CN116048069A - Outdoor full-coverage path planning method based on GPS positioning and robot - Google Patents
Outdoor full-coverage path planning method based on GPS positioning and robot Download PDFInfo
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Abstract
The invention discloses an outdoor full-coverage path planning method and a robot based on GPS positioning, wherein the method comprises the following steps: constructing an operation area of the robot according to the GPS positioning information, and fitting a contour line of the operation area and a contour line of the obstacle into a polygon; decomposing the operation area into a plurality of units by adopting a cattle cultivation type unit decomposition method; determining a first unit to be traversed according to the current position of the robot, and solving the problem of a traveling company by adopting a depth-first search algorithm to obtain the traversing sequence of each unit; carrying out intra-cell full-coverage path planning on a first unit according to a sideline translation strategy, and carrying out intra-cell full-coverage path planning on corresponding units according to the traversal sequence of other units; and outputting a full-coverage path planning result of the operation area, and navigating the robot according to the full-coverage path planning result. According to the full-coverage path planning method and the full-coverage path planning device, full-coverage path planning is achieved through the sideline translation strategy, and the efficiency and coverage rate of the full-coverage path planning of the robot operation area are improved.
Description
Technical Field
The invention relates to the technical field of robots, in particular to an outdoor full-coverage path planning method based on GPS positioning and a robot.
Background
The robot navigation system is a basis that the robot can freely move in different working environments, and the path planning is one of key technologies in the robot navigation system and directly affects the working quality and the working efficiency of the robot. The traditional point-to-point path planning method is to find a path from optimum in the working area. With the continuous application of robots to more fields, the conventional path planning method has difficulty in meeting the operation demands of part of fields, such as agriculture, gardens, sanitation, military industry and the like. The work in these fields is different from the traditional method that a certain station in the working area is reached to perform a specified operation, namely, a certain point is reached, the robot is required to reach each point in the working area, and therefore, the robot needs to plan a path which can pass through the point in the working area, namely, full coverage planning.
The premise of the existing full-coverage planning algorithm is that the working area of the robot is known, namely, a robot navigation map expressed by a binary image or grid mode is adopted, how the robot obtains the working area is not explained, and the method is not sufficient in integrity.
The most commonly used full-coverage method of a single unit at present is cattle cultivation type reciprocating motion, and the method is easy to generate multiple coverage modes in one unit, namely multiple solutions are generated, uncertainty is generated in actual operation, the evaluation mode of the optimal solution has no unified standard, and the problem of high-efficiency connection with the next unit is not considered, so that the operation efficiency is influenced.
The other part of schemes only solve the full coverage in a single unit, do not mention how to carry out optimal route planning on a plurality of units, but connect the units in series according to the nearest distance, and do not consider the optimization problem of the route; for another example, the business problem is solved, and the greedy algorithm used by the business problem is faster in solving speed, but the finally obtained solution is not necessarily the optimal solution, so that the efficiency of the full coverage operation is affected.
Therefore, the prior art also has the problems of low full coverage planning efficiency and low coverage rate.
Disclosure of Invention
The invention aims to solve the technical problems of low planning efficiency and low coverage rate of the traditional full-coverage planning method by providing an outdoor full-coverage path planning method and a robot based on GPS positioning aiming at the defects of the prior art.
The technical scheme adopted for solving the technical problems is as follows:
in a first aspect, the present invention provides a method for planning an outdoor full coverage path based on GPS positioning, including:
constructing a working area of the robot according to GPS positioning information, and fitting a contour line of the working area and a contour line of an obstacle into a polygon;
decomposing the operation area into a plurality of units by adopting a cattle cultivation type unit decomposition method;
determining a first traversed unit according to the current position of the robot, and solving a traveling business problem by adopting a depth-first search algorithm to obtain the traversing sequence of each unit;
performing intra-cell full-coverage path planning on the first cell according to a sideline translation strategy, and performing intra-cell full-coverage path planning on the corresponding cell according to the traversal sequence of the rest cells;
and outputting a full-coverage path planning result of the working area, and navigating the robot according to the full-coverage path planning result.
In one implementation, the constructing the working area of the robot according to the GPS positioning information includes:
acquiring a first remote control instruction, and controlling the robot to bypass a first area according to the first remote control instruction to obtain a contour line of the operation area;
and acquiring a second remote control instruction, and controlling the robot to bypass the second area according to the second remote control instruction to obtain the contour line of the obstacle in the working area.
