CN118068842B - Low repetition rate coverage path planning method based on spanning tree - Google Patents
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Abstract
The invention relates to a spanning tree-based low-repetition-rate coverage path planning method, belongs to the technical field of autonomous planning control of robots, and solves the problem that a region coverage method in the prior art is difficult to fully cover a target region with any shape by using fewer repetition paths. The method fuses the spanning tree grids and other grids, and improves the coverage rate of the area; by processing the branch grids and the auxiliary grids, the coverage rate of the coverage path planning method area based on the spanning tree is improved, and meanwhile, fewer repeated coverage paths are generated; in addition, the area to be covered is mapped by a grid array model, and each grid to be covered in the array model is classified by a main grid, a branch grid and an auxiliary grid, and the full coverage path which is not repeated in the main grid is expanded to all the grids to be covered at the cost of less repeated paths by establishing rules for the branch grid and the auxiliary grid, so that the coverage rate of the coverage area of the unmanned equipment is improved.
Description
Technical Field
The invention belongs to the technical field of autonomous planning control of robots, and particularly relates to a low-repetition-rate coverage path planning method based on a spanning tree.
Background
Robot area coverage is a classical problem in the field of robot path planning. In the civil field, the two are combined to meet the actual requirements of indoor cleaning, lawn repair, pesticide spraying, disaster searching and rescuing and the like; in the military field, the two are combined with modern application in aspects of unmanned vehicle mine discharge, unmanned aerial vehicle coverage reconnaissance and the like to provide support. Such as chinese patent application: CN113219984A and CN117055570a.
In order to reduce the energy consumption of the coverage process, reduce the time for completing the coverage task, complete the coverage of a larger area within a specified mileage, and the like, it is desirable to reduce the repeated exploration of the non-covered area and the covered area on the premise of achieving the full coverage of the area. The traditional method adopts simple movement modes such as simple cow-ploughing type reciprocating movement and the like and combines the regional decomposition technology to plan the full coverage path, and the method is inevitably repeated or omitted when planning the coverage path in the face of regions with different shapes. There is a practical need to propose a method applicable under various zone shapes to minimize the repetition path during the coverage process and to ensure complete coverage of the zone.
Compared with a method of completing coverage in each sub-area by adopting simple movement based on accurate area division, the method of rasterizing the area and generating the coverage path based on the spanning tree is more suitable for planning the coverage path in any shape area with less repetition, and the method is easy to popularize in the field of multi-machine collaborative coverage. However, since the spanning tree-based coverage path planning method uses a grid approximation to map the area to be covered, and requires the integrity of a "large grid" when constructing the spanning tree, it is difficult for the conventional spanning tree-based coverage path planning method to ensure complete coverage of the area.
Disclosure of Invention
In view of the above problems, the present invention provides a spanning tree-based low repetition rate coverage path planning method, which solves the problem that in the prior art, it is difficult to fully cover an arbitrary shape target area with a small number of repetition paths.
The invention provides a spanning tree-based low repetition rate coverage path planning method, which specifically comprises the following steps:
step 1, mapping a region to be covered by using a rectangular grid array model; obtaining a grid to be covered comprising binary value assignment;
Step 2, dividing the grid to be covered into an auxiliary grid set, a branch grid set and a main grid set;
step 3, searching an expandable branch grid and establishing an expansion rule; obtaining an updated main grid set and an updated auxiliary grid set according to the expansion rule;
step 4, establishing a connection rule of the auxiliary grid and the attached grid; searching for an accessory grid connection set of the accessory grid corresponding to the updated accessory grid set according to the connection rule; determining a path of the robot through the attached grid based on the attached grid connection set of the attached grid;
step 5, constructing a spanning tree and a non-repeated annular coverage path in the trunk grid set obtained in the step 2;
And 6, expanding the non-repeated annular coverage path in the step 5 to a branch grid set and an auxiliary grid set in the step 3 to obtain paths capable of covering all grids to be covered.
Optionally, the specific steps of step1 are:
step 11, enveloping the area to be covered by using a rectangular grid array;
step 12, acquiring position points of a corresponding grid when the robot actually passes through the rectangular grid array when covering the area to be covered, the area of the grid to be covered and the grid outline of the grid;
Step 13, constructing a binary matrix based on position points of grids in the rectangular grid array, the grid area to be covered and the grid outline when the robot covers the area to be covered; the area to be covered is mapped using a binary matrix.
