CN113534822A - Sweeping robot and path control method and device thereof - Google Patents
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Abstract
The embodiment of the invention discloses a path control method and device of a sweeping robot and the sweeping robot, wherein the method comprises the following steps: acquiring a pre-constructed map, dividing the map into a plurality of areas, and determining the communication relation among the areas; performing path planning on each area according to the communication relation among the areas, and determining at least one sub-path of each area; determining at least one alternative path according to at least one sub-path of each region and the communication relation between the regions; and respectively calculating cost value scores of each alternative path under a plurality of path evaluation dimensions according to each alternative path, calculating the cost value of each alternative path according to a preset path evaluation dimension coefficient and the cost values under the plurality of path evaluation dimensions, and determining one alternative path from at least one alternative path as a target planning path according to the cost values. By adopting the invention, the accuracy of path planning can be improved, and the working efficiency of the sweeping robot can be improved.
Description
Technical Field
The invention relates to the technical field of sweeping robots, in particular to a path control method and device of a sweeping robot and the sweeping robot.
Background
The floor sweeping robot is also called an automatic cleaner, intelligent dust collection, a robot dust collector and the like, is one of intelligent household appliances, and can automatically complete floor cleaning work in a room by means of certain artificial intelligence. In the existing sweeping robot scheme, a map is constructed in advance, and then a path is divided according to the map when the sweeping robot works, but the path planning usually does not consider the particularity of an indoor environment, and the obtained planned path is not an optimal path, so that the working efficiency of the sweeping robot is influenced.
Disclosure of Invention
In view of the above, it is necessary to provide a path control method and device for a sweeping robot, and a sweeping robot.
In a first aspect of the present invention, there is provided a path control method of a sweeping robot, the method including:
acquiring a pre-constructed map, dividing the map according to historical data, dividing the map into a plurality of areas, and determining the communication relation among the areas;
performing path planning on each area according to the communication relation among the areas, and determining at least one sub-path of each area;
determining at least one alternative path according to at least one sub-path of each region and the communication relation between the regions;
calculating cost value scores of each alternative path under a plurality of path evaluation dimensions respectively aiming at each alternative path, and calculating a cost value of each alternative path according to a preset path evaluation dimension coefficient and the cost values under the plurality of path evaluation dimensions, wherein the path evaluation dimensions comprise one or more of path length, movement time, power consumption, repeated path length and repeated area size of the alternative path;
and determining one alternative path from the at least one alternative path as a target planning path according to the cost value.
Optionally, the step of dividing the map according to the historical data, dividing the map into a plurality of regions, and determining a communication relationship between the plurality of regions further includes:
dividing a map into a plurality of grids;
determining a plurality of basic grid points in the grids, and outwards expanding in the grids divided into the map based on each basic grid point to obtain an expanded rectangular area corresponding to each basic grid point, wherein expansion is stopped when an obstacle is encountered or the expansion is stopped when the number of the grids corresponding to the obstacle area is greater than a preset value;
for a plurality of rectangular regions:
performing first region processing operation on the plurality of rectangular regions according to the repeated relationship and the inclusion relationship among the rectangular regions, wherein the first region processing operation comprises one or more of deduplication operation, deletion operation and combination operation;
traversing each rectangular region, and calculating the ratio of the overlapping area between the traversed first rectangular region and other second rectangular regions with overlapping regions to the size of the region between the first rectangular region and the second rectangular region as a first ratio/a second ratio;
if the first ratio and the second ratio are both larger than a preset ratio threshold, merging the first rectangular area and the second rectangular area;
and if the first ratio is smaller than a preset ratio threshold value and/or the second ratio is smaller than a preset ratio threshold value, performing segmentation processing on the first rectangular area and the second rectangular area, wherein under the condition that the first ratio is smaller than the second ratio, the segmentation processing is to delete the intersection area of the first rectangular area and the second rectangular area from the first rectangular area.
Optionally, the step of dividing the map according to the historical data, dividing the map into a plurality of regions, and determining a communication relationship between the plurality of regions further includes:
in the process of deleting the intersection region of the first rectangular region and the second rectangular region from the first rectangular region, the intersection line between the first rectangular region and the second rectangular region is set as a dividing line, and the dividing line is set as a communicating position between the regions corresponding to the first rectangular region and the second rectangular region after the dividing processing.
