A cleaning robot cleaning control method

Abstract

The application provides a cleaning control method of a cleaning robot, which comprises the following steps: controlling the cleaning robot to travel and clean in a to-be-cleaned area; if it is monitored that the cleaning robot successfully escapes from a trapped area during the traveling, marking the trapped area as a target cleaned area; generating a first cleaning path in a remaining cleaning area; and controlling the cleaning robot to travel according to the first cleaning path and clean the remaining cleaning area; wherein the remaining cleaning area is a remaining area in the to-be-cleaned area except the cleaned area; and the cleaned area comprises the target cleaned area and a historical cleaned area, or the cleaned area comprises the historical cleaned area, and the historical cleaned area is an area that has been cleaned by the cleaning robot. The method effectively avoids the cleaning robot from entering the trapped area twice, and effectively ensures that the cleaning robot can perform cross-area cleaning.

Description

A cleaning control method for a cleaning robot Technical Field

[0001] This application relates to the field of robot cleaning planning technology, and in particular to a cleaning control method for a cleaning robot. Background Technology

[0002] Cleaning robots are a general term encompassing sweeping robots, mopping robots, and sweeping-mopping robots. These robots are suitable for both home and outdoor environments, reducing household cleaning workload and replacing manual labor for basic floor maintenance. They are gradually gaining acceptance and becoming a new favorite in the small appliance market. Sweeping-mopping robots, in particular, combine a sweeping robot with a mop. Besides using side brushes, roller brushes, and a vacuuming mechanism to clean light dirt, their most important function is mopping. Specifically, these mopping components can be active, such as rolling or oscillating parts, or passively moving mops.

[0003] When a cleaning robot is performing cleaning tasks, obstacles such as rocking chairs, U-shaped chairs, thresholds, and table and chair legs in the user's home can cause it to get stuck in the area where these obstacles are located (hereinafter referred to as the "stuck area"). Specifically, the reason for getting stuck may be that the robot is held up by the obstacle, reducing its mobility and preventing it from completing normal cleaning movements; or, the size of the cleaning robot may be similar to the size of the stuck area, allowing it to enter but making escape difficult. After getting stuck, the cleaning robot can recover its state and escape the stuck area through certain combinations of movements. However, since the main function of a cleaning robot in the home is to clean as many areas as possible, it is very likely that the robot will re-enter the stuck area during the cleaning process, resulting in secondary entrapment. When a robot gets stuck in the same area multiple times, it can easily cause the following problems: 1. Low cleaning efficiency, unable to clean as much area as possible with limited battery capacity; 2. Damage to the home environment, as the movement to escape is usually quite large, which can easily cause damage to the environment during the movement; 3. Damage to the robot itself, for the same reason as 2.

[0004] Therefore, to prevent the aforementioned issues, the common practice is to designate the trapped area as a restricted zone. The size and effective range of this zone vary depending on the manufacturer. However, if a restricted zone is established, the robot needs to switch states multiple times during the cleaning process: from edge cleaning to bow sweeping, and then back to edge cleaning of the restricted zone. This process is complex. If multiple restricted zones exist near the robot, the number of state switching increases exponentially. Furthermore, tracking even more restricted zones adds complexity and increases the risk of errors, significantly reducing the cleaning efficiency and user experience. Additionally, establishing restricted zones can lead to the following problem: when the robot needs to clean across areas, and the trapped area connects two adjacent areas (for example, the threshold between two rooms), the presence of the restricted zone prevents the robot from re-entering the trapped area. This prevents cross-area cleaning and significantly reduces the cleaning effectiveness. Summary of the Invention

[0005] The purpose of this application is to provide a cleaning control method for a cleaning robot, which effectively prevents the cleaning robot from re-entering the trapped area and effectively ensures that the cleaning robot can perform cross-area cleaning.

[0006] This application provides a cleaning control method for a cleaning robot, including:

[0007] Control the cleaning robot to move and clean the area to be cleaned. If the cleaning robot successfully escapes from the trapped area during the process, mark the trapped area as the target cleaned area.

