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

Abstract

The present disclosure provides a control method and apparatus for a self-propelled device, a medium and a self-propelled device. The method comprises: receiving a setting instruction of a user for a cleaning and obstacle avoidance mode and / or cleaning and obstacle avoidance parameters; on the basis of the setting instruction, determining a corresponding collision probability and / or cleaning missing probability; and cleaning a target area on the basis of the collision probability and / or the cleaning missing probability.

Description

Control method, device, medium and self-propelled device

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to Chinese patent application No. 202311102977.X filed on August 29, 2023. The contents of the above-mentioned Chinese patent application disclosure are hereby cited in their entirety as part of this disclosure. Technical Field

[0003] The present application relates to the technical field of self-propelled equipment, and in particular to a control method, device, medium and self-propelled equipment. Background Art

[0004] With the development of self-propelled vehicle technology, self-propelled vehicles are widely used in people's daily lives. However, current self-propelled vehicles usually perform cleaning tasks according to a preset program. This form cannot meet the diverse needs of users, such as when users want to clean a room quickly and easily.

[0005] Summary of the Invention

[0006] In response to the above situation, the embodiments of the present application provide a control method, device, medium and self-propelled device for a self-propelled device to overcome or at least partially overcome the deficiencies of the prior art.

[0007] In a first aspect, the present application provides a method for controlling a self-propelled walking device, comprising:

[0008] Receive instructions from the user for setting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters through the front-end application;

[0009] Determine the corresponding collision probability and / or missed scan probability according to the setting instruction;

[0010] The target area is cleaned according to the collision probability and / or the missed scanning probability.

[0011] Optionally, in the above method, the cleaning obstacle avoidance parameter includes at least one of the following: a wall collision level parameter, an obstacle avoidance collision level parameter, and an obstacle-dense area collision level parameter.

[0012] Optionally, in the above method, the wall collision level parameter includes a wall side collision level parameter and a head-on wall collision level parameter.

[0013] Optionally, in the above method, the sweeping obstacle avoidance mode includes: a cautious obstacle avoidance mode and a relaxed obstacle avoidance mode, and the cautious obstacle avoidance mode corresponds to a lower collision probability and / or a higher missed sweep probability than the relaxed obstacle avoidance mode;

[0014] Optionally, in the above method, the cautious obstacle avoidance mode and the relaxed obstacle avoidance mode respectively include multiple levels of obstacle avoidance levels.

[0015] Optionally, in the above method, performing cleaning of the target area according to the collision probability and / or the missed scanning probability includes:

[0016] Determining corresponding cleaning parameters based on the collision probability and / or the missed sweep probability, the cleaning parameters including at least one of: a distance along the wall, a turning amplitude along the wall, a forward travel along the wall, and a distance from the opposite wall after turning; wherein a lower collision probability and / or a higher missed sweep probability corresponds to a longer distance along the wall, a larger turning amplitude, a longer forward travel along the wall, and a longer distance from the opposite wall after turning;

[0017] The target area is cleaned according to the cleaning parameters.

[0018] Optionally, in the above method, performing cleaning of the target area according to the collision probability and / or the missed scanning probability includes:

[0019] Determining corresponding cleaning parameters according to the collision probability and / or the missed scan probability, the cleaning parameters including at least one of an obstacle avoidance range and the number of point clouds in the obstacle avoidance range, wherein a lower collision probability and / or a higher missed scan probability corresponds to a greater obstacle avoidance range and a smaller number of point clouds in the obstacle avoidance range;

[0020] The target area is cleaned according to the cleaning parameters.

[0021] Optionally, in the above method, performing cleaning of the target area according to the collision probability and / or the missed scanning probability includes:

[0022] Determining corresponding cleaning parameters according to the collision probability and / or the missed scanning probability, the cleaning parameters including at least one of the number of dense area point clouds, the size of the accessible space, the priority of traveling through the dense area, and the dense area cleaning coverage rate, wherein a lower collision probability and / or a higher missed scanning probability corresponds to a smaller number of dense area point clouds, a larger size of the accessible space, a lower priority of traveling through the dense area, and a smaller dense area cleaning coverage rate;

[0023] The target area is cleaned according to the cleaning parameters.