Optionally, the step of performing path planning on each region according to the communication relationship between the regions and determining at least one sub-path of each region further includes:
planning a path of each area to obtain a planned path of which the starting point and the end point are in the communication positions with other areas as alternative sub-paths;
respectively calculating the cost value of each alternative sub-path, respectively calculating the cost value score of each alternative sub-path under a plurality of path evaluation dimensions, and respectively calculating the cost value of each alternative sub-path according to a preset path evaluation dimension coefficient and the cost values under the plurality of path evaluation dimensions, wherein the path evaluation dimensions comprise one or more of path length, movement time, power consumption, repeated path length and repeated area size of the alternative sub-paths; and determining one or more alternative sub-paths in the alternative sub-paths according to the cost value as at least one sub-path corresponding to the region.
Optionally, the method further includes:
recording the cleaning time, unit power consumption and cleaning mode of each area in the cleaning process of the cleaning robot;
determining the unit power consumption and the cleaning mode of each area according to the historical data, and determining the average power consumption of each area;
the step of determining one alternative path from at least one alternative path as a target planning path according to the cost value further includes:
calculating the total power consumption of each alternative path according to the average power consumption of each region; judging whether the total power consumption is less than or equal to a preset power threshold, wherein the power threshold is the total power of the sweeping robot;
optionally, the method further includes:
when the sweeping robot moves to a region to be swept based on a target planned path, acquiring a target image of the region to be swept through a camera device arranged on the sweeping robot, carrying out image recognition on the acquired target image so as to determine regional characteristics of the region to be swept, and determining a target sweeping mode corresponding to the region to be swept in a plurality of preset sweeping modes according to the regional characteristics;
and cleaning the area to be cleaned based on the target cleaning mode and the target planning path.
Optionally, the step of obtaining a target image of an area to be cleaned and performing image recognition on the collected target image by using the camera device arranged on the sweeping robot to determine the regional characteristics of the area to be cleaned further includes:
converting the target image into a gray scale image to obtain a target image of the gray scale image;
calculating the gray level average value of pixel points contained in each line of the target image, calculating the difference value between each pixel point and the gray level average value of the line as a gray level difference value, and calculating the gray level standard deviation under each line based on the gray level difference value; calculating the gray average value of each row of the pixel points with the gray values smaller than the limit error threshold determined according to the gray standard deviation, and generating a first difference image according to the gray average value of each row;
determining a second differential image according to the absolute value of the gray difference between the target image and the first differential image, and performing binarization processing on the second differential image to obtain a binarized second differential image;
calculating the gray level average value of pixel points contained in each row of the target image, calculating the difference value between each pixel point and the gray level average value of the row as a gray level difference value, and calculating the gray level standard deviation of each row based on the gray level difference value; calculating the gray average value of each row of the pixel points with the gray values smaller than the limit error threshold determined according to the gray standard deviation, and generating a third difference image according to the gray average value of each row;
determining a fourth differential image according to the absolute value of the gray difference between the target image and the third differential image, and performing binarization processing on the fourth differential image to obtain a binarized fourth differential image;
fusing the second differential image and the fourth differential image to obtain a fifth differential image, wherein the fifth differential image is a binary image;
identifying a fifth difference image to determine an ROI area in the target image;
acquiring an image of an ROI (region of interest) in the target image as a detection image;
acquiring a plurality of preset feature templates corresponding to the cleaning modes, and extracting features of the detection image based on the feature templates to acquire the features and confidence coefficients of the detection image under each feature template;
and determining the features under one feature template as the region features according to the confidence.
In a second aspect of the present invention, there is provided a path control apparatus for a sweeping robot, comprising:
the map dividing module is used for acquiring a pre-constructed map, dividing the map according to historical data, dividing the map into a plurality of areas and determining the communication relation among the areas;
the regional path planning module is used for planning paths of each region according to the communication relation among the regions and determining at least one sub-path of each region;
the path communication module is used for determining at least one alternative path according to at least one sub-path of each region and the communication relation among the regions;
the cost calculation module is used for calculating cost value scores of each alternative path under a plurality of path evaluation dimensions respectively according to each alternative path, and calculating the cost value of each alternative path according to a preset path evaluation dimension coefficient and the cost values under the plurality of path evaluation dimensions, wherein the path evaluation dimensions comprise one or more of path length, movement time, power consumption, repeated path length and repeated area size of the alternative path;
and the target path selection module is used for determining one alternative path from the at least one alternative path as a target planning path according to the cost value.