[0008] In the remaining clean area, generate the first clean path;

[0009] The cleaning robot is controlled to move along the first cleaning path and clean the remaining cleaning area; among which, the remaining

[0010] The remaining area to be cleaned is the area outside the already cleaned areas within the area to be cleaned; the already cleaned areas include the target already cleaned areas and historically cleaned areas, or, the already cleaned areas include historically cleaned areas.

[0011] The historically cleaned area refers to the area that has already been cleaned by the cleaning robot.

[0012] In one embodiment, the cleaning robot is equipped with sensors;

[0013] The cleaning control methods for cleaning robots also include:

[0014] When the cleaning robot is detected to be stuck, the robot is controlled to perform an escape maneuver. During the escape maneuver, the robot is judged to have successfully escaped based on the sensor data sent by the sensors.

[0015] In one embodiment, multiple sensors are provided;

[0016] The system determines whether the cleaning robot has successfully escaped its predicament based on sensor data, including:

[0017] By fusing sensor data from multiple sensors, five target data reflecting the status of the cleaning robot are obtained;

[0018] Based on the target data, determine whether the cleaning robot has successfully escaped the obstacle.

[0019] In one embodiment, before marking the trapped area as a target cleaned area, the process includes:

[0020] The trapped area is determined based on the first location information when the cleaning robot is trapped and the second location information when the cleaning robot successfully escapes.

[0021] In one embodiment, determining the trapped area includes:

[0022] The geometric region enclosed by the first and second location information as diagonal points is designated as the trapped region.

[0023] In one embodiment, generating a first cleaning path in the remaining cleaning area includes:

[0024] A first cleaning path is generated based on the second cleaning path; wherein, the second cleaning path is the original path of the cleaning robot before it gets stuck.

[0025] In one embodiment, generating a first cleaning path based on a second cleaning path includes:

[0026] When the cleaned area includes both the target cleaned area and the historical cleaned area, the second cleaning path is adjusted, and the adjusted second cleaning path is used as the first cleaning path.

[0027] When the cleaned area includes a historically cleaned area, the second cleaning path is used as the first cleaning path.

[0028] In one embodiment, adjusting the second cleaning path includes:

[0029] Delete the portion of the second cleaning path that is covered by the target already cleaned area.

[0030] In one embodiment, when the area to be cleaned includes multiple sub-areas, and the target cleaned area connects two adjacent sub-areas, the cleaned area includes historically cleaned areas.

[0031] In one embodiment, the cleaning control method for the cleaning robot further includes:

[0032] When the cleaning robot is performing path planning, if the target cleaned area is within the planned unique path range, the cleaning robot is controlled to pass through the target cleaned area.

[0033] In this application, during the cleaning process of the cleaning robot in the area to be cleaned, if it is detected that the cleaning robot has successfully escaped from a stuck area, the stuck area is marked as the target cleaned area. After successful marking, a first cleaning path is generated in the remaining cleaning area. Then, the cleaning robot is controlled to move along the first cleaning path to clean the remaining cleaning area. The remaining cleaning area refers to the area remaining in the area to be cleaned, excluding the already cleaned areas; the cleaned areas include the target cleaned area and historically cleaned areas, or the cleaned areas include historically cleaned areas, which are areas already cleaned by the cleaning robot.

[0034] It can be seen that in this application, after marking the trapped area as a cleaned area, the trapped area will be classified as a planable area or an unplanable area according to the cleaning environment of the cleaning robot.

[0035] On the one hand, by treating the trapped area as an unplanned zone, the cleaning robot generates a primary cleaning path within the remaining cleaning area after excluding previously cleaned and trapped areas. This effectively prevents the robot from re-entering the trapped area while cleaning the area to be cleaned, improving cleaning efficiency and preventing damage to the robot itself or the user's home. Furthermore, this method eliminates the need for restricted areas, is simple to implement, and the robot only needs to follow the generated primary cleaning path to avoid re-entering the trapped area. It avoids multiple state switching, reduces the likelihood of errors, and further enhances cleaning efficiency and user experience.