In one implementation, the constructing the working area of the robot according to the GPS positioning information further includes:
acquiring a first point drawing line in a visual interface, and determining a contour line of the operation area according to the first point drawing line;
and acquiring a second point drawing line in the visual interface, and determining the contour line of the obstacle in the working area according to the second point drawing line.
In one implementation, the constructing a working area of the robot according to the GPS positioning information, and fitting a contour line of the working area and a contour line of an obstacle into a polygon, includes:
calculating GPS coordinate information corresponding to the contour line of the operation area and the contour line of the obstacle respectively, and mapping the corresponding GPS coordinate information to image pixel points to obtain a gray value map of the operation area;
generating a grid map of the operation area according to the gray value graph of the operation area;
generating the working area according to the grid map of the working area;
and fitting the contour line of the working area and the contour line of the obstacle into straight lines respectively to obtain a polygon with holes.
In one implementation, the decomposing the work area into a plurality of units using a ox cultivation type unit decomposition method includes:
decomposing the operation area by adopting the cattle cultivation type unit decomposition method to obtain a plurality of non-porous polygons;
merging adjacent ones of the non-porous polygons rightward from the leftmost non-porous polygon or leftward from the rightmost non-porous polygon, each merging one of the non-porous polygons, detecting whether the merged polygon is a convex polygon;
if the polygon is the convex polygon, the combined polygon is set as a convex polygon unit;
and obtaining a plurality of convex polygon units according to the combined polygons.
In one implementation, the determining the first unit traversed according to the current position of the robot, and solving the problem of the traveling business by adopting a depth-first search algorithm, to obtain the traversing sequence of each unit, includes:
acquiring real-time position information of the current robot according to the GPS positioning information of the robot;
determining a unit where the current robot is located according to the real-time position information and the position information of each unit to obtain a first traversed unit;
and solving the problem of the traveling staff by adopting the depth-first search algorithm according to the first unit, and obtaining the traversal sequence of each unit.
In one implementation manner, the performing intra-unit full coverage path planning on the first unit according to the sideline translation policy, and performing intra-unit full coverage path planning on the corresponding unit according to the traversal sequence of the rest units, includes:
determining a coverage direction and a cost function of the first unit according to the sideline translation strategy, and planning a full-coverage path in the first unit according to the coverage direction and the cost function;
and carrying out intra-cell full-coverage path planning on the corresponding units according to the traversal sequence of the rest units and the corresponding coverage directions and cost functions.
In one implementation manner, the determining the coverage direction and the cost function of the first unit according to the sideline translation policy, and performing intra-unit full coverage path planning on the first unit according to the coverage direction and the cost function includes:
calculating the height from edge to edge in each first unit, determining the direction with the minimum height, and setting the direction with the minimum height as the covering direction;
determining the cost function according to the evaluation index with the shortest path, calculating the path length required by translational coverage corresponding to each side of the first unit according to the cost function, and setting the side of the shortest path as the side of translational coverage in the unit;
and moving the side of the translational coverage in the first unit according to the interval set by the user parameter from the bottom of the first unit, and performing translational coverage to obtain the intra-unit full coverage path planning of the first unit.
In a second aspect, the present invention also provides a robot comprising: the system comprises a processor and a memory, wherein the memory stores an outdoor full coverage path planning program based on GPS positioning, and the outdoor full coverage path planning program based on GPS positioning is used for realizing the operation of the outdoor full coverage path planning method based on GPS positioning according to the first aspect when being executed by the processor.
In a third aspect, the present invention also provides a storage medium, which is a computer readable storage medium, storing a GPS positioning based outdoor full coverage path planning program, which when executed by a processor, is configured to implement the operation of the GPS positioning based outdoor full coverage path planning method according to the first aspect.
The technical scheme adopted by the invention has the following effects:
according to the invention, a robot operation area is constructed according to GPS positioning information, and an operation area contour line and an obstacle contour line are fitted into a polygon, so that the operation area can be decomposed into a plurality of units by adopting a cattle-ploughing type unit decomposition method during path planning, and a traveling business problem can be solved by adopting depth-first search, so that the traversing sequence of each unit is obtained; according to the full-coverage path planning method and the full-coverage path planning device, full-coverage path planning is achieved through the sideline translation strategy, and the efficiency and coverage rate of the full-coverage path planning of the robot operation area are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of an outdoor full coverage path planning method based on GPS positioning in one implementation of the invention.
FIG. 2 is a schematic diagram of a high-precision map in a visual interface in one implementation of the invention.
FIG. 3 is a schematic diagram of a mapping after manually checking contours of a visual interface in one implementation of the invention.
FIG. 4 is a graph of gray values after binarization of an image in one implementation of the invention.
