CN117109596B - Self-mobile device, coverage path planning method and device thereof, and storage medium - Google Patents

Self-mobile device, coverage path planning method and device thereof, and storage medium Download PDF

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CN117109596B
CN117109596B CN202311371657.4A CN202311371657A CN117109596B CN 117109596 B CN117109596 B CN 117109596B CN 202311371657 A CN202311371657 A CN 202311371657A CN 117109596 B CN117109596 B CN 117109596B
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basic
paths
region
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CN117109596A (en
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林世城
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Shenzhen Pudu Technology Co Ltd
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Shenzhen Pudu Technology Co Ltd
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20Instruments for performing navigational calculations
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02DCLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00Reducing energy consumption in communication networks
    • Y02D30/70Reducing energy consumption in communication networks in wireless communication networks

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Automation & Control Theory (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

The application relates to a coverage path planning method and device for a self-mobile device, the self-mobile device, a storage medium and a computer program product. The method comprises the following steps: acquiring each sub-region in a target operation region; respectively acquiring a basic path set of each subarea; determining intermediate reference lines of all sub-areas from the basic path set respectively, and connecting the basic paths in the basic path set in a mode of crossing the intermediate reference lines to obtain local coverage planning paths in all the sub-areas respectively; and planning inter-region connection paths among all the subareas based on the local coverage planning paths in all the subareas to obtain a global coverage planning path of the target operation region. The path obtained by the coverage path planning method of the self-mobile equipment accords with the motion behavior of the real vehicle kinematic constraint, so that the potential safety hazard of the self-mobile equipment is avoided, and the motion safety of the self-mobile equipment is improved.

Description

Self-mobile device, coverage path planning method and device thereof, and storage medium
Technical Field
The present invention relates to the field of path planning technologies, and in particular, to a coverage path planning method and apparatus for a self-mobile device, a storage medium, and a computer program product.
Background
As the application of the overlay type self-mobile device is more and more widespread, more consideration is required for the security of the self-mobile device while the coverage rate is ensured.
The existing full-coverage path method is mostly suitable for indoor household cleaning robots, the generated coverage path allows routes such as broken lines, in-situ turning around and the like, has no limit of turning radius, does not accord with the restriction of real vehicle kinematics, cannot meet the path driving requirement of outdoor or commercial coverage type self-moving equipment, and easily causes potential safety hazards.
Disclosure of Invention
Based on this, it is necessary to provide a method, an apparatus, a self-mobile device, a computer readable storage medium and a computer program product for planning a coverage path of a self-mobile device, so as to generate a running path meeting the requirements of real vehicle kinematic constraint, so as to meet the requirements of safe motion of the outdoor, commercial and other coverage self-mobile devices.
In a first aspect, the present application provides a coverage path planning method of a self-mobile device, the method including the steps of:
acquiring each sub-region in a target operation region;
respectively acquiring a basic path set of each subarea;
Determining intermediate reference lines of all sub-areas based on the basic path set respectively, and connecting basic paths in the basic path set in a mode of crossing the intermediate reference lines to obtain local coverage planning paths in all the sub-areas respectively;
and planning inter-region connection paths among all the subareas based on the local coverage planning paths in all the subareas to obtain a global coverage planning path of the target operation region.
In a second aspect, the application further provides a coverage path planning device of the self-mobile device. The device comprises:
the target operation area decomposing module is used for decomposing the target operation area to obtain each sub-area;
the sub-region basic path searching module is used for acquiring a basic path set of each sub-region;
the local path planning module in the subarea is used for determining the middle reference line of each subarea based on the basic path set, and connecting the basic paths in the basic path set in a mode of crossing the middle reference line to respectively obtain local coverage planning paths in each subarea;
and the inter-region path connection planning module is used for planning inter-region connection paths among all the sub-regions based on the local coverage planning paths in all the sub-regions to obtain a global coverage planning path of the target operation region.
In a third aspect, the present application also provides a self-mobile device. The self-mobile device comprises a memory storing a computer program and a processor implementing the steps of the method described above when the processor executes the computer program.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the above method.
In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of the above method.
The self-mobile device and the coverage path planning method, the device, the storage medium and the computer program product of the self-mobile device comprise the following steps: acquiring each sub-region in a target operation region; respectively acquiring a basic path set of each subarea; determining intermediate reference lines of all sub-areas based on the basic path set respectively, and connecting basic paths in the basic path set in a mode of crossing the intermediate reference lines to obtain local coverage planning paths in all the sub-areas respectively; and planning inter-region connection paths among all the subareas based on the local coverage planning paths in all the subareas to obtain a global coverage planning path of the target operation region. According to the coverage path planning method of the self-mobile device, as the local planning in the subarea of the target operation area is connected with the basic paths in the basic path set in a mode of crossing the middle reference line, the movement behaviors of the self-mobile device, such as in-situ turning, small-radius turning and the like, which do not accord with the real vehicle kinematic constraint are avoided, the potential safety hazard caused by the movement behaviors of the self-mobile device are avoided, and the movement safety of the self-mobile device is improved.
Drawings
FIG. 1 is an application environment diagram of a coverage path planning method for a self-mobile device in one embodiment;
FIG. 2 is a flow diagram of a method for coverage path planning for a self-mobile device in one embodiment;
FIG. 3 is a flow chart of a coverage path planning method of a self-mobile device according to another embodiment;
FIG. 4 is a schematic diagram of an original environment map after preprocessing and connected domain searching in one embodiment;
FIG. 5 is a schematic diagram of a map of a target job area and its elongated sub-areas in one embodiment;
FIG. 6 is a schematic diagram of a map containing a set of base paths for each sub-region obtained after performing a linear path search for each sub-region in one embodiment;
FIG. 7 is a view of the sub-region of FIG. 6 in one embodimentMap schematic diagram after local path planning is carried out;
FIG. 8 is a view of the sub-region of FIG. 6 in one embodimentMap schematic diagram after local path planning is carried out;
FIG. 9 is a block diagram of an overlay path planning apparatus for a self-mobile device in one embodiment;
fig. 10 is an internal structural diagram of a self-mobile device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail 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 present application.