Optionally, in step 2, an auxiliary grid set is obtained according to an auxiliary grid division principle, specifically:
If the position points actually passed by the robot when covering the grids to be covered are in other grids, the grids to be covered are auxiliary grids, the grids to be covered are added into an auxiliary grid set, and the assignment of the binary value of the grids to be covered is adjusted to be 0.
Optionally, in step 2, an auxiliary grid set is obtained according to an auxiliary grid division principle, specifically: if the grid to be covered is adjacent to one other non-affiliated grid to be covered, the grid to be covered belongs to affiliated grids, the grid to be covered is added into an affiliated grid set, and assignment in a binary matrix corresponding to the grid to be covered is adjusted to be 0.
Optionally, in step 2, a branch grid set is obtained according to a branch grid division principle, specifically:
Dividing a binary matrix into a plurality of adjacent but disjoint blocks A sub-matrix; and if the binary values of one to three grids in the submatrix are assigned to be 1, adding the grids to be covered, which are assigned to be 1 in the submatrix, into the branch grid set.
Optionally, in step 2, a backbone grid set is obtained according to a backbone grid division principle, specifically:
Dividing a binary matrix into a plurality of adjacent but disjoint blocks And if the binary values of the four grids in the submatrix are assigned to be 1, adding all grids to be covered in the submatrix into the trunk grid set.
Optionally, the specific steps of step3 are as follows:
step 31, dividing a branch grid in a branch grid set into a plurality of connected domains;
Step 32, traversing a plurality of connected domains, and adding all single-layer annular grids in the connected domains into a single-layer annular grid set; adding all the double-layer strip grids in the connected domain into a double-layer strip grid set; acquiring all single-layer non-annular grids in the connected domain, packing branch grids of only one adjacent grid in the single-layer non-annular grids and the adjacent grids into branch grid pairs, and adding the branch grid pairs into a grid pair set; wherein the branch grids added to the single-layer annular branch grid sequence set or the double-layer strip-shaped branch grid sequence set or the branch grid pair set are expandable branch grids;
step 33, adding the rest branch grids divided in the step 32 into an affiliated grid set;
Step 34, examining all branch grid sequences in a single-layer annular branch grid sequence set, a double-layer strip branch grid sequence set and a branch grid pair set according to the expansion condition; adding all expandable branch grids in the branch grid sequences meeting the expansion conditions into a trunk grid set to obtain an updated trunk grid set; checking other branch grid sequences in the branch grid sequence set based on the updated trunk grid set, and traversing all branch grid sequences in the single-layer annular branch grid sequence set, the double-layer strip branch grid sequence set and the branch grid pair set until the branch grid sequences which do not meet the expansion condition; adding branch grids that do not satisfy the expansion condition to the auxiliary grid set in step 33 obtains an updated auxiliary grid set.
Optionally, the specific steps of step 4 are as follows:
step 41, establishing an affiliated grid relation between the affiliated grid and the affiliated grid;
Step 42, determining the connection mode of the robot from entering the attached grid to leaving the path between the attached grids by using the attached grid relation.
Optionally, the subsidiary grid relationship in step 41 is:
for the subsidiary relations generated when the position points actually passed when the robot covers the grid to be covered are in other grids, the grid to be covered and the other grids are recorded as subsidiary grid relations;
And/or the number of the groups of groups,
For the subsidiary relation generated by the condition that the grid to be covered by the robot is adjacent to one other non-subsidiary grid to be covered, recording the subsidiary relation between the grid to be covered and the other non-subsidiary grid to be covered as subsidiary grid relation;
And/or the number of the groups of groups,
And for the grids to be covered added into the affiliated grid set because the branch grids do not meet the expansion conditions, searching any random adjacent grid in adjacent grids according to a random principle, and recording the grids to be covered and the random adjacent grids as affiliated grid relations.
Optionally, the specific steps of step 42 are:
step 421, finding the auxiliary grids directly attached to the attached grid in all updated auxiliary grid sets according to the auxiliary grid relation obtained in step 41; establishing all affiliated connection grid sets of affiliated grids;
Step 422, based on the attached grid set of attached grids, an attached sequence of attached grids is obtained, and a path of the robot passing through the attached grids is obtained according to the ordering order of the elements in the attached sequence.
