Control method, apparatus, medium, and self-propelled device for a self-propelled device

Abstract

This disclosure provides a control method, apparatus, medium and self-propelled device for a self-propelled device, the method comprising: receiving a command from a user to set a cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters; determining a corresponding collision probability and / or cleaning miss probability based on the setting command; and performing cleaning of a target area based on the collision probability and / or cleaning miss probability.

Description

Technical Field

[0001] (Related Application) This application claims the priority of Chinese Patent Application No. 202311102977.X filed on August 29, 2023, and all the disclosure contents of the above Chinese patent application are incorporated herein by reference as part of this disclosure.

[0002] This application relates to the technical field of self-propelled devices, specifically, to a control method, apparatus, medium, and self-propelled device of a self-propelled device.

Background Art

[0003] With the development of self-propelled device technology, self-propelled devices are widely used in people's daily lives. However, current self-propelled devices usually execute cleaning operations according to a preset fixed program, so they cannot meet the diverse needs of users, such as the need for users to quickly and easily clean a room.

Summary of the Invention

[0004] Embodiments of this application provide a control method, apparatus, medium, and self-propelled device of a self-propelled device to overcome or at least partially overcome the drawbacks of the prior art in view of the above situation.

[0005] As a first aspect, this application provides a control method of a self-propelled device, receiving a command from a user to set a cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters through a front-end application; determining a corresponding collision probability and / or cleaning omission probability based on the setting command; and performing cleaning of a target area based on the collision probability and / or the cleaning omission probability.

[0006] Selectively, in the above method, the cleaning obstacle avoidance parameter includes at least one of a wall-side collision level parameter, an obstacle avoidance collision level parameter, and an obstacle-dense area collision level parameter.

[0007] In the above method, the wall-side collision level parameter may be selected to include a wall-edge collision level parameter and a wall-front collision level parameter.

[0008] Selectively, in the above method, the cleaning obstacle avoidance mode includes an obstacle avoidance cautious mode and an obstacle avoidance mitigation mode, wherein the obstacle avoidance cautious mode corresponds to a lower collision probability and / or a higher cleaning failure probability compared to the obstacle avoidance mitigation mode. Selectively, in the above method, the obstacle avoidance caution mode and the obstacle avoidance mitigation mode each include multiple levels of obstacle avoidance.

[0009] Optionally, the above method includes the step of performing cleaning of the target area based on the collision probability and / or the cleaning failure probability, which includes: Based on the collision probability and / or the cleaning failure probability, a corresponding cleaning parameter is determined, the cleaning parameter including at least one of the distance along the wall, the degree of turning along the wall, the forward distance along the wall, and the distance from the wall after turning, where a lower collision probability and / or a higher cleaning failure probability corresponds to a longer distance along the wall, a greater degree of turning, a longer forward distance along the wall, and a longer distance from the wall after turning. The target area is cleaned based on the cleaning parameters.

[0010] Optionally, the above method includes the step of performing cleaning of the target area based on the collision probability and / or the cleaning failure probability, which includes: Based on the collision probability and / or the cleaning failure probability, a corresponding cleaning parameter is determined, the cleaning parameter including at least one of the obstacle avoidance range and the number of obstacle avoidance range point clouds, where a lower collision probability and / or a higher cleaning failure probability corresponds to a larger obstacle avoidance range and a smaller number of obstacle avoidance range point clouds. The target area is cleaned based on the cleaning parameters.

[0011] Optionally, the above method includes the step of performing cleaning of the target area based on the collision probability and / or the cleaning failure probability, which includes: Based on the collision probability and / or the cleaning failure probability, a corresponding cleaning parameter is determined, the cleaning parameter comprising at least one of the following: the number of points in the dense area, the size of the accessible space, the priority for crossing the dense area, and the cleaning coverage of the dense area, where a lower collision probability and / or a higher cleaning failure probability corresponds to a smaller number of points in the dense area, a larger size of the accessible space, a lower priority for crossing the dense area, and a smaller cleaning coverage of the dense area. The target area is cleaned based on the cleaning parameters.

[0012] The method can be selected as follows: The further steps include intelligently identifying the current scene of a target area, matching corresponding cleaning parameters based on the scene identification result in combination with the collision probability and / or the cleaning omission probability, and performing cleaning of the target area.

[0013] The method can be selected as follows: The process involves receiving a command from a user to specify a target area based on a pre-built map, and The system further includes at least one of the following steps: determining by intelligent identification whether the self-propelled device has entered the target area, and if so, deciding to perform a step of cleaning the target area based on the collision probability and / or the cleaning failure probability.

[0014] The method can be selected as follows: The steps include reading the history cleanup logs for at least a portion of the target area, The further step includes automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters based on the aforementioned cleaning history log.

[0015] Selectively, the above method includes the step of automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters based on the history cleaning log, If it is determined that the number of collisions with any obstacle is greater than a predetermined first threshold based on the history cleaning log, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are adjusted to achieve a lower collision probability.

[0016] The method can be selected as follows: If the current collision probability is less than a preset second threshold, the step of adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters is further included.

[0017] Secondly, the embodiments of this application provide a control device for a self-propelled device, the device is A receiving unit used to receive commands from the user to set the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters via a front-end application, A probability determination unit used to determine the corresponding collision probability and / or cleaning failure probability based on the setting command, The system comprises an execution unit used to perform cleaning of a target area based on the collision probability and / or the cleaning omission probability.