[0036] On the other hand, by treating the trapped area as a planarable area, the cleaning robot generates a first cleaning path within the remaining clean area after removing previously cleaned areas from the area to be cleaned. In this method, when the trapped area is used to connect two adjacent cleaning sub-areas, treating the trapped area as a planarable area effectively ensures that the cleaning robot can plan a cleaning path that enables cross-area cleaning, fully guaranteeing that the cleaning robot can perform cross-area cleaning and greatly improving the cleaning effect of the cleaning robot. Attached Figure Description

[0037] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly described below.

[0038] Figure 1 is a schematic diagram of the structure of a cleaning robot provided in an embodiment of this application;

[0039] Figure 2 is a schematic diagram of the structure of a control module provided in an embodiment of this application;

[0040] Figure 3 is a flowchart illustrating the cleaning control method of a cleaning robot provided in an embodiment of this application;

[0041] Figure 4 is a schematic diagram of the cleaning robot provided in the first embodiment of this application cleaning the area to be cleaned;

[0042] Figure 5 is a schematic diagram of the cleaning robot provided in the second embodiment of this application cleaning the area to be cleaned;

[0043] Figure 6 is a schematic diagram of the cleaning robot provided in the third embodiment of this application cleaning the area to be cleaned;

[0044] Figure 7 is a schematic diagram of the cleaning robot provided in the fourth embodiment of this application cleaning the area to be cleaned;

[0045] Figure 8 is a schematic diagram of the cleaning robot provided in the fifth embodiment of this application cleaning the area to be cleaned;

[0046] Figure 9 is a schematic diagram of the cleaning robot provided in the sixth embodiment of this application cleaning the area to be cleaned;

[0047] Figure 10 is a schematic diagram of the cleaning robot provided in the seventh embodiment of this application cleaning the area to be cleaned;

[0048] Figure 11 is a schematic diagram of the cleaning robot provided in the eighth embodiment of this application cleaning the area to be cleaned.

[0049] Figure label:

[0050] 1-Control module; 10-Bus; 11-Processor; 12-Memory; 100-Cleaning robot. Detailed Implementation

[0051] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0052] Similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0053] Please refer to Figure 1, which is a structural schematic diagram of a cleaning robot 100 provided in an embodiment of this application. Please refer to Figure 2, which is a structural schematic diagram of a control module 1 provided in an embodiment of this application. The cleaning robot 100 in this application is used to perform cleaning tasks. Specifically, the cleaning robot 100 can be a sweeping robot, a sweeping robot, or a sweeping and mopping robot, etc. As shown in Figure 1, the cleaning robot 100 is provided with a control module 1, which is used to execute the cleaning control method of the cleaning robot 100 provided in the following embodiments of this application. As shown in Figure 2, the control module 1 includes: at least one processor 11 and a memory 12. In Figure 2, one processor 11 is used as an example. The processor 11 and the memory 12 are connected through a bus 10. The memory 12 stores instructions that can be executed by the processor 11. The instructions are executed by the processor 11 so that the control module 1 can execute all or part of the cleaning control method of the cleaning robot 100 in the following embodiments.

[0054] The memory 12 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0055] This application also provides a computer-readable storage medium storing a computer program that can be executed by a processor 11 to perform the cleaning control method of the cleaning robot 100 provided in the following embodiments of this application.

[0056] Please refer to Figure 3, which is a flowchart illustrating the cleaning control method of a cleaning robot 100 provided in an embodiment of this application. As shown in Figure 3, the method includes the following steps S210-S230.

[0057] Step S210: Control the cleaning robot 100 to move and clean in the area to be cleaned. If the cleaning robot 100 is detected to have successfully escaped from the trapped area during the movement, mark the trapped area as the target cleaned area.