Compared with the prior art, the invention has at least the following beneficial effects:
(1) The method fuses the spanning tree grids and other grids, and improves the coverage rate of the area;
(2) The invention improves the spanning tree based by special treatment of branch grids and auxiliary grids
The coverage of the coverage path planning method area can generate less repeated coverage paths;
(3) When the unmanned equipment is used for executing area coverage tasks (such as cleaning, pesticide spraying, mine discharging and reconnaissance), the area to be covered is mapped by the grid array model, and each grid to be covered in the main grid, the branch grids and the auxiliary grids are classified by the grid array model, and a specific rule is established for the branch grids and the auxiliary grids, so that a full coverage path which is not repeated in the main grid originally is expanded to all grids to be covered at the cost of less repeated paths, and the coverage rate of the unmanned equipment coverage area is reduced.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention.
FIG. 1 is a flow chart of a spanning tree based low repetition rate coverage path planning method of the present invention;
FIG. 2 is a schematic diagram of a map, grid array and lattice map of an area to be covered according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating the classification of areas to be covered according to a large grid in accordance with an embodiment of the present invention;
FIG. 4 is a schematic diagram of a classification of a grid to be covered according to an embodiment of the present invention;
FIG. 5 is a schematic view of an accessory grid shown in an embodiment of the present invention;
FIG. 6 is a schematic diagram of a clockwise, counterclockwise and straight path traveled according to a grid, according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a spanning tree shown in an embodiment of the present invention;
fig. 8 is a schematic diagram of a coverage path according to an embodiment of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present invention and features in the embodiments may be combined with each other. In addition, the invention may be practiced otherwise than as specifically described and thus the scope of the invention is not limited by the specific embodiments disclosed herein.
1-8, A spanning tree-based low repetition rate coverage path planning method is disclosed, comprising the following steps:
step 1, mapping a region to be covered by using a rectangular grid array model; obtaining a grid to be covered comprising binary value assignment;
Step 11, using rectangular grid array Enveloping the area to be covered;
Further, rectangular grid array The grid shape of the grid is square; the side length of the grid is the diameter or the side length of the detection range of the robot; rectangular grid array/>The number of rows and columns of the grid array are respectively the smallest even numbers that enable the grid array to completely envelop the area to be covered. Rectangular grid array/>Including n grids.
It can be understood that the detection range of the robot is set as the side lengthIs the square of the grid side length/>; The side lengths of the areas to be covered in the horizontal direction and the vertical direction are respectively/>And/>Is a rectangle with grid array column number/>Grid array row number isSymbol/>Representing an upward rounding. Referring to FIG. 2, the side length/>, for the robot probe rangeIs 0.1km,/>And/>The coverage area, grid array and lattice map are all 1.9 km.
Further, the area to be covered comprises a connected area.
Step 12, acquiring position points of a corresponding grid, a grid area to be covered of the grid and a grid outline when the robot actually passes through the rectangular grid array when covering the area to be covered, wherein the expression is as follows:
Wherein, Represents the i-th grid/>, which actually passes through the rectangular grid array when the robot covers the area to be coveredIs a position point of (2); /(I)Representing the region of the ith grid to be covered; /(I)A grid profile representing an ith grid; /(I)Represents grid profile/>, with the ith gridBoxes of the same size; /(I)A set of points representing orthogonal intermediate lines of the grid profile of the ith grid; /(I)Representation area/>Is a part of the area of (2); /(I)Representation area/>Is defined by a geometric center of the mold; i=1, 2, …, I representing the total number of grids in the rectangular grid array.
Specifically, the point set of orthogonal intermediate lines of the grid profile of the ith gridIs the set of all points on the two orthogonal intermediate lines of the grid profile of the ith grid.
Wherein the grid profileIs a square, the middle line refers to the grid outline/>Which are parallel to the sides of the square and intersect at the center point of the square, dividing the square equally into four equally small squares.
Step 13, constructing a binary matrix based on position points of grids in the rectangular grid array, the grid area to be covered and the grid outline when the robot covers the area to be covered; the area to be covered is mapped using a binary matrix.
In particular, if the firstTo-be-covered area of individual grids/>If the area of (2) is greater than 0, the binary value/>, of the ith gridIs assigned a value of 1; if/>To-be-covered area of individual grids/>Is equal to 0, the binary value/>, of the ith gridIs assigned a value of 0;
If the binary value of the ith grid Is 1, and when the position point actually passing through the ith grid when the robot covers the area to be covered is not in the area to be covered, the binary value/>, of the ith gridIs adjusted to 0.