[0018] As a third aspect, the embodiments of this application further provide a method for controlling a self-propelled device. The steps include reading a history cleaning log generated by a self-propelled device cleaning at least a portion of the target area, Based on the history cleaning log, automatically adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device, where the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are default or determined based on a user's setting command, and include the step of

[0019] Optionally, in the above method, the step of automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device based on the history cleaning log is Based on the history cleaning log, when it is determined that the number of collisions with any obstacle is greater than a predetermined first threshold, adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters so as to achieve a lower collision probability, and include

[0020] Optionally, the method is When the current collision probability is less than a preset second threshold, further include the step of not executing the step of adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device.

[0021] As a fourth aspect, the embodiment of the present application further provides a control device for a self-propelled device, and the device is A reading unit used to read the history cleaning log generated when the self-propelled device cleans at least a part of the target area; Based on the history cleaning log, it is used to automatically adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device, where the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are default or determined based on a user's setting command, and include an adjustment unit.

[0022] As a fifth aspect, embodiments of the present application further provide a computer-readable storage medium in which computer program instructions are stored, and the computer program instructions are loaded and executed by a processor to realize operations performed by the method described above.

[0023] As a sixth aspect, embodiments of the present application further provide a self-propelled device comprising a processor and memory, wherein the memory stores computer program instructions that can be executed by the processor, and the above method is realized when the processor executes the computer program instructions. [Effects of the Invention]

[0024] The at least one technical solution employed in the embodiments of this application has the following beneficial effects.

[0025] This application supports users setting cleaning obstacle avoidance modes and / or cleaning obstacle avoidance parameters for self-driving devices in a front-end application, determines collision probabilities and / or cleaning omission probabilities corresponding to the user-set cleaning obstacle avoidance modes and / or cleaning obstacle avoidance parameters, and performs cleaning of target areas based on these collision probabilities and / or cleaning omission probabilities, thereby meeting the diverse individualization and differentiation needs of users, precisely meeting the user's need to avoid collisions as much as possible in specific areas and avoid cleaning omissions as much as possible in specific areas, and while ensuring cleaning quality, it significantly saves cleaning time, improves the utilization rate of self-driving devices, and the algorithm is simple and highly practical.

[0026] The accompanying drawings described herein are used to further understand this application and constitute part of this application, and the exemplary embodiments and descriptions herein are used to interpret this application and do not constitute an unreasonable limitation of this application. In the accompanying drawings, [Brief explanation of the drawing]

[0027] [Figure 1]A schematic flowchart illustrating a control method for a self-propelled device according to the first embodiment of this application. [Figure 2] A schematic flowchart illustrating a control method for a self-propelled device according to a second embodiment of this application. [Figure 3] Schematic diagram showing a control device for a self-propelled device according to the third embodiment of this application. [Figure 4] Schematic diagram showing a control device for a self-propelled device according to the fourth embodiment of this application. [Modes for carrying out the invention]

[0028] To further clarify the purpose, technical solution, and merits of this application, the technical solution of this application will be clearly and completely described below with reference to specific embodiments of this application and the corresponding accompanying drawings. Clearly, the embodiments described are only a selection of embodiments of this application, not all embodiments. Any other embodiments that can be obtained by a person skilled in the art without creative work based on the embodiments of this application are all included within the scope of protection of this application.

[0029] The technical solutions provided by each embodiment of this application will be described in detail below with reference to the attached drawings.

[0030] Self-propelled devices, also known as automatic vacuum cleaners, cleaning robots, smart vacuum cleaners, cleaning vacuums, or vacuum cleaners, are a type of smart home appliance that relies on a certain level of artificial intelligence to automatically complete floor cleaning tasks within a room. Self-propelled devices generally employ a brush cleaning and vacuuming method, first sucking up debris from the ground into their own dustbin to complete the floor cleaning function. Generally, vacuum cleaners that complete cleaning, dusting, and floor wiping tasks can also be collectively categorized as self-propelled devices.

[0031] In conventional technology, after a user activates a self-propelled device, the device cleans the target area according to a pre-set strategy. However, this pre-set strategy is usually immutable, which fails to meet some differentiated user needs, such as wanting to easily clean a clean room. The self-propelled device still cleans according to a default mode, which typically requires a relatively large amount of time and effort.

[0032] Based on the aforementioned shortcomings of existing self-propelled devices, this application proposes the following concept: the front-end application of the self-propelled device displays configurable options for cleaning obstacle avoidance modes and / or cleaning obstacle avoidance parameters; the front-end application supports the user in setting the cleaning obstacle avoidance modes and / or cleaning obstacle avoidance parameters of the self-propelled device; the collision probability and / or cleaning failure probability corresponding to the cleaning obstacle avoidance modes and / or cleaning obstacle avoidance parameters set by the user are determined; and cleaning of the target area is performed based on this collision probability and / or cleaning failure probability, thereby meeting the diverse individualization and differentiation needs of the user.

[0033] Figure 1 is a schematic flowchart showing a control method for a self-propelled device according to the first embodiment of this application, and as can be seen from Figure 1, the first embodiment includes at least steps S110 to S130: Step S110: The system receives a command from the user to set the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters.