FIG. 5 is a grid diagram after rasterization processing through an image in one implementation of the present invention.
FIG. 6 is a schematic diagram of an apertured polygon in one implementation of the invention.
FIG. 7 is a schematic representation of a plurality of non-porous polygons obtained using a ox-type cell decomposition process in one implementation of the invention.
FIG. 8 is a schematic representation of a convex polygon in one implementation of the invention after merging a plurality of non-porous polygons.
Fig. 9 is a schematic diagram of a cell in which a robot is located in one implementation of the invention.
FIG. 10 is a schematic diagram of the traversal order of the units in one implementation of the invention.
FIG. 11 is a schematic diagram of intra-cell full coverage path planning in one implementation of the invention.
FIG. 12 is a schematic diagram of a full coverage path plan within a work area in one implementation of the invention.
Fig. 13 is a flow chart of outdoor full coverage path planning for practical use in one implementation of the present invention.
FIG. 14 is a flow chart of generating a job area in one implementation of the present invention.
FIG. 15 is a flow chart of a full coverage path planning for an entire work area using a method of translating one side of a polygon in one implementation of the present invention.
Figure 16 is a functional schematic of a robot in one implementation of the invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clear and clear, the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Exemplary method
The premise of the existing full-coverage planning algorithm is that the working area of the robot is known, namely, a robot navigation map expressed by a binary image or grid mode is adopted, how the robot obtains the working area is not explained, and the method is not sufficient in integrity.
The most commonly used full-coverage method of a single unit at present is cattle cultivation type reciprocating motion, and the method is easy to generate multiple coverage modes in one unit, namely multiple solutions are generated, uncertainty is generated in actual operation, the evaluation mode of the optimal solution has no unified standard, and the problem of high-efficiency connection with the next unit is not considered, so that the operation efficiency is influenced.
The other part of schemes only solve the full coverage in a single unit, do not mention how to carry out optimal route planning on a plurality of units, but connect the units in series according to the nearest distance, and do not consider the optimization problem of the route; for another example, the business problem is solved, and the greedy algorithm used by the business problem is faster in solving speed, but the finally obtained solution is not necessarily the optimal solution, so that the efficiency of the full coverage operation is affected.
Therefore, the prior art also has the problems of low full coverage planning efficiency and low coverage rate.
Aiming at the technical problems, the embodiment of the invention provides an outdoor full-coverage path planning method based on GPS positioning, which constructs a robot operation area according to GPS positioning information, and fits the outline of the operation area and the outline of an obstacle into polygons, so that the operation area can be decomposed into a plurality of units by adopting a ox-type unit decomposition method during path planning, and travel business problems can be solved by adopting depth-first search, and the traversing sequence of each unit is obtained; according to the embodiment of the invention, the full-coverage path planning is realized through the sideline translation strategy, and the efficiency and coverage rate of the full-coverage path planning of the robot operation area are improved.
As shown in fig. 1, an embodiment of the present invention provides an outdoor full coverage path planning method based on GPS positioning, including the following steps:
step S100, a working area of the robot is constructed according to GPS positioning information, and a contour line of the working area and a contour line of an obstacle are fitted into a polygon.
In this embodiment, the outdoor full-coverage path planning method based on GPS positioning is applied to a robot; of course, the outdoor full-coverage path planning method based on GPS positioning can also be applied to other terminals or path planning equipment.
In this embodiment, the first step of this embodiment is to obtain a work area, i.e., a grid map, of the robot that needs to be fully covered for path planning; secondly, fitting edge contour lines and barrier contour lines of an operation area on the grid map into a polygon with holes to prepare for unit decomposition of the next step; the third step is to decompose the operation area (i.e. the perforated polygon) into a plurality of units (i.e. the non-perforated polygon) by adopting a ox-ploughing type unit decomposition method, so that no static obstacle exists in the area when the single unit full coverage scanning is performed; the fourth step is to determine the first unit through the current robot positioning; fifthly, solving the problem of the tourist by adopting depth-first search, and acquiring the traversal sequence of each unit; and step six, completing the full coverage in the units by adopting a polygonal side translation method, repeating the coverage method according to the unit traversing sequence obtained in the step five to sequentially complete the coverage of all the units, and then completing the full coverage path planning of the whole operation area.
In this embodiment, before the working area of the robot is constructed, a manner in which the robot acquires the working area needs to be determined, where the acquisition manner is: manually remotely controlling the robot movement to obtain the operation area by giving a command manually, or manually selecting the operation area on a high-precision map in a visual interface; the visual interface is an interface in a computer, a mobile phone and other equipment, and is a user operation interface.
