Path planning method and related equipment

Abstract

The path planning method provided by the embodiment of the invention is used for a cleaning robot, and comprises the following steps: acquiring an environment map, and marking a cleaned area and a to-be-cleaned area on the environment map; determining an intersection boundary of the cleaned area and the adjacent to-be-cleaned area; calculating and comparing the distance from the intersection boundary to the cleaning robot to obtain the shortest distance; and selecting the to-be-cleaned area corresponding to the shortest distance as the next target cleaning area. According to the path planning method provided by the embodiment of the invention, the next target cleaning area with the shortest or most reasonable path can be determined in real time, the cleaning path of the cleaning robot can be prevented from being too long, unnecessary consumed time is prevented from being increased, and thus the cleaning efficiency of the cleaning robot is improved. The embodiment of the invention further provides a path planning device, the cleaning robot and a computer readable storage medium.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of cleaning devices, and in particular to a path planning method and related equipment. Background Art

[0002] With the rapid development of electronic technology, more and more electronic products are being used in our lives, and smart home appliances are one of them. Among the many smart home appliances, cleaning robots fully liberate human labor in cleaning the floor. With a certain degree of artificial intelligence, they can automatically complete the floor cleaning work. The body of the cleaning robot includes a movable device with automation technology and a vacuum cleaner with a dust collection box. At the same time, in conjunction with the control trajectory set by the body, it can walk repeatedly on the ground that needs to be cleaned to achieve an anthropomorphic home cleaning effect.

[0003] When the cleaning robot performs intelligent cleaning, the home environment is divided into rooms of different sizes, and the cleaning robot selects these rooms for cleaning according to a certain logic and order. There are two logics for the existing cleaning robots to select rooms to be cleaned: 1. Get all the room information, sort all the rooms before cleaning, confirm the order, and all subsequent cleaning is done in this order; 2. Get only one room to be cleaned through the algorithm, and after cleaning the room, call the algorithm again to get the next room to be cleaned for cleaning, and so on, until all the rooms are cleaned.

[0004] The above cleaning methods all have the problem of non-optimal cleaning paths, which increases unnecessary time consumption and thus reduces the cleaning efficiency of the cleaning robot. Summary of the invention

[0005] To achieve the above-mentioned objectives, the embodiments of the present application provide a path planning method, a path planning device, a cleaning robot and a computer-readable storage medium, which can determine in real time the next target cleaning area with the shortest or most reasonable path, avoid the cleaning path of the cleaning robot being too long, avoid unnecessary time consumption, and thus improve the cleaning efficiency of the cleaning robot.

[0006] In a first aspect, an embodiment of the present application provides a path planning method for a cleaning robot, comprising:

[0007] Obtaining an environmental map, and marking the cleaned area and the area to be cleaned on the environmental map;

[0008] Determining an intersection boundary between the cleaned area and the adjacent area to be cleaned;

[0009] Calculating and comparing the distances from the intersection boundary to the cleaning robot to obtain the shortest distance; and

[0010] The area to be cleaned corresponding to the shortest distance is selected as the next target cleaning area.

[0011] Further, the cleaned area includes a plurality of cleaned sub-areas, and when the plurality of cleaned sub-areas are connected, the plurality of cleaned sub-areas constitute the cleaned area.

[0012] Furthermore, after obtaining the environmental map and identifying the cleaned area and the area to be cleaned on the environmental map, it also includes: judging whether the cleaning robot is located in the cleaned area, and if so, determining the intersection boundary between the cleaned area and the adjacent area to be cleaned; if not, defining the area where the cleaning robot is located as the target cleaning area.

[0013] Further, the calculating and comparing the distance from the intersection boundary to the cleaning robot to obtain the shortest distance includes: calculating and comparing the distance between the midpoint of the intersection boundary and the cleaning robot to obtain the shortest distance.

[0014] Further, calculating and comparing the distance from the intersection boundary to the cleaning robot to obtain the shortest distance includes: calculating and comparing the distance between each point of the intersection boundary and the cleaning robot to obtain the shortest distance.

[0015] Further, the calculating and comparing the distance from the intersection boundary to the cleaning robot to obtain the shortest distance includes calculating the JPS distance from the intersection boundary to the cleaning robot by using a JPS algorithm, and obtaining the shortest JPS distance by comparison.