[0034] In some embodiments, the self-propelled device itself has a display screen, virtual buttons, or physical buttons, and on the display screen, the self-propelled device displays selection items for the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters, allowing the user to set them, or adopt the default mode if the user does not set them.

[0035] In some other embodiments, the self-driving device is a smart device, typically connected to a front-end application in a communicative manner, allowing the user to control the self-driving device via the front-end application, i.e., the front-end application displays and allows the user to configure selections for the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters.

[0036] This application provides various configurations, for example, in some embodiments, several control parameters are abstracted into different cleaning obstacle avoidance modes, and the self-propelled device cleans a target area in a mode simply by the user setting a specific level of cleaning obstacle avoidance mode. For example, in some embodiments, the cleaning obstacle avoidance modes include, but are not limited to, an obstacle avoidance caution mode and an obstacle avoidance mitigation mode, and more levels of other cleaning obstacle avoidance modes may be set as needed, and this application is not limited thereto.

[0037] In some other embodiments, the cleaning obstacle avoidance parameter can be directly displayed, and the cleaning obstacle avoidance parameter includes, but is not limited to, at least one of the following: wall-side collision level parameter, obstacle avoidance collision level parameter, and obstacle-crowded area collision level parameter, wherein the wall-side collision level parameter includes wall edge collision level parameter and wall front collision level parameter. Here, the wall-side collision level parameter represents the magnitude of the probability that the self-propelled device will collide during the wall-side process, mainly referring to the possibility of collision with wall edges and the possibility of collision with the front wall. The obstacle avoidance collision level parameter represents the possibility of collision with low obstacles, such as shoes, slippers, weighing scales, etc. The obstacle-crowded area collision level parameter represents the possibility of collision with areas where desks and chairs are densely packed, sofas and tables, etc.

[0038] In some embodiments, to facilitate user operation, all cleaning obstacle avoidance parameters can be set in level format, allowing the user to simply specify a particular level without having to enter specific parameters. Each of the wall-side collision level parameters, obstacle avoidance collision level parameters, and obstacle-dense area collision level parameters can be set to multiple levels, thereby meeting different user needs.

[0039] Compared to the one-touch mode setting method, this method is slightly more complicated, but it is suitable for some special scenarios. For example, in a target area where the area along the wall is relatively dirty and the intermediate wide area is relatively clean, setting the wall-side collision level parameter relatively strictly and the obstacle avoidance collision level parameter point cloud relatively lenient allows the self-propelled device to spend more time cleaning along the wall and reduce the obstacle avoidance requirement in the intermediate wide area, resulting in easier cleaning.

[0040] In some other embodiments, cleaning obstacle avoidance modes and cleaning obstacle avoidance parameters can be combined. For example, this allows users to set different levels of cleaning obstacle avoidance modes, as well as set several parameters for a single set cleaning obstacle avoidance mode, thereby meeting differentiated user needs and making user operation more convenient. For instance, a user can set a tolerable obstacle density collision level parameter in an obstacle avoidance caution mode. This allows for thorough cleaning of large areas while ignoring narrow spaces between multiple obstacles, saving cleaning time and improving cleaning efficiency. Furthermore, the simultaneous setting of modes and parameters makes user operation very convenient.

[0041] Step S120: Based on the setting command, the corresponding collision probability and / or cleaning failure probability is determined.

[0042] The actual meaning of the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters can be understood as the probability of actually colliding with an obstacle during the operation of the self-propelled device desired by the user, and the probability of missing an obstacle in a confined space, which will be denoted as collision probability and cleaning miss probability, respectively.

[0043] A certain correspondence has been established in advance between the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters and the collision probability and / or cleaning failure probability. This correspondence can be understood as a simple mapping relationship, meaning that a certain cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters correspond to a certain collision probability or cleaning failure probability, or both. In practice, taking the cleaning obstacle avoidance mode as an example, the parameter values ​​of several parameters of the cleaning obstacle avoidance mode are converted into collision probability and / or cleaning failure probability according to a certain algorithm.

[0044] After the user sets the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters, the corresponding collision probability and / or cleaning failure probability can be determined based on the mapping relationship.

[0045] Therefore, by setting different levels of cleaning obstacle avoidance modes and / or cleaning obstacle avoidance parameters, different degrees of collision probability and / or cleaning miss probability can be achieved. As described above, if the cleaning obstacle avoidance modes are configured to include a cautious obstacle avoidance mode and a mitigated obstacle avoidance mode, the cautious obstacle avoidance mode can be configured to correspond to a lower collision probability and a higher cleaning miss probability compared to the mitigated obstacle avoidance mode, and both the cautious and mitigated obstacle avoidance modes can be configured to set multiple levels of obstacle avoidance, for example, 1-10 levels of obstacle avoidance, with higher levels corresponding to lower collision probabilities and / or higher cleaning miss probabilities. The user can select a level that is either the cautious or mitigated obstacle avoidance mode.

[0046] Step S130: Clean the target area based on the collision probability and / or the cleaning omission probability.

[0047] A certain probability of collision and / or probability of missed cleaning corresponds to a certain cleaning strategy, which refers to how the self-propelled device handles obstacles such as wall corners and sofas when it encounters them. The cleaning strategy usually appears in the form of parameters.