[0024] Optionally, the method further includes:

[0025] Intelligently identify the current scene of the target area, and match corresponding cleaning parameters based on the scene recognition result, combined with the collision probability and / or the missed scanning probability, to execute cleaning of the target area.

[0026] Optionally, the method further includes at least one of the following:

[0027] Receive user instructions for a target area based on a pre-built map;

[0028] It is determined by intelligent identification whether the self-propelled device has entered the target area. If so, it is determined to execute the step of performing cleaning of the target area according to the collision probability and / or the missed cleaning probability.

[0029] Optionally, the method further includes:

[0030] Reading at least a portion of a historical cleaning log in the target area;

[0031] Automatically adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters according to the historical cleaning log.

[0032] Optionally, in the above method, automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters according to the historical cleaning log includes:

[0033] If it is determined according to the historical cleaning log that the number of collisions with any obstacle is greater than a preset first threshold, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are adjusted to achieve a higher collision probability.

[0034] Optionally, the method further includes:

[0035] If the current collision probability is less than the preset second threshold, the step of adjusting the sweeping obstacle avoidance mode and / or sweeping obstacle avoidance parameters is not performed.

[0036] In a second aspect, an embodiment of the present application provides a control device for a self-propelled vehicle, the device comprising:

[0037] A receiving unit, configured to receive a setting instruction for a cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters from a user via a front-end application;

[0038] A probability hit unit, configured to determine a corresponding collision probability and / or missed scan probability according to the setting instruction;

[0039] An execution unit is configured to execute cleaning of the target area according to the collision probability and / or the missed cleaning probability.

[0040] In a third aspect, an embodiment of the present application further provides a method for controlling a self-propelled device, comprising:

[0041] Reading a historical cleaning log generated by a self-propelled device cleaning at least a portion of a target area;

[0042] According to the historical cleaning log, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device are automatically adjusted, wherein the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are default or determined according to user setting instructions.

[0043] Optionally, in the above method, automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device according to the historical cleaning log includes:

[0044] If it is determined according to the historical cleaning log that the number of collisions with any obstacle is greater than a preset first threshold, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are adjusted to achieve a lower collision probability.

[0045] Optionally, the method further includes:

[0046] If the current collision probability is less than the preset second threshold, the step of adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device is not performed.

[0047] In a fourth aspect, an embodiment of the present application further provides a control device for a self-propelled walking device, the device comprising:

[0048] a reading unit, configured to read a historical cleaning log generated by the self-propelled device when cleaning at least a portion of the target area;

[0049] An adjustment unit is used to automatically adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device according to the historical cleaning log, wherein the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are default or determined according to user setting instructions.

[0050] In a fifth aspect, an embodiment of the present application further provides a computer-readable storage medium, in which computer program instructions are stored. The computer program instructions are loaded and executed by a processor to implement the operations performed by the method described above.

[0051] In a sixth aspect, an embodiment of the present application further provides a self-propelled walking device, comprising a processor and a memory, wherein the memory stores computer program instructions that can be executed by the processor, and when the processor executes the computer program instructions, the above-mentioned method is implemented.

[0052] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects:

[0053] This application supports users to set the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled walking device in the front-end application, determines the corresponding collision probability and / or missed scanning probability according to the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters set by the user, and performs cleaning of the target area according to the collision probability and / or missed scanning probability, meeting the user's various personalized and differentiated needs, and realizing the refined satisfaction of the user's needs to avoid collisions in certain areas as much as possible and avoid missing scanning in certain areas as much as possible. On the premise of ensuring the cleaning quality, it greatly saves cleaning time and improves the utilization rate of the self-propelled walking device. The algorithm is simple and practical. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0055] FIG1 is a schematic flow chart showing a control method for a self-propelled vehicle according to a first embodiment of the present application;

[0056] FIG2 is a schematic flow chart showing a control method for a self-propelled vehicle according to a second embodiment of the present application;

[0057] FIG3 is a schematic structural diagram of a control device for a self-propelled vehicle according to a third embodiment of the present application;

[0058] FIG4 is a schematic structural diagram of a control device for a self-propelled vehicle according to a fourth embodiment of the present application. DETAILED DESCRIPTION

[0059] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0060] The following describes in detail the technical solutions provided by various embodiments of the present application in conjunction with the accompanying drawings.