As the application of the overlay type self-mobile device is more and more widespread, more consideration is required for the security of the self-mobile device while the coverage rate is ensured. The existing full-coverage path method is mostly suitable for indoor household cleaning robots, and because the household cleaning robots are small in size and low in running speed in an indoor operation scene, and the user has a certain predictability on the movement behavior of the household cleaning robots, the potential safety hazard is low, so that the coverage path is allowed to have routes such as broken lines, in-situ turning around and the like, the turning radius is not required to be limited, and the movement track of the household cleaning robots is not required to conform to the restriction of the real vehicle kinematics. However, various covering type self-moving devices running in public places such as outdoors are large in size and high in movement speed, and in addition, if the covering paths of the covering type self-moving devices are allowed to have movement behaviors such as broken lines, in-situ turning and small-radius turning which do not conform to the movement constraints of real vehicles, the covering type self-moving devices are extremely easy to damage other traffic participants in application scenes of the covering type self-moving devices, so that potential safety hazards are brought.
Based on this, in order to solve the above technical problems, embodiments of the present application provide a coverage path planning method for a self-mobile device, where the generated global coverage planning path meets kinematic constraints of a real vehicle, so as to meet safe driving requirements of outdoor or commercial coverage self-mobile devices.
The coverage path planning method of the self-mobile device, provided by the embodiment of the application, can be applied to an application environment shown in fig. 1. The coverage path planning method may be performed by the self-mobile device 102 or the server 104, wherein the self-mobile device 102 communicates with the server 104 over a network. The data storage system may store data that the server 104 needs to process, such as space-time state information and current location information from the mobile device 102. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. The self-mobile device 102 first acquires each sub-region in the target job region; then, respectively acquiring a basic path set of each sub-region; then, respectively determining intermediate reference lines of all sub-areas based on the basic path sets, and connecting the basic paths in the basic path sets in a mode of crossing the intermediate reference lines so as to respectively obtain local coverage planning paths in all the sub-areas; and finally, planning inter-region connection paths among all the subareas based on the obtained local coverage planning paths in all the subareas, and obtaining a global coverage planning path of the target operation region. Among them, the self-moving device 102 includes, but is not limited to, various kinds of blanket robots (e.g., cleaning robots, painting robots, mowing robots, etc.), unmanned cleaning vehicles, plant protection robots, etc., which perform blanket job tasks by autonomous movement.
The present application provides a coverage path planning method for a self-mobile device, which is illustrated by way of example as performed by the self-mobile device 102 including the context aware sensor in fig. 1.
In one embodiment, as shown in fig. 2, a coverage path planning method of a self-mobile device includes the following steps S240 to S270:
s240, acquiring each sub-region in the target working region;
s250, respectively acquiring a basic path set of each sub-region;
s260, determining middle reference lines of all sub-areas based on the basic path sets respectively, and connecting basic paths in the basic path sets in a mode of crossing the middle reference lines to obtain local coverage planning paths in all the sub-areas respectively;
s270, planning inter-region connection paths among all sub-regions based on the local coverage planning paths in all sub-regions to obtain a global coverage planning path of the target operation region.
According to the coverage path planning method of the self-mobile device, the local planning in the subarea of the target operation area is to connect the basic paths in the basic path set in a mode of crossing the middle reference line, so that the movement behaviors of the self-mobile device, such as in-situ turning, small-radius turning and the like, which do not accord with the kinematic constraint of a real vehicle are avoided, the potential safety hazard caused by the movement behaviors of the self-mobile device are avoided, and the movement safety of the self-mobile device is improved.
Further, in one embodiment, as shown in fig. 3, before each sub-region in the target job region is acquired (i.e., step S240), the following steps are further included:
s220, preprocessing an original environment map to obtain a smooth map;
s230, searching the connected domain of the smooth map to obtain the area with the largest connected domain area, and taking the area as a target working area.
Illustratively, as shown in fig. 4, fig. 4 is a map obtained by preprocessing an original environment map and searching for connected domains, in which an area 410 in the map is a boundary of the map, an area 420 is an obstacle in the map, and a connected area is a target working area 430.
It should be noted that, the original environment map is an environment map of the operation scene where the self-mobile device is located, and is a map of the real operation environment, and the original environment map displays information such as static obstacles and boundaries in the environment in an original ecology manner. The user usually moves the self-mobile device in the operation scene through pushing, remote control of the self-mobile device or autonomous movement of the self-mobile device, and the like, and acquires objects in the environment of the user through sensing sensors such as a laser radar and/or a camera on the device in real time to acquire information such as distance, direction angle and the like of the environmental objects and the self-mobile device, and transmits the information to a processor, and the processor acquires an original environment map through mapping.
In one embodiment, preprocessing an original environment map to obtain a smooth map includes:
and carrying out binarization processing on the original environment map to obtain a binarized environment map.
Specifically, the pixel value of the pixel point with the pixel value smaller than T in the original environment map is changed to 0, and the pixel point with the pixel value larger than T is changed to 255 by setting a pixel threshold T, so that the original map is subjected to binarization processing. It can be understood that the environment map obtained after the binarization process only contains pixels of two colors, namely, the binarized environment map only comprises black blocks and white blocks.
And performing edge detection on the binarized environment map, identifying the outline of the obstacle, and performing outline drawing based on the outline of the obstacle. It can be appreciated that the contour of the obstacle in the map is enhanced by outlining or the like, so that the contour of the obstacle is more obvious and smooth, and the subsequent expansion and corrosion treatment is facilitated.
And (3) performing expansion treatment and corrosion treatment on the binarized environment map with the outline sketched, and obtaining a smooth map after treatment. It is understood that the expansion and corrosion treatment of the map can remove burrs and noise points in the binarized environment map.
The operation of preprocessing the original environment map may include, but is not limited to, the above-mentioned binarization process, contour enhancement process, erosion and expansion process.