[0048] Specifically, in some embodiments of the present application, the step of performing cleaning of a target area based on the collision probability and / or the cleaning miss probability includes: determining corresponding cleaning parameters based on the collision probability and the cleaning miss probability, wherein the cleaning parameters include at least one of wall-side distance, wall-side turning degree, wall-side forward distance, and distance from the wall after turning, wherein a lower collision probability and / or a higher cleaning miss probability corresponds to a longer wall-side distance, a greater turning degree, a longer wall-side forward distance, and a longer distance from the wall after turning, and cleaning the target area based on the cleaning parameters.

[0049] The cleaning parameters include, but are not limited to, at least one of the following: wall-side distance, wall-side turning degree, wall-side forward travel distance, and distance from the wall after turning. These parameters are primarily relevant when the self-propelled device moves along a wall. Here, wall-side distance can be understood as the distance from the wall surface held by the self-propelled device during the wall-side process using wall-side sensors. Wall-side turning degree can be understood as the degree of turning by the self-propelled device during the wall-side process. Wall-side forward travel distance can be understood as the distance advanced after turning. Distance from the wall after turning can be understood as the distance from the opposing wall surface after turning.

[0050] When setting up a cleaning strategy, lower collision probabilities and higher cleaning miss probabilities correspond to longer wall-side distances, greater turning angles, longer wall-side forward travel distances, and longer distances from the wall after turning. Lower collision probabilities and higher cleaning miss probabilities can be understood as being more stringent in minimizing collisions and more tolerant of missed cleaning in certain areas. Simply put, when setting collision levels during the wall-side process of an autonomous device, lower collision probabilities correspond to longer wall-side distances, and at the same time, greater turning angles, longer forward travel distances, and greater distance from the opposing wall after turning.

[0051] For example, if the collision probability is 20% and the cleaning failure probability is 5%, and this is mapped to a distance along the wall of 0.7 cm, a turning degree along the wall of 2 cm, a forward distance along the wall of 1.5 cm, and a distance from the wall after turning of 1 cm, then the target area will be automatically cleaned according to these cleaning parameters. The above data is merely illustrative and does not limit this application in any way.

[0052] In some embodiments of this application, the step of performing cleaning of a target area based on the collision probability and / or the cleaning miss probability includes: determining a corresponding cleaning parameter based on the collision probability and / or the cleaning miss probability, the cleaning parameter comprising at least one of an obstacle avoidance range and an obstacle avoidance range point cloud number, where a lower collision probability and a higher cleaning miss probability correspond to a larger obstacle avoidance range and a smaller obstacle avoidance range point cloud number, and cleaning the target area based on the cleaning parameter.

[0053] In some embodiments, the cleaning parameters include, but are not limited to, the obstacle avoidance range and the number of points in the obstacle avoidance range, where the obstacle avoidance range can be understood as the obstacle avoidance range formed using LDS (Laser Distance Sensor) technology during the travel process of a self-propelled device. LDS is a laser distance sensor and is typically used in obstacle avoidance functions of devices such as robots and smart homes. The obstacle avoidance range of an LDS is largely related to its design parameters, and generally, LDS technology has a distance range of several meters to tens of meters in which it can detect and avoid obstacles ahead. The number of points in the obstacle avoidance range can be understood as the number of points in the collected obstacle avoidance range.

[0054] The fact that lower collision probabilities and higher cleaning failure probabilities correspond to larger obstacle avoidance ranges and fewer obstacle avoidance range point clouds means that for collision scenarios in obstacle avoidance for self-driving devices, the lower the collision probability, i.e., the stricter the low collision capability, the larger the LDS obstacle avoidance range, meaning that the further away obstacle avoidance is initiated, the fewer LDS points (point clouds) are required within the obstacle avoidance range.

[0055] Based on collision probability and / or cleaning omission probability, the obstacle avoidance range and the number of point clouds within the obstacle avoidance range are determined, and the target area is cleaned according to these cleaning parameters.

[0056] In some embodiments of this application, the step of performing cleaning of a target area based on the collision probability and / or the cleaning miss probability includes: determining corresponding cleaning parameters based on the collision probability and / or the cleaning miss probability, the cleaning parameters including at least one of the number of dense area points, the size of the accessible space, the priority of crossing the dense area, and the cleaning coverage of the dense area, where a lower collision probability and a higher cleaning miss probability correspond to a smaller number of dense area points, a larger size of the accessible space, a lower priority of crossing the dense area, and a smaller cleaning coverage of the dense area, and cleaning the target area based on the cleaning parameters.

[0057] In some embodiments, the cleaning parameters include at least one of the following: number of dense area point clouds, accessible space size, dense area crossing priority, and dense area cleaning coverage, which are set for cleaning of obstacle dense areas by a self-propelled device. Here, the number of dense area point clouds can be understood as the number of LDS points collected for one dense area, the accessible space size can be understood as the size of the narrow space between multiple obstacles that the self-propelled device can access, the dense area crossing priority indicates whether to cross the dense area preferentially, and the dense area cleaning coverage can be understood as the proportion of the total dense area that is cleaned.

[0058] A lower collision probability and a higher cleaning failure probability correspond to fewer point clouds in dense areas, a larger size of accessible space, a lower priority for crossing dense areas, and smaller cleaning coverage in dense areas. In other words, the stricter the low collision capability, the fewer points there are within the LDS obstacle avoidance range in dense areas, the larger the narrow space between multiple obstacles that the self-propelled device can enter, the less priority given to crossing dense areas, and the reduced cleaning coverage in dense areas.