[0016] Furthermore, after determining the intersection boundary of the area to be cleaned and the cleaned area, it also includes: judging whether the length of the intersection boundary is smaller than the body size of the cleaning robot, and if so, excluding the area to be cleaned corresponding to the intersection boundary from the range of the adjacent area to be cleaned; if not, calculating and comparing the distance from the intersection boundary to the cleaning robot to obtain the shortest distance.

[0017] In a second aspect, an embodiment of the present application provides a path planning device for a cleaning robot, the path planning device comprising:

[0018] A map construction module, used to obtain an environmental map and mark the cleaned area and the area to be cleaned on the environmental map;

[0019] A line segment confirmation module is used to determine the intersection boundary between the cleaned area and the adjacent area to be cleaned;

[0020] a distance calculation module, used to calculate and compare the distance from the intersection boundary to the cleaning robot to obtain the shortest distance; and

[0021] The area selection module is used to select the area to be cleaned corresponding to the shortest distance as the target cleaning area.

[0022] In a third aspect, an embodiment of the present application provides a cleaning robot, comprising: a memory and at least one processor, wherein a computer program is stored in the memory; the at least one processor calls the computer program in the memory so that the smart device executes each step of the path planning method described in any one of the above.

[0023] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various steps of the path planning method described in any one of the above items are implemented.

[0024] Compared with the existing path planning methods, the route planning method provided in the embodiment of the present application first obtains the environmental map and identifies the cleaned area and the area to be cleaned on the environmental map, then determines the intersection boundary of the cleaned area and the adjacent area to be cleaned, calculates and compares the distance from the intersection boundary to the cleaning robot, and obtains the shortest distance. When the shortest distance is calculated, the area to be cleaned corresponding to the shortest distance is selected as the target cleaning area. The cleaning path of the cleaning robot is not set in advance, but the next target cleaning area with the shortest path or the most reasonable path is determined in real time according to the current position of the cleaning robot and the relative distance between the cleaning robot and the area to be cleaned, thereby avoiding the cleaning path of the cleaning robot being too long, such as bypassing long-side obstacles or selecting areas at a farther distance, avoiding unnecessary time consumption, and thus improving the cleaning efficiency of the cleaning robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0026] Figure 1 A schematic diagram of a process flow of a path planning method provided in Example 1 of the present application;

[0027] Figure 2 A schematic diagram of an environment map provided in an embodiment of the present application;

[0028] Figure 3 A schematic diagram of a flow chart of a path planning method provided in Embodiment 2 of the present application;

[0029] Figure 4A schematic diagram of the structure of a path planning device provided in an embodiment of the present application;

[0030] Figure 5 A schematic diagram of the structure of the cleaning robot provided in an embodiment of the present application.

[0031] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0032] In order to make the technical problems, technical solutions and beneficial effects solved by the embodiments of the present application more clearly understood, the embodiments of the present application are further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present application.

[0033] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0034] In the description of the embodiments of the present application, it should be understood that the terms "lateral", "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "clockwise", "counterclockwise", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0035] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the embodiments of the present application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0036] In the embodiments of the present application, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral one; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly limited. For ordinary technicians in this field, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0037] In the embodiments of the present application, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0038] The shape of the robot disclosed in this embodiment is not limited, and can be constructed into any suitable shape. The robot in this application can be a household cleaning robot or a commercial cleaning robot.

[0039] Reference Figure 1 , the embodiment of the present application provides a path planning method for a cleaning robot, comprising the following steps S1 to S4:

[0040] S1: Obtain an environment map, and mark the cleaned area and the area to be cleaned on the environment map;

[0041] Common cleaning robots all have detectors. The detectors may include infrared sensors. Considering the detection range of infrared rays and the unknown nature of the cleaning environment, a learning-along-the-edge method is adopted, that is, the cleaning robot is allowed to walk around the room counterclockwise (or clockwise) along the outer edge of the wall and obstacles close to the wall from a designated position, and the position coordinates of the center point of the cleaning robot are recorded in real time during the walking process. In this way, the outline of the cleaning environment and the distribution of obstacles close to the wall can be roughly described. When an obstacle is very close to the wall and the cleaning robot cannot pass through them, the cleaning robot will treat the obstacle as a wall obstacle and handle it accordingly.

[0042] The robot starts edge learning in a counterclockwise direction with the charging station as the origin. After edge learning, a local environment model of the cleaning environment boundary can be established. The edge learning detection method has the following advantages:

[0043] 1) It reduces the requirements for infrared sensors, and does not require a large visual detection range. In addition, infrared sensors have higher accuracy and speed, which can make full use of the performance of infrared sensors.

