CN114255241B - Region segmentation method, device, equipment and storage medium for path planning - Google Patents
Region segmentation method, device, equipment and storage medium for path planning Download PDFInfo
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Abstract
The invention relates to the technical field of path planning of robots, in particular to a region segmentation method, a device, equipment and a storage medium for path planning. Dividing the region to be divided by using a voronoi diagram dividing method to obtain a voronoi diagram; according to the Voronoi division diagram, obtaining an alternative edge contained in the Voronoi division diagram, wherein two vertexes of the alternative edge are positioned in a task area, and the task area is an area for executing a task by a terminal in the area to be divided; obtaining a priori boundary edge according to the alternative edge; and obtaining a target segmentation area according to the priori boundary edges and the Veno segmentation map. According to the method, firstly, the non-task area in the task area to be segmented is removed through the alternative edge, and then the area is segmented according to the priori boundary edge, so that the turning times can be reduced when the terminal moves on a path obtained after segmentation, and the task execution efficiency of the terminal is improved.
Description
Technical Field
The invention relates to the technical field of path planning of robots, in particular to a region segmentation method, a device, equipment and a storage medium for path planning.
Background
The regional coverage path planning is a basic technology relied on when the sweeping robot, the investigation and exploration unmanned aerial vehicle and the agricultural robot execute tasks (the robots, the investigation and exploration unmanned aerial vehicle and the agricultural robot are all terminals for executing tasks). The existing area coverage path planning algorithm comprises the following steps in whole: 1. dividing the area to be covered; 2. path planning is carried out inside each sub-area; 3. the order and path of access to each sub-region is calculated.
Because the robot needs to accelerate and decelerate during turns, one important indicator of the area coverage algorithm is the number of turns in the planned path in order to quickly complete the area coverage task. For this reason, in the second step, the robot often travels by using an arcuate movement route. In order to ensure that the robot can advance in an arcuate path in each sub-area, in step one, the area to be covered needs to be segmented. The existing research has made an important advance in the problem of how to divide the area that can be covered by the archwire route, namely the archwire decomposition algorithm (BCD algorithm). By utilizing the algorithm, the area to be covered can be divided into a plurality of subareas on the premise of giving the cleaning direction, and the interior of each subarea can be ensured to be cleaned by using an arcuate route.
The BCD algorithm solves the problem of realizing the first step and the second step to a certain extent, and on the basis, researchers in recent years propose a series of algorithms based on optimizing and solving the access sequence of the subareas. Mannadiar et al propose to use the "key points" employed in decomposing the regions in the BCD algorithm as vertices of the graph, use each decomposed region as an edge of the graph, and then convert the problem of traversing all regions into a mail-drop problem on the graph (i.e., how to traverse all edges). Vandermeulon et al propose that the sweep start point, end point, virtual center of the sub-region can be made the vertex of the graph for each sub-region, constructing the traveler problem to optimize the traversal order.
The algorithm can be summarized as realizing the first and second steps by using the BCD algorithm, and then optimizing the third step. A common limitation of these algorithms is that tasks must be performed in the same direction for each sub-region, and for some more square-shaped, or less obstructed environments, better processing of the task may be achieved even if each sub-region is performed in the same direction. However, for the outdoor environment, since the boundaries in the outdoor environment are often no longer regular, the number of obstacles in the outdoor environment is various and dense, and taking the minimum turn number of the terminal as a standard, the performance of the area coverage algorithm is greatly reduced by adopting a single direction. For this purpose, an optimization algorithm for the first and second steps needs to be designed.
In summary, in the prior art, the division of the area to be covered increases the number of turns when the terminal executes the task, thereby reducing the efficiency of executing the task by the terminal.
Accordingly, there is a need for improvement and advancement in the art.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method, a device, equipment and a storage medium for dividing a region for path planning, which solve the problems that in the prior art, the dividing of a region to be covered increases the turning times when a terminal executes a task, thereby reducing the efficiency of executing the task by the terminal.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
in a first aspect, the present invention provides a region segmentation method for path planning, including:
dividing the region to be divided by using a voronoi diagram dividing method to obtain a voronoi diagram;
obtaining an alternative edge contained in the voronoi segmentation diagram according to the voronoi segmentation diagram, wherein two vertexes of the alternative edge are positioned in a task area, and the task area is an area which needs to execute tasks in the area to be segmented;
obtaining a priori boundary edge according to the alternative edge;
and obtaining a target segmentation area according to the prior boundary and the Veno segmentation map, wherein the target segmentation area is used for planning a path required by executing a task.
In one implementation manner, the obtaining, according to the voronoi segmentation diagram, an alternative edge included in the voronoi segmentation diagram includes:
obtaining a segmentation surface contained in the voronoi segmentation map according to the voronoi segmentation map;
preprocessing the Veno segmentation map according to the vertex corresponding to the segmentation surface and the task area to obtain the preprocessed Veno segmentation map;
and obtaining the alternative edges according to the pre-processed Veno segmentation graph.