In one embodiment, acquiring each sub-region in the target job region (i.e., step S240) includes:
decomposing the target operation area into sub-areas by using a unit decomposition method; and/or the number of the groups of groups,
if the long and narrow subareas exist in each subarea, the long and narrow subareas are combined with any subarea adjacent to the long and narrow subarea.
It is understood that the unit decomposition method, also called the region decomposition method or segmentation method, is a type of region segmentation method commonly used in the art. The method divides the target operation area to be traversed into a plurality of sub-areas according to a certain rule, so that all the sub-areas are combined to be still the original target operation area. The decomposition method generally selects edge vertexes of the obstacle as cutting points, cuts the non-obstacle part in the target area according to the appointed direction of the corresponding decomposition method by using cutting lines, and the number of the segmented subareas is related to the specific decomposition method. Common unit decomposition methods are approximate unit decomposition (Approximate Cell Decomposition, ACD), exact unit decomposition (Exact Cell Decomposition, ECD), trapezoidal unit decomposition (Trapezoidal Cell Decomposition, TCD), bolstering unit decomposition (Boustrophedon CellularDecomposition, BCD), and the like.
In one embodiment of the present application, the target job area is decomposed into a plurality of sub-areas, specifically using BCD decomposition. The sub-areas generated by using the BCD decomposition method are fewer, so that the path redundancy can be reduced, and the energy consumption and the time consumption are further reduced.
The principle of BCD decomposition is that assuming a vertical (or horizontal) dividing line, the whole bounded region with obstacles is scanned from left to right (or from top to bottom), and the boundary is divided whenever the edge vertex on the outermost side of the left and right (or top and bottom) of the obstacle is encountered, and finally the bounded environment is divided into a plurality of sub-regions without obstacles. The specific decomposition process can be to traverse the array column number (or row number) and determine each column (or row)) Connectivity of the dividing line, return the column number (or row number) and connected area; when connectivity of the dividing line changes, judging whether the dividing line is IN an off state (OUT event) or IN a converging state (IN event) according to the adjacent matrix, returning a data result to the current subarea for storage, displaying subarea partition information on a grid map, and marking each subarea as a subarea according to the generation sequence of each subarea Sub-area->…, subregion->
As shown in fig. 5 (a), for example, fig. 5 (a) is a map obtained by BCD-decomposing a target work area in the map of fig. 4, wherein the BCD-decomposing method uses a horizontal dividing line, the dividing direction is a horizontal direction, and 9 sub-areas obtained after dividing are respectively: sub-regionsSub-area->Sub-area->…, subregion->. As shown in fig. 5 (b), fig. 5 (b) is a map in which the target work area in the map of fig. 4 is BCD-decomposed, and the elongated subregion obtained by the decomposition is merged with the subregion adjacent thereto. As can be seen by comparing FIG. 5 (a), the sub-region in FIG. 5 (a) is +.>And subregion->Is a narrow region, so it is combined with its adjacent sub-region, i.e. the narrow sub-region +.>Adjacent to it subregion->Merging, the narrow sub-region +.>Adjacent subregions->Merging and renumbering to obtain 7 sub-regions in (b) of fig. 5, respectively: subregion->Sub-area->Sub-area->…, subregion->
In one embodiment, if there is an elongated sub-region in each sub-region, merging the elongated sub-region with any sub-region adjacent thereto, including:
Traversing the side length and the area of each subarea, comparing the side length with the first side length threshold value, and comparing the area with the first area threshold value;
if there is a sub-region with a side length less than the first side length threshold or an area less than the first area threshold, merging the sub-region with any one of the sub-regions adjacent to the sub-region.
In this embodiment, the merging of the long and narrow sub-regions can be reducedAnd the path redundancy improves the efficiency of linear path searching and path planning in the subsequent steps, thereby improving the working efficiency of the self-mobile equipment. The side length of each traversed subarea refers to the length or width of each traversed subarea; the first edge length threshold (i.e., length or width threshold) and the first area threshold may be set according to a specification parameter of the self-mobile device, e.g., preferably the first edge length threshold is set to 2d and/or the first area threshold is set to pi r 2 D is the width of the self-moving device and r is the minimum turning radius of the self-moving device. The above two determination conditions (the side length of the sub-region is smaller than the first side length threshold value, and the area of the sub-region is smaller than the first area threshold value) may be determined as "long sub-region" as long as they satisfy one of them.
It should be noted that, in the sub-area obtained after the target operation area unit is decomposed, there are usually two adjacent sub-areas, and when the sub-area is combined, it is preferable to combine it with the relatively smaller sub-area of the two adjacent sub-areas, for example, the sub-area in fig. 5 (a)Having two adjacent subregions->And->Due to its adjacent subregion->Is less than the adjacent other sub-region +.>Therefore, narrow sub-region->The relatively small subregion adjacent thereto>And combining. By doing so, the area difference between the subareas can be reduced, the inter-area connection path between the subareas is planned in the subsequent steps, the running path meeting the real vehicle kinematic constraint requirement is planned better, and the running safety of the self-moving equipment during operation is further improved.
In one embodiment, the acquiring the basic path set of each sub-region (i.e. step S250) includes:
respectively determining the long side direction of each subarea, and taking the long side direction as the searching direction of the corresponding subarea;
taking one long side of each sub-area as a base line, shifting preset intervals, and searching a straight line path of each sub-area along a searching direction until encountering a boundary or an obstacle of the sub-area to obtain a 1 st line segment serving as a 1 st basic path;
Taking the 1 st basic path as a base line, shifting by a preset interval, repeating the linear path searching process along the searching direction until encountering a sub-region boundary or an obstacle to obtain a 2 nd line segment serving as the 2 nd basic path;
each time, taking the previous basic path as a base line, shifting a preset interval along the searching direction, repeating the linear path searching process until each sub-area is searched, and taking n basic paths which are parallel to each other as a basic path set of each sub-area.
In this embodiment, the long-side direction of the sub-area is used as the search direction to perform the linear path search, and compared with the search mode in which the short-side direction is used as the search direction to perform the search, the basic path length obtained by the search mode in which the long-side direction is used as the search direction is longer and the number of the basic paths is smaller, so that frequent turning of the local planned paths in each sub-area can be effectively reduced, the path redundancy can be reduced, and the operation efficiency of the self-mobile device can be improved.