[0061] Self-propelled devices, also known as automatic sweepers, robot vacuums, smart vacuums, floor sweepers, and sweeping robots, are a type of smart home appliance that utilizes artificial intelligence to automatically clean floors. These devices typically use a brushing and vacuuming system to collect debris from the floor into their own waste collection bins, completing the cleaning process. Generally speaking, sweepers that also perform sweeping, vacuuming, and mopping are also categorized as self-propelled devices.

[0062] In the existing technology, when a user turns on a self-propelled device, the self-propelled device will clean the target area according to a preset strategy. This preset strategy is usually unchanged, which cannot meet some differentiated needs of users. For example, for a room that is not dirty, the user may only want to clean it simply. The self-propelled device will still clean according to the established mode, which usually takes a lot of time and workload.

[0063] Based on the above-mentioned defects of existing self-propelled devices, the present application is proposed. The idea of ​​the present application is to display configurable options for cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters on the front-end application of the self-propelled device, support users to set the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device on the front-end application, determine the corresponding collision probability and / or missed scanning probability according to the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters set by the user, and perform cleaning of the target area according to the collision probability and / or missed scanning probability, thereby meeting the user's various personalized and differentiated needs.

[0064] FIG1 is a flow chart showing a control method for a self-propelled device according to a first embodiment of the present application. As can be seen from FIG1 , the first embodiment includes at least steps S110 to S130:

[0065] Step S110: receiving a user's instruction to set a cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters.

[0066] In some embodiments, the self-propelled device itself has a display screen, virtual buttons or physical buttons. On the display screen, the self-propelled device can display options for the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters for the user to set. If the user does not set it, the default mode can be used.

[0067] In other embodiments, the self-propelled device, as a smart device, is usually connected to a front-end application for communication, and the user can control the self-propelled device through the front-end application, that is, the front-end application displays the options of the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters for the user to set.

[0068] This application provides multiple configuration options. For example, in some embodiments, certain control parameters are abstracted into different cleaning and obstacle avoidance modes. The user only needs to specify a certain level of cleaning and obstacle avoidance mode, and the autonomous vehicle will then clean the target area in that mode. For example, in some embodiments, cleaning and obstacle avoidance modes include but are not limited to: cautious obstacle avoidance mode and relaxed obstacle avoidance mode. More levels of cleaning and obstacle avoidance modes can be set as needed, and this application does not limit this.

[0069] In other embodiments, the cleaning obstacle avoidance parameters can be directly displayed, and the cleaning obstacle avoidance parameters include but are not limited to: at least one of the following parameters: wall collision level parameter, obstacle avoidance collision level parameter, and obstacle-dense area collision level parameter; wherein, the wall collision level parameter includes a wall edge collision level parameter and a head-on wall collision level parameter. The wall collision level parameter characterizes the probability of collision of the self-propelled walking device along the wall, mainly referring to the possibility of collision against the wall edge and the possibility of collision against the head-on wall. The obstacle avoidance collision level parameter characterizes the possibility of collision against low obstacles, such as shoes, slippers, and scales. The obstacle-dense area collision level parameter characterizes the possibility of collision against table and chair arrays, sofa and coffee table areas, and the like.

[0070] In some embodiments, to facilitate user operation, the obstacle avoidance parameters for cleaning can be configured as levels. Users only need to specify a level without having to fill in specific parameters. Each of the wall collision level parameter, obstacle avoidance collision level parameter, and obstacle dense area collision level parameter can be set to multiple levels to meet different user needs.

[0071] Compared with the one-button setting mode, this method is slightly more cumbersome, but it is more suitable for some special scenarios. In a target area, the areas along the wall are relatively dirty, while the open area in the middle is relatively clean. In this way, by setting the wall collision level parameters relatively strictly and the obstacle avoidance collision level parameter point cloud relatively loosely, the self-propelled walking device will spend more time cleaning along the wall, and the obstacle avoidance requirements in the open area in the middle will be relaxed, thus achieving simple cleaning.