In one implementation manner, the preprocessing the voronoi segmentation map according to the vertex corresponding to the segmentation surface and the task area to obtain the preprocessed voronoi segmentation map includes:
and deleting the segmentation surfaces corresponding to the vertexes outside the task area to obtain the pre-processed Veno segmentation map.
In one implementation, the obtaining the prior boundary edge according to the alternative edge includes:
calculating the distance between the point on the alternative side and the boundary corresponding to the task area;
calculating a distance gradient corresponding to the point on the alternative side according to the distance;
obtaining an evaluation function value corresponding to the alternative edge according to the distance and the distance gradient;
And obtaining the priori boundary edge according to the evaluation function value.
In one implementation manner, the calculating, according to the distance, a distance gradient corresponding to the point on the candidate edge includes:
calculating a point corresponding to the minimum distance between the candidate edge and the nearest boundary of the task area, and marking the point as the nearest point;
calculating the distance between the nearest point and the nearest boundary of the task area, and calculating the tangent vector of the candidate edge at the nearest point as a first distance;
calculating the distance between the coordinate corresponding to the nearest point and the coordinate corresponding to the sum of the tangent vectors and the nearest boundary of the task area, and marking the distance as a second distance;
and obtaining the distance gradient according to the difference between the second distance and the first distance.
In one implementation manner, the obtaining the evaluation function value corresponding to the candidate edge according to the distance and the distance gradient includes:
and obtaining an evaluation function value corresponding to the alternative edge according to the sum of the absolute value of the first distance and the distance gradient.
In one implementation, the obtaining the priori boundary edge according to the evaluation function value includes:
Obtaining an alternative edge adjacent to the alternative edge according to the alternative edge, and marking the alternative edge as an alternative adjacent edge, wherein the alternative edge and the alternative adjacent edge have a common vertex;
when the evaluation function value corresponding to the alternative adjacent edge is larger than the evaluation function value corresponding to the alternative edge, marking the alternative edge as a cutting edge;
calculating a point corresponding to the minimum distance between the cutting edge and the nearest boundary of the task area, and marking the point as a cutting point;
and obtaining the prior boundary edge according to the cutting point, the cutting edge and the task area, wherein the cutting point is positioned on the prior boundary edge, the prior boundary edge is perpendicular to the cutting edge, and two end points of the prior boundary edge are positioned on the boundary of the task area.
In one implementation manner, the obtaining, according to the prior boundary edge and the voronoi segmentation map, a target segmentation region, where the target segmentation region is used for planning a path required for executing a task, includes:
obtaining adjacent segmentation surfaces contained in the voronoi segmentation map according to the voronoi segmentation map, wherein the adjacent segmentation surfaces have common edges;
Fusing the adjacent segmentation surfaces which do not contain the priori boundary edges and the boundaries of the task areas in the Veno segmentation map into a plane to obtain a primary segmentation area;
obtaining each primary segmentation plane contained in the primary segmentation area according to the primary segmentation area;
dividing each primary division plane along the longest side of each primary division plane by adopting an arch-shaped decomposition algorithm to obtain a secondary division area;
and obtaining the target segmentation area according to the secondary segmentation area.
In one implementation manner, the obtaining the target segmentation area according to the secondary segmentation area includes:
obtaining each secondary partition plane contained in the secondary partition area according to the secondary partition area;
fusing the adjacent secondary segmentation planes which do not contain the prior boundary edge into a plane to obtain the fused secondary segmentation area;
dividing each plane along the longest edge of the planes contained in the secondary divided regions after fusion by adopting an arch-shaped decomposition algorithm to obtain a tertiary divided region;
obtaining the height corresponding to each secondary segmentation plane according to the normal vector of each vertex of each secondary segmentation plane and a first unit vector, wherein the first unit vector is a unit vector perpendicular to the direction of the longest edge of the primary segmentation plane;
Obtaining each cubic division plane contained in the cubic division area according to the cubic division area;
obtaining the height corresponding to each three-time dividing plane according to the normal vector of each vertex of each three-time dividing plane and a second unit vector, wherein the second unit vector is a unit vector perpendicular to the direction of the longest side of the plane contained in the two-time dividing area;
and obtaining the target segmentation area by the height corresponding to each secondary segmentation plane and the height corresponding to each tertiary segmentation plane.
In one implementation, the region segmentation method further includes, after the steps:
acquiring each target segmentation plane corresponding to the target segmentation area;
obtaining bow-shaped paths corresponding to the target segmentation planes through the target segmentation planes;
and applying a travel provider planning algorithm to the arcuate path to obtain the order of executing tasks of each target segmentation plane.
In a second aspect, an embodiment of the present invention further provides an apparatus for a region segmentation method for path planning, where the apparatus includes the following components:
the device comprises a Veno segmentation module, a Veno segmentation module and a Veno segmentation module, wherein the Veno segmentation module is used for segmenting a region to be segmented by applying a Veno graph segmentation method to obtain a Veno segmentation graph;
The alternative edge calculation module is used for obtaining alternative edges contained in the voronoi segmentation diagram according to the voronoi segmentation diagram, wherein two vertexes of the alternative edges are positioned in a task area, and the task area is an area which needs to execute tasks in the area to be segmented;
the priori boundary edge calculation module is used for obtaining a priori boundary edge according to the alternative edge;
and the segmentation module is used for obtaining a target segmentation area according to the prior boundary edge and the Veno segmentation graph, and the target segmentation area is used for planning a path required by executing a task.