In a third aspect of the present invention, there is provided a sweeping robot, comprising a memory and a processor, wherein the memory has an executable code, and when the executable code runs on the processor, the method for controlling the path of the sweeping robot as mentioned in the first aspect is implemented
The embodiment of the invention has the following beneficial effects:
after the path control method and the path control device of the sweeping robot and the sweeping robot are adopted, before the sweeping robot sweeps, firstly, area division needs to be carried out on a pre-constructed map to obtain a plurality of areas, and the communication relation among the areas is determined; performing path planning on each area according to the communication relation among the areas, and determining at least one sub-path of each area; determining at least one alternative path according to at least one sub-path of each region and the communication relation between the regions; calculating cost value scores of each alternative path under a plurality of path evaluation dimensions respectively aiming at each alternative path, and calculating a cost value of each alternative path according to a preset path evaluation dimension coefficient and the cost values under the plurality of path evaluation dimensions, wherein the path evaluation dimensions comprise one or more of path length, movement time, power consumption, repeated path length and repeated area size of the alternative path; and determining one alternative path from the at least one alternative path as a target planning path according to the cost value. The map planning method has the advantages that the regions are reasonably divided, the overall path planning of the map is divided into the path planning problems of the regions, the calculated amount of the path planning can be reduced under the condition that the overall optimal situation of the planned path is guaranteed, and the working efficiency of the sweeping robot in sweeping work is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Wherein:
fig. 1 is a schematic flow chart illustrating a path control method of a sweeping robot according to an embodiment;
fig. 2 is a schematic diagram illustrating a path control apparatus of a sweeping robot according to an embodiment;
fig. 3 is a schematic structural diagram of a computer device for performing path control of the sweeping robot in one embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In this embodiment, a path control method for a sweeping robot is provided, and the method can be implemented based on a sweeping robot.
In this embodiment, in order to sweep the whole house through the sweeping robot, a map of the whole house needs to be constructed in advance, and then a path planning is performed based on the constructed map, so that the sweeping robot can move according to the planned path, and the sweeping of the whole house is completed in the moving process, thereby reducing the sweeping task for the user.
The method is an important link in the sweeping robot, and how to plan the path of the sweeping robot so as to obtain the path which has few repeated paths and can cover all areas in a map. In this embodiment, a path control method for a sweeping robot is provided, which can optimize a path plan of the sweeping robot, so that the sweeping robot consumes a short time or moves a short distance when moving and sweeping along the planned path.
Specifically, referring to fig. 1, fig. 1 shows a schematic flow chart of the path control method of the sweeping robot, where the method includes:
step S101: the method comprises the steps of obtaining a map which is constructed in advance, dividing the map into a plurality of areas according to historical data, and determining the communication relation among the areas.
The method comprises the steps of obtaining a map of the sweeping robot, wherein the map is constructed in advance according to data collected by the sweeping robot, and for example, the map is a whole-house map. Generally, the area to be cleaned includes one or more rooms. In this embodiment, before performing path planning, the map needs to be divided into a plurality of areas, where each area corresponds to one room or one functional area. Wherein each region is a rectangular shape or a plurality of rectangular connected regions.
In a specific implementation, the map is divided into grids, and the size of the grid may be determined according to the specific shape of the map and the historical data, for example, according to the size of the smallest rectangle included in the map, and for example, according to the size of the area where the obstacle is located in the historical data. Generally, the size of the grid is smaller than the size of the smallest rectangle in the map, and also smaller than the size of the obstacle, and only if the grid is small enough, the subsequent partitioning of the grid-based area can be accurate enough.
A number of base grid points is selected evenly in the grid, wherein the number of base grid points is larger than the number of the finally determined regions, and preferably much larger than the number of regions. The expansion is performed on the basis of the basic grid points, wherein the expansion is performed towards the outer layer of grid, and the expansion is performed one layer by one layer to obtain the expanded grid in the condition that the expanded grid can not be expanded any more. Here, the expansion includes not only the expansion toward the periphery based on the grid points but also the expansion in one direction (i.e., the expansion toward the outside of one side of the rectangle). The number of base grid points is sufficient to cover the entire area of the map.
If an obstacle is encountered in the expansion process, if the number of grids in the area where the obstacle is located is smaller than or equal to a preset threshold value, the expansion is continued, but if the number of grids in the area where the obstacle is located is larger than the preset threshold value, the expansion is stopped when the obstacle is encountered. After the mesh expansion, rectangular areas of multiple meshes can be obtained. It should be noted that, here, the multiple rectangular area areas obtained by expansion completely cover the area where the map is located, and if not, the basic grid points need to be further increased, so that the multiple rectangular area areas obtained by expansion of the basic grid points can completely cover the area where the map is located.
Here, because outward expansion of each basic grid point is performed by itself, there is an overlap between rectangular areas expanded by different basic grid points, and further processing is required for these rectangular areas to obtain the final divided areas.