All binary values of all grids form a binary matrixThe binary matrix S is used to map the area to be covered.
It can be understood that the number of rows and columns of the binary matrix S and the number of rows and columns of the rectangular grid array are respectively equal; one element in the binary matrix S corresponds to one grid in the rectangular grid array; the binary value of each element in the binary matrix S is 0 or 1,0 representing the grid not to be covered and 1 representing the grid to be covered.
Step 2, dividing the grid to be covered into an auxiliary grid set, a branch grid set and a main grid set;
Obtaining an auxiliary grid set according to an auxiliary grid division principle, specifically:
A. If the robot covers the grid to be covered Location points actually passed byAt other grids/>In, the grid to be covered/>For the subsidiary grid, the grid to be covered/>Adding an affiliated grid set A, and adding the binary value/>, of the grid to be coveredIs adjusted to 0, a=1, 2, …, I representing the total number of grids in the rectangular grid array.
It will be appreciated that other gridsFor grid not to be covered in rectangular grid array/>Is arranged in the grid of the display device.
B. If the robot covers the grid to be coveredWith only one other non-affiliated grid/>Adjacent, the grid to be covered/>Belonging to an auxiliary grid, the grid to be covered/>Adding an affiliated grid set A, and adding the binary value/>, of the grid to be coveredIs adjusted to 0.
Obtaining a branch grid set and a trunk grid set according to a branch grid and trunk grid dividing principle, and specifically:
Binary matrix Divided into several adjacent but disjoint/>Submatrix/>Kth submatrix/>Corresponds to a grid subset/>; If the kth submatrix/>Where the value of the binary value of one to three grids is 1, the kth submatrix/>, is assignedTo-be-covered grid/>, with value of 1Join branch grid set/>If the kth submatrix/>The assignment of binary values of the four grids is 1, and the kth submatrix/>All grids to be covered are added into a main grid set/>; K=1, 2, …, I/4, I denotes the total number of grids in the rectangular grid array.
Illustratively, referring to FIG. 3, the binary matrix S is divided into several adjacent but disjoint componentsSubmatrix/>Is/are each grid subset of (C)Each grid subset/>Four grids are included, and classification of each grid of the grid array according to the rule division in this embodiment is given with reference to fig. 3.
Step 3, searching an expandable branch grid and establishing an expansion rule; obtaining an updated affiliated grid set;
Step 31, assembling branch grids The branch grids in the tree are divided into a plurality of connected domains according to adjacent relations;
step 32, traversing a plurality of connected domains, and adding all single-layer annular grids in the connected domains into a single-layer annular branch grid sequence set In (a) and (b); adding all double-layer strip grids in the connected domain into a double-layer strip branch grid sequence set/>; Acquiring all single-layer non-annular grids in the connected domain, packing branch grids of only one adjacent grid in the single-layer non-annular grids and the adjacent grids into branch grid pairs, and adding the branch grid pairs into a branch grid pair set/>; Wherein, added to the single-layer circular branch grid sequence set/>Or double-layer strip-shaped branch grid sequence set/>Or branch grid pair set/>Is an expandable branch grid.
Step 33, adding the remaining branch grids divided in step 32 to the affiliated grid set。
Step 34, examining the single-layer annular branch grid sequence set according to the expansion ruleDouble-layer strip-shaped branch grid sequence set/>And branch grid pair set/>A branched trellis sequence; adding all grids in the branch grid sequence into a trunk grid set T to obtain an updated trunk grid set T1; based on updating the backbone grid set T1 to examine other branch grid sequences in the branch grid sequence set, traversing the single-layer circular branch grid sequence set/>Double-layer strip-shaped branch grid sequence set/>And branch grid pair set/>Until no finger trellis sequence satisfying the extension rule is satisfied.
The extension rule is: the expansion rule is satisfied if there are two branch grids c ybm、cybn in the branch grid sequence that are adjacent to two backbone grids c ytp、cytq in the backbone grid set T, respectively, and two backbone grids c ytp、cytq are also adjacent.