In a third aspect, an embodiment of the present invention further provides a terminal device, where the terminal device includes a memory, a processor, and a region segmentation program for path planning stored in the memory and capable of running on the processor, where the processor implements the steps of the region segmentation method for path planning when executing the region segmentation program for path planning.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where a region segmentation program for path planning is stored in the computer readable storage medium, where the region segmentation program for path planning, when executed by a processor, implements the steps of the region segmentation method for path planning described above.
The beneficial effects are that: the method comprises the steps of defining edges of two vertexes in a task area (the area to be segmented comprises a task area and a non-task area, the task area is an area where a terminal needs to execute tasks, and the non-task area is an area where the terminal does not need to execute tasks) as alternative edges, obtaining priori boundary edges according to the alternative edges, and finally segmenting the area to be segmented according to the priori boundary edges to obtain a target segmented area comprising each segmented plane.
When the terminal performs a task, it is required to turn when it reaches a non-task area (an area with an obstacle), and the turning may reduce the efficiency of the terminal to perform the task. According to the method and the device, the non-task area in the task area to be segmented is removed through the alternative edge, and the area is segmented according to the priori boundary edge, so that the turning times can be reduced when the terminal moves on a path obtained after segmentation, and the task execution efficiency of the terminal is improved.
Drawings
FIG. 1 is a flow chart of the present invention;
fig. 2 is a schematic block diagram of an internal structure of a terminal device according to an embodiment of the present invention.
Detailed Description
The technical scheme of the invention is clearly and completely described below with reference to the examples and the drawings. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The study finds that the regional coverage path planning is a basic technology (the robot, the investigation and exploration unmanned aerial vehicle and the agricultural robot are all terminals for executing tasks) which is relied on when the sweeping robot, the investigation and exploration unmanned aerial vehicle and the agricultural robot execute tasks. The existing area coverage path planning algorithm comprises the following steps in whole: 1. dividing the area to be covered; 2. path planning is carried out inside each sub-area; 3. the order and path of access to each sub-region is calculated.
Because the robot needs to accelerate and decelerate during turns, one important indicator of the area coverage algorithm is the number of turns in the planned path in order to quickly complete the area coverage task. For this reason, in the second step, the robot often travels by using an arcuate movement route. In order to ensure that the robot can advance in an arcuate path in each sub-area, in step one, the area to be covered needs to be segmented. The existing research has made an important advance in the problem of how to divide the area that can be covered by the archwire route, namely the archwire decomposition algorithm (BCD algorithm). By utilizing the algorithm, the area to be covered can be divided into a plurality of subareas on the premise of giving the cleaning direction, and the interior of each subarea can be ensured to be cleaned by using an arcuate route.
The BCD algorithm solves the problem of realizing the first step and the second step to a certain extent, and on the basis, researchers in recent years propose a series of algorithms based on optimizing and solving the access sequence of the subareas. Mannadiar et al propose to use the "key points" employed in decomposing the regions in the BCD algorithm as vertices of the graph, use each decomposed region as an edge of the graph, and then convert the problem of traversing all regions into a mail-drop problem on the graph (i.e., how to traverse all edges). Vandermeulon et al propose that the sweep start point, end point, virtual center of the sub-region can be made the vertex of the graph for each sub-region, constructing the traveler problem to optimize the traversal order.
The algorithm can be summarized as realizing the first and second steps by using the BCD algorithm, and then optimizing the third step. A common limitation of these algorithms is that tasks must be performed in the same direction for each sub-region, and for some more square-shaped, or less obstructed environments, better processing of the task may be achieved even if each sub-region is performed in the same direction. However, for the outdoor environment, since the boundaries in the outdoor environment are often no longer regular, the number of obstacles in the outdoor environment is various and dense, and taking the minimum turn number of the terminal as a standard, the performance of the area coverage algorithm is greatly reduced by adopting a single direction. For this purpose, an optimization algorithm for the first and second steps needs to be designed. In the prior art, the division of the area to be covered increases the turning times when the terminal executes the task, thereby reducing the efficiency of executing the task by the terminal.
In order to solve the technical problems, the invention provides a method, a device, equipment and a storage medium for dividing a region for path planning, which solve the problems that in the prior art, the dividing of a region to be covered increases the turning times when a terminal executes a task, thereby reducing the efficiency of executing the task by the terminal. When the method is implemented, a voronoi diagram segmentation method is firstly applied to a region to be segmented for segmentation to obtain a voronoi diagram; then, according to the Veno segmentation map, obtaining alternative edges contained in the Veno segmentation map; and then obtaining a priori boundary edge according to the alternative edge. And finally, obtaining a target segmentation area according to the prior boundary and the Veno segmentation map. According to the method and the device for planning the paths of the target segmentation areas, the number of turns of the terminal on the paths can be reduced, and therefore the task execution efficiency of the terminal is improved.