If the two rectangular areas are repeated, deleting the repeated rectangular areas and only reserving one rectangular area;
if one rectangular area A is completely contained in the other rectangular area B, deleting the rectangular area A and reserving the rectangular area B;
and for other rectangular areas with overlapped areas, processing according to the following method:
and selecting one rectangular region, determining all rectangular regions with overlapped regions, traversing each overlapped rectangular region, determining the corresponding overlapped area, calculating a first ratio of the overlapped area to the area of the selected rectangular region and a second ratio between edits of the traversed rectangular region, and determining whether to combine the two rectangular regions according to whether the first ratio and the second ratio are both greater than or equal to a preset threshold value. If so, merging, and if not, deleting the intersection areas of the 2 rectangular areas from one of the rectangular areas, for example, determining the sizes of the first ratio and the second ratio, determining the rectangular area with the smaller ratio, and deleting the intersection areas from the rectangular area with the smaller ratio to obtain the rectangular area after deleting the intersection areas and the complete rectangular area with the larger ratio.
Then, the region after the processing is also regarded as a rectangular region, and the processing of the overlapping area between the rectangular regions is continued, and the processing is terminated when there is no overlapping area between the rectangular regions.
In the process, in the acquisition process of the areas, the deletion action when the intersection areas between the local areas are deleted from one area determines that the time of the two areas is communicated according to the intersection relation between the areas, and then determines the communication relation between the areas. That is, in this step, a plurality of regions are obtained by the above-described processing of the regions, and each region corresponds to one room or one relatively independent region.
Step S102: and planning a path of each region according to the communication relation among the regions, and determining at least one sub-path of each region.
In this embodiment, the starting point and the end point of the path for cleaning in each area need to be at the communication between the area and other areas, so as to facilitate the circulation of the sweeping robot between the areas. Therefore, when the path planning is performed in this step, the starting point and the end point of the sub-path planned by each area are located at the communication position between the area and other areas.
When the path is planned for each area, the path in the area can be planned according to the path in the shape of the Chinese character 'gong', so that the planned path can cover all the areas in the area, and the sweeping robot can sweep all the areas in the map when sweeping according to the path. The path planning algorithm used in the path planning in the area may be any path planning algorithm, and is not limited in this embodiment. Through the step, the path planning result of each area can be obtained, and the path planning result of each area comprises one or more realizable sub-paths.
For the path planning of each area, the cleaning condition of each area in the historical data needs to be considered, and for the area which needs to be cleaned strongly, each place in the area can be cleaned more than a plurality of times when the path planning is carried out. Specifically, according to the historical data, a thermal force value of each area is determined, wherein the thermal force value of each area is used for representing the movement speed and the power consumption value of each area in the historical data, and the movement speeds corresponding to different cleaning modes are different. That is, the movement speed during the cleaning process is different for different dirty areas and different types of areas, and the corresponding power consumption is also different. And calculating the corresponding thermal value of each area according to the movement speed and the power consumption in the historical data. Then, whether each area needs to be repeatedly cleaned is determined according to the thermal value, for example, in the case that the thermal value is larger than a preset value, repeated cleaning is determined, and the number of times of repeated cleaning in the area is determined according to the magnitude of the thermal value. Then, when at least one sub-path is obtained by path planning of the area, each point in each sub-path where planning is needed needs to be repeatedly cleaned by two or more than two times, and the area repetition rate corresponding to the area is larger than a preset value.
Step S103: determining at least one alternative path according to at least one sub-path of each region and the connection relation between the regions, and calculating a cost value corresponding to each alternative path according to a preset calculation formula, wherein the cost value comprises one or more of path length, movement time and power consumption of the alternative path.
In this embodiment, the final path planning is obtained according to the result of the path planning of each area, and specifically, the result of the path planning of each area is connected according to the communication relationship between the areas to obtain a path that can cover all the areas; however, because the path planning result of each area has multiple sub-paths and there are multiple possible connection relationships between paths in the areas, in this embodiment, there are multiple paths obtained by performing connection in this way, that is, multiple candidate paths can be obtained.
Considering the connection relationship between the regions and the positions of the starting point and the ending point of the sub-path of each region, when generating a connected path, it is also necessary to connect the ending point of one region and the starting point of the next region according to the connection relationship between the regions and the positions of the starting point and the ending point of the sub-path, and generate a connected path therebetween, and there may be an overlap between this part of the connected path and the originally planned path.
And regarding each path connecting each area, taking the path as a path for the sweeping robot to complete the sweeping work of all the areas of the map, and obtaining a plurality of alternative paths. Then, one of the multiple candidate paths needs to be selected as a final target planning path.