It should be noted that, the preset interval in the above embodiment may be set according to the specification parameters of the mobile device and the job requirements of the user. Preferably, the preset interval is set to a value not wider than the width d of the self-moving device. For example, to avoid repeated coverage or missing coverage areas from the mobile device when performing a job task, the aforementioned preset interval may be set to d.
In one embodiment, the linear path search process in the above embodiment may be performed using the Bresenham's line algorism (Bresenham). The branchiom linear algorithm Lei Senhan is a well-known linear generation algorithm in the field of graphics, on the basis of which, a later researcher proposes a plurality of improved branchiom linear algorithms, which can be applied to the linear path searching process in the above embodiments without contradiction with other technical means in the embodiments of the present application.
As shown in fig. 6, for example, fig. 6 is a map in which a basic path set of each sub-region is obtained after performing a linear path search for each sub-region in the map of fig. 5 (b), wherein a broken line in each sub-region is a basic path obtained by the linear path search. For example, FIG. 6 is a neutron regionSince the longitudinal direction of (1) is horizontal, the horizontal direction is taken as sub-region +.>Is searched for the first time with the sub-region +.>The upper long side of (2) is the base line, shifted by a preset interval d, and the sub-region +.>Performing a straight-line path search until a sub-region +.>The barrier on the right side obtains a 1 st line segment as a 1 st basic path; the second search takes the 1 st basic path as a base line, shifts by the same preset interval d, and repeats the linear path searching process Until sub-area +.>Obtaining a 2 nd line segment as a 2 nd basic path; repeating the process with the previous basic path as the base line, shifting by the same preset interval d, and repeating the process of searching straight path along the same searching direction until the sub-area +.>After the search is completed, a plurality of mutually parallel basic paths are obtained to form subareasIs described herein). Other subregions->To sub-area->And performing the same linear path searching process to obtain respective basic path sets. In the embodiment shown in fig. 6, the subregion +.>Sub-area->Sub-area->Sub-regionSub-area->The searching directions of the system are all horizontal directions, and the number n of the basic paths is 8, 18, 4, 15 and 5 respectively; subregion->And subregion->The search directions of (a) are all vertical directions, and the number n of the respective basic paths is 7 and 7 respectively.
In one embodiment, determining intermediate reference lines of the sub-regions based on the base path sets respectively, and joining the base paths in the base path sets in a manner of crossing the intermediate reference lines to obtain local coverage planning paths in the sub-regions respectively (i.e. step S260), including:
And respectively acquiring the number n of the basic paths in the basic path set of each sub-region, and judging the parity of the number n of the basic paths.
If the number n of the basic paths is an odd number, taking the (n+1)/2 th basic path in the basic path set as an intermediate reference line; if the number n of the basic paths is even, the central line between the n/2 th basic path and the (n+2)/2 nd basic path and parallel to the n/2 th basic path and the (n+2)/2 nd basic path is used as an intermediate reference line; and taking the basic paths positioned at one side of the middle reference line in the basic path set as a first subset, and taking the basic paths positioned at the other side of the middle reference line in the basic path set as a second subset. In other words, if the number n of the basic paths is an odd number, the first subset is {1,2,3, …, (n-1)/2 }, and the second subset is { (n+3)/2, (n+5)/2, (n+7)/2, …, n }; if the number of base paths n is even, the first subset is {1,2,3, …, n/2}, and the second subset is { (n+2)/2, (n+4)/2, (n+6)/2, …, n }.
A job order sequence of the base paths in the first subset and the second subset of each sub-region is determined in a manner that spans the intermediate reference line, respectively.
It will be appreciated that a job order sequence refers to an ordered set of pre-planned base path precedence orders for executing job tasks from a mobile device in a local area (i.e., within any sub-area). The sequence of the order of the operation of the base paths is determined in such a way that it crosses the intermediate reference line, i.e. the base paths are alternately selected from the first subset and the second subset as a sequence of ordered paths as the sequence of the order of the operation of the self-mobile device.
And respectively connecting the basic paths in the operation sequence based on the operation sequence to respectively obtain the local coverage planning paths in each subarea.
It will be appreciated that the present embodiment determines the intermediate reference line based on the number n of base paths in the base path set of each sub-region, i.e. the position of the intermediate reference line is determined from the parity of the number n of base paths of each sub-region. If the number n is an odd number, taking the middle basic path (i.e., (n+1)/2 basic paths) in the basic path set as an intermediate reference line; if the number n is even, the middle line between the two base paths at the middle (i.e. the middle line between the n/2 base path and the (n+2)/2 base path) is used as the middle reference line. Then, by crossing the intermediate reference line, a job order sequence of the base path set of the respective sub-regions is determined, thereby determining a local path plan within each sub-region. Because the local planning in the subarea of the target operation area is to connect the basic paths in the basic path set in a mode of crossing the middle reference line, the movement behaviors of the self-moving equipment, such as in-situ turning, small-radius turning and the like, which do not accord with the real vehicle kinematic constraint are avoided, the potential safety hazard caused by the movement behaviors are avoided, and the movement safety of the self-moving equipment is improved. In contrast to the prior art, the coverage of the local operation area is generally realized by adopting an arc-shaped mode, in this case, the current operation path of the self-moving equipment is adjacent to the previous operation path every time, and in the switching process of the two adjacent operation paths, the in-situ turning, turning and other motion behaviors which do not accord with the kinematic constraint of the real vehicle often exist.
Exemplary, as shown in FIG. 7, FIG. 7 is a sub-region of the map of FIG. 6 after a straight line search to obtain a set of base pathsIs an enlarged view of (a). Subregion->Through the above-mentioned straight line searching process, the obtained basic path set includes the 1 st, 2 nd, 3 rd, 4 th and 5 th basic paths from top to bottom, and because the number n of basic paths is 5 and the number n of basic paths is odd, the middle reference line is the 3 rd path, the 1 st and 2 nd basic paths on one side of the middle reference line (i.e. the 3 rd basic path) are used as the first subset, and the 4 th and 5 th basic paths on the other side are used as the second subset.