[0058] The area to be cleaned is the area where the cleaning robot 100 performs cleaning operations. This area can consist of a single cleaning zone, or it can include multiple sub-cleaning zones. For example, the areas to be cleaned can be arranged in combinations, including the study floor, living room floor, bedroom floor, kitchen floor, and bathroom floor, where each of these sub-zones constitutes a cleaning zone. The "trapped area" is the area that traps the cleaning robot 100. When the cleaning robot 100 enters a trapped area, its movement is obstructed, and it cannot continue cleaning the area to be cleaned. For example, a trapped area can be a threshold, under a sofa, under a bed, or a narrow area formed between multiple pieces of furniture.

[0059] In this step, when a user needs the cleaning robot 100 to clean the floor area of ​​their home, they can send a cleaning command to the cleaning robot 100 via a mobile phone or other terminal device. The terminal device can store an environmental map of the user's home floor layout. The user can use this environmental map to specify the area to be cleaned by the cleaning robot 100, and can also specify the cleaning time at which the cleaning robot 100 should begin cleaning the area. For example, the cleaning time can be immediately upon receiving the cleaning command, or it can be a fixed time interval.

[0060] After receiving an instruction, the control module 1 of the cleaning robot 100 can parse the cleaning instruction to obtain the cleaning time and the area to be cleaned. Then, when the set cleaning time is reached, the cleaning robot 100 can clean the area to be cleaned by moving forward. While cleaning the area to be cleaned, the control module 1 monitors in real time whether the cleaning robot 100 enters a trapped area. If it detects that the cleaning robot 100 has entered a trapped area and is trapped, in order to continue cleaning the area to be cleaned, the control module 1 will control the cleaning robot 100 to perform a specific combination of movements to escape the trapped area. When the control module 1 detects that the cleaning robot 100 has successfully escaped from the trapped area, it can mark the trapped area as a target cleaned area. After successful marking, the cleaning robot 100 can continue to execute the subsequent cleaning logic.

[0061] Step S220: Generate a first cleaning path in the remaining cleaning area.

[0062] The remaining cleaning area refers to the remaining cleaning area in the area to be cleaned, excluding the already cleaned area; the cleaned area includes the target cleaned area and the historically cleaned area, or the cleaned area only includes the historically cleaned area but not the target cleaned area, and the historically cleaned area is the area already cleaned by the cleaning robot 100.

[0063] In this step, after marking the trapped area as a target cleaned area, the control module 1 can generate a first cleaning path in the remaining cleaned area. Specifically, the cleaning robot 100 can generate a first cleaning path based on whether the trapped area is a planable or unplanable area.

[0064] ① The trapped area is designated as an unplannable area. The cleaning robot 100 then generates a first cleaning path within the remaining clean area after removing previously cleaned areas and the trapped area from the area to be cleaned. In other words, the cleaned area at this point includes both the target cleaned area and previously cleaned areas. The unplannable area refers to the area where path planning is impossible.

[0065] For example, as shown in Figures 4 and 5, the rectangular area represents the area to be cleaned, the gray area represents the previously cleaned area (i.e., the area already cleaned by the cleaning robot 100), the triangular arrow indicates the current position of the cleaning robot 100, and the direction of the apex of the triangular arrow represents the forward direction of the cleaning robot 100. The circular area represents the trapped area. In Figure 4, the area to be cleaned contains only one cleaning area, while in Figure 5, the area to be cleaned contains two cleaning sub-areas, namely area 1 and area 2. When the control module 1 detects that the cleaning robot 100 has successfully escaped from the circular area (the trapped area) in the figure, the control module 1 marks the trapped area as the target cleaned area. After successful marking, the control module 1 can generate a first cleaning path in the area of ​​the rectangular area excluding the gray area and the circular area. Specifically, the straight lines marked with numbers 1, 2, 3, 4, 5, and 6 in the figure represent the first cleaning path planned by the control module 1.

[0066] By implementing the above measures, the trapped area is designated as an unplanned zone. This effectively prevents the cleaning robot 100 from re-entering the trapped area while cleaning the remaining areas according to the first cleaning path, thus improving the cleaning efficiency of the robot 100. It also prevents damage to the robot itself and avoids any disruption to the user's home. Furthermore, this method eliminates the need for restricted areas, simplifies implementation, and the robot 100 only needs to follow the generated first cleaning path to avoid re-entering the trapped area. It eliminates the need for multiple state switching, reducing the likelihood of errors, improving cleaning efficiency, simplifying the cleaning logic of the robot 100, enhancing cleaning robustness, and improving the user experience.

