorithm to solve the distance between the stations. Due to factors such as floating point errors, the inter-site distance calculated in the previous step may violate a triangle inequality, and after the inter-site distance is preprocessed by using the Floyd algorithm, the inter-site distance can be guaranteed to meet the measurement property, so that the total traversal length is shortened. The cost is to cause repeated passes through part of the sites, but without affecting the practical application.
The traveler problem is an NP-hard problem in combinatorial optimization whose deterministic optimal solution algorithm can only be used for small scale problems. In practice, heuristic algorithms are mostly used. Although an optimal solution cannot be guaranteed, a better solution can be given within a limited time. The method in the embodiment of the invention adopts the ant-colony algorithm, and the algorithm flow is shown in fig. 7.
The stage scene point cloud scanning site selecting and path planning method according to the embodiment of the invention is described in detail with reference to fig. 1 to 8. It is to be understood that the following description is only exemplary, and not a specific limitation of the invention.
Step A: and manually controlling the mobile platform to traverse the scene to be scanned, and establishing a map for the scene by using the information returned by the laser sensor by using an SLAM module in the mobile platform.
And B: the program realized based on the method of the invention is operated, and the program can automatically obtain the built map and obtain the two-dimensional grid map of the stage. And inputting parameters such as the radius of the mobile platform, the rejection coefficient, the maximum station number and the like. Clicking the planning button, the program will output the planned site list and global path plan. And clicking a start automatic scanning button, and automatically sending the path to the next station to the local path planning module by the program.
And C: a local path planning module in the mobile platform can obtain barrier information transmitted back by the laser sensor in real time, make barrier avoiding actions and plan a path again to bypass the barrier when necessary. The local path planning module transmits the motion speed vector information to the motion control module of the mobile platform to drive each motor respectively, so that the motion platform moves according to the planned route.
Step D: after the station is reached, the program controls the support to automatically lift, and the scanner is started to start scanning. After the scanning completion instruction is given in a given scanning time or manually sent out, the program control support is automatically retracted, so that the gravity center of the system is reduced, and the moving speed and the stability are improved. If all the sites are traversed, the scanning is finished; otherwise the program will automatically jump to step C.
Step E: and (5) carrying out registration, splicing and post-processing on the point cloud data of each station to complete scene reconstruction.
Through the result contrastive analysis with manual scanning, the time of automatic scanning can be greatly shortened, the registration precision is also improved, and the scanning efficiency and the reconstruction effect are effectively improved.
It should be recognized that the method steps in embodiments of the present invention may be embodied or carried out by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The method may use standard programming techniques. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.
Further, the operations of processes described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and/or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) collectively executed on one or more processors, by hardware, or combinations thereof. The computer program includes a plurality of instructions executable by one or more processors.
Further, the method may be implemented in any type of computing platform operatively connected to a suitable connection, including but not limited to a personal computer, mini computer, mainframe, workstation, networked or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, or the like. Aspects of the invention may be embodied in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optically read and/or write storage medium, RS1M, ROM, or the like, such that it may be read by a programmable computer, which when read by the computer may be used to configure and operate the computer to perform the procedures described herein. Further, the machine-readable code, or portions thereof, may be transmitted over a wired or wireless network. The invention described herein includes these and other different types of non-transitory computer-readable storage media when such media include instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor. The invention may also include the computer itself when programmed according to the methods and techniques described herein.
A computer program can be applied to input data to perform the functions described herein to transform the input data to generate output data that is stored to non-volatile memory. The output information may also be applied to one or more output devices, such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including particular visual depictions of physical and tangible objects produced on a display.
The above description is only a preferred embodiment of the present invention, and the present invention is not limited to the above embodiment, and any modifications, equivalent substitutions, improvements, etc. within the spirit and principle of the present invention should be included in the protection scope of the present invention as long as the technical effects of the present invention are achieved by the same means. The invention is capable of other modifications and variations in its technical solution and/or its implementation, within the scope of protection of the invention.
Claims (9)
1. A method for selecting and planning paths of a stage scene point cloud scanning station is applied to scanning equipment, wherein the scanning equipment comprises a scanner body, an elevator and a mobile platform;
characterized in that the method comprises the steps of:
s100, traversing a scene to be scanned through a mobile platform to obtain a two-dimensional grid map of a stage;
s200, calculating and obtaining an optimal site based on the SDF directed distance field, and obtaining an optimal path based on a Dijkstra algorithm and an ant colony algorithm;
s300, controlling the mobile platform to move to an optimal station according to an optimal path, and starting the elevator and the scanner body to scan; and judging whether the scanning equipment traverses all the optimal sites or not, and if not, repeating the step S200.
2. The method of claim 1, wherein the step S200 comprises:
s210, initializing a subprogram to obtain an initial SDF;
s220, judging whether feasible sites exist or not;
s230, if yes, updating the SDF and the path;
s240, if not, solving a station traversal path.
3. The method of claim 2, wherein the step S210 comprises:
s211, loading the two-dimensional grid map;
s212, cutting the two-dimensional grid map to reduce the size of the map;
s213, calculating the reachable area of the two-dimensional grid map;
s214, calculating the initial SDF of the two-dimensional grid map.
4. The method of claim 2, wherein the step S230 comprises:
s231, creating a priority queue Q with a (d, P) binary group as an element, wherein the elements d are arranged in an ascending order, P represents an reachable point in a map, Si represents a given station, and d represents the length of a certain path from Si to P;
s232, the initial value of Q is (0, Si), wherein all reachable points except Si are set to be not accessed;
s233, if Q is not null, taking out the head element (d, P); otherwise, skipping to execute step S225;
s234, loosening the neighbor N of the P, and skipping to execute the step S223;
and S235, ending the program.
5. The method of claim 4, wherein in step S230, the SDF is updated by the following algorithm:
6. The method of claim 4, wherein the step S234 comprises:
if the relaxed point N is an obstacle, the azimuth angle interval [ phi-delta phi, phi + delta phi]Joining collections
If the N azimuth phi of the relaxed point is in the set of the azimuth angles of the obstacleIf so, newly building a hop point N, and pressing the hop point N into a priority queue;
7. The method of claim 4, wherein the step S240 includes:
s241, calculating the distance between the stations through a Floyd algorithm;
and S242, selecting a global optimal path through an ant colony algorithm, and solving a station traversal path.
8. A computer readable storage medium having stored thereon program instructions which, when executed by a processor, implement the method of any one of claims 1 to 7.
9. A stage scene scanning apparatus, comprising:
a computer device comprising the computer-readable storage medium of claim 8.
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