Specifically, one or more cost values such as path length, movement time, repetition path length, repetition region size, power consumption and the like of each alternative path are respectively determined, and the multiple cost values show the advantages and disadvantages of the alternative paths in various aspects from different aspects; here, the path length, the movement time length, the repetition path length, the repetition region size, and the like of each candidate path are taken as one path evaluation dimension. And calculating the score of each alternative path under each path evaluation dimension, wherein a corresponding cost value calculation formula is set for each path evaluation dimension, so that the cost value score under each path evaluation dimension of the alternative paths can be obtained, wherein the cost value score is a value between-1 and 1.
And then, calculating a cost value corresponding to each alternative path according to a preset calculation formula according to a preset weight coefficient corresponding to each path evaluation dimension and the cost value score under each path evaluation dimension.
Step S104: and determining one alternative path from the at least one alternative path as a target planning path according to the cost value.
In this embodiment, the candidate route with the minimum cost value is determined from the multiple candidate routes as the final result of the route planning, that is, the finally obtained target planned route.
Further, in this embodiment, in order to reduce the calculation amount, not all the sub-routes obtained by path planning for each area enter the process of obtaining the alternative paths by path connection in step S103, that is, it is also necessary to filter the sub-routes obtained by path planning for each area. Specifically, for each sub-route, according to the above calculation manner of the cost value, a cost value corresponding to each sub-route is calculated, and then the sub-routes having the cost value smaller than or equal to a preset value are screened to obtain the screened sub-routes, so as to obtain the final sub-routes entering step S103 for route connection.
Further, in this embodiment, it is also necessary to determine a cleaning mode corresponding to each region in the cleaning process of each region. In specific implementation, when the sweeping robot moves to each area (at this time, the area is an area to be swept), an image (target image) corresponding to the area is acquired through a camera device arranged on the sweeping robot, the image is identified, and a target sweeping mode required to be adopted is determined according to an identification result.
In specific implementation, when an area to be cleaned is cleaned, a camera device arranged on the cleaning robot is used for collecting a target image of the area to be cleaned, and then the collected target image is identified so as to obtain the area characteristics of the area to be cleaned.
The following describes in detail how the target image is identified to obtain the region feature.
First, a region (referred to as an ROI region) including a region feature in the target image needs to be acquired, the ROI region includes a feature of the region to be cleaned, and the region feature of the region to be cleaned can be determined according to the feature of the ROI region. For example, there is water stain in a partial region (ROI region) on the floor, a region where the water stain is located may be acquired as the ROI region by image recognition, and then specific feature extraction is performed on the ROI region.
Firstly, the target image is converted into a gray scale image to obtain the target image of the gray scale image, and the outline of the ROI area is acquired by identifying the gray scale target image. In this case, the gray-scale image is processed instead of the original target image, and the amount of calculation can be reduced.
Calculating the gray level average value of pixel points contained in each line of the target image, calculating the difference value between each pixel point and the gray level average value of the line as a gray level difference value, and calculating the gray level standard deviation under each line based on the gray level difference value; and calculating the gray average value of each row of the pixel points with the gray values smaller than the limit error threshold determined according to the gray standard deviation, and generating a first difference image according to the gray average value of each row. And determining a second differential image according to the absolute value of the gray difference between the target image and the first differential image, and performing binarization processing on the second differential image to obtain a binarized second differential image. Calculating the gray level average value of pixel points contained in each row of the target image, calculating the difference value between each pixel point and the gray level average value of the row as a gray level difference value, and calculating the gray level standard deviation of each row based on the gray level difference value; and calculating the gray average value of each row of the pixel points with the gray values smaller than the limit error threshold determined according to the gray standard deviation, and generating a third difference image according to the gray average value of each row. And determining a fourth differential image according to the absolute value of the gray difference between the target image and the third differential image, and performing binarization processing on the fourth differential image to obtain a binarized fourth differential image. Then, carrying out fusion processing on the second differential image and the fourth differential image to obtain a fifth differential image, wherein the fifth differential image is a binary image; and finally, identifying the fifth differential image to determine the ROI area in the target image.
In this case, the difference image is acquired, and the salient processing can be performed on the part of the target image that is different from the other area, so that the ROI area in the target image can be determined by simple recognition through the difference calculation process. Generally, the floor is pure color or fixed patterns, and differences in templates which are distinguished from the floor in the target image can be simply extracted through row-column difference processing, so that the ROI area in the target image can be simply identified.