[0067] ② The trapped area is designated as a plannable area, allowing the cleaning robot 100 to generate a first cleaning path within the remaining clean area after removing previously cleaned areas from the area to be cleaned. In other words, the cleaned area at this point only includes previously cleaned areas but not the target cleaned area. Here, the plannable area refers to the area where path planning is possible.

[0068] For example, as shown in Figure 6, the rectangular area represents the area to be cleaned, which contains two sub-areas, area 1 and area 2. The circular rectangular area represents the trapped area, connecting area 1 and area 2. To perform cross-area cleaning between area 1 and area 2, the cleaning robot 100 must pass through the circular rectangular area. Specifically, the circular rectangular area can be a threshold. The gray area represents the historically cleaned area, i.e., the area already cleaned by the cleaning robot 100. When the cleaning robot 100 is cleaning area 1, it may get trapped within the circular rectangular area. When trapped, the control module 1 controls the cleaning robot 100 to perform an escape movement. After successful escape, the control module 1 marks the circular rectangular area as the target cleaned area. After successful marking, since the cleaning robot 100 still needs to perform cross-area cleaning in area 2, the cleaning robot 100 will then treat the circular rectangular area as a plannable area and generate a first cleaning path in the area of ​​the rectangular area excluding the gray area. By employing the aforementioned path planning method, it is ensured that when the cleaning robot 100 travels along the planned path, it can traverse the blocked area after cleaning area 1 and enter area 2 to continue cleaning, thus fully guaranteeing that the cleaning robot 100 can complete cross-area cleaning. Specifically, while traveling along the planned path, the cleaning robot 100 can use obstacle-avoidance maneuvers to escape the blocked area and then enter area 2 to continue cleaning.

[0069] Through the above measures, when the trapped area is used to connect two adjacent cleaning sub-areas, the trapped area is treated as a planable area, which effectively ensures that the cleaning robot 100 can plan a cleaning path that can achieve cross-area cleaning, fully guaranteeing that the cleaning robot 100 can perform cross-area cleaning and greatly improving the cleaning effect of the cleaning robot 100.

[0070] Step S230: Control the cleaning robot 100 to move along the first cleaning path and clean the remaining cleaning area.

[0071] In this step, after the cleaning robot 100 plans the first cleaning path, the cleaning robot 100 can be controlled to move along the first cleaning path and clean the remaining cleaning area.

[0072] In existing technologies, as shown in Figures 7 and 8, after the cleaning robot 100 successfully escapes from black rectangular areas 1 and 2, it sets these areas as restricted zones to prevent the robot from re-entering the restricted areas. However, this method requires the cleaning robot 100 to switch states multiple times during cleaning. When cleaning areas far from the restricted zones, it switches to a bow-sweeping state; when moving to areas around the restricted zones, it switches back to the edge-of-restriction state; and so on, making the process very complex. If there are multiple restricted zones near the cleaning robot 100, the number of state switches increases exponentially. Furthermore, tracking more restricted zones further complicates the implementation and increases the risk of errors. For example, as shown in Figures 7 and 8, if the cleaning robot 100 encounters restricted zone 1 while avoiding restricted zone 2, multiple restricted zone switching issues arise, making the situation extremely complex. However, by using the method described in this application, the trapped area is directly marked as the target cleaned area, and the target cleaned area is designated as an unplanned area. This fully ensures that the cleaning robot 100 will not plan its path in the trapped area, thus preventing it from re-entering the trapped area when following the planned path. The implementation is simple, requires no multiple state switching, is less prone to errors, improves cleaning efficiency, and enhances the user experience.