Adding branch grids in the branch grid sequence which do not meet adjacent conditions into the affiliated grid setObtaining updated affiliated grid set/>。
Exemplary, referring to FIG. 5, for a single layer circular grid sequence setDouble layer stripe grid sequence set/>And grid pair set/>Any one of the branched trellis sequences/>If it satisfies the following formula, the rule/>, is extendedRecord:
；
；
；/>；/>；
；
Wherein, And/>Are respectively with the branching grid sequence/>Two adjacent backbone grids; /(I)For grid sequence/>Middle/>A grid; /(I)For grid sequence/>Middle/>A grid; p represents a grid sequence/>In the total number of grids.
After the searching process is finished, adding all branch grids which do not meet the expansion rule into an affiliated grid set. Step 4, establishing a connection rule of the auxiliary grid and the attached grid; searching for an accessory grid connection set of the accessory grid corresponding to the updated accessory grid set according to the connection rule; determining a path of the robot through the attached grid based on the attached grid connection set of the attached grid;
Step 41, establishing an affiliated grid relationship between the affiliated grid and the affiliated grid ；
Specifically, for covering the grid to be covered by the robotLocation points actually passed byAt other grids/>The affiliation generated in the grid layer records the grid layer to be covered/>And the other grid/>Is an affiliated grid relationship;
For the grid to be covered With only one other non-affiliated grid/>The affiliation generated by the adjacent cells records the grid/>With the other non-affiliated coverage grid/>Is an affiliated grid relationship;
For joining to affiliated grid set because branch grid does not meet expansion rule To be covered grid/>Searching any adjacent grid/>, according to a random principle, in the adjacent non-affiliated gridsRecord the grid to be covered/>Adjacent to the random grid/>Is an affiliated grid relationship.
As can be appreciated, with the grid to be coveredThe corresponding various grids that have an affiliated grid relationship are affiliated grids.
Step 42, determining the robot from entering the first step by using the subsidiary grid relationship obtained in step 41Each affiliated grid/>To leave the attached grid/>Path between/>The connection mode of the method comprises the following specific steps: step 421, finding all the updated auxiliary grids in the auxiliary grid relation obtained in step 41 to directly attach to the attached grid/>Attached grid set/>，/>Represents the/>Updating the affiliated grids; build attached grid/>Attached grid set/>，/>Represents the/>And a plurality of subsidiary connection grids.
Step 422, based on the attached gridTo obtain an attached grid/>According to the ordering order of the elements in the attached sequence, the path of the robot passing through the attached grid is obtained.
Specifically, as shown in FIG. 6, if the next grid of the attached grid is the next to the last grid of the attached grid, and the attached sequence of attached grids=/>Counterclockwise, then let/>For starting reference point, in the order/>, of the position points of the attached grid and the grid immediately above the attached gridFor the starting direction, arranged counter-clockwise/>, based on spatial positionObtaining an arranged grid sequence: /(I)Obtaining the attached grid/>, of the robotPath/>：/>Wherein/>Represent the firstGrid after arrangement,/>Representing the secondary attached grid/>Location points/>Pointing to the attached grid/>Position point of last grid/>Is a vector of (a).
Wherein, for the attached grids which are not attached to other gridsLet us assume that the affiliated grid is not considered in the path, where the last grid is/>The next grid is/>In the path considering the subsidiary grid, the last grid is/>；
As shown in fig. 6, if attachedClockwise, then arranged in a clockwise fashion based on spatial positionThe rest of the settings are unchanged.
As shown in fig. 6, if attachedIs arranged in a straight line, at/>Finding the last grid/>Nearest grid/>Above grid/>For starting reference point toFor the starting direction, arranged clockwise/>, based on spatial positionThe aligned grid sequence is/>Pass/>Path/>For/>。
Step 5, constructing a spanning tree and a non-repeated annular coverage path in the trunk grid set obtained in the step 2;
The area of the main grid set is composed of a plurality of grid sets Composition,/>Is the serial number of the main grid set, and selects each grid set/>Generating a mesh pattern/>, for a node, for the geometric center of the node；
Establishing an extension rule requiring additional rules to be followed by the spanning tree;
In particular, if an extension rule is generated Generated and branched lattice sequence/>Two adjacent backbone grids/>And/>Belonging to two different grid sets/>And/>When generating a spanning tree,/>And/>The corresponding tree nodes should be connected; if it is not possible to connect, then branch trellis sequence/>All branch grids in the list are added to the affiliated grid set/>, because the extension rule is not satisfiedThen update the affiliated grid relation/>；
Establishing an affiliated grid relationship according to step 41As new subsidiary grid relationships are created, connection rules for these subsidiary grids need to be established. To this step only the connection rules/>Need to be updated so we just re-execute step 4 for the newly generated auxiliary grid.