For example, the area to be divided is an irregular polygon, a circular area (the area where the obstacle is located, i.e. the non-task area) is inside the polygon, and the task is not needed to be executed by the terminal, and the circular area is the task area inside the polygon. In order to ensure that the directions of executing tasks are inconsistent (the directions are inconsistent and the turning times of a terminal can be reduced), a Voronoi diagram segmentation method is adopted to divide a region to be segmented to obtain five segmentation surfaces, the five segmentation surfaces correspond to thirteen sides, and two vertexes of two sides in the thirteen sides are completely positioned in a non-task region; three sides are that one vertex is positioned in a task area, and one vertex is positioned in a non-task area; only two vertexes of eight sides are completely positioned in a task area, the eight sides are defined as alternative sides, the priori boundary sides are obtained according to the eight sides, the area to be segmented is segmented according to the priori boundary sides, a target segmentation area is obtained, and finally, the path of the terminal when executing the task is planned according to the target segmentation area, so that the turning times of the terminal when executing the task can be reduced, and the working efficiency of the terminal is improved.
Exemplary method
The region segmentation method for path planning in the embodiment can be applied to terminal equipment, and the terminal equipment can be a terminal product with a mobile function, such as a sweeping robot, a detection and exploration unmanned aerial vehicle, an agricultural robot and the like. In this embodiment, as shown in fig. 1, the region segmentation method for path planning specifically includes the following steps:
s100, dividing the region to be divided by using a Voronoi diagram dividing method to obtain a Voronoi diagram.
In this embodiment, the area to be segmented is a task area covered by the task to be executed by the sweeping robot, the area to be segmented is a polygon, the polygonal field is provided with an obstacle, an unvented area and a building (all the three are non-task areas, the polygonal field is provided with a task area except for the three areas), and the obstacle, the unvented area and the building are also polygons. And taking each side of the polygon as input of a Voronoi diagram segmentation method to obtain the Voronoi diagram.
The method is characterized in that the region to be segmented is subjected to the Veno segmentation firstly, so that the directions of the sweeping robots in the subsequent target segmented regions are inconsistent as much as possible, and the turning times of the sweeping robots can be reduced due to the inconsistent directions, and the sweeping efficiency of the sweeping robots is improved.
S200, obtaining an alternative edge contained in the Voronoi division diagram according to the Voronoi division diagram, wherein two vertexes of the alternative edge are both positioned in a task area, and the task area is an area in which a terminal in the area to be divided needs to execute a task.
Step S200 includes steps S201, S202, S203 as follows:
s201, obtaining a division plane contained in the Veno division map according to the Veno division map.
The region to be segmented is subjected to the voronoi segmentation, so that a plurality of segmentation surfaces can be obtained, and the segmentation surfaces can be irregular patterns.
S202, preprocessing the Veno segmentation map according to the vertex corresponding to the segmentation surface and the task area to obtain the preprocessed Veno segmentation map.
In the embodiment, the vertices corresponding to the segmentation plane obtained in step S201 are located in the task area, and the vertices are located outside the task area, and the segmentation plane with the vertices all located outside the task area is deleted from the voronoi segmentation map, that is, the voronoi segmentation map is preprocessed. The preprocessing is performed on the voronoi diagram to reduce the subsequent calculation amount.
And S203, obtaining the alternative edges according to the pre-processed Veno segmentation map.
In this embodiment, for any one edge in the voronoi diagram obtained in step 202, if both vertices are in the task area, the edge is referred to as an alternative edge.
For example, the voronoi segmentation map includes five segmentation planes, and five vertices of one pentagonal segmentation plane are all located outside the task area, so that the pentagonal segmentation plane is deleted from the voronoi segmentation map, and then only four segmentation planes remain in the voronoi segmentation map. Then searching the edges corresponding to the four dividing surfaces, assuming twenty edges of the four dividing surfaces, and selecting fifteen edges of which two vertexes are in the task area from the twenty edges, wherein the fifteen edges are candidate edges.
S300, obtaining a priori boundary edge according to the alternative edge.
Step S300 includes steps S301, S302, S303, S304, S305, S306, S307, S308, S309, S3010, S3011 as follows:
s301, calculating the distance between the point on the alternative side and the boundary corresponding to the task area.
S302, calculating a point corresponding to the minimum distance between the candidate edge and the nearest boundary of the task area, and recording the point as the nearest point.
S303, calculating the distance between the nearest point and the nearest boundary of the task area, and recording the distance as a first distance.
S304, calculating the tangent vector of the candidate edge at the nearest point.
S305, calculating the distance between the coordinate corresponding to the nearest point and the coordinate corresponding to the sum of the tangent vectors and the nearest boundary of the task area, and marking the distance as a second distance.
S306, obtaining the distance gradient according to the difference between the second distance and the first distance.