Then, further feature extraction needs to be performed on the ROI region in the target image to obtain the region features of the region to be cleaned.
Specifically, the image of the ROI region in the target image is taken as the detection image, and then only the detection image is subjected to feature recognition, so that the amount of calculation of the features of the feature extraction can be reduced.
In one embodiment, a plurality of preset feature templates are obtained, wherein the feature templates are preset feature templates corresponding to a scanning mode, and each feature template includes features that the image in the corresponding scanning mode should have. And then extracting features in the detected image based on the feature templates, specifically, inputting the feature templates and the detected image into a preset feature extraction model to calculate the features contained in the detected image under each feature template and the confidence degrees with the features, wherein the confidence degrees represent the similarity between the feature templates and the detected image, that is, the confidence degrees of the detected image containing the corresponding feature templates. Then, one target feature template is selected from the plurality of feature templates according to the confidence degrees, and the features under the feature template are used as the region features extracted from the target image of the region to be cleaned.
In a specific embodiment, the detection image is input into a preset convolutional neural network model, a confidence corresponding to each feature is output, and then the feature with the confidence higher than a preset value is taken as the region feature, or the feature with the maximum confidence is taken as the region feature.
The sweeping robot can support multiple multi-sweeping modes, such as a water stain sweeping mode, a dust sweeping mode, a hair sweeping mode, an oil stain sweeping mode and a carpet sweeping mode, and what multi-sweeping mode is adopted for each area to sweep is determined according to the area characteristics corresponding to the areas.
In this embodiment, an image of an area corresponding to each of the scanning modes is obtained in advance, and features of the image are extracted as sample features corresponding to each of the multiple scanning modes; then, in this step, according to a preset feature matching algorithm, calculating a similarity between the regional feature of the region to be cleaned and the sample feature, which is also equivalent to calculating a similarity between the two features, and then determining which cleaning mode the regional feature specifically corresponds to according to the similarity, in specific implementation, determining the cleaning mode corresponding to the sample feature with the maximum similarity as the target cleaning mode.
Further, for each area, before starting to sweep the area, it is required to judge whether the remaining power of the sweeping robot can support completion of sweeping work of the area, specifically, determine preset mode power consumption data corresponding to each sweeping mode, where the preset mode power consumption data may be unit power consumption corresponding to each multiple sweeping mode, and determine a first power consumption of the area to be swept according to the first planned path and the mode power consumption data corresponding to the target sweeping mode; then judging whether the first power consumption is less than or equal to the residual power of the sweeping robot, if so, controlling the sweeping robot to move according to a target planning route to finish the sweeping work of the area to be swept; if not, the sweeping robot is controlled to move to the charging seat for charging, and the sweeping work of the area to be swept is executed after the charging is finished. Therefore, the situation that the electric quantity is insufficient in the middle of sweeping of one area by the sweeping robot is avoided.
In another aspect of the present embodiment, there is provided a path control device for a sweeping robot, as shown in fig. 2, the device including:
the map dividing module 101 is configured to acquire a map that is constructed in advance, divide the map according to historical data, divide the map into a plurality of regions, and determine a communication relationship between the plurality of regions;
the regional path planning module 102 is configured to perform path planning on each region according to a communication relationship between the regions, and determine at least one sub-path of each region;
a path communication module 103, configured to determine at least one alternative path according to at least one sub-path of each region and a communication relationship between the regions;
the cost calculation module 104 is configured to calculate, for each alternative path, a cost value score of the alternative path in multiple path evaluation dimensions, and calculate a cost value of each alternative path according to a preset path evaluation dimension coefficient and the cost values in the multiple path evaluation dimensions, where the path evaluation dimensions include one or more of path length, movement time, power consumption, repeated path length, and repeated area size of the alternative path;
and the target path selection module 105 is configured to determine one alternative path from the at least one alternative path as the target planning path according to the cost value.