[0044] 2) Before the cleaning robot starts cleaning, all areas are unknown. Selecting any direction for cleaning involves solving the coordinate values ​​of blank areas and obstacles. Edge-based learning can prevent the cleaning robot from blindly selecting a direction for cleaning and can also reduce the amount of calculation for the system. At the same time, the contour map established after edge-based learning also provides navigation for the next step of traversal cleaning.

[0045] 3) Although learning along the edge will consume some cleaning time of the cleaning robot, it is actually a cleaning behavior. And pre-clean the dusty places such as the wall first.

[0046] In the process of learning along the edge, the reliability and stability of information acquisition are enhanced by combining infrared sensors with collision sensors. In addition, the characteristics of the cleaning environment can be represented in the form of a "map" based on the robot's positioning information. In addition to the form of learning along the edge, if the performance of the detector is good, other detection methods such as ultrasonic echo can be used.

[0047] The method of constructing the map in this step can be represented by a topological map, geometric information or a grid. A topological map is a compact representation method. When the environment is large and simple, this method can represent the environment as a topological map. However, the resolution of the topological map depends on the complexity of the environment. When there are two very similar places in the environment, it is difficult for the topological map to determine whether they are the same node.

[0048] Geometric information representation is to abstract the sensor information extracted by the robot into geometric representations, such as straight lines, curves, etc. This representation method is vivid, compact and convenient for position estimation and target recognition, but it increases the requirements for sensor information collection, requires additional algorithm processing, and requires a certain amount of perception data to obtain results.

[0049] Rasterization is to divide the whole environment into several grids of the same size, and indicate whether there are obstacles in each grid. Grid maps are easy to create and maintain. The information of each grid known by the cleaning robot directly corresponds to a certain area in the environment. The information for creating the map can be obtained and added to the map using cheap sensors such as ultrasound or infrared. With the help of the map, self-positioning and path planning can be easily performed. Therefore, the grid-processed map is used in this embodiment.

[0050] After the rasterized map is established, the cleaned area and the to-be-cleaned area in the map are determined, wherein the cleaned area is the area where the cleaning robot has completed the cleaning work on the bottom surface to be cleaned, and the to-be-cleaned area is the area where the cleaning work has not yet been completed.

[0051] Reference Figure 2 , Figure 2 A schematic diagram of an environmental map provided in an embodiment of the present application, wherein the map includes areas 1 to 6, and the cleaning robot constructs an environmental map by learning along the edge of the detector, and rasterizes the environmental map to form a raster map. For example, if the cleaning robot has completed the cleaning work of area 2, the area where area 2 is located is the cleaned area, and the areas where other areas are located are the areas to be cleaned.

[0052] S2: Determine the intersection boundary between the cleaned area and the adjacent area to be cleaned;

[0053] Specifically, the intersection boundary refers to the line segment where the outline or boundary line of the cleaned area intersects with the outline or boundary line of the adjacent area to be cleaned. When performing image processing, the path planning method provided in some embodiments of the present application obtains the intersection boundary through the dilate function. The dilate function is an expansion operation in image processing, and its function is to expand the neighborhood of non-zero pixels in a given binary image, which can also be said to be an image expansion operation. In some embodiments of the present application, the dilate function is used to expand the outline or boundary line of the cleaned area and the outline or boundary line of the adjacent area to be cleaned by one grid, thereby obtaining the intersection boundary of the cleaned area and the adjacent area to be cleaned.

[0054] S3: Calculate and compare the distances from the intersection boundary to the cleaning robot to obtain the shortest distance;

[0055] There are usually multiple areas to be cleaned, so there are usually multiple intersection boundaries between the cleaned area and the adjacent areas to be cleaned. The distances from the multiple intersection boundaries between the cleaned area and the multiple adjacent areas to be cleaned to the cleaning robot are calculated, and these distances are compared to obtain the shortest distance.

[0056] S4: Select the to-be-cleaned area corresponding to the shortest distance as the next target cleaning area.