[0072] In other embodiments, the cleaning obstacle avoidance mode and the cleaning obstacle avoidance parameters can be combined together. For example, not only can the user be allowed to set different levels of cleaning obstacle avoidance modes, but also some parameters of a set cleaning obstacle avoidance mode can be set. This can not only meet the differentiated needs of users, but also facilitate user operation. For example, the user can set a loose obstacle dense area collision level parameter in the cautious obstacle avoidance mode. In this way, strict cleaning of a large area is achieved, and the narrow space between multiple obstacles can be ignored, thereby saving cleaning time and improving cleaning efficiency. The way of setting the mode and parameters at the same time can greatly simplify the user's operation.

[0073] Step S120: Determine the corresponding collision probability and / or missed scan probability according to the setting instruction.

[0074] The actual meaning of the sweeping obstacle avoidance mode and / or the sweeping obstacle avoidance parameters can be understood as the probability that the user hopes the self-propelled device may actually collide with an obstacle during operation and the probability that it may miss scanning a narrow space, which are respectively recorded as the collision probability and the miss scanning probability.

[0075] A pre-established correspondence between the obstacle avoidance and / or sweeping modes and parameters and the collision and / or missed sweep probabilities can be understood as a mapping relationship: a certain obstacle avoidance and / or sweeping mode corresponds to a certain collision or missed sweep probability, or both. In practice, for example, the values ​​of multiple parameters in the obstacle avoidance and sweeping mode are converted into collision and / or missed sweep probabilities using a specific algorithm.

[0076] After the user sets the sweeping obstacle avoidance mode and / or sweeping obstacle avoidance parameters, the corresponding collision probability and / or missed sweep probability can be determined according to the aforementioned mapping relationship.

[0077] Therefore, by setting different levels of sweeping obstacle avoidance modes and / or sweeping obstacle avoidance parameters, collision probabilities and / or missed sweep probabilities of different degrees of strictness can be achieved. As mentioned above, when the sweeping obstacle avoidance mode is configured to include a cautious obstacle avoidance mode and a relaxed obstacle avoidance mode, the cautious obstacle avoidance mode can be configured to correspond to a lower collision probability and a higher missed sweep probability relative to the relaxed obstacle avoidance mode; and the cautious obstacle avoidance mode and the relaxed obstacle avoidance mode can also be configured to include multiple levels of obstacle avoidance, such as 1-10 levels of obstacle avoidance, etc. The higher the level, the lower the collision probability and / or the higher the missed sweep probability. The user can select a certain level in the cautious obstacle avoidance mode or the relaxed obstacle avoidance mode.

[0078] Step S130: Cleaning the target area according to the collision probability and / or the missed scanning probability.

[0079] A certain collision probability and / or missed sweep probability corresponds to a certain cleaning strategy. The so-called cleaning strategy refers to how the autonomous vehicle handles obstacles such as corners and sofas. The cleaning strategy is usually presented in the form of parameters.

[0080] Specifically, in some embodiments of the present application, the cleaning of the target area according to the collision probability and / or the missed scanning probability includes: determining corresponding cleaning parameters according to the collision probability and the missed scanning probability, wherein the cleaning parameters include: at least one of the distance along the wall, the turning amplitude along the wall, the forward travel along the wall, and the distance from the opposite wall after turning; wherein, the lower the collision probability and / or the higher the missed scanning probability corresponds to the longer distance along the wall, the larger the turning amplitude, the longer the forward travel along the wall, and the longer the distance from the opposite wall after turning; and the target area is cleaned according to the cleaning parameters.

[0081] Cleaning parameters include, but are not limited to, at least one of the following: distance along the wall, turning range along the wall, forward travel along the wall, and distance from the opposite wall after turning. These parameters are primarily relevant to the self-propelled device's movement along the wall. The distance along the wall can be understood as the distance the self-propelled device maintains from the wall using a wall-following sensor while following the wall. The turning range along the wall can be understood as the turning range of the self-propelled device while following the wall. The forward travel along the wall can be understood as the distance traveled forward after turning. The distance from the opposite wall after turning can be understood as the distance from the opposite wall after turning.