[0059] Based on collision probability and / or cleaning omission probability, the number of points in the dense area, the size of the accessible space, the priority for crossing the dense area, and the cleaning coverage of the dense area are determined, and the target area is cleaned according to these cleaning parameters.

[0060] Furthermore, in some embodiments of the present application, the method further includes the steps of intelligently identifying the current scene of a target area, matching corresponding cleaning parameters based on the scene identification result in combination with the collision probability and / or the cleaning miss probability, and performing cleaning of the target area.

[0061] This application also supports the adoption of different cleaning strategies under different scenarios. For example, in the case of the cleaning obstacle avoidance mode, even with the same level of cleaning obstacle avoidance mode, the corresponding collision probability and cleaning failure probability values ​​will differ under different scenarios, thereby meeting the diverse needs of multiple scenarios. Please refer to Table 1:

[0062] [Table 1]

[0063] As can be seen from Table 1, in the same obstacle avoidance caution mode, under Scene 1 the set collision probability is a1% and the cleaning failure probability is b1%, while under Scene 2 the set collision probability is a2% and the cleaning failure probability is b2%. Therefore, when performing a cleaning task based on the collision probability and cleaning failure probability, different cleaning strategies can be matched from the different collision and cleaning failure probabilities to meet different scene needs.

[0064] In some embodiments of the present application, before performing cleaning of the target area based on the collision probability and / or the cleaning miss probability, the method further includes at least one of the steps of: receiving a command from a user to specify a target area based on a pre-built map; and determining by intelligent identification whether a self-driving device has entered the target area, and if so, deciding to perform the step of performing cleaning of the target area based on the collision probability and / or the cleaning miss probability.

[0065] In some embodiments of this application, the target area may be within the entire map or a portion of the map, and the original map is usually pre-constructed and pre-stored in the self-propelled device. The user can designate a region on a saved map as a target region and set the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters for the target region. The self-propelled device can identify its current location, and when it determines that it has entered the user-specified target region, it performs cleaning of the target region according to the collision probability and / or cleaning failure probability mapped based on the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters specified by the user.

[0066] In some embodiments of the present application, the method further includes the steps of reading at least a portion of the history cleaning logs in the target area, and automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters based on the history cleaning logs.

[0067] This application supports adaptive adjustment of the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters, specifically, the ability to automatically adjust them based on the cleaning history log of a self-propelled device.

[0068] Specifically, if it is determined, based on the history cleaning log, that the number of collisions with any obstacle is greater than a predetermined first threshold, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are adjusted to achieve a lower collision probability.

[0069] For example, if a self-driving device collides with a single obstacle in a target area multiple times within a historical time, and the number of collisions exceeds a certain threshold, e.g., 10 times, the obstacle avoidance mode and / or obstacle avoidance parameters are adjusted to a stricter level, i.e., the probability of collision is further reduced, thereby decreasing the likelihood of collisions with that obstacle in the area in the future.

[0070] In some embodiments of the present application, the method further includes the step of not performing the step of adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters if the current collision probability is less than a preset second threshold.

[0071] In other words, if the collision probability determined from the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters in a given area is less severe than a certain threshold, it means that the current collision mode is already significantly mitigated, and no adjustments are made to the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters.

[0072] As can be seen from the method shown in Figure 1, this application supports the user setting a cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters for a self-driving device in a front-end application, determining the corresponding collision probability and / or cleaning miss probability based on the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters set by the user, and performing cleaning of the target area based on the collision probability and / or cleaning miss probability. This meets the diverse individualization and differentiation needs of the user, precisely meeting the user's need to avoid collisions as much as possible in specific areas and avoid cleaning misses as much as possible in specific areas, and while guaranteeing cleaning quality, it significantly saves cleaning time, improves the utilization rate of the self-driving device, and the algorithm is simple and highly practical.

[0073] Figure 2 shows a schematic flowchart of a control method for a self-propelled device according to a second embodiment of this application, and as can be seen from Figure 2, this embodiment includes at least steps S210 to S220: Step S210: Read the history cleaning log generated by the self-propelled device after it has cleaned at least a portion of the target area.

[0074] As described above, this application provides a self-propelled device on which cleaning obstacle avoidance modes and / or cleaning obstacle avoidance parameters can be set. Specifically, in some embodiments, the self-propelled device itself has a display screen, virtual buttons, or physical buttons, and on the display screen, the self-propelled device can display selection items for cleaning obstacle avoidance modes and / or cleaning obstacle avoidance parameters, which the user can set. If the user does not set them, the default mode can be adopted. In some other embodiments, the self-propelled device is a smart device and is typically connected to a front-end application, which the user can control. That is, the front-end application can display selection items for cleaning obstacle avoidance modes and / or cleaning obstacle avoidance parameters, which the user can set.

[0075] This application provides various configurations, for example, in some embodiments, several control parameters are abstracted into different cleaning obstacle avoidance modes, and the user simply specifies a certain level of cleaning obstacle avoidance mode, and the self-propelled device cleans the target area under that mode. For example, in some embodiments, the cleaning obstacle avoidance modes include, but are not limited to, a cautious obstacle avoidance mode and a mitigated obstacle avoidance mode, and multiple levels of different cleaning obstacle avoidance modes may be set as needed, and this application is not limited thereto.