Specifically, in one implementation of the present embodiment, the step S100 includes the following steps before:
step S100a, a first remote control instruction is obtained, and the robot is controlled to bypass a first area according to the first remote control instruction, so that a contour line of the operation area is obtained;
step S100b, obtaining a second remote control command, and controlling the robot to bypass the second area according to the second remote control command, so as to obtain the contour line of the obstacle in the working area.
In this embodiment, if the operation area is obtained by manually remotely controlling the movement of the robot, the robot is manually controlled (or remotely controlled on a visual interface) to make a circle around the area where the robot is required to work in the area where the robot is required to work, so as to obtain the contour line of the operation area, that is, the robot is controlled to make a circle around the first area according to the first remote control instruction, so as to obtain the contour line of the operation area.
Then, winding a circle of static barriers in the area along the edges by using a manual remote control robot, so as to obtain contour lines of the barriers; and controlling the robot to bypass the second area according to the second remote control instruction to obtain the contour line of the obstacle in the working area.
Specifically, in one implementation of the present embodiment, the following steps are further included before step S100:
step S021, obtaining a first point drawing line in a visual interface, and determining the contour line of the operation area according to the first point drawing line;
step S022, a second point drawing line in the visual interface is obtained, and the outline of the obstacle in the operation area is determined according to the second point drawing line.
In this embodiment, if a manner of manually selecting and obtaining a working area on a high-precision map in a visual interface is adopted, manual selection is required on the high-precision map (as shown in fig. 2); determining the contour line of the operation area in a line drawing and point mode on the existing high-precision map by manually using a visual interface (GUI), namely determining the contour line of the operation area according to the first point line drawing; then, the contour line of the obstacle is determined in the same way, i.e. the contour line of the obstacle in the working area is determined from the second stippled line.
In this embodiment, after the contour line of the operation area and the contour line of the obstacle are obtained, the corresponding GPS coordinate information is calculated, and the image of the area where the two contour lines are located is processed, so that the polygon with holes formed in the operation area can be obtained.
Specifically, in one implementation of the present embodiment, step S100 includes the steps of:
step S101, calculating GPS coordinate information corresponding to the contour line of the operation area and the contour line of the obstacle respectively, and mapping the corresponding GPS coordinate information to image pixel points to obtain a gray value diagram of the operation area;
step S102, generating a grid map of the operation area according to the gray value map of the operation area;
step S103, generating the working area according to the grid map of the working area;
and step S104, fitting the contour line of the working area and the contour line of the obstacle into straight lines respectively to obtain a polygon with holes.
In this embodiment, after the operation area is obtained, all GPS coordinate information on the two contour lines are calculated respectively, and mapped onto the image pixels, so as to obtain a map as shown in fig. 3; then, the map is converted into a gray value map as shown in fig. 4 by the image binarization process; and converting the gray value map into a grid map as shown in fig. 5 through an image rasterization process.
After the grid map is obtained, fitting the edge contour line of the operation area and the contour line of the obstacle, which are represented in the obtained grid map, into a straight line to obtain a polygon with holes; wherein the edge contour of the working area is the side of the perforated polygon and the contour of the obstacle is the hole inside the perforated polygon, as shown in fig. 6.
In the embodiment, a working area of the robot is obtained in two ways, a first way is that a remote controller or a visual interface (GUI) is used for controlling the robot to make a circle on a working field to determine a contour line of the working area, then an obstacle in the contour line is made to make a circle to determine the contour line of the obstacle by the same method, and the two contour lines are overlapped to obtain the robot working area; secondly, determining the contour line of a working area on an existing high-precision map by using a visual interface (GUI) manually, determining the contour line of an obstacle by using the same method, and overlapping the two contour lines to obtain a robot working area; the accuracy of the acquisition of the working area is improved in two different ways.
As shown in fig. 1, an embodiment of the present invention provides an outdoor full coverage path planning method based on GPS positioning, including the following steps:
and step 200, decomposing the operation area into a plurality of units by adopting a cattle cultivation type unit decomposition method.
In this embodiment, after obtaining the porous polygon, the porous polygon is subjected to cell decomposition to obtain a plurality of non-porous polygons, as shown in fig. 7.
The decomposition method adopted in the embodiment is a cattle-ploughing type unit decomposition method, and a plurality of non-porous polygons obtained by preliminary decomposition are effectively combined on the basis of the cattle-ploughing type unit decomposition method to obtain a plurality of final non-porous convex polygons; wherein, niu Geng type unit decomposition method is round trip type decomposition method, and is similar to the way of cattle farming to decompose, obtain a plurality of preliminary units.