Fig. 3 shows an internal structure diagram of a sweeping robot (computer device) for implementing the path control method of the sweeping robot in one embodiment. The computer device may specifically be a terminal, and may also be a server. As shown in fig. 3, the computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program which, when executed by the processor, causes the processor to carry out the above-mentioned method. The internal memory may also have stored therein a computer program which, when executed by the processor, causes the processor to perform the method described above. Those skilled in the art will appreciate that the architecture shown in fig. 3 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
After the path control method and the path control device of the sweeping robot and the sweeping robot are adopted, before the sweeping robot sweeps, firstly, area division needs to be carried out on a pre-constructed map to obtain a plurality of areas, and the communication relation among the areas is determined; performing path planning on each area according to the communication relation among the areas, and determining at least one sub-path of each area; determining at least one alternative path according to at least one sub-path of each region and the communication relation between the regions; calculating cost value scores of each alternative path under a plurality of path evaluation dimensions respectively aiming at each alternative path, and calculating a cost value of each alternative path according to a preset path evaluation dimension coefficient and the cost values under the plurality of path evaluation dimensions, wherein the path evaluation dimensions comprise one or more of path length, movement time, power consumption, repeated path length and repeated area size of the alternative path; and determining one alternative path from the at least one alternative path as a target planning path according to the cost value. The map planning method has the advantages that the regions are reasonably divided, the overall path planning of the map is divided into the path planning problems of the regions, the calculated amount of the path planning can be reduced under the condition that the overall optimal situation of the planned path is guaranteed, and the working efficiency of the sweeping robot in sweeping work is improved.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims. Please enter the implementation content part.
Claims (10)
1. A path control method of a sweeping robot is characterized by comprising the following steps:
acquiring a pre-constructed map, dividing the map according to historical data, dividing the map into a plurality of areas, and determining the communication relation among the areas;
performing path planning on each area according to the communication relation among the areas, and determining at least one sub-path of each area;
determining at least one alternative path according to at least one sub-path of each region and the communication relation between the regions;
calculating cost value scores of each alternative path under a plurality of path evaluation dimensions respectively aiming at each alternative path, and calculating a cost value of each alternative path according to a preset path evaluation dimension coefficient and the cost values under the plurality of path evaluation dimensions, wherein the path evaluation dimensions comprise one or more of path length, movement time, power consumption, repeated path length and repeated area size of the alternative path;
and determining one alternative path from the at least one alternative path as a target planning path according to the cost value.
2. The method of claim 1, wherein the step of dividing the map according to the historical data, dividing the map into a plurality of areas, and determining the connectivity between the plurality of areas further comprises:
dividing a map into a plurality of grids;
determining a plurality of basic grid points in the grids, and outwards expanding in the grids divided into the map based on each basic grid point to obtain an expanded rectangular area corresponding to each basic grid point, wherein expansion is stopped when an obstacle is encountered or the expansion is stopped when the number of the grids corresponding to the obstacle area is greater than a preset value;
for a plurality of rectangular regions:
performing first region processing operation on the plurality of rectangular regions according to the repeated relationship and the inclusion relationship among the rectangular regions, wherein the first region processing operation comprises one or more of deduplication operation, deletion operation and combination operation;
traversing each rectangular region, and calculating the ratio of the overlapping area between the traversed first rectangular region and other second rectangular regions with overlapping regions to the size of the region between the first rectangular region and the second rectangular region as a first ratio/a second ratio;
if the first ratio and the second ratio are both larger than a preset ratio threshold, merging the first rectangular area and the second rectangular area;
and if the first ratio is smaller than a preset ratio threshold value and/or the second ratio is smaller than a preset ratio threshold value, performing segmentation processing on the first rectangular area and the second rectangular area, wherein under the condition that the first ratio is smaller than the second ratio, the segmentation processing is to delete the intersection area of the first rectangular area and the second rectangular area from the first rectangular area.
3. The method of claim 2, wherein the step of dividing the map according to the historical data, dividing the map into a plurality of areas, and determining the connectivity between the plurality of areas further comprises:
in the process of deleting the intersection region of the first rectangular region and the second rectangular region from the first rectangular region, the intersection line between the first rectangular region and the second rectangular region is set as a dividing line, and the dividing line is set as a communicating position between the regions corresponding to the first rectangular region and the second rectangular region after the dividing processing.
4. The path control method of the sweeping robot according to claim 1, wherein the step of performing path planning on each area according to the communication relationship between the areas and determining at least one sub-path of each area further comprises:
planning a path of each area to obtain a planned path of which the starting point and the end point are in the communication positions with other areas as alternative sub-paths;
respectively calculating the cost value of each alternative sub-path, respectively calculating the cost value score of each alternative sub-path under a plurality of path evaluation dimensions, and respectively calculating the cost value of each alternative sub-path according to a preset path evaluation dimension coefficient and the cost values under the plurality of path evaluation dimensions, wherein the path evaluation dimensions comprise one or more of path length, movement time, power consumption, repeated path length and repeated area size of the alternative sub-paths; and determining one or more alternative sub-paths in the alternative sub-paths according to the cost value as at least one sub-path corresponding to the region.