Illustratively, as further shown in FIG. 8, FIG. 8 is a sub-region of the map of FIG. 6 after a linear search to obtain a set of base pathsIs an enlarged view of (a). Subregion->Through the above straight line searching process, the obtained basic path set includes the 1 st, 2 nd, 3 rd and 4 th basic paths from top to bottom, and because the number n of the basic paths is 4 and belongs to the situation that the number n of the basic paths is even, the middle line between the 2 nd basic path and the 3 rd basic path is taken as the middle reference line, the 1 st and 2 nd basic paths on one side of the middle reference line are taken as the first subset, and the 3 rd and 4 th basic paths on the other side are taken as the second subset.
Further, in one embodiment, determining a job order sequence of the base path in the first subset and the base path in the second subset of each sub-region, respectively, in a manner that spans the intermediate reference line, includes:
if the number of base paths n is an odd number, the job sequence is determined to be {1, (n+3)/2, (n+5)/2, 3, (n+7)/2, …, (n-1)/2, n, (n+1)/2 }; if the number of base paths n is even, the job sequence is determined to be {1, (n+2)/2, (n+4)/2, 3, (n+6)/2, …, n/2, n }.
Exemplary, please refer again to fig. 7 and 8, sub-regionsHezi (Hezi)Zone->The number of the basic paths is 5 and 4 respectively, and the corresponding operation sequence is {1,4,2,5,3}, {1,3,2,4}, respectively.
It can be understood that the basic paths in the job sequence in this embodiment are arranged in the order of the first subset and the second subset, that is, the basic paths of the odd items are selected from one subset, the basic paths of the even items are selected from the other subset, and the sequence of the basic paths of the odd items and the sequence of the basic paths of the even items are the same as the sequence of the basic paths of the odd items in the original subset. By the arrangement, local coverage operation of the self-mobile device in each sub-area can be more regular and efficient. However, the above-mentioned job sequence is not limited, and any job sequence that can cross the middle reference line can be used as the local planned path in the sub-area of the embodiment of the present application, for example, in other embodiments, one possible job sequence setting manner is as follows: if the number of base paths n is an odd number, the job sequence is determined as {1, n,2, (n-1), 3, (n-2), …, (n-1)/2, (n+3)/2, (n+1)/2 }; if the number of base paths n is even, then the job order sequence is determined to be {1, n,2, (n-1), 3, (n-2), …, n/2, (n+2)/2 }.
In one embodiment, linking the base paths in the job sequence based on the job sequence, respectively, includes:
if the number n of the basic paths is greater than or equal to 3, sequentially connecting the tail end of the first path in the operation sequence with the tail end of the second path in the operation sequence by adopting a connection curve based on the sequence in the operation sequence, and analogizing the head end of the second path in the operation sequence with the head end of the third path in the operation sequence until the head end of the penultimate path in the operation sequence and the head end of the last path in the operation sequence or the tail end of the penultimate path in the operation sequence and the tail end of the last path in the operation sequence; preferably, the engagement curve may be Du Binsi (Dubins) curve.
If the number n of the basic paths is smaller than 3, the tail end of the first path in the operation sequence and the tail end of the second path in the operation sequence are connected by adopting a connecting straight line based on the sequence in the operation sequence.
If the engagement curve or the engagement straight line collides with the boundary or the obstacle, the obstacle detouring engagement is carried out by adopting an A-type algorithm. The a (Star) algorithm is a very common path finding and graph traversing algorithm in the art, and is not described herein because it is not a point of improvement in the present application.
In this embodiment, a linking process is performed on the basic paths in the operation sequence, and in short, if the number of basic paths is more than two, a linking curve is adopted to link the basic paths in the operation sequence in a manner of connecting the head end to the head end or connecting the tail end to the tail end according to the sequence of the basic paths in the operation sequence until the first path in the operation sequence reserves a starting point and the last path reserves an ending point; if the number of the basic paths is two, directly adopting a connecting straight line to connect the tail end of the first path with the tail end of the last path, wherein the head end of the first path is a starting point and the head end of the last path is an ending point; if the engagement curve or the engagement straight line for engagement collides with the boundary or the obstacle, the obstacle detouring engagement is carried out by adopting an A-type algorithm.
Illustratively, please refer again to FIG. 7, the sub-regions in FIG. 7The number of the basic paths is 5 and is more than 3, the operation sequence is {1,4,2,5,3}, so that the tail end of the first path and the tail end of the second path (namely the tail end of the 1 st basic path and the tail end of the 4 th basic path) in the operation sequence are sequentially connected by adopting a connection curve (curve with an arrow in the figure), and the head end of the second path and the operation sequence in the operation sequence The head end of the third path in the sequence (i.e., the head end of the 4 th base path and the head end of the 2 nd base path), the tail end of the third path in the sequence and the tail end of the fourth path in the sequence (i.e., the tail end of the 2 nd base path and the tail end of the 5 th base path), the head end of the penultimate path in the sequence and the head end of the last path in the sequence (i.e., the head end of the 5 th base path and the head end of the 3 rd base path), wherein "good" represents the starting point of the sub-region traversal and ". DELTA" represents the ending point of the sub-region traversal.
Illustratively, please refer again to FIG. 8, the sub-regions in FIG. 8The number of the basic paths is 4 and is more than 3, and the operation sequence is {1,3,2,4}. Therefore, a joining curve (curve with an arrow in the figure) is adopted to sequentially join the tail end of the first path and the tail end of the second path (namely, the tail end of the 1 st basic path and the tail end of the 3 rd basic path) in the operation sequence, the head end of the second path and the head end of the third path (namely, the head end of the 3 rd basic path and the head end of the 2 nd basic path) in the operation sequence, and the tail end of the last path (namely, the tail end of the 2 nd basic path and the tail end of the 4 th basic path) in the operation sequence, wherein 'O' represents the starting point of the traversal of the subarea, and 'delta' represents the ending point of the traversal of the subarea.