In this embodiment, the distance gradient g (p * (e))：
Wherein p is * (e) For the nearest point (closest point in coordinates) on candidate edge e, d (p * (e) Point p) * (e) Distance from nearest boundary of the task area (first distance), delta is candidate edge e at p * (e) The tangent vector at t is a constant, in this example t is 0.01, d (p * (e) +tδ) as coordinate p * (e) Distance of +tδ to the nearest boundary of the task area.
S307, according to the distance and the distance gradient, obtaining an evaluation function value corresponding to the candidate edge, namely, according to the sum of the absolute value of the first distance and the distance gradient, obtaining an evaluation function value V (e) corresponding to the candidate edge:
V(e)＝ad(p * (e))+b|g(p * (e))|
wherein a and b are parameters, |g (p * (e) Is g (p) * (e) Absolute value of (c).
And S308, obtaining the alternative edge adjacent to the alternative edge according to the alternative edge, and marking the alternative edge as an alternative adjacent edge, wherein the alternative edge and the alternative adjacent edge have a common vertex.
S309, when the evaluation function value corresponding to the alternative adjacent edge is larger than the evaluation function value corresponding to the alternative edge, marking the alternative edge as a cutting edge.
Illustrating: for example, one of the alternative edges a has three adjacent alternative edges b, c, and t. The evaluation function value of the first is larger than the evaluation function values corresponding to the second, third and fourth, and then the first is a cutting edge.
S3010, calculating a point corresponding to the minimum distance between the cutting edge and the nearest boundary of the task area, and marking the point as a cutting point.
There are many points on the cut edge, among which there is one point that is the cut point where the distance to the nearest boundary of the task area is the smallest.
S3011, the prior boundary edge is obtained after the line segments of the cutting points, which are perpendicular to the cutting edge and the two end points are positioned on the boundary of the task area are made.
S400, obtaining a target segmentation area according to the priori boundary and the Veno segmentation map, wherein the target segmentation area is used for planning a path required by executing a task.
Step S400 includes steps S401, S402, S403, S404, S405, S406, S407, S408, S409, S410, S411 as follows:
S401, obtaining adjacent segmentation surfaces contained in the Veno segmentation map according to the Veno segmentation map, wherein the adjacent segmentation surfaces have common edges.
S402, fusing the adjacent segmentation surfaces which do not contain the priori boundary edges and the boundaries of the task area in the Veno segmentation map into a plane to obtain a primary segmentation area.
In this embodiment, the voronoi segmentation map is stored in a half-graph, and the planes in the voronoi graph are fused by using a half-graph data structure: for any two adjacent faces (adjacent means that the two adjacent faces have a common edge), if the common edge is not an priori boundary edge or a boundary of a task area, the two adjacent faces are fused into one face. In the planar segmentation finally obtained in this embodiment, only the task area boundary and the prior boundary edge are included. The primary segmentation of the task area by using prior information and heuristic algorithm is realized.
S403, obtaining each primary segmentation plane contained in the primary segmentation area according to the primary segmentation area.
S404, dividing each primary division plane along the longest side of each primary division plane by adopting an arch-shaped decomposition algorithm to obtain a secondary division area.
For the primary division planes obtained in step S403, in each primary division plane, further division is performed along the longest side of the plane using a BCD algorithm or a trapezoidal division algorithm. In the dividing process, the direction of dividing each surface is recorded, and the current dividing direction of any surface c is dir 1 (c) A. The invention relates to a method for producing a fibre-reinforced plastic composite Furthermore, if the prior boundary edge needs to be split into two, then the newly split edge needs to be marked as the prior boundary edge as well.
And S405, obtaining each secondary division plane contained in the secondary division area according to the secondary division area.
S406, fusing the adjacent secondary segmentation planes which do not contain the prior boundary edge into a plane to obtain the fused secondary segmentation area.
Randomly selecting a surface c1, randomly selecting a surface c2 adjacent to the surface c1, and if the prior boundary edge does not exist in the edges shared by the surface c1 and the surface c2, fusing the surface c1 and the surface c2 into one surface, and marking the surface as a surface c3.
And S407, dividing each plane along the longest edge of the planes contained in the fused secondary division area by adopting an arch-shaped decomposition algorithm to obtain a tertiary division area.
Decomposing c3 along the longest side direction by using a BCD algorithm; in the decomposition process, the direction dir of decomposition needs to be recorded 2 (c) And marks the prior boundary edge.
S408, according to the normal vector of each vertex of each secondary division plane and a first unit vector, the height corresponding to each secondary division plane is obtained, and the first unit vector is a unit vector perpendicular to the direction of the longest edge of the primary division plane.
Let us assume that the secondary segment has only two faces c1, c2, c1 corresponding to a height h (c 1):
h(c1)＝max k＝1,…,m {n(c 1 ) T p k |}-min k＝1,…,m {n(c 1 ) T p k |}
height h (c 1) corresponding to c 2:
h(c2)＝max k＝1,…,m {n(c 2 ) T p k |}-min k＝1,…,m {n(c 2 ) T p k |}
wherein n (c) 1 ) Is equal to sum n (c) 2 ) Are unit vectors, T is the transposition of the vectors, p k For vertices on a face, m is the number of vertices.