Specifically, in one implementation of the present embodiment, step S200 includes the steps of:
step S201, decomposing the operation area by adopting the cattle cultivation type unit decomposition method to obtain a plurality of non-porous polygons;
step S202, merging adjacent non-porous polygons to the right from the leftmost non-porous polygon or merging adjacent non-porous polygons to the left from the rightmost non-porous polygon, and detecting whether the merged polygon is a convex polygon or not when each non-porous polygon is merged;
step S203, if the polygon is the convex polygon, the combined polygon is set as a convex polygon unit;
step S204, obtaining a plurality of convex polygon units according to the combined polygons.
In this embodiment, when merging a plurality of non-porous polygons, merging is performed according to a preset merging order; wherein the preset merge sequence is a left-to-right (or right-to-left) sequence; as shown in fig. 7, adjacent polygons (polygons B) are first merged to the right from the leftmost element (polygon a) in fig. 7, and then each merging is performed to detect whether the next merged polygon is a convex polygon, where the detection rule is:
judging whether the combined polygons have inner angles larger than 180 degrees or not; if the internal angle is larger than 180 degrees, the polygon A is set as the first unit after the combination, the polygon B is set as the polygon A, and the combination of the set polygon A (namely the original polygon B) is continued. If no internal angle is larger than 180 degrees, the new polygon after combination is formed into a polygon A, and the combination is continued until the internal angle is larger than 180 degrees.
As shown in fig. 8, in this embodiment, the merging principle is adopted in which all units after merging are convex polygons.
In this embodiment, after the primary unit decomposition is performed on the working area (i.e. the perforated polygon), unit combination is required to achieve the optimal number of units, which is helpful for improving the final coverage efficiency.
As shown in fig. 1, an embodiment of the present invention provides an outdoor full coverage path planning method based on GPS positioning, including the following steps:
step S300, determining a first unit to be traversed according to the current position of the robot, and solving the problem of the traveling business by adopting a depth-first search algorithm to obtain the traversing sequence of each unit.
In this embodiment, the real-time position information of the current robot is obtained according to the GPS positioning of the robot, the unit where the robot is currently located is determined by combining the obtained multiple units (i.e., the non-porous convex polygon), as shown in fig. 9, the unit where the current robot is located is set as the first unit to be traversed, and then the traversing sequence of other units is determined according to the first unit.
Specifically, in one implementation of the present embodiment, step S300 includes the steps of:
step S301, acquiring real-time position information of a current robot according to GPS positioning information of the robot;
step S302, determining a unit where the current robot is located according to the real-time position information and the position information of each unit, and obtaining a first traversed unit;
step S303, solving the traveling business problem by adopting the depth-first search algorithm according to the first unit, and obtaining the traversal sequence of each unit.
In this embodiment, according to the obtained units (i.e., the non-hole convex polygon) and the unit where the obtained robot is currently located, the travel business problem is solved by using depth-first search, so that the traversal order (the order shown in fig. 10) of each unit can be obtained; the optimal solution of the depth-first search is the traversal order of each unit.
When depth-first search is adopted, firstly, the centroid point of each unit (namely, a non-porous convex polygon) is set as the center point of the unit, and the distance from the unit to all adjacent units is calculated; then, taking the unit where the current robot is located as a starting node, and starting searching for one adjacent unit of the units; then, searching for the next non-passing unit by taking the second unit as a node; if the adjacent units of the current unit are all passed, but the non-passed units are in the global, the method returns to the previous unit, if the adjacent units are not adjacent to the non-passed units, the method continues to return until the adjacent units are the non-passed units, and returns to search for the next non-passed unit by taking the second unit as a node.
Finally, the unit where the current robot is located is taken as an initial node, and searching is started to the next node of another adjacent unit; all directions are traversed to obtain all paths (all solutions), each path has a sum of distances, namely a total path, and the shortest path is the optimal solution.
In the embodiment, the travel business problem is solved by adopting the depth-first search, and the traversal order of each unit is obtained, wherein the depth-first search is a traversal algorithm based on graph optimization for solving the travel business problem, and the efficiency of full-coverage planning is improved.
As shown in fig. 1, an embodiment of the present invention provides an outdoor full coverage path planning method based on GPS positioning, including the following steps:
and step S400, carrying out intra-cell full-coverage path planning on the first cell according to a sideline translation strategy, and carrying out intra-cell full-coverage path planning on the corresponding cell according to the traversing sequence of the rest cells.