[0057] Specifically, when the shortest distance is calculated, the area to be cleaned corresponding to the shortest distance is selected as the target cleaning area. That is, compared with the existing path planning method, the route planning method provided in the embodiment of the present application does not set the cleaning path of the cleaning robot in advance, but determines the next target cleaning area with the shortest or most reasonable path in real time according to the current position of the cleaning robot and the relative distance between the cleaning robot and the area to be cleaned, thereby avoiding the cleaning path of the cleaning robot being too long, such as bypassing long-side obstacles or selecting areas at a long distance, avoiding unnecessary time consumption, and thus improving the cleaning efficiency of the cleaning robot. For example, Figure 2 As shown, when the cleaning robot is located in the cleaned area 2, the cleaning robot completes the cleaning work on the cleaned area 2. If it stays at the position of the adjacent area 5, the path planning method provided in the embodiment of the present application will define area 5 as the target cleaning area. When it stays at the position of the adjacent area 6, the path planning method provided in the embodiment of the present application will define area 6 as the target cleaning area. Therefore, the path planning method provided in the embodiment of the present application can dynamically and reasonably select the target cleaning area, thereby avoiding the cleaning path of the cleaning robot being too long, avoiding unnecessary time consumption, and improving the cleaning efficiency of the cleaning robot.

[0058] It should be noted that, in some embodiments of the present application, when there are multiple and equal shortest distances obtained, the method provided in the embodiments of the present application will select the area to be cleaned corresponding to any one of the shortest distances as the target cleaning area.

[0059] Further, in some embodiments of the present application, the cleaned area includes a plurality of cleaned sub-areas, and when the plurality of cleaned sub-areas are connected, the plurality of cleaned sub-areas constitute the cleaned area.

[0060] Specifically, connectivity generally refers to an image region composed of foreground pixels with the same pixel value and adjacent positions in the image. During image processing, multiple adjacent cleaned sub-regions are assigned the same pixel value, so they can together form a clean region. Figure 2 As shown, when the cleaning robot has completed the cleaning work of area 21 and area 22, during image processing, area 21 and area 22 are assigned the same pixel value, and area 21 and area 22 are adjacent, so area 21 and area 22 constitute the cleaned area 2.

[0061] Therefore, in the path planning method provided in the embodiment of the present application, by merging multiple connected cleaned sub-areas into a cleaned area, repeated calculations can be avoided, the calculation speed can be improved, the generation of calculation results can be accelerated, and the target cleaning area can be obtained more quickly, thereby improving the cleaning efficiency of the cleaning robot.

[0062] Further, refer to Figure 3 In some embodiments of the present application, after step S1, i.e., obtaining the environmental map and identifying the cleaned area and the area to be cleaned on the environmental map, the path planning method provided in the embodiments of the present application also includes: determining whether the cleaning robot is located in the cleaned area, and if so, determining the intersection boundary between the cleaned area and the adjacent area to be cleaned; if not, defining the area where the cleaning robot is located as the target cleaning area.

[0063] Specifically, the path planning method provided in the embodiment of the present application is to determine in real time the next target cleaning area with the shortest or most reasonable path based on the current position of the cleaning robot and the relative distance between the cleaning robot and the area to be cleaned. When the cleaning robot is located in the cleaned area, the next target cleaning area is determined according to the method. When the cleaning robot is not located in the cleaned area, the area where the cleaning robot is located is defined as the target cleaning area. This can avoid the cleaning robot moving to the cleaned area first and then selecting the target cleaning area, thereby further avoiding the cleaning path of the cleaning robot being too long and avoiding unnecessary time consumption, thereby improving the cleaning efficiency of the cleaning robot.

[0064] In addition, in some embodiments of the present application, step S3, namely calculating and comparing the distance from the intersection boundary to the cleaning robot, and obtaining the shortest distance, includes: calculating and comparing the distance between the midpoint of the intersection boundary and the cleaning robot, and obtaining the shortest distance.

[0065] Specifically, the path planning method provided in the embodiment of the present application selects the next target cleaning area by calculating the distance between the midpoint of the intersection boundary of the adjacent area to be cleaned and the cleaned area and the cleaning robot, and obtaining the shortest distance by comparison. Compared with the existing path planning method, the route planning method provided in the embodiment of the present application does not set the cleaning path of the cleaning robot in advance, but determines the next target cleaning area with the shortest or most reasonable path in real time based on the current position of the cleaning robot and the relative distance between the cleaning robot and the area to be cleaned, thereby avoiding the cleaning path of the cleaning robot being too long, such as bypassing long-side obstacles or selecting areas that are far away, avoiding unnecessary time consumption, and thus improving the cleaning efficiency of the cleaning robot.