Likewise, the partial coverage plan paths in the other sub-areas in FIG. 6, also refer to the sub-areas in the example aboveAnd subregion->By determining a sequence of the order of the basic paths of the set of basic paths in each sub-region and then performing the processing on the basic paths in the sequence of the order of the operationAnd (3) connecting the connecting curves or connecting straight lines and/or connecting the connecting lines around the obstacle, and finally obtaining a partial coverage planning path from the starting point O to the ending point delta from each sub-area, wherein the partial coverage planning path of each sub-area meets the requirement of the real vehicle kinematics constraint.
In one embodiment, based on the local coverage planning path in each sub-area, the inter-area linking path between each sub-area is planned to obtain a global coverage planning path of the target job area (i.e. step S270), including: and constructing a heuristic function, carrying out path search among all the subareas by adopting a mixed A-type algorithm based on the heuristic function, and determining inter-area connection paths among all the subareas to obtain a global coverage planning path of the target operation area.
In other words, in this embodiment, based on the local coverage planning paths of the sub-areas, positions of a start point "o" and an end point "Δ" of the local coverage planning path of each sub-area are globally considered, a heuristic function is constructed, and based on the heuristic function, a mixed a-algorithm is used to perform path search on all the start points "o" and the end points "Δ" so as to determine inter-area connection paths between the sub-areas, and finally, a global coverage planning path of the entire target operation area is obtained.
Illustratively, a heuristic function h is constructed,
h=w1×kinetic_cost+w2×jps_cost+w3×theta_cost; wherein:
kinematic_cost = max { Dubins (x, y, theta, k, sampled_dis), reeds_shepp (x, y, theta, k, sampled_dis) }, kinematic_cost representing Kinematic constraint information, wherein Dubins () represents Du Binsi curve solving function, reeds_shepp () represents Reeds-Shepp curve solving function, x, y, theta representing start point position, end point position and orientation, respectively; k=1/r, representing the curvature constraint size; sampled dis represents the distance value of the search sample;
jps_cost= { JPS _asstar (x, y, theta) }, where jps_cost represents shortest distance constraint information;
theta_cost=min { theta_end }, wherein theta_cost represents orientation deviation weight constraint information, and theta_end is an orientation deviation of the self-mobile device corresponding to the area connection location.
The three weights w1, w2 and w3 represent the preference degrees of the Kinematic constraint (kinematic_cost), the shortest distance constraint (jps_cost) and the direction deviation constraint (theta_cost), and can be set according to specific working conditions and the use preference of the user. Preferably, the weight w1 may be set relatively large, while w2 and w3 are set relatively small. By the arrangement, the inter-region joint path between the sub-regions can further meet the kinematic constraint of a real vehicle as far as possible.
In this embodiment, the path search between the sub-regions is performed by using the hybrid a-algorithm, so as to determine the inter-region joint path between the sub-regions, and because the theta dimension is increased, the expansion of the position (x, y) direction is considered, the expansion of the motion direction theta is considered, and the planned inter-region joint path can better satisfy the kinematic constraint of the real vehicle.
It should be understood that, although the steps in the flowcharts related to the above embodiments are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a path planning device for realizing the coverage path planning method of the self-mobile device. The implementation of the solution provided by the apparatus is similar to the implementation described in the above method, so the specific limitation in the embodiments of the path planning apparatus for a self-mobile device provided below may be referred to the limitation of the coverage path planning method for a self-mobile device hereinabove, and will not be repeated here.
In one embodiment, as shown in fig. 9, there is provided a coverage path planning apparatus of a self-mobile device, including:
a target job area decomposition module 940 for decomposing the target job area to obtain respective sub-areas;
a sub-region basic path search module 950, configured to obtain a basic path set of each sub-region;
the local path planning module 960 in each sub-area is used for determining an intermediate reference line of each sub-area based on the basic path set, and connecting the basic paths in the basic path set in a mode of crossing the intermediate reference line to respectively obtain local coverage planning paths in each sub-area;
the inter-area path linking planning module 970 is configured to plan inter-area linking paths between each sub-area based on the local coverage planning paths in each sub-area, and obtain a global coverage planning path of the target operation area.
In an embodiment, the coverage path planning apparatus of the self-mobile device further includes:
the map preprocessing module is used for preprocessing an original environment map to obtain a smooth map;
and the connected domain searching module is used for searching the connected domain of the smooth map to obtain a region with the largest connected domain area as a target operation region.
In one embodiment, the preprocessing module is further configured to preprocess the original environment map to obtain a smooth map:
performing binarization processing on the original environment map to obtain a binarized environment map;
edge detection is carried out on the environment map which is greater than or equal to the binarization, the outline of the obstacle is identified, and outline drawing is carried out on the basis of the outline of the obstacle which is greater than or equal to the binarization;
and (3) performing expansion treatment and corrosion treatment on the environment map with the outline greater than or equal to binarization to obtain a treated smooth map.
In one embodiment, in acquiring each sub-region in the target job region, the target job region decomposition module 940 is further configured to:
decomposing the target operation area into sub-areas by using a unit decomposition method; and/or the number of the groups of groups,
If the long and narrow subareas exist in each subarea, the long and narrow subareas are combined with any subarea adjacent to the long and narrow subarea.
In one embodiment, if there is an elongated sub-region in each sub-region, the above-mentioned target job region decomposition module 940 is further configured to:
traversing the side length and the area of each subarea, comparing the side length with the first side length threshold value, and comparing the area with the first area threshold value;
if there is a sub-region with a side length smaller than the first side length threshold or an area smaller than the first area threshold, merging the sub-region with any one of the adjacent sub-regions.