[0073] Furthermore, as shown in Figure 6, the trapped area connects two adjacent cleaning sub-areas. By setting a restricted area, the cleaning robot 100 will not enter the restricted area. This prevents the cleaning robot 100 from planning a reasonable path to enter area 2 after cleaning area 1, causing it to become trapped in area 1 and unable to complete the remaining cleaning tasks, greatly reducing its cleaning efficiency. However, this application considers that the cleaning robot 100 can actively escape the trapped area through some special movement patterns when trapped. Therefore, the trapped area is treated as a planarable area, allowing the cleaning robot 100 to plan its path within the trapped area. This ensures that the cleaning robot 100 can plan a path that allows for cross-area cleaning, fully guaranteeing its ability to perform cross-area cleaning and greatly improving its cleaning efficiency.

[0074] In one embodiment, the control module 1 can determine whether the trapped area is a planable or unplanable area in the following way:

[0075] Based on the cleaning environment of the cleaning robot 100, the trapped area is determined to be either a plannable or unplannable area. As shown in Figures 4 and 5, if the area to be cleaned contains only one cleaning area, or if the area to be cleaned contains multiple cleaning sub-areas but the trapped area is not used to connect two adjacent cleaning sub-areas, the trapped area is considered an unplannable area. As shown in Figure 6, if the area to be cleaned contains multiple cleaning sub-areas, and the trapped area is used to connect two adjacent cleaning sub-areas, the trapped area is considered a plannable area.

[0076] In another embodiment, when the cleaning robot 100 cleans the area to be cleaned, the following steps are also performed: when the cleaning robot 100 performs path planning, if the target cleaned area is within the planned unique path range, the cleaning robot 100 is controlled to pass through the target cleaned area.

[0077] The unique path range refers to the fact that all planned paths pass through the target cleaned area. Path planning can be real-time path planning, that is, planning the path while controlling the cleaning robot 100 to move according to the planned path. Alternatively, path planning can involve first planning the entire travel path, and then controlling the cleaning robot 100 to move according to the planned path.

[0078] In this embodiment, path planning is required when the cleaning robot 100 performs actions such as returning to the base station, moving away from the base station, and cleaning.

[0079] On the one hand, when the cleaning robot 100 needs to return to or move away from the base station, it needs to plan a path to complete the corresponding task of returning to or moving away from the base station. Therefore, in this embodiment, when the cleaning robot 100 needs to return to or move away from the base station, the control module 1 performs path planning. If, after path planning, it is found that all planned paths must pass through the target cleaned area, then the target cleaned area is designated as a plannable area, allowing the generation of a path within it. This enables the cleaning robot 100 to traverse the target cleaned area and complete the task of returning to or moving away from the base station while following the planned path.

[0080] On the other hand, when the cleaning robot 100 performs cleaning movements, the control module 1 first generates a corresponding travel path. Then, after generation, it determines whether the generated travel path passes through the target cleaned area. If the cleaning path passes through the target cleaned area, the trapped area is designated as a plannable area, allowing the generation of a first cleaning path within the target cleaned area. This enables the cleaning robot 100 to traverse the target cleaned area and complete cross-area cleaning tasks while traveling along the first cleaning path. It is worth noting that this embodiment and the determination of whether the trapped area is a plannable or unplannable area mentioned in the previous embodiments are two parallel embodiments; the first cleaning path can be the aforementioned travel path, or it can be a newly planned cleaning path by the cleaning robot 100 after determining that the trapped area is a plannable area.

[0081] In existing technologies, if a restricted area is located on the path of the cleaning robot 100 returning to the base station, the cleaning robot 100 will not enter the restricted area, preventing it from returning to the base station. This can easily lead to battery depletion and threaten the robot's safety. However, using the method described in this application, when the trapped area is located on the path of the cleaning robot 100 returning to the base station, the cleaning robot 100 is allowed to pass through the trapped area to return to the base station, effectively preventing the cleaning robot 100 from running out of power and ensuring its safety.

[0082] In one embodiment, when the control module 1 performs the above step S210 and controls the cleaning robot 100 to move and clean in the area to be cleaned, it can control the cleaning robot 100 to perform an escape movement when it detects that the cleaning robot 100 is stuck. At the same time, during the escape movement, the control module 1 can determine whether the cleaning robot 100 has successfully escaped based on the sensing data sent by the sensor.