[0076] In some other embodiments, the cleaning obstacle avoidance parameter can be directly displayed, and the cleaning obstacle avoidance parameter includes, but is not limited to, at least one of the following: wall-side collision level parameter, obstacle avoidance collision level parameter, and obstacle-crowded area collision level parameter, wherein the wall-side collision level parameter includes wall edge collision level parameter and wall front collision level parameter. Here, the wall-side collision level parameter represents the magnitude of the collision probability of the self-propelled device during the wall-side process, mainly referring to the possibility of collision with wall edges and the possibility of collision with the front wall. The obstacle avoidance collision level parameter represents the possibility of collision with low obstacles such as shoes, slippers, and weighing scales. The obstacle-crowded area collision level parameter represents the possibility of collision with areas such as densely packed desks and chairs, sofas and tables, etc.

[0077] In some embodiments, to facilitate user operation, all cleaning obstacle avoidance parameters can be set in level format, requiring the user to simply specify a level without needing to enter specific parameters. Multiple levels can be set for each of the wall-side collision level parameters, obstacle avoidance collision level parameters, and obstacle-dense area collision level parameters to meet different user needs.

[0078] While this method is somewhat more cumbersome than the one-touch mode setting method, it is suitable for certain specific scenarios. For example, if in one target area the area along the wall is relatively dirty and the intermediate wide area is relatively clean, setting the wall-side collision level parameter relatively strictly and the obstacle avoidance collision level parameter point cloud relatively lenient allows the self-propelled device to spend more time cleaning along the wall, easing the obstacle avoidance requirement for the intermediate wide area and enabling easier cleaning.

[0079] In some other embodiments, cleaning obstacle avoidance modes and cleaning obstacle avoidance parameters can be combined. For example, it may be possible to not only allow the user to set different levels of cleaning obstacle avoidance modes, but also to set several parameters for a single set cleaning obstacle avoidance mode, thereby making user operation convenient while meeting the user's differentiation needs. For example, a user can set one tolerable obstacle density collision level parameter in an obstacle avoidance caution mode. This allows for thorough cleaning of large areas while ignoring narrow spaces between multiple obstacles, saving cleaning time and improving cleaning efficiency, and the simultaneous setting of modes and parameters makes user operation very convenient.

[0080] Step S220: Based on the history cleaning log, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device are automatically adjusted, where the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are either default or determined based on user setting commands.

[0081] This application supports not only the user manually adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters, but also the automatic adjustment of the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters. Specifically, it acquires a log generated by cleaning performed by a self-propelled device on a certain area within a historical time period, records it as a historical cleaning log, and then adaptively adjusts the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters based on this historical cleaning log.

[0082] Specifically, in some embodiments, the step of automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device based on the history cleaning log includes adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters to achieve a lower collision probability if it is determined, based on the history cleaning log, that the number of collisions with any obstacle is greater than a predetermined first threshold.

[0083] For example, if a self-driving device collides with a single obstacle in a target area multiple times within a historical time, and the number of collisions exceeds a certain threshold, for example, 10 times, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are adjusted to a stricter level, i.e., further reducing the probability of collisions and decreasing collisions with the obstacle in the area in the future.

[0084] In some other embodiments, the method further includes the step of not performing the step of adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device if the current collision probability is less than a preset second threshold.

[0085] In other words, if the collision probability determined from the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters in a given area is less severe than a certain threshold, it is explained that the current collision mode is already significantly mitigated, and no adjustments are made to the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters.

[0086] As can be seen from the method shown in Figure 2, this application supports the adaptive adjustment of the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of a self-propelled device, not only freeing the user from operation but also meeting the diverse individualization and differentiation needs of the user. It precisely meets the user's need to avoid collisions as much as possible in certain areas and avoid cleaning omissions as much as possible in certain areas, and while ensuring cleaning quality, it significantly reduces cleaning time and improves the utilization rate of the self-propelled device. The algorithm is simple and highly practical.

[0087] Figure 3 shows a schematic diagram of the control device for a self-propelled device according to the third embodiment of this application. As can be seen from Figure 3, the control device 200 for the self-propelled device is: A receiving unit 210 is used to receive commands from the user to set the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters via a front-end application, A probability determination unit 220 used to determine the corresponding collision probability and / or cleaning failure probability based on the setting command, Includes an execution unit 230 used to perform cleaning of a target area based on the collision probability and / or the cleaning omission probability.

[0088] In some embodiments of this application, the cleaning obstacle avoidance parameter in the apparatus includes at least one of a wall-side collision level parameter, an obstacle avoidance collision level parameter, and an obstacle-dense area collision level parameter.

[0089] In some embodiments of this application, the wall-side collision parameter in the apparatus includes a wall edge collision level parameter and a wall front collision level parameter.

[0090] In some embodiments of this application, the cleaning obstacle avoidance mode in the apparatus includes an obstacle avoidance caution mode and an obstacle avoidance mitigation mode, wherein the obstacle avoidance caution mode corresponds to a lower collision probability and a higher cleaning failure probability compared to the obstacle avoidance mitigation mode.

[0091] In some embodiments of this application, the above-described apparatus includes, each, a cautionary obstacle avoidance mode and a mitigation obstacle avoidance mode, each comprising multiple levels of obstacle avoidance.