In this embodiment, for the full coverage path planning of a single cell, a coverage manner is proposed in which the full coverage path planning is implemented with translation of a certain side of the cell (i.e., the non-porous convex polygon).
Specifically, in one implementation of the present embodiment, step S400 includes the following steps:
step S401, determining a coverage direction and a cost function of the first unit according to the sideline translation policy, and performing intra-unit full coverage path planning on the first unit according to the coverage direction and the cost function.
In this embodiment, the sideline translation strategy is: and determining the coverage direction in a height calculation mode, and designing a cost function by taking the shortest path as an evaluation index to determine the side of the unit for translating coverage.
Specifically, in one implementation of the present embodiment, step S401 includes the steps of:
step S401a, calculating the height from edge to edge in the first unit, determining the direction with the minimum height, and setting the direction with the minimum height as the covering direction;
step S401b, determining the cost function according to the shortest evaluation index of the path, calculating the path length required by translational coverage corresponding to each side of the first unit according to the cost function, and setting the side of the shortest path as the side of translational coverage in the unit;
and step S401c, moving the side of the intra-cell translational coverage from the bottom of the first cell according to the interval set by the user parameter, and performing translational coverage to obtain the intra-cell full-coverage path planning of the first cell.
In this embodiment, first, the height from side to side of each unit where the robot is currently located is calculated, and the direction with the smallest height is taken as the direction of coverage; secondly, designing a cost function by taking the shortest path as an evaluation index, and calculating the path length required by translational coverage of each side of the current unit, wherein the side with the shortest path is the side which is finally subjected to intra-unit translational coverage; finally, moving the edge obtained in the last step according to the interval set by the user parameter from the bottom of the current unit to carry out translational coverage until the distance between the edge and the top is smaller than the interval set by the user parameter; the result of the intra-cell full coverage path planning for the first cell is shown in fig. 11.
Specifically, in one implementation of the present embodiment, step S400 further includes the following steps:
and step S402, carrying out intra-cell full-coverage path planning on the corresponding units according to the traversal sequence of the rest units, the corresponding coverage directions and the cost function.
In this embodiment, after the complete coverage path planning in the unit is completed once, whether the current unit is the last unit is determined, if not, the current unit is moved to the next unit, and the same planning step as the first unit is executed; if so, the coverage is ended, and the full coverage path planning of the operation area is completed, as shown in fig. 12.
In this embodiment, the side obtained in the previous step may be moved from the bottom of the unit according to the interval set by the user parameter to perform translational coverage until the distance from the top is smaller than the interval set by the user parameter, so as to obtain an intra-unit full-coverage path plan, and then, according to the traversal sequence obtained by depth-first search, the intra-unit full-coverage path plans are sequentially performed on the remaining units, so as to obtain the result of the full-coverage path plan of the operation area.
As shown in fig. 1, an embodiment of the present invention provides an outdoor full coverage path planning method based on GPS positioning, including the following steps:
and S500, outputting a full-coverage path planning result of the working area, and navigating the robot according to the full-coverage path planning result.
In this embodiment, after the full-coverage path planning result of the operation area is obtained, the robot may be navigated according to the full-coverage path planning result, so as to control the robot to perform operation in the operation area; by the path planning mode in the embodiment, the path coverage rate of the operation area is improved, and the path planning efficiency and the operation efficiency of the robot are also improved.
As shown in fig. 13, in an actual application scenario of the present embodiment, the full coverage path planning of the job area may include the following steps:
step S11, selecting boundary lines on a high-precision map by manual remote control of a robot or manual operation, and generating a working area;
step S12, fitting the edge contour line of the operation area and the obstacle contour line into a polygon;
step S13, decomposing the operation area (the perforated polygon) into a plurality of units (the non-perforated polygon) by adopting a cattle cultivation type unit decomposition method;
step S14, determining a first unit according to the current position of the robot;
step S15, solving the problem of the tourist by adopting depth-first search, and acquiring the traversal sequence of each unit;
step S16, completing the whole coverage in the unit by using a side line translation method;
step S17, judging whether the current unit is the last unit; if yes, go to step S18; if not, returning to the step S16;
step S18, ends.
As shown in fig. 14, specifically, in the above steps S11 to S18, step S11 includes the steps of:
step S21, starting;
step S22, judging whether the remote control is manual remote control; if yes, go to step S23; if not, executing step S24;
step S23, selecting boundary lines by a manual remote control robot;
step S24, selecting boundary lines on the high-precision map;
step S25, judging whether boundary selection is completed; if yes, go to step S26; if not, returning to the step S22;
step S26, GPS information corresponding to all points on the boundary is obtained and mapped to image pixel points;
step S27, generating an ash value graph;
step S28, generating a grid map;
step S29, generating a job area.