[0083] In this embodiment, the cleaning robot 100 is equipped with sensors that can send sensing data to the control module 1. Based on the sensing data, the control module 1 can determine whether the cleaning robot 100 is trapped and whether it has successfully escaped. The sensing data reflects the positional state of the cleaning robot 100.

[0084] In one embodiment, the cleaning robot 100 is equipped with multiple sensors. After receiving sensing data from the multiple sensors, the cleaning robot 100 can fuse the sensing data and then determine whether the cleaning robot 100 has successfully escaped the obstacle based on the target data obtained after fusion. The target data reflects the positional state of the cleaning robot 100.

[0085] In existing technologies, cleaning robots 100 are typically equipped with sensors such as odometers, gyroscopes, accelerometers, impact sensors, lidar, cameras, and Time-of-Flight (ToF) sensors. However, these sensors are installed at different locations, angles, and heights, and their effective range, measurement methods, and final performance also vary. Furthermore, manufacturing costs limit the measurement accuracy and number of sensors, making it difficult to characterize the state of the cleaning robot 100 using data from a single sensor, even in the same scenario. Therefore, in this embodiment, sensor data from multiple sensors is fused to obtain sensor data that accurately reflects the state of the cleaning robot 100. This ensures that the robot's pose can be accurately determined based on the sensor data, improving the accuracy of the determination.

[0086] In one embodiment, before executing step S210 to mark the trapped area as the target cleaned area, the control module 1 can further determine the trapped area based on the first position information of the cleaning robot 100 when it is trapped and the second position information of the cleaning robot 100 when it successfully escapes the trap. Specifically, the trapped area can be the geometric region enclosed by the first and second position information as diagonal points. For example, the geometric region can be a rectangle, rhombus, or parallelogram, etc.

[0087] As shown in Figures 9, 10 and 11, the triangular arrow indicates the position information of the cleaning robot 100 when it successfully escapes the trap, i.e., the second position information. The circular area indicates the position information of the cleaning robot 100 when it is trapped, i.e., the first position information. At this time, the rectangular area enclosed by the first position information and the second position information as the diagonal points is taken as the trapped area.

[0088] Through the above measures, since the cleaning robot 100 also performs cleaning work during the escape movement, in this embodiment, the geometric area enclosed by the trapped position and the escape position of the cleaning robot 100 is marked as the target cleaned area. This avoids the cleaning robot 100 from entering the trapped area twice and avoids the cleaning robot 100 from cleaning the same area repeatedly, thereby improving the cleaning efficiency of the cleaning robot 100.

[0089] In one embodiment, when the control module 1 performs step S220 to generate a first cleaning path in the remaining cleaning area, it can generate the first cleaning path based on the second cleaning path. The second cleaning path is the original path taken by the cleaning robot 100 before it became trapped. The original path refers to the cleaning path planned by the cleaning robot 100 before it began cleaning the area to be cleaned. The cleaning robot 100 then follows this path during actual cleaning.

[0090] The above measures allow for the direct generation of the first cleaning path based on the second cleaning path, a simple process.

[0091] The following explains in detail the principle of generating the first cleaning path based on the second cleaning path:

[0092] ① When the cleaned area includes both the target cleaned area and the historically cleaned area, the second cleaning path can be adjusted and used as the first cleaning path. Specifically, the first cleaning path can be generated by deleting the portion of the second cleaning path that is covered by the target cleaned area.

[0093] For example, as shown in Figures 9, 10, and 11, the largest rectangular area is the area to be cleaned, the gray area is the area already cleaned by the cleaning robot 100 (i.e., the historically cleaned area), and the gray rectangular area is the trapped area. When the cleaning robot 100 moves to the trapped area, the second cleaning path is the original path planned by the cleaning robot 100 before starting to clean the area to be cleaned. When the cleaning robot 100 is trapped, the original path of the historically cleaned area has already been completed, so the second cleaning path does not include the original path of the historically cleaned area. In this case, the part of the second cleaning path covered by the target cleaned area can be directly deleted, and the deleted second cleaning path can be used as the first cleaning path. As shown in Figures 9, 10, and 11, regardless of which direction the cleaning robot 100 moves to escape, generating the first cleaning path in this way can effectively prevent the cleaning robot 100 from entering the trapped area a second time.