[0092] In some embodiments of the present application, in the apparatus, the execution unit 230 is used to determine corresponding cleaning parameters based on the collision probability and / or the cleaning failure probability, wherein the cleaning parameters include at least one of the distance along the wall, the degree of turning along the wall, the forward distance along the wall, and the distance from the wall after turning, wherein a lower collision probability and a higher cleaning failure probability correspond to a longer distance along the wall, a greater degree of turning, a longer forward distance along the wall, and a longer distance from the wall after turning, and the target area is cleaned based on the cleaning parameters.

[0093] In some embodiments of this application, in the apparatus, the execution unit 230 determines corresponding cleaning parameters based on the collision probability and / or the cleaning failure probability, wherein the cleaning parameters include at least one of an obstacle avoidance range and an obstacle avoidance range point cloud number, where a lower collision probability and a higher cleaning failure probability correspond to a larger obstacle avoidance range and a smaller obstacle avoidance range point cloud number, and are used to clean the target area based on the cleaning parameters.

[0094] In some embodiments of this application, the execution unit 230 determines corresponding cleaning parameters based on the collision probability and / or the cleaning failure probability, wherein the cleaning parameters include at least one of the number of points in a dense area, the size of the accessible space, the priority of crossing the dense area, and the cleaning coverage of the dense area, wherein a lower collision probability and a higher cleaning failure probability correspond to a smaller number of points in a dense area, a larger size of the accessible space, a lower priority of crossing the dense area, and a smaller cleaning coverage of the dense area, and are used to clean the target area based on the cleaning parameters.

[0095] In some embodiments of this application, the execution unit 230 is used in the apparatus to intelligently identify the current scene of a target area, match the corresponding cleaning parameters based on the scene identification result in combination with the collision probability and / or the cleaning missed probability, and perform cleaning of the target area.

[0096] In some embodiments of the present application, the execution unit 230 is further used in the apparatus to receive a command from a user specifying a target area based on a pre-built map, and if intelligent identification determines to enter the target area, to perform the step of cleaning the target area based on the collision probability and / or the cleaning omission probability.

[0097] In some embodiments of the present application, the execution unit 230 is further used in the apparatus to read at least some of the history cleaning logs in the target area and to automatically adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters based on the history cleaning logs.

[0098] In some embodiments of this application, the execution unit 230 is used to adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters to achieve a lower collision probability when it determines, based on the history cleaning log, that the number of collisions with any obstacle is greater than a predetermined first threshold.

[0099] In some embodiments of this application, the execution unit 230 is further used in the apparatus to refrain from performing the step of adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters if the current collision probability is less than a preset second threshold.

[0100] Furthermore, the control device 200 for the self-propelled device described above can implement each of the control methods for the self-propelled device shown in Figure 1, and the same technical features as those of the control methods for the self-propelled device shown in Figure 1 are omitted here.

[0101] Figure 4 shows a schematic diagram of the control device for a self-propelled device according to the fourth embodiment of this application. As can be seen from Figure 4, the control device 300 for the self-propelled device is: A reading unit 310 is used to read a history cleaning log generated when a self-propelled device cleans at least a portion of the target area, Based on the history cleaning log, the system includes an adjustment unit 320 used to automatically adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device, wherein the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are either default or determined based on user setting commands.

[0102] Optionally, in the above-described device, the adjustment unit 320 is used to adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters to achieve a lower collision probability if it determines, based on the history cleaning log, that the number of collisions with any obstacle is greater than a predetermined first threshold.

[0103] Optionally, in the above apparatus, the adjustment unit 320 is further used not to perform the step of adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device if the current collision probability is less than a preset second threshold.

[0104] Furthermore, the control device 300 for the self-propelled device described above can implement each of the control methods for the self-propelled device shown in Figure 2, and the same technical features as those of the control methods for the self-propelled device shown in Figure 2 are omitted here.

[0105] A fifth embodiment of this application is a computer-readable storage medium in which computer program commands are stored, and the computer program commands are executed by processor loading to realize the operation performed by the method described in the first embodiment.

[0106] A sixth embodiment of this application is a self-propelled device comprising a processor and memory, wherein the memory stores computer program commands executable by the processor, and when the processor executes the computer program commands, it implements the commands of the method described above. The apparatus corresponds to the method embodiment and has the same technical effects as the method embodiment; a detailed explanation should be found in the method embodiment. The apparatus embodiment is derived from the method embodiment, and a detailed explanation should be found in the section of the method embodiment, which is omitted here. Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of one embodiment, and that the modules and flows in the accompanying drawings are not necessarily essential for carrying out this application.

[0107] Those skilled in the art will understand that the modules in the apparatus of the embodiment may be distributed within the apparatus of the embodiment in accordance with the description of the embodiment, or may be arranged in one or more different apparatuses with corresponding modifications. The modules of the above embodiment may be integrated into a single module or divided into multiple submodules.

[0108] Finally, the above embodiments are used solely to illustrate the technical solutions of this application and are not intended to limit them. While the application has been described in detail with reference to the above embodiments, those skilled in the art can still modify the technical solutions described in the above embodiments or substitute equivalent features of some of them, and such modifications or equivalent substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. The steps include receiving a command from the user to set the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters, The steps include determining the corresponding collision probability and / or cleaning failure probability based on the setting command, A method for controlling a self-propelled device, comprising the step of performing cleaning of a target area based on the collision probability and / or the cleaning failure probability.