5. The path control method of a sweeping robot of claim 1, further comprising:
recording the cleaning time, unit power consumption and cleaning mode of each area in the cleaning process of the cleaning robot;
determining the unit power consumption and the cleaning mode of each area according to the historical data, and determining the average power consumption of each area;
the step of determining one alternative path from at least one alternative path as a target planning path according to the cost value further includes:
calculating the total power consumption of each alternative path according to the average power consumption of each region; and judging whether the total power consumption is less than or equal to a preset power threshold, wherein the power threshold is the total power of the sweeping robot.
6. The path control method of a sweeping robot according to claim 2, further comprising:
when the sweeping robot moves to a region to be swept based on a target planned path, acquiring a target image of the region to be swept through a camera device arranged on the sweeping robot, carrying out image recognition on the acquired target image so as to determine regional characteristics of the region to be swept, and determining a target sweeping mode corresponding to the region to be swept in a plurality of preset sweeping modes according to the regional characteristics;
and cleaning the area to be cleaned based on the target cleaning mode and the target planning path.
7. The path control method of the sweeping robot according to claim 6, wherein the step of obtaining the target image of the area to be swept by the camera device arranged on the sweeping robot and performing image recognition on the obtained target image to determine the area characteristics of the area to be swept further comprises:
converting the target image into a gray scale image to obtain a target image of the gray scale image;
calculating the gray level average value of pixel points contained in each line of the target image, calculating the difference value between each pixel point and the gray level average value of the line as a gray level difference value, and calculating the gray level standard deviation under each line based on the gray level difference value; calculating the gray average value of each row of the pixel points with the gray values smaller than the limit error threshold determined according to the gray standard deviation, and generating a first difference image according to the gray average value of each row;
determining a second differential image according to the absolute value of the gray difference between the target image and the first differential image, and performing binarization processing on the second differential image to obtain a binarized second differential image;
calculating the gray level average value of pixel points contained in each row of the target image, calculating the difference value between each pixel point and the gray level average value of the row as a gray level difference value, and calculating the gray level standard deviation of each row based on the gray level difference value; calculating the gray average value of each row of the pixel points with the gray values smaller than the limit error threshold determined according to the gray standard deviation, and generating a third difference image according to the gray average value of each row;
determining a fourth differential image according to the absolute value of the gray difference between the target image and the third differential image, and performing binarization processing on the fourth differential image to obtain a binarized fourth differential image;
fusing the second differential image and the fourth differential image to obtain a fifth differential image, wherein the fifth differential image is a binary image;
identifying a fifth difference image to determine an ROI area in the target image;
acquiring an image of an ROI (region of interest) in the target image as a detection image;
acquiring a plurality of preset feature templates corresponding to the cleaning modes, and extracting features of the detection image based on the feature templates to acquire the features and confidence coefficients of the detection image under each feature template;
and determining the features under one feature template as the region features according to the confidence.
8. The path control method of the sweeping robot according to claim 6, wherein the step of performing path planning on each area according to the communication relationship between the areas and determining at least one sub-path of each area further comprises:
determining a thermal value of each area according to historical data, wherein the thermal value of each area is used for representing the movement speed and the power consumption value of each area in the historical data, and the movement speeds corresponding to different cleaning modes are different;
and determining whether each area needs to be repeatedly cleaned according to the thermal value, and under the condition that the area needs to be repeatedly cleaned, performing path planning on the area to obtain at least one sub-path, wherein the area repetition rate corresponding to each sub-path is greater than a preset value, and any grid in the area is repeatedly cleaned for 2 times or more in the sub-paths obtained by the cleaning robot according to the path planning.
9. A path control device of a sweeping robot is characterized in that the device comprises:
the map dividing module is used for acquiring a pre-constructed map, dividing the map according to historical data, dividing the map into a plurality of areas and determining the communication relation among the areas;
the regional path planning module is used for planning paths of each region according to the communication relation among the regions and determining at least one sub-path of each region;
the path communication module is used for determining at least one alternative path according to at least one sub-path of each region and the communication relation among the regions;
the cost calculation module is used for calculating cost value scores of each alternative path under a plurality of path evaluation dimensions respectively according to each alternative path, and calculating the cost value of each alternative path according to a preset path evaluation dimension coefficient and the cost values under the plurality of path evaluation dimensions, wherein the path evaluation dimensions comprise one or more of path length, movement time, power consumption, repeated path length and repeated area size of the alternative path;
and the target path selection module is used for determining one alternative path from the at least one alternative path as a target planning path according to the cost value.
10. A sweeping robot, comprising a memory and a processor, wherein the memory has executable code, and when the executable code runs on the processor, the sweeping robot path control method according to any one of claims 1 to 8 is implemented.
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