S409, obtaining each cubic division plane contained in the cubic division area according to the cubic division area.
S410, obtaining the height corresponding to each cubic dividing plane according to the normal vector of each vertex of each cubic dividing plane and a second unit vector, wherein the second unit vector is a unit vector perpendicular to the direction of the longest edge of the plane contained in the secondary dividing area.
Calculating a cubic segmentation plane s by adopting the formula 1 ,…s k′ Corresponding height
S411, obtaining the target segmentation area by the height corresponding to each secondary segmentation plane and the height corresponding to each tertiary segmentation plane.
Calculating a cost value f ({ c) composed of the heights corresponding to the respective quadratic division planes 1 ,c 2 })：
f({c 1 ,c 2 })＝h(c 1 )+h(c 2 )+γ
Calculating a cost value f ({ s) composed of the heights corresponding to the three-time division planes 1 ,…s k′ })：
f({s 1 ,…s k′ })＝h(s 1 )+…+h(s k′ )+γ(k′-1)
If f ({ s) 1 ,…s k′ })≤f({c 1 ,c 2 -j) retaining the current decomposition result, namely, a segmentation region obtained by segmentation after fusion is used as a target segmentation region; otherwise, the secondary segmentation area before the fusion of the faces c1 and c2 is not used as the target segmentation area.
In this embodiment, the secondary division plane is selected repeatedly and randomly, and whether the secondary division plane needs to be fused is determined until the number of repetitions reaches the set number.
After the target segmentation area is obtained in the steps S100-S400, the sweeping robot plans a path in the target segmentation area, and the path planning method comprises the following steps: acquiring each target segmentation plane corresponding to the target segmentation area; obtaining bow-shaped paths corresponding to the target segmentation planes through the target segmentation planes; and applying a travel provider planning algorithm to the arcuate path to obtain the order of executing tasks of each target segmentation plane.
Specifically: for the target division area (planar division result) obtained in S400, an arcuate path is planned for each of the surfaces, and the cleaning direction of any surface C is the division direction dir (C) thereof. The start point and the end point of the arcuate path of each surface are recorded, and the start point and the end point of the arcuate path of any surface C are denoted as P (C) and Q (C). The traversal order of each sub-region (face) is determined by solving an asymmetric traveller problem. I.e. construct graph G, with each face C of the current segmentation as a vertex in graph G; two directional sides (C1, C2) and (C2, C1) exist between any two surfaces C1 and C2, the lengths of the sides (C1, C2) are the lengths of the non-collision shortest paths from Q (C1) to P (C2) on the plane, and the lengths of the sides (C2, C1) are the lengths of the non-collision shortest paths from P (C1) to Q (C2) on the plane. After the composition G is thus formed, the asymmetric traveler problem traversing all vertices in the graph G can be solved using existing tools (e.g., using LKH software). The traversal order of the robot graph G plans an access order to access the faces within the target division area.
In summary, the method defines the edges of two vertexes in a task area (the area to be segmented comprises a task area and a non-task area, the task area is an area where a terminal needs to execute tasks, and the non-task area is an area where the terminal does not need to execute tasks) as alternative edges, obtains prior boundary edges according to the alternative edges, and finally segments the area to be segmented according to the prior boundary edges to obtain a target segmented area comprising each segmented plane. When the terminal performs a task, it is required to turn when it reaches a non-task area (an area with an obstacle), and the turning may reduce the efficiency of the terminal to perform the task. According to the method and the device, the non-task area in the task area to be segmented is removed through the alternative edge, and the area is segmented according to the priori boundary edge, so that the turning times can be reduced when the terminal moves on a path obtained after segmentation, and the task execution efficiency of the terminal is improved.
Exemplary apparatus
The embodiment also provides a device for a region segmentation method for path planning, which comprises the following components:
the device comprises a Veno segmentation module, a Veno segmentation module and a Veno segmentation module, wherein the Veno segmentation module is used for segmenting a region to be segmented by applying a Veno graph segmentation method to obtain a Veno segmentation graph;
The alternative edge calculation module is used for obtaining alternative edges contained in the voronoi segmentation diagram according to the voronoi segmentation diagram, wherein two vertexes of the alternative edges are positioned in a task area, and the task area is an area in which a terminal in the area to be segmented needs to execute a task;
the priori boundary edge calculation module is used for obtaining a priori boundary edge according to the alternative edge;
and the segmentation module is used for obtaining a target segmentation area according to the prior boundary edge and the Veno segmentation graph, and the target segmentation area is used for planning a path required by executing a task.
Based on the above embodiment, the present invention also provides a terminal device, and a functional block diagram thereof may be shown in fig. 2. The terminal equipment comprises a processor, a memory, a network interface, a display screen and a temperature sensor which are connected through a system bus. Wherein the processor of the terminal device is adapted to provide computing and control capabilities. The memory of the terminal device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the terminal device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a region segmentation method for path planning. The display screen of the terminal equipment can be a liquid crystal display screen or an electronic ink display screen, and the temperature sensor of the terminal equipment is preset in the terminal equipment and is used for detecting the running temperature of the internal equipment.