[0066] Furthermore, in some embodiments of the present application, step S3, namely calculating and comparing the distance from the intersection boundary to the cleaning robot, and obtaining the shortest distance, includes: calculating and comparing the distance between each point of the intersection boundary and the cleaning robot, and obtaining the shortest distance.

[0067] Specifically, the path planning method provided in the embodiment of the present application selects the next target cleaning area by calculating the distance between each point of the intersection boundary of the adjacent area to be cleaned and the cleaned area and the cleaning robot, and obtaining the shortest distance by comparison. Compared with the existing path planning method, the route planning method provided in the embodiment of the present application does not set the cleaning path of the cleaning robot in advance, but determines the next target cleaning area with the shortest or most reasonable path in real time based on the current position of the cleaning robot and the relative distance between the cleaning robot and the area to be cleaned, thereby avoiding the cleaning path of the cleaning robot being too long, such as bypassing long-side obstacles or selecting areas that are far away, avoiding unnecessary time consumption, and thus improving the cleaning efficiency of the cleaning robot.

[0068] In addition, in some embodiments of the present application, step S3 calculates and compares the distance from the intersection boundary to the cleaning robot, and obtaining the shortest distance includes calculating the JPS distance from the intersection boundary to the cleaning robot through the JPS algorithm, and obtaining the shortest JPS distance through comparison.

[0069] Specifically, the JPS algorithm (Jump Point Search) is an optimization algorithm for path planning. It reduces the number of nodes searched by the jump point search method, thereby improving the search efficiency. The JPS algorithm constructs a path planning algorithm by searching the jump point of the parent node or forcing the neighbor point. The path planning by this algorithm can reduce the number of calculations of the navigation point. Therefore, the path planning method provided by the embodiment of the present application can quickly obtain relevant distance information through the JPS algorithm, thereby saving calculation time and further providing the cleaning efficiency of the cleaning robot. Compared with the existing path planning method, the route planning method provided by the embodiment of the present application does not set the cleaning path of the cleaning robot in advance, but determines the next target cleaning area with the shortest or most reasonable path in real time according to the current position of the cleaning robot and the relative distance between the cleaning robot and the area to be cleaned, thereby avoiding the cleaning path of the cleaning robot from being too long, such as going around long side obstacles or selecting areas with a long distance, avoiding unnecessary time consumption, thereby improving the cleaning efficiency of the cleaning robot.

[0070] In addition, if Figure 3 As shown, in some embodiments of the present application, in step S2, i.e., after determining the intersection boundary of the area to be cleaned and the cleaned area, the path planning method provided in the embodiments of the present application also includes: judging whether the length of the intersection boundary is smaller than the body size of the cleaning robot, and if so, excluding the area to be cleaned corresponding to the intersection boundary from the range of the adjacent area to be cleaned; if not, calculating and comparing the distance from the intersection boundary to the cleaning robot to obtain the shortest distance.

[0071] Specifically, for example, the door of the room where the area to be cleaned is located is half open, and the intersection boundary of its outline or dividing line with the outline or dividing line of the cleaned area is smaller than the body size of the cleaning robot, such as the diameter of the cleaning robot. The cleaning robot cannot enter the room to perform cleaning work. At this time, the path planning method provided in the embodiment of the present application excludes the area to be cleaned corresponding to the room, thereby avoiding ineffective work of the cleaning robot, avoiding unnecessary time wasting, and improving cleaning efficiency.

[0072] Reference Figure 4 , an embodiment of the present application provides a path planning device 100, which is used for a cleaning robot, and the path planning device 100 includes: a map construction module 101, a line segment confirmation module 102, a distance calculation module 103 and an area selection module 104, wherein the map construction module 101 is used to obtain an environmental map and identify cleaned areas and areas to be cleaned on the environmental map; the line segment confirmation module 102 is used to determine the intersection boundary between the cleaned area and the adjacent area to be cleaned; the distance calculation module 103 is used to calculate and compare the distance from the intersection boundary to the cleaning robot to obtain the shortest distance; the area selection module 104 is used to select the area to be cleaned corresponding to the shortest distance as the target cleaning area.