[0082] When configuring a cleaning strategy, lower collision probabilities and higher missed sweep probabilities correspond to longer wall-following distances, wider turns, longer forward travel along the wall, and longer distance from the opposite wall after turning. Lower collision probabilities and higher missed sweep probabilities can be understood as stricter enforcement of minimal collisions, while allowing for more leniency in areas where missed sweeps are necessary. Simply put, when setting the collision level for self-propelled devices along walls, lower collision probabilities result in longer wall-following distances, wider turns, longer forward travel along the wall, and greater distance from the opposite wall after turning.

[0083] For example, when the collision probability is 20% and the missed scanning probability is 5%, the mapped distance along the wall is 0.7 cm, the turning amplitude along the wall is 2 cm, the forward travel along the wall is 1.5 cm, and the distance from the opposite wall after turning is 1 cm. Then, according to the cleaning parameters, the target area is cleaned automatically. The above data is only an exemplary description and does not constitute any limitation to this application.

[0084] In some embodiments of the present application, the cleaning of the target area according to the collision probability and / or the missed scanning probability includes: determining corresponding cleaning parameters according to the collision probability and / or the missed scanning probability, and the cleaning parameters include: obstacle avoidance range, and at least one of the number of obstacle avoidance range point clouds, wherein a lower collision probability and a higher missed scanning probability correspond to a larger obstacle avoidance range and a smaller number of obstacle avoidance range point clouds; and the target area is cleaned according to the cleaning parameters.

[0085] In some embodiments, cleaning parameters include, but are not limited to, at least one of an obstacle avoidance range and the number of point clouds within the obstacle avoidance range. The obstacle avoidance range can be understood as the obstacle avoidance range formed by the use of LDS (Laser Distance Sensor) technology during the movement of the self-propelled walking device. LDS is a laser ranging sensor commonly used for obstacle avoidance functions in devices such as robots and smart homes. The obstacle avoidance range of LDS is closely related to its design parameters. Generally speaking, the distance range within which LDS technology can detect and avoid obstacles ahead is usually between a few meters and more than ten meters. The number of point clouds within the obstacle avoidance range can be understood as the number of point clouds collected within the obstacle avoidance range.

[0086] The lower the collision probability and the higher the missed scan probability, the larger the obstacle avoidance range and the smaller the number of point clouds in the obstacle avoidance range. This can be understood as follows: for collision scenarios in which autonomous walking devices avoid obstacles, the lower the collision probability, that is, the stricter the collision avoidance capability, the larger the LDS obstacle avoidance range is configured, that is, the farther away from the obstacle, the obstacle avoidance begins, and the fewer LDS points (point clouds) are required within the obstacle avoidance range.

[0087] According to the collision probability and / or missed scanning probability, the obstacle avoidance range and the number of point clouds in the obstacle avoidance range are determined, and the target area can be cleaned according to the cleaning parameters.

[0088] In some embodiments of the present application, the cleaning of the target area according to the collision probability and / or the missed scanning probability includes: determining corresponding cleaning parameters according to the collision probability and / or the missed scanning probability, and the cleaning parameters include: the number of dense area point clouds, the size of the accessible space, the priority of traveling through the dense area, and at least one of the dense area cleaning coverage rate, wherein the lower the collision probability and the higher the missed scanning probability correspond to the fewer number of dense area point clouds, the larger the size of the accessible space, the lower the priority of traveling through the dense area, and the smaller the dense area cleaning coverage rate; according to the cleaning parameters, the target area is cleaned.

[0089] In some embodiments, cleaning parameters include at least one of: the number of dense area point clouds, the size of accessible space, the priority for traversing dense areas, and the coverage rate of dense area cleaning. These parameters are set for the autonomous vehicle to clean dense areas of obstacles. The number of dense area point clouds can be understood as the number of LDS points collected for a dense area, the size of accessible space can be understood as the size of the narrow space between multiple obstacles that the autonomous vehicle can enter, the priority for traversing dense areas indicates whether to prioritize traversing dense areas, and the coverage rate of dense areas can be understood as the proportion of cleaned dense areas to the total dense areas.