As shown in fig. 15, specifically, in the above steps S11 to S18, step S16 includes the steps of:
step S31, taking the direction with the minimum polygon height as the optimal direction;
step S32, calculating the shortest path to obtain an edge needing to be translated;
step S33 of calculating a scan by moving from the bottom to the top of the polygon;
step S34, judging whether the current unit is the last unit; if yes, go to step S35; if not, returning to the step S33;
step S35, ends.
For the steps S12 to S15 in the above-mentioned practical application scenario, please refer to the steps S200 to S400 in detail, and the detailed steps corresponding thereto are not described herein.
The following technical effects are achieved through the technical scheme:
according to the embodiment, a robot operation area is constructed according to GPS positioning information, and an operation area contour line and an obstacle contour line are fitted into a polygon, so that the operation area can be decomposed into a plurality of units by adopting a cattle-ploughing type unit decomposition method during path planning, and a traveling business problem can be solved by adopting depth-first search, so that the traversing sequence of each unit is obtained; according to the embodiment, full-coverage path planning is realized through the sideline translation strategy, and the efficiency and coverage rate of the full-coverage path planning of the robot operation area are improved.
Exemplary apparatus
Based on the above embodiment, the present invention further provides a robot including: the system comprises a processor, a memory, an interface, a display screen and a communication module which are connected through a system bus; wherein the processor is configured to provide computing and control capabilities; the memory includes a storage medium and an internal memory; the 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 storage medium; the interface is used for connecting external equipment, such as mobile terminals, computers and other equipment; the display screen is used for displaying corresponding information; the communication module is used for communicating with a cloud server or a mobile terminal.
The computer program when executed by the processor is configured to implement the operations of an outdoor full coverage path planning method based on GPS positioning.
It will be appreciated by those skilled in the art that the schematic block diagram shown in fig. 16 is merely a block diagram of a portion of the structure associated with the present inventive arrangements and is not limiting of the robots to which the present inventive arrangements are applied, and that a particular robot may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a robot is provided, comprising: the system comprises a processor and a memory, wherein the memory stores an outdoor full coverage path planning program based on GPS positioning, and the outdoor full coverage path planning program based on GPS positioning is used for realizing the operation of the outdoor full coverage path planning method based on GPS positioning when being executed by the processor.
In one embodiment, a storage medium is provided, wherein the storage medium stores a GPS positioning based outdoor full coverage path planning program, which when executed by the processor, is operative to implement the GPS positioning based outdoor full coverage path planning method as described above.
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 comprising instructions for the relevant hardware, the computer program being stored on a non-volatile storage medium, the computer program when executed comprising 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.
In summary, the invention provides an outdoor full-coverage path planning method and a robot based on GPS positioning, wherein the method comprises the following steps: constructing an operation area of the robot according to the GPS positioning information, and fitting a contour line of the operation area and a contour line of the obstacle into a polygon; decomposing the operation area into a plurality of units by adopting a cattle cultivation type unit decomposition method; determining a first unit to be traversed according to the current position of the robot, and solving the problem of a traveling company by adopting a depth-first search algorithm to obtain the traversing sequence of each unit; carrying out intra-cell full-coverage path planning on a first unit according to a sideline translation strategy, and carrying out intra-cell full-coverage path planning on corresponding units according to the traversal sequence of other units; and outputting a full-coverage path planning result of the operation area, and navigating the robot according to the full-coverage path planning result. According to the full-coverage path planning method and the full-coverage path planning device, full-coverage path planning is achieved through the sideline translation strategy, and the efficiency and coverage rate of the full-coverage path planning of the robot operation area are improved.
It is to be understood that the invention is not limited in its application to the examples described above, but is capable of modification and variation in light of the above teachings by those skilled in the art, and that all such modifications and variations are intended to be included within the scope of the appended claims.
Claims (10)
1. The outdoor full-coverage path planning method based on GPS positioning is characterized by comprising the following steps of:
constructing a working area of the robot according to GPS positioning information, and fitting a contour line of the working area and a contour line of an obstacle into a polygon;
decomposing the operation area into a plurality of units by adopting a cattle cultivation type unit decomposition method;
determining a first traversed unit according to the current position of the robot, and solving a traveling business problem by adopting a depth-first search algorithm to obtain the traversing sequence of each unit;
performing intra-cell full-coverage path planning on the first cell according to a sideline translation strategy, and performing intra-cell full-coverage path planning on the corresponding cell according to the traversal sequence of the rest cells;
and outputting a full-coverage path planning result of the working area, and navigating the robot according to the full-coverage path planning result.