In the grid patternOptionally, constructing a spanning tree by taking one node as a root node according to a depth-first searching method, following the additional rule in the construction process, then optionally taking a trunk grid in a trunk grid area as a starting point to generate a ring-shaped coverage path, traversing the grids along the spanning tree from the trunk grid in a anticlockwise direction until returning to the starting grid (namely, the trunk grid serving as the starting point) again to form a loop, and connecting actual coordinate points corresponding to each trunk grid in the traversing process to form a non-repeated ring-shaped coverage path/>。
In particular, referring to fig. 7, it is illustrated how spanning trees are constructed in the backbone grid described in this embodiment.
And 6, expanding the non-repeated annular coverage path in the step 5 to a branch grid set and an auxiliary grid set in the step 3 to obtain paths capable of covering all grids to be covered.
Specifically, according to the extension rule of the step 3 and the connection rule of the step 4, the non-repeated annular coverage path of the step 5 is extended to the branch grid set, the affiliated grid set of the step 3 and the path of the robot passing through the affiliated grids, so that the paths capable of covering all grids to be covered are obtained.
In particular, the method comprises the steps of,Is a branching lattice sequence/>The path points corresponding to the grids involved in the process; /(I)Is a non-repeating circular coverage path/>Is provided.
For extension ruleEach branch trellis sequence involved/>Disconnect the non-repeating annular coverage path/>Middle/>In the absence of duplicate circular coverage path/>Establishment of/>To extend the non-repeating annular coverage path to a branching grid;
For each attached grid And affiliated grid set/>According to the subsidiary grid relation/>Will originally pass/>Step 4 of (a) obtaining a path of the robot through the attached grid to be replaced by/>。
In particular, referring to fig. 8, it is shown how, in the present embodiment, a coverage path is constructed to cover the area to be covered described in the present embodiment, with the coverage path construction rule.
While this specification contains many specific implementation details, these should not be construed as limitations on the scope of any invention or of what may be claimed, but rather as descriptions of features of specific embodiments of particular inventions. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. On the other hand, the various features described in the individual embodiments may also be implemented separately in the various embodiments or in any suitable subcombination. Furthermore, although features may be acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.
Similarly, although operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results.
The foregoing detailed description of the invention is provided for illustration, and it is not to be construed that the detailed description of the invention is limited to only those illustration, but that several simple deductions and substitutions can be made by those skilled in the art without departing from the spirit of the invention, and are to be considered as falling within the scope of the invention.
Claims (8)
1. The low repetition rate coverage path planning method based on the spanning tree is characterized by comprising the following steps of:
Step 1, mapping a region to be covered by using a rectangular grid array model; the method comprises the specific steps of:
step 11, enveloping the area to be covered by using a rectangular grid array;
step 12, acquiring position points of a corresponding grid when the robot actually passes through the rectangular grid array when covering the area to be covered, the area of the grid to be covered and the grid outline of the grid;
step 13, constructing a binary matrix based on position points of grids in the rectangular grid array, the grid area to be covered and the grid outline when the robot covers the area to be covered; mapping the area to be covered using a binary matrix;
Step 2, dividing the grid to be covered into an auxiliary grid set, a branch grid set and a main grid set;
Step 3, searching an expandable branch grid and establishing an expansion rule; obtaining an updated affiliated grid set;
Step 4, establishing a connection rule of the auxiliary grid and the attached grid; searching for an accessory grid connection set of the accessory grid corresponding to the updated accessory grid set according to the connection rule; determining a path of the robot passing through the attached grid based on the attached grid connection set of the attached grid, wherein the method comprises the following specific steps of:
step 41, establishing an affiliated grid relation between the affiliated grid and the affiliated grid;
Step 42, determining a connection mode of the robot from entering the attached grid to leaving the attached grid by using the attached grid relation;
step 5, constructing a spanning tree and a non-repeated annular coverage path in the trunk grid set obtained in the step 2;
And 6, expanding the non-repeated annular coverage path in the step 5 to a branch grid set, an auxiliary grid set in the step 3 and a path of the robot passing through the auxiliary grids, so as to obtain paths capable of covering all grids to be covered.