In one embodiment, in acquiring the basic path sets of the sub-regions respectively, the sub-region basic path search module 950 is further configured to:
respectively determining the long side direction of each subarea, and taking the long side direction as the searching direction of the corresponding subarea;
taking one long side of each sub-area as a base line, shifting preset intervals, and searching a straight line path of each sub-area along a searching direction until encountering a boundary or an obstacle of the sub-area to obtain a 1 st line segment serving as a 1 st basic path;
Taking the 1 st basic path as a base line, shifting by a preset interval, repeating the linear path searching process along the searching direction until encountering the boundary or the obstacle of the subarea to obtain the 2 nd line segment as the 2 nd basic path;
each time, taking the previous basic path as a base line, shifting by a preset interval, repeating the linear path searching process along the searching direction until each sub-area is searched, and obtaining n basic paths which are parallel to each other in each sub-area as a basic path set of each sub-area.
In one embodiment, in determining the middle reference line of each sub-region based on the base path set respectively, and linking the base paths in the base path set in a manner of crossing the middle reference line, to obtain the local coverage planning paths in each sub-region respectively, the local path planning module 960 in the sub-region is further configured to:
respectively acquiring the number n of basic paths in a basic path set of each sub-region, and judging the parity of the number n of the basic paths;
if the number n of the basic paths is an odd number, taking the (n+1)/2 th basic path in the basic path set as an intermediate reference line; if the number n of the basic paths is even, the central line between the n/2 th basic path and the (n+2)/2 nd basic path and parallel to the n/2 th basic path and the (n+2)/2 nd basic path is used as an intermediate reference line; taking a basic path positioned at one side of the middle reference line in the basic path set as a first subset, and taking a basic path positioned at the other side of the middle reference line in the basic path set as a second subset;
Determining a job order sequence of the base paths in the first subset and the second subset of each sub-region in a manner that spans the intermediate reference line;
and respectively connecting the basic paths in the operation sequence based on the operation sequence to respectively obtain the local coverage planning paths in each subarea.
In one embodiment, the intra-subarea local path planning module 960 is further configured to, in determining the order sequence of the base paths in the first subset and the second subset of each subarea in such a manner as to cross the intermediate reference line, respectively:
if the number of base paths n is an odd number, the job sequence is determined to be {1, (n+3)/2, (n+5)/2, 3, (n+7)/2, …, (n-1)/2, n, (n+1)/2 };
if the number of base paths n is even, the job sequence is determined to be {1, (n+2)/2, (n+4)/2, 3, (n+6)/2, …, n/2, n }.
In one embodiment, in terms of linking the basic paths in the job sequence based on the job sequence, respectively, to obtain the local coverage planning paths in each sub-area, the local path planning module 960 in the sub-area is further configured to:
If the number n of the basic paths is greater than or equal to 3, sequentially connecting the tail end of the first path in the operation sequence with the tail end of the second path in the operation sequence by adopting a connection curve based on the sequence in the operation sequence, and analogizing the head end of the second path in the operation sequence with the head end of the third path in the operation sequence until the head end of the penultimate path in the operation sequence and the head end of the last path in the operation sequence or the tail end of the penultimate path in the operation sequence and the tail end of the last path in the operation sequence;
if the number n of the basic paths is smaller than 3, adopting a connecting straight line to connect the tail end of a first path in the operation sequence with the tail end of a second path in the operation sequence based on the sequence in the operation sequence;
if the engagement curve or the engagement straight line collides with the boundary or the obstacle, the obstacle detouring engagement is carried out by adopting an A-type algorithm.
In one embodiment, in planning inter-area link paths between sub-areas based on the local coverage planning paths in the sub-areas, the inter-area link planning module 970 is further configured to: and constructing a heuristic function, carrying out path search among all the subareas by adopting a mixed A-type algorithm based on the heuristic function, and determining inter-area connection paths among all the subareas to obtain a global coverage planning path of the target operation area.
The respective modules in the coverage path planning apparatus of the self-mobile device may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or independent of a processor in the electronic device, or may be stored in software in a memory in the electronic device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a self-mobile device is provided, the internal structure of which may be as shown in FIG. 10. The self-mobile device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input device. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the self-mobile device is configured to provide computing and control capabilities. The memory of the self-mobile device includes a non-volatile 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 input/output interface of the self-mobile device is used to exchange information between the processor and the external device. The communication interface of the self-mobile device is used for carrying out wired or wireless communication with external self-mobile devices, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a coverage path planning method for a self-mobile device. The display unit of the self-mobile device is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device, wherein the display screen can be a liquid crystal display screen or an electronic ink display screen, the input device of the self-mobile device can be a touch layer covered on the display screen, can also be a key, a track ball or a touch pad arranged on a shell of the self-mobile device, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 10 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the self-moving device to which the present application is applied, and that a particular self-moving device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.
It should be noted that, the data (including, but not limited to, data for analysis, stored data, displayed data, etc.) referred to in the present application are all information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data are required to comply with the related laws and regulations and standards of the related countries and regions.
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, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (MagnetoresistiveRandom Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can take many forms, such as static Random access memory (Static Random Access Memory, SRAM) or Dynamic Random access memory (Dynamic Random AccessMemory, DRAM), among others. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims (12)

1. A method for coverage path planning for a self-mobile device, the method comprising the steps of:
acquiring each sub-region in a target operation region;
respectively acquiring a basic path set of each subarea;
determining intermediate reference lines of all sub-areas based on the basic path set respectively, and connecting basic paths in the basic path set in a mode of crossing the intermediate reference lines to obtain local coverage planning paths in all the sub-areas respectively;
Planning inter-region connection paths among all the subareas based on the local coverage planning paths in all the subareas to obtain a global coverage planning path of the target operation region;
the step of obtaining the basic path set of each sub-region respectively comprises the following steps:
respectively determining the long side direction of each subarea, and taking the long side direction as the searching direction of the corresponding subarea;
taking one long side of each sub-area as a base line, shifting preset intervals, and searching a straight line path of each sub-area along the searching direction until encountering the boundary or barrier of the sub-area to obtain a 1 st line segment as a 1 st basic path;
taking the 1 st basic path as a base line, shifting the preset interval, repeating the linear path searching process along the searching direction until encountering the boundary or the obstacle of the subarea to obtain a 2 nd line segment serving as the 2 nd basic path;
each time, taking the previous basic path as a base line, shifting the preset interval, and repeating the linear path searching process along the searching direction until each sub-area is searched, and each sub-area obtains n basic paths which are parallel to each other as the basic path set of each sub-area.