[0073] Compared with the existing path planning device, the route planning device provided in the embodiment of the present application does not set the cleaning path of the cleaning robot in advance, but determines the shortest or most reasonable next target cleaning area in real time according to the current position of the cleaning robot and the relative distance between the cleaning robot and the area to be cleaned, thereby avoiding the cleaning path of the cleaning robot being too long, such as bypassing long-side obstacles or selecting areas that are far away, avoiding unnecessary time consumption, and thus improving the cleaning efficiency of the cleaning robot. Figure 2 As shown, when the cleaning robot is located in the cleaned area 2, the cleaning robot completes the cleaning work on the cleaned area 2. If it stays at the position of the adjacent area 5, the path planning device provided in the embodiment of the present application will define area 5 as the target cleaning area. When it stays at the position of the adjacent area 6, the path planning device provided in the embodiment of the present application will define area 6 as the target cleaning area. Therefore, the path planning method provided in the embodiment of the present application can dynamically and reasonably select the target cleaning area, thereby avoiding the cleaning path of the cleaning robot being too long, avoiding unnecessary time consumption, and improving the cleaning efficiency of the cleaning robot.

[0074] Reference Figure 5 , Figure 5 This is a structural block diagram of the robot provided in the embodiment of the present application. Figure 5 As shown, the robot 200 may include: a robot body, an obstacle detection device, a processor 201 , a memory 202 and a communication module 203 .

[0075] The obstacle detection device is arranged on the robot body, and is used to receive the reflected signal reflected by the obstacle in real time. In this embodiment, the obstacle detection device is a light sensor, including but not limited to an infrared sensor.

[0076] The mobile robot body is provided with a walking mechanism. The processor 201 is built in the robot body.

[0077] The robot body is the main structure of the robot. The corresponding shape structure and manufacturing material (such as hard plastic or metals such as aluminum and iron) can be selected according to the actual needs of the robot. For example, it can be set to a relatively flat cylindrical shape that is common in sweeping robots.

[0078] The walking mechanism is a structural device arranged on the robot body to provide the mobile robot with mobility. The walking mechanism can be implemented by any type of mobile device, such as rollers, crawlers, etc.

[0079] The processor 201, the memory 202 and the communication module 203 can establish a communication connection between any two of them through a bus.

[0080] The processor 201 may be any type of control chip with one or more processing cores, which can perform single-thread or multi-thread operations, and is used to parse instructions to perform operations such as acquiring data, performing logical operations, and issuing operation processing results.

[0081] The memory 202 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store the robot's walking route, and the robot's walking control strategy, etc. In addition, the memory 202 may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 202 may optionally include a memory remotely arranged relative to the processor 201, and these remote memories may be connected to the robot 200 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0082] The memory 202 stores instructions that can be executed by at least one control chip in the processor 201; the at least one control chip is used to execute the instructions to implement the path planning method of the cleaning robot in any of the above method embodiments.

[0083] The communication module 203 is a functional module for establishing a communication connection and providing a physical channel. The communication module 203 can be any type of wireless or wired communication module, including but not limited to a WiFi module or a Bluetooth module.

[0084] Compared with the existing path planning device, the cleaning robot provided by the embodiment of the present application does not set the cleaning path of the cleaning robot in advance, but determines the next target cleaning area with the shortest or most reasonable path in real time according to the current position of the cleaning robot and the relative distance between the cleaning robot and the area to be cleaned, thereby avoiding the cleaning path of the cleaning robot being too long, such as bypassing long-side obstacles or selecting an area that is far away, avoiding unnecessary time consumption, and thus improving the cleaning efficiency of the cleaning robot. For example, Figure 2 As shown, when the cleaning robot is located in the cleaned area 2, the cleaning robot completes the cleaning work on the cleaned area 2. If it stays at the position of the adjacent area 5, the path planning device provided in the embodiment of the present application will define area 5 as the target cleaning area. When it stays at the position of the adjacent area 6, the path planning device provided in the embodiment of the present application will define area 6 as the target cleaning area. Therefore, the path planning method provided in the embodiment of the present application can dynamically and reasonably select the target cleaning area, thereby avoiding the cleaning path of the cleaning robot being too long, avoiding unnecessary time consumption, and improving the cleaning efficiency of the cleaning robot.

[0085] The embodiment of the present application further provides a main control chip, which is assembled in the cleaning robot 200. The main control chip is used to control the cleaning robot 200 to execute the path planning method provided in the present application.

[0086] The present application also provides a cleaning robot, which is equipped with a main control chip provided in an embodiment of the present application. Through the main control chip, the cleaning robot can be controlled to execute the path planning method provided in the present application.