2. The method according to claim 1, characterized in that the cleaning obstacle avoidance parameter includes at least one of a wall-side collision level parameter, an obstacle avoidance collision level parameter, and an obstacle-dense area collision level parameter.

3. The method according to claim 2, characterized in that the wall-side collision level parameter includes a wall edge collision level parameter and a wall front collision level parameter.

4. The method according to claim 1, wherein the cleaning obstacle avoidance mode includes an obstacle avoidance caution mode and an obstacle avoidance mitigation mode, the obstacle avoidance caution mode corresponds to a lower collision probability and / or a higher cleaning failure probability compared to the obstacle avoidance mitigation mode.

5. The method according to 4, characterized in that the aforementioned obstacle avoidance caution mode and the aforementioned obstacle avoidance mitigation mode each include multiple levels of obstacle avoidance.

6. The step of performing cleaning of the target area based on the collision probability and / or the cleaning omission probability is: Based on the collision probability and / or the cleaning failure probability, a corresponding cleaning parameter is determined, wherein the cleaning parameter includes at least one of the distance along the wall, the degree of turning along the wall, the forward distance along the wall, and the distance from the wall after turning, and a lower collision probability and / or a higher cleaning failure probability corresponds to a longer distance along the wall, a greater degree of turning, a longer forward distance along the wall, and a longer distance from the wall after turning. The method according to claim 1, characterized by comprising cleaning the target area based on the cleaning parameters.

7. The step of performing cleaning of the target area based on the collision probability and / or the cleaning omission probability is: Based on the collision probability and / or the cleaning failure probability, a corresponding cleaning parameter is determined, wherein the cleaning parameter includes at least one of the obstacle avoidance range and the number of obstacle avoidance range point clouds, and a lower collision probability and / or a higher cleaning failure probability corresponds to a larger obstacle avoidance range and a smaller number of obstacle avoidance range point clouds. The method according to claim 1, characterized by comprising cleaning the target area based on the cleaning parameters.

8. The step of performing cleaning of the target area based on the collision probability and / or the cleaning omission probability is: Based on the collision probability and / or the cleaning failure probability, a corresponding cleaning parameter is determined, the cleaning parameter including at least one of the number of points in the dense area, the size of the accessible space, the priority for crossing the dense area, and the cleaning coverage of the dense area, wherein a lower collision probability and / or a higher cleaning failure probability corresponds to a smaller number of points in the dense area, a larger size of the accessible space, a lower priority for crossing the dense area, and a smaller cleaning coverage of the dense area. The method according to claim 1, characterized by comprising cleaning the target area based on the cleaning parameters.

9. The method according to any one of claims 1 to 8, further comprising the steps of intelligently identifying the current scene of the target area, referring to the collision probability and / or the cleaning omission probability based on the scene identification result, matching corresponding cleaning parameters, and performing cleaning of the target area.

10. The steps include receiving a command from a user to specify the target area based on a pre-built map, The method according to any one of claims 1 to 8, further comprising at least one step of: determining by intelligent identification whether the self-propelled device has entered the target area, and if so, determining to perform a step of cleaning the target area based on the probability of collision and / or the probability of missed cleaning.

11. The steps include reading at least a portion of the history cleaning logs in the aforementioned target area, The method according to any one of claims 1 to 8, further comprising the step of automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters based on the history cleaning log.

12. The step of automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters based on the aforementioned cleaning history log is: The method according to 11, characterized in that, if it is determined that the number of collisions with any obstacle is greater than a preset first threshold based on the history cleaning log, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are adjusted to achieve a lower collision probability.

13. The method according to 11 or 12, further comprising not performing the step of adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters if the current collision probability is less than a preset second threshold.

14. A control device for a self-propelled device, A receiving unit used to receive commands from the user to set the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters via a front-end application, A probability determination unit used to determine the corresponding collision probability and / or cleaning failure probability based on the setting command, A control device for a self-propelled device, comprising: an execution unit used to perform cleaning of a target area based on the collision probability and / or the cleaning failure probability.

15. The steps include reading a history cleaning log generated by a self-propelled device cleaning at least a portion of the target area, A method for controlling a self-propelled device, comprising the steps of: automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device based on the history cleaning log, wherein the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are either default or determined based on user setting commands.

16. The step of automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device based on the aforementioned cleaning history log is: The method according to 15, further comprising adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters to achieve a lower collision probability when it is determined, based on the history cleaning log, that the number of collisions with any obstacle is greater than a predetermined first threshold.

17. The method according to 15 or 16, further comprising not performing the step of adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device if the current collision probability is less than a preset second threshold.

18. A control device for a self-propelled device, A reading unit used to read a history cleaning log generated when a self-propelled device cleans at least a portion of the target area, A control device for a self-propelled device, comprising: an adjustment unit that automatically adjusts the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device based on the aforementioned cleaning history log, wherein the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are either default or determined based on user setting commands.

19. A computer-readable storage medium, A computer-readable storage medium characterized in that a computer program command is stored in the computer-readable storage medium, and the computer program command is loaded and executed by a processor to realize an operation performed by the method according to any one of claims 1 to 13 or 15 to 17.

20. A self-driving device equipped with a processor and memory, A self-propelled device characterized in that a computer program command executable by the processor is stored in the memory, and when the processor executes the computer program command, the method according to any one of claims 1 to 13 or 15 to 17 is realized.

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