[0090] Lower collision probabilities and higher missed scan probabilities correspond to fewer point clouds in dense areas, larger accessible spaces, lower priority for traversing dense areas, and lower cleaning coverage in dense areas. Specifically, stricter collision avoidance capabilities result in fewer points within the LDS obstacle avoidance range in dense areas, a larger area between multiple obstacles that autonomous vehicles can enter, and a higher priority for avoiding dense areas, thus reducing cleaning coverage in dense areas.

[0091] Based on the collision probability and / or missed scanning probability, the number of point clouds in the dense area, the size of the accessible space, the priority of traversing the dense area, and the cleaning coverage of the dense area are determined. The target area can then be cleaned according to the cleaning parameters.

[0092] In addition, in some embodiments of the present application, the method also includes: intelligently identifying the current scene of the target area, and matching corresponding cleaning parameters based on the scene recognition results, combined with the collision probability and / or the missed scanning probability, to perform cleaning of the target area.

[0093] This application also supports different cleaning strategies in different scenarios. Taking the cleaning obstacle avoidance mode as an example, the collision probability and missed sweep probability values ​​of the same level of cleaning obstacle avoidance mode in different scenarios are different, thus meeting the different needs of multiple scenarios. Please refer to Table 1:

[0094] Table 1

[0095] As can be seen from Table 1, in the cautious obstacle avoidance mode, in scenario 1, the collision probability is configured as a1% and the missed sweep probability is b1%. In scenario 2, the collision probability is configured as a2% and the missed sweep probability is b2%. Therefore, when performing cleaning tasks based on the collision probability and missed sweep probability, different cleaning strategies can be matched with different collision probabilities and missed sweep probabilities to meet different scenario requirements.

[0096] In some embodiments of the present application, before executing the cleaning of the target area according to the collision probability and / or the missed scanning probability, the method further includes at least one of the following: receiving a user's designated instruction for the target area based on a pre-built map; determining through intelligent identification whether the self-propelled device enters the target area, and if so, determining to execute the step of executing the cleaning of the target area according to the collision probability and / or the missed scanning probability.

[0097] In some embodiments of the present application, the target area may be in the entire map or a portion of the map. The original map is usually constructed in advance and pre-stored in the self-propelled device.

[0098] The user can designate an area as a target area on a saved map and set the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters for the target area. The self-propelled device can identify the current area. When it is determined to have entered the target area specified by the user, the target area will be cleaned according to the collision probability and / or the missed scanning probability mapped to the user-specified cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters.

[0099] In some embodiments of the present application, the method further includes: reading at least part of the historical cleaning logs in the target area; and automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters according to the historical cleaning logs.

[0100] This application also supports adaptive adjustment of the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters. Specifically, it can be automatically adjusted according to the historical cleaning log of the self-propelled device.

[0101] Specifically, if it is determined according to the historical cleaning log that the number of collisions with any obstacle is greater than a preset first threshold, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are adjusted to achieve a lower collision probability.

[0102] For example, for an obstacle in the target area, if the self-propelled vehicle has collided with the obstacle multiple times in the historical period, when the number of collisions exceeds a threshold, such as 10 times, the obstacle avoidance mode and / or obstacle avoidance parameters will be adjusted to a more stringent level, further reducing the collision probability, thereby reducing collisions with the obstacle in the area in the future.

[0103] In some embodiments of the present application, the method further includes: if the current collision probability is less than a preset second threshold, not performing the step of adjusting the sweeping obstacle avoidance mode and / or sweeping obstacle avoidance parameters.

[0104] That is to say, when the collision probability of the self-propelled walking device in a certain area through the cleaning obstacle avoidance mode and / or the cleaning obstacle avoidance parameters is more relaxed than a certain threshold, it means that the current collision mode is already quite relaxed, and the cleaning obstacle avoidance mode and / or the cleaning obstacle avoidance parameters are not adjusted.

[0105] It can be seen from the method shown in Figure 1 that the present application supports users to set the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled walking