[0087] Furthermore, an embodiment of the present application also provides a computer storage medium, which stores computer executable instructions, and the computer executable instructions are executed by one or more control chips in the processor 201, so that the one or more control chips execute the robot path planning method in any of the above method embodiments.

[0088] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0089] Through the description of the above implementation methods, ordinary technicians in this field can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course, it can also be implemented by hardware. Ordinary technicians in this field can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program in a computer program product. The computer program can be stored in a non-transient computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by the relevant device, the relevant device can execute the process of the embodiment of the above-mentioned method. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0090] The above-mentioned product can execute the path planning method of the robot provided in the embodiment of the present application, and has the functional modules and beneficial effects corresponding to the path planning method of the robot. For technical details not described in detail in this embodiment, please refer to the path planning method of the cleaning robot provided in the embodiment of the present application.

[0091] An embodiment of the present application also provides a computer program product, which includes a computer program stored on a non-volatile computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a cleaning robot, the cleaning robot executes any one of the path planning methods described.

[0092] The above described device or equipment embodiments are merely illustrative, wherein the unit modules described as separate components may or may not be physically separated, and the components displayed as module units may or may not be physical units, that is, they may be located in one place, or may be distributed on multiple network module units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0093] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0094] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0095] The above description is only a preferred embodiment of the present application, and does not limit the patent scope of the present application. All equivalent structural changes made by using the contents of the present application specification and drawings under the application concept of the present application, or directly / indirectly used in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A path planning method for a cleaning robot, characterized in that: include: Obtaining an environmental map, and marking the cleaned area and the area to be cleaned on the environmental map; Determining an intersection boundary between the cleaned area and the adjacent area to be cleaned; Calculating and comparing the distance from the intersection boundary to the cleaning robot to obtain the shortest distance; The area to be cleaned corresponding to the shortest distance is selected as the next target cleaning area.

2. The method according to claim 1, characterized in that The cleaned area includes a plurality of cleaned sub-areas. When the plurality of cleaned sub-areas are connected, the plurality of cleaned sub-areas constitute the cleaned area.

3. The method according to claim 2, characterized in that After obtaining the environmental map and marking the cleaned area and the area to be cleaned on the environmental map, it also includes: judging whether the cleaning robot is located in the cleaned area, and if so, determining the intersection boundary between the cleaned area and the adjacent area to be cleaned; if not, defining the area where the cleaning robot is located as the target cleaning area.

4. The method according to claim 1, characterized in that The calculating and comparing the distance from the intersection boundary to the cleaning robot to obtain the shortest distance includes: calculating and comparing the distance between the midpoint of the intersection boundary and the cleaning robot to obtain the shortest distance.

5. The method according to claim 1, characterized in that The calculating and comparing the distance from the intersection boundary to the cleaning robot to obtain the shortest distance includes: calculating and comparing the distance between each point of the intersection boundary and the cleaning robot to obtain the shortest distance.

6. The method according to claim 1, characterized in that The calculating and comparing the distance from the intersection boundary to the cleaning robot to obtain the shortest distance includes calculating the JPS distance from the intersection boundary to the cleaning robot by using a JPS algorithm, and obtaining the shortest JPS distance by comparison.

7. The method according to any one of claims 1 to 6, characterized in that: After determining the intersection boundary between the area to be cleaned and the adjacent cleaned area, it also includes: judging whether the length of the intersection boundary is smaller than the body size of the cleaning robot, and if so, excluding the area to be cleaned corresponding to the intersection boundary from the range of the adjacent area to be cleaned; if not, calculating and comparing the distance from the intersection boundary to the cleaning robot to obtain the shortest distance.

8. A path planning device for a cleaning robot, characterized in that: The path planning device comprises: A map construction module, used to obtain an environmental map and mark the cleaned area and the area to be cleaned on the environmental map; A line segment confirmation module is used to determine the intersection boundary between the cleaned area and the adjacent area to be cleaned; a distance calculation module, used to calculate and compare the distance from the intersection boundary to the cleaning robot to obtain the shortest distance; and The area selection module is used to select the area to be cleaned corresponding to the shortest distance as the target cleaning area.

9. A cleaning robot, characterized in that: The cleaning robot comprises: a memory and at least one processor, wherein a computer program is stored in the memory; the at least one processor calls the computer program in the memory so that the smart device executes each step of the path planning method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the path planning method according to any one of claims 1 to 7 are implemented.

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