2. The low repetition rate coverage path planning method according to claim 1, characterized in that in step2, an auxiliary grid set is obtained according to an auxiliary grid division principle, in particular:
If the position points actually passed by the robot when covering the grids to be covered are in other grids, the grids to be covered are auxiliary grids, the grids to be covered are added into an auxiliary grid set, and the assignment of the binary value of the grids to be covered is adjusted to be 0.
3. The low repetition rate coverage path planning method according to any of the claims 1-2, characterized in that in step 2, an auxiliary grid set is obtained according to an auxiliary grid partitioning principle, in particular: if the grid to be covered is adjacent to one other non-affiliated grid to be covered, the grid to be covered belongs to affiliated grids, the grid to be covered is added into an affiliated grid set, and assignment in a binary matrix corresponding to the grid to be covered is adjusted to be 0.
4. The low repetition rate coverage path planning method according to claim 1, characterized in that in step2, a set of branch grids is obtained according to a branch grid partitioning principle, in particular:
Dividing a binary matrix into a plurality of adjacent but disjoint blocks A sub-matrix; and if the binary values of one to three grids in the submatrix are assigned to be 1, adding the grids to be covered, which are assigned to be 1 in the submatrix, into the branch grid set.
5. The low repetition rate coverage path planning method according to claim 4, characterized in that in step2, a set of backbone grids is obtained according to a backbone grid partitioning principle, in particular:
Dividing a binary matrix into a plurality of adjacent but disjoint blocks And if the binary values of the four grids in the submatrix are assigned to be 1, adding all grids to be covered in the submatrix into the trunk grid set.
6. The method for planning a coverage path with low repetition rate according to claim 1, wherein the specific steps of the step 3 are as follows:
step 31, dividing a branch grid in a branch grid set into a plurality of connected domains;
Step 32, traversing a plurality of connected domains, and adding all single-layer annular grids in the connected domains into a single-layer annular grid set; adding all the double-layer strip grids in the connected domain into a double-layer strip grid set; acquiring all single-layer non-annular grids in the connected domain, packing branch grids of only one adjacent grid in the single-layer non-annular grids and the adjacent grids into branch grid pairs, and adding the branch grid pairs into a grid pair set; wherein the branch grids added to the single-layer annular branch grid sequence set or the double-layer strip-shaped branch grid sequence set or the branch grid pair set are expandable branch grids;
step 33, adding the rest branch grids divided in the step 32 into an affiliated grid set;
Step 34, examining all branch grid sequences in a single-layer annular branch grid sequence set, a double-layer strip branch grid sequence set and a branch grid pair set according to the expansion condition; adding all expandable branch grids in the branch grid sequences meeting the expansion conditions into a trunk grid set to obtain an updated trunk grid set; checking other branch grid sequences in the branch grid sequence set based on the updated trunk grid set, and traversing all branch grid sequences in the single-layer annular branch grid sequence set, the double-layer strip branch grid sequence set and the branch grid pair set until the branch grid sequences which do not meet the expansion condition; adding branch grids that do not satisfy the expansion condition to the auxiliary grid set in step 33 obtains an updated auxiliary grid set.
7. The low repetition rate coverage path planning method of claim 1, wherein the affiliated grid relationship in step 41 is:
for the subsidiary relations generated when the position points actually passed when the robot covers the grid to be covered are in other grids, the grid to be covered and the other grids are recorded as subsidiary grid relations;
And/or the number of the groups of groups,
For the subsidiary relation generated by the condition that the grid to be covered by the robot is adjacent to one other non-subsidiary grid to be covered, recording the subsidiary relation between the grid to be covered and the other non-subsidiary grid to be covered as subsidiary grid relation;
And/or the number of the groups of groups,
And for the grids to be covered added into the affiliated grid set because the branch grids do not meet the expansion conditions, searching any random adjacent grid in adjacent grids according to a random principle, and recording the grids to be covered and the random adjacent grids as affiliated grid relations.
8. The method of claim 7, wherein the specific steps of step 42 are as follows:
step 421, finding the auxiliary grids directly attached to the attached grid in all updated auxiliary grid sets according to the auxiliary grid relation obtained in step 41; establishing all affiliated connection grid sets of affiliated grids;
Step 422, based on the attached grid set of attached grids, an attached sequence of attached grids is obtained, and a path of the robot passing through the attached grids is obtained according to the ordering order of the elements in the attached sequence.
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