2. The outdoor full-coverage path planning method based on GPS positioning according to claim 1, wherein the constructing the working area of the robot according to the GPS positioning information previously includes:
acquiring a first remote control instruction, and controlling the robot to bypass a first area according to the first remote control instruction to obtain a contour line of the operation area;
and acquiring a second remote control instruction, and controlling the robot to bypass the second area according to the second remote control instruction to obtain the contour line of the obstacle in the working area.
3. The outdoor full-coverage path planning method based on GPS positioning according to claim 1, wherein the constructing the working area of the robot according to the GPS positioning information further comprises:
acquiring a first point drawing line in a visual interface, and determining a contour line of the operation area according to the first point drawing line;
and acquiring a second point drawing line in the visual interface, and determining the contour line of the obstacle in the working area according to the second point drawing line.
4. The outdoor full coverage path planning method based on GPS positioning according to claim 2 or 3, wherein the constructing a working area of a robot according to GPS positioning information and fitting a contour line of the working area and an obstacle contour line into a polygon comprises:
calculating GPS coordinate information corresponding to the contour line of the operation area and the contour line of the obstacle respectively, and mapping the corresponding GPS coordinate information to image pixel points to obtain a gray value map of the operation area;
generating a grid map of the operation area according to the gray value graph of the operation area;
generating the working area according to the grid map of the working area;
and fitting the contour line of the working area and the contour line of the obstacle into straight lines respectively to obtain a polygon with holes.
5. The outdoor full coverage path planning method based on GPS positioning according to claim 1, wherein the decomposing the work area into a plurality of units by using a ox-type unit decomposition method comprises:
decomposing the operation area by adopting the cattle cultivation type unit decomposition method to obtain a plurality of non-porous polygons;
merging adjacent ones of the non-porous polygons rightward from the leftmost non-porous polygon or leftward from the rightmost non-porous polygon, each merging one of the non-porous polygons, detecting whether the merged polygon is a convex polygon;
if the polygon is the convex polygon, the combined polygon is set as a convex polygon unit;
and obtaining a plurality of convex polygon units according to the combined polygons.
6. The outdoor full-coverage path planning method based on GPS positioning according to claim 1, wherein determining a first unit traversed according to a current position of the robot, and solving a traveling business problem by using a depth-first search algorithm, and obtaining a traversal order of each unit comprises:
acquiring real-time position information of the current robot according to the GPS positioning information of the robot;
determining a unit where the current robot is located according to the real-time position information and the position information of each unit to obtain a first traversed unit;
and solving the problem of the traveling staff by adopting the depth-first search algorithm according to the first unit, and obtaining the traversal sequence of each unit.
7. The outdoor full-coverage path planning method based on GPS positioning according to claim 1, wherein the performing intra-unit full-coverage path planning on the first unit according to a sideline translation policy, and performing intra-unit full-coverage path planning on a corresponding unit according to a traversal order of remaining units, includes:
determining a coverage direction and a cost function of the first unit according to the sideline translation strategy, and planning a full-coverage path in the first unit according to the coverage direction and the cost function;
and carrying out intra-cell full-coverage path planning on the corresponding units according to the traversal sequence of the rest units and the corresponding coverage directions and cost functions.
8. The outdoor full coverage path planning method according to claim 7, wherein the determining the coverage direction and the cost function of the first unit according to the sideline translation policy, and performing intra-unit full coverage path planning on the first unit according to the coverage direction and the cost function, comprises:
calculating the height from edge to edge in each first unit, determining the direction with the minimum height, and setting the direction with the minimum height as the covering direction;
determining the cost function according to the evaluation index with the shortest path, calculating the path length required by translational coverage corresponding to each side of the first unit according to the cost function, and setting the side of the shortest path as the side of translational coverage in the unit;
and moving the side of the translational coverage in the first unit according to the interval set by the user parameter from the bottom of the first unit, and performing translational coverage to obtain the intra-unit full coverage path planning of the first unit.
9. A robot, comprising: a processor and a memory storing a GPS positioning based outdoor full coverage path planning program which when executed by the processor is operative to implement the GPS positioning based outdoor full coverage path planning method of any of claims 1-8.
10. A storage medium, characterized in that the storage medium is a computer readable storage medium, the storage medium storing a GPS positioning based outdoor full coverage path planning program, which when executed by a processor is adapted to implement the operations of the GPS positioning based outdoor full coverage path planning method according to any of claims 1-8.
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