It will be appreciated by persons skilled in the art that the functional block diagram shown in fig. 2 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the terminal device to which the present inventive arrangements are applied, and that a particular terminal device may include more or fewer components than shown, or may combine some of the components, or may have a different arrangement of components.
In one embodiment, there is provided a terminal device including a memory, a processor, and a region segmentation program for path planning stored in the memory and executable on the processor, the processor implementing the following operation instructions when executing the region segmentation program for path planning:
dividing the region to be divided by using a voronoi diagram dividing method to obtain a voronoi diagram;
obtaining an alternative edge contained in the voronoi segmentation diagram according to the voronoi segmentation diagram, wherein two vertexes of the alternative edge are positioned in a task area, and the task area is an area in the area to be segmented, in which a terminal needs to execute a task;
obtaining a priori boundary edge according to the alternative edge;
and obtaining a target segmentation area according to the prior boundary and the Veno segmentation map, wherein the target segmentation area is used for planning a path required by executing a task.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
In summary, the invention discloses a region segmentation method, a device, equipment and a storage medium for path planning, wherein the method comprises the following steps: dividing the region to be divided by using a voronoi diagram dividing method to obtain a voronoi diagram; obtaining an alternative edge contained in the voronoi segmentation diagram according to the voronoi segmentation diagram, wherein two vertexes of the alternative edge are positioned in a task area, and the task area is an area in the area to be segmented, in which a terminal needs to execute a task; obtaining a priori boundary edge according to the alternative edge; and obtaining a target segmentation area according to the prior boundary and the Veno segmentation map, wherein the target segmentation area is used for planning a path required by executing a task. The invention can reduce the turning times when the terminal moves on the path obtained after the segmentation, thereby improving the efficiency of executing the task by the terminal.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (11)
1. A region segmentation method for path planning, comprising:
dividing the region to be divided by using a voronoi diagram dividing method to obtain a voronoi diagram;
obtaining an alternative edge contained in the voronoi segmentation diagram according to the voronoi segmentation diagram, wherein two vertexes of the alternative edge are positioned in a task area, and the task area is an area for executing a task by a terminal in the area to be segmented;
obtaining a priori boundary edge according to the alternative edge;
obtaining a target segmentation area according to the prior boundary edge and the Veno segmentation map, wherein the target segmentation area is used for planning a path required by executing a task;
obtaining a priori boundary edge according to the alternative edge comprises the following steps:
calculating the distance between the point on the alternative side and the boundary corresponding to the task area;
calculating a distance gradient corresponding to the point on the alternative side according to the distance;
obtaining an evaluation function value corresponding to the alternative edge according to the distance and the distance gradient;
obtaining the priori boundary edge according to the evaluation function value;
obtaining a target segmentation area according to the prior boundary and the voronoi segmentation map, wherein the target segmentation area is used for planning a path required by executing a task and comprises the following steps:
Obtaining adjacent segmentation surfaces contained in the voronoi segmentation map according to the voronoi segmentation map, wherein the adjacent segmentation surfaces have common edges;
fusing the adjacent segmentation surfaces which do not contain the priori boundary edges and the boundaries of the task areas in the Veno segmentation map into a plane to obtain a primary segmentation area;
obtaining each primary segmentation plane contained in the primary segmentation area according to the primary segmentation area;
dividing each primary division plane along the longest side of each primary division plane by adopting an arch-shaped decomposition algorithm to obtain a secondary division area;
and obtaining the target segmentation area according to the secondary segmentation area.
2. The method for regional segmentation for path planning according to claim 1, wherein the obtaining, from the voronoi segmentation map, the candidate edges included in the voronoi segmentation map comprises:
obtaining a segmentation surface contained in the voronoi segmentation map according to the voronoi segmentation map;
preprocessing the Veno segmentation map according to the vertex corresponding to the segmentation surface and the task area to obtain the preprocessed Veno segmentation map;
And obtaining the alternative edges according to the pre-processed Veno segmentation graph.
3. The method for area segmentation for path planning according to claim 2, wherein preprocessing the voronoi segmentation map according to the vertex corresponding to the segmentation surface and the task area to obtain the preprocessed voronoi segmentation map comprises:
and deleting the segmentation surfaces corresponding to the vertexes outside the task area to obtain the pre-processed Veno segmentation map.
4. The method for area segmentation for path planning according to claim 1, wherein the calculating a distance gradient corresponding to a point on the candidate side according to the distance comprises:
calculating a point corresponding to the minimum distance between the candidate edge and the nearest boundary of the task area, and marking the point as the nearest point;
calculating the distance between the nearest point and the nearest boundary of the task area, and recording the distance as a first distance;
calculating a tangent vector of the candidate edge at the nearest point;
calculating the distance between the coordinate corresponding to the nearest point and the coordinate corresponding to the sum of the tangent vectors and the nearest boundary of the task area, and marking the distance as a second distance;
And obtaining the distance gradient according to the difference between the second distance and the first distance.