[0094] ② When the cleaned area only includes historically cleaned areas but not the target cleaned area, the second cleaned area is used as the first cleaning path.

[0095] For example, as shown in Figure 6, before cleaning multiple sub-areas, the cleaning robot 100 plans an initial travel path. The robot then follows this initial path to clean the areas to be cleaned. If the cleaning robot 100 becomes stuck, and the initial travel path for the previously cleaned area has already been completed, then the second cleaning path does not include that portion. In this case, the cleaning robot 100 can directly use the second cleaning path as the first cleaning path.

[0096] It is worth noting that in this embodiment, when the cleaning robot 100 initially plans its path to the area to be cleaned, it does not know that it will be trapped in the rectangular area shown in Figure 6. Therefore, it treats the rectangular area as a plannable area and plans the corresponding original cleaning path. This ensures that when the cleaning robot 100 uses the second cleaning path as the first cleaning path and performs cleaning operations according to the first cleaning path, it will definitely be able to complete cross-area cleaning.

[0097] The apparatuses and methods disclosed in the several embodiments provided in this application can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatuses, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0098] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0099] If a function is implemented as a software module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

Claims

1. A cleaning control method for a cleaning robot, characterized in that, include: The cleaning robot is controlled to move and clean within the area to be cleaned. During its movement, if the cleaning robot successfully escapes from a trapped area, the trapped area is marked as a target cleaned area. In the remaining cleaning area, a first cleaning path is generated. The cleaning robot is then controlled to move along the first cleaning path to clean the remaining cleaning area. The remaining cleaning area refers to the area remaining in the area to be cleaned, excluding the already cleaned areas. The cleaned areas include the target cleaned area and historically cleaned areas, or the cleaned areas include the historically cleaned areas, which are areas already cleaned by the cleaning robot. In the remaining cleaning area, a first cleaning path is generated. A cleaning path includes: when the cleaned area includes the target cleaned area and the historical cleaned area, deleting the portion of the second cleaning path covered by the target cleaned area, and using the deleted second cleaning path as the first cleaning path; when the cleaned area includes the historical cleaned area, using the second cleaning path as the first cleaning path; wherein the second cleaning path is the original travel path of the cleaning robot before it gets stuck; or, when the cleaning robot performs path planning, if the target cleaned area is within the planned unique path range, controlling the cleaning robot to pass through the target cleaned area.

2. The cleaning control method for the cleaning robot according to claim 1, characterized in that, The cleaning robot is equipped with sensors; the method further includes: when the cleaning robot is detected to be trapped, controlling the cleaning robot to perform an escape movement; during the escape movement, determining whether the cleaning robot has successfully escaped based on the sensor data sent by the sensors.

3. The cleaning control method for the cleaning robot according to claim 2, characterized in that, The sensor is provided in multiple parts; the step of determining whether the cleaning robot has successfully escaped the obstacle based on the sensing data sent by the sensor includes: fusing the sensing data sent by multiple sensors to obtain target data reflecting the status of the cleaning robot; and determining whether the cleaning robot has successfully escaped the obstacle based on the target data.

4. The cleaning control method for the cleaning robot according to claim 1, characterized in that, Before marking the trapped area as a target cleaned area, the process includes: determining the trapped area based on first location information when the cleaning robot is trapped and second location information when the cleaning robot successfully escapes the trap.

5. The cleaning control method for a cleaning robot according to claim 4, characterized in that, Determining the trapped area includes: defining the geometric region enclosed by the first location information and the second location information as diagonal points as the trapped area.

6. The cleaning control method for a cleaning robot according to claim 1, characterized in that, When the area to be cleaned includes multiple sub-areas, and the target cleaned area connects two adjacent sub-areas, the cleaned area includes the historically cleaned area.

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