2. The method of claim 1, wherein the step of acquiring each sub-region in the target job region comprises:
decomposing the target operation area into the sub-areas by using a unit decomposition method; and/or the number of the groups of groups,
and if the long and narrow subareas exist in the subareas, merging the long and narrow subareas with any subarea adjacent to the long and narrow subareas.
3. The method according to claim 2, wherein if there is an elongated sub-region in the respective sub-regions, merging the elongated sub-region with any sub-region adjacent thereto, comprises:
traversing the side length and the area of each subarea, comparing the side length with a first side length threshold value, and comparing the area with a first area threshold value;
if there is a sub-region whose side length is smaller than the first side length threshold or whose area is smaller than the first area threshold, merging the sub-region with any sub-region adjacent to the sub-region.
4. The method according to claim 1, wherein the step of determining intermediate reference lines of the sub-areas based on the base path sets, respectively, and joining the base paths in the base path sets in a manner crossing the intermediate reference lines, respectively, to obtain the local coverage plan paths in the sub-areas, respectively, comprises:
Respectively acquiring the number n of the basic paths in the basic path set of each sub-region, and judging the parity of the number n of the basic paths;
if the number n of the basic paths is an odd number, taking the (n+1)/2 th basic path in the basic path set as the middle reference line; if the number n of the basic paths is even, taking a central line which is positioned between the n/2 th basic path and the (n+2)/2 nd basic path and is parallel to the n/2 th basic path and the (n+2)/2 nd basic path as the middle reference line; taking a basic path positioned at one side of the middle reference line in the basic path set as a first subset, and taking a basic path positioned at the other side of the middle reference line in the basic path set as a second subset;
determining a sequence of order of operation of the base path in the first and second subsets of the respective sub-regions, respectively, in a manner spanning the intermediate reference line;
and respectively connecting the basic paths in the operation sequence based on the operation sequence to respectively obtain the local coverage planning paths in each subarea.
5. The method of claim 4, wherein the determining the order of the sequence of jobs for the base paths in the first and second subsets of the respective sub-regions, respectively, in a manner that spans the intermediate reference line, comprises:
If the number n of the basic paths is an odd number, the operation sequence is determined as {1, (n+3)/2, (n+5)/2, 3, (n+7)/2, …, (n-1)/2, n, (n+1)/2 };
if the number of base paths n is even, the job order sequence is determined to be {1, (n+2)/2, (n+4)/2, 3, (n+6)/2, …, n/2, n }.
6. The method of claim 5, wherein the concatenating the base paths in the job order sequence based on the job order sequence, respectively, comprises:
if the number n of the basic paths is greater than or equal to 3, sequentially connecting the tail end of a first path in the operation sequence with the tail end of a second path in the operation sequence by adopting a connection curve based on the sequence in the operation sequence, and analogizing the head end of the second path in the operation sequence with the head end of a third path in the operation sequence until the head end of the last-last second path in the operation sequence and the head end of the last path in the operation sequence or the tail end of the last-last second path in the operation sequence and the tail end of the last path in the operation sequence;
If the number n of the basic paths is smaller than 3, adopting a connecting straight line to connect the tail end of a first path in the operation sequence with the tail end of a second path in the operation sequence based on the sequence in the operation sequence;
and if the engagement curve or the engagement straight line collides with the boundary or the obstacle, performing obstacle detouring engagement by adopting an A-algorithm.
7. The method according to claim 1, wherein the step of planning inter-region join paths between the sub-regions based on the local coverage planned paths in the respective sub-regions, to obtain a global coverage planned path for the target job region, comprises: and constructing a heuristic function, carrying out path search among all the subareas by adopting a mixed A-type algorithm based on the heuristic function, and determining inter-area connection paths among all the subareas to obtain a global coverage planning path of the target operation area.
8. The method according to any one of claims 1 to 7, further comprising, prior to the step of acquiring each sub-region in the target job region:
Preprocessing an original environment map to obtain a smooth map;
and searching the connected domain of the smooth map to obtain a region with the largest connected domain area as the target operation region.
9. The method of claim 8, wherein preprocessing the original environment map to obtain a smooth map comprises:
performing binarization processing on the original environment map to obtain a binarized environment map;
performing edge detection on the binarized environment map, identifying an obstacle outline, and performing outline drawing based on the obstacle outline;
and performing expansion treatment and corrosion treatment on the binarized environment map with the outline sketched, and obtaining the processed smooth map.
10. A coverage path planning apparatus for a self-mobile device, the apparatus comprising:
the target operation area decomposing module is used for decomposing the target operation area to obtain each sub-area;
the sub-region basic path searching module is used for acquiring a basic path set of each sub-region;
the local path planning module in the subarea is used for determining the middle reference line of each subarea based on the basic path set, and connecting the basic paths in the basic path set in a mode of crossing the middle reference line to respectively obtain local coverage planning paths in each subarea;
The inter-region path connection planning module is used for planning inter-region connection paths among all the sub-regions based on the local coverage planning paths in all the sub-regions to obtain a global coverage planning path of the target operation region;
wherein the obtaining the basic path set of each sub-region includes:
respectively determining the long side direction of each subarea, and taking the long side direction as the searching direction of the corresponding subarea;
taking one long side of each sub-area as a base line, shifting preset intervals, and searching a straight line path of each sub-area along the searching direction until encountering the boundary or barrier of the sub-area to obtain a 1 st line segment as a 1 st basic path;
taking the 1 st basic path as a base line, shifting the preset interval, repeating the linear path searching process along the searching direction until encountering the boundary or the obstacle of the subarea to obtain a 2 nd line segment serving as the 2 nd basic path;
each time, taking the previous basic path as a base line, shifting the preset interval, and repeating the linear path searching process along the searching direction until each sub-area is searched, and each sub-area obtains n basic paths which are parallel to each other as the basic path set of each sub-area.
11. A self-mobile device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 9 when the computer program is executed.
12. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 9.
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