5. The method for area segmentation for path planning according to claim 4, wherein the obtaining the evaluation function value corresponding to the candidate edge according to the distance and the distance gradient comprises:
and obtaining an evaluation function value corresponding to the alternative edge according to the sum of the absolute value of the first distance and the distance gradient.
6. The method for area segmentation for path planning according to claim 1, wherein the obtaining the prior boundary edge according to the evaluation function value comprises:
obtaining an alternative edge adjacent to the alternative edge according to the alternative edge, and marking the alternative edge as an alternative adjacent edge, wherein the alternative edge and the alternative adjacent edge have a common vertex;
when the evaluation function value corresponding to the alternative adjacent edge is larger than the evaluation function value corresponding to the alternative edge, marking the alternative edge as a cutting edge;
calculating a point corresponding to the minimum distance between the cutting edge and the nearest boundary of the task area, and marking the point as a cutting point;
and obtaining the prior boundary edge according to the cutting point, the cutting edge and the task area, wherein the cutting point is positioned on the prior boundary edge, the prior boundary edge is perpendicular to the cutting edge, and two end points of the prior boundary edge are positioned on the boundary of the task area.
7. The area segmentation method for path planning according to claim 1, wherein the obtaining the target segmented area according to the secondary segmented area comprises:
obtaining each secondary partition plane contained in the secondary partition area according to the secondary partition area;
fusing the adjacent secondary segmentation planes which do not contain the prior boundary edge into a plane to obtain the fused secondary segmentation area;
dividing each plane along the longest edge of the planes contained in the secondary divided regions after fusion by adopting an arch-shaped decomposition algorithm to obtain a tertiary divided region;
obtaining the height corresponding to each secondary segmentation plane according to the normal vector of each vertex of each secondary segmentation plane and a first unit vector, wherein the first unit vector is a unit vector perpendicular to the direction of the longest edge of the primary segmentation plane;
obtaining each cubic division plane contained in the cubic division area according to the cubic division area;
obtaining the height corresponding to each three-time dividing plane according to the normal vector of each vertex of each three-time dividing plane and a second unit vector, wherein the second unit vector is a unit vector perpendicular to the direction of the longest side of the plane contained in the two-time dividing area;
And obtaining the target segmentation area by the height corresponding to each secondary segmentation plane and the height corresponding to each tertiary segmentation plane.
8. The area segmentation method for path planning of claim 7, further comprising, after the area segmentation method step:
acquiring each target segmentation plane corresponding to the target segmentation area;
obtaining bow-shaped paths corresponding to the target segmentation planes through the target segmentation planes;
and applying a travel provider planning algorithm to the arcuate path to obtain the order of executing tasks of each target segmentation plane.
9. An apparatus for a region segmentation method for path planning, the apparatus comprising:
the device comprises a Veno segmentation module, a Veno segmentation module and a Veno segmentation module, wherein the Veno segmentation module is used for segmenting a region to be segmented by applying a Veno graph segmentation method to obtain a Veno segmentation graph;
the alternative edge calculation module is used for obtaining alternative edges contained in the voronoi segmentation diagram according to the voronoi segmentation diagram, wherein two vertexes of the alternative edges are positioned in a task area, and the task area is an area for executing a task by a terminal in the area to be segmented;
the priori boundary edge calculation module is used for obtaining a priori boundary edge according to the alternative edge;
The segmentation module is used for obtaining a target segmentation area according to the priori boundary edge and the Veno segmentation map, and the target segmentation area is used for planning a path required by executing a task;
obtaining a priori boundary edge according to the alternative edge comprises the following steps:
calculating the distance between the point on the alternative side and the boundary corresponding to the task area;
calculating a distance gradient corresponding to the point on the alternative side according to the distance;
obtaining an evaluation function value corresponding to the alternative edge according to the distance and the distance gradient;
obtaining the priori boundary edge according to the evaluation function value;
obtaining a target segmentation area according to the prior boundary and the voronoi segmentation map, wherein the target segmentation area is used for planning a path required by executing a task and comprises the following steps:
obtaining adjacent segmentation surfaces contained in the voronoi segmentation map according to the voronoi segmentation map, wherein the adjacent segmentation surfaces have common edges;
fusing the adjacent segmentation surfaces which do not contain the priori boundary edges and the boundaries of the task areas in the Veno segmentation map into a plane to obtain a primary segmentation area;
Obtaining each primary segmentation plane contained in the primary segmentation area according to the primary segmentation area;
dividing each primary division plane along the longest side of each primary division plane by adopting an arch-shaped decomposition algorithm to obtain a secondary division area;
and obtaining the target segmentation area according to the secondary segmentation area.
10. Terminal equipment, characterized in that it comprises a memory, a processor and a region segmentation program for path planning stored in the memory and executable on the processor, which processor, when executing the region segmentation program for path planning, implements the steps of the region segmentation method for path planning according to any of claims 1-8.
11. A computer-readable storage medium, on which a region segmentation program for path planning is stored, which, when executed by a processor, implements the steps of the region segmentation method for path planning as claimed in any one of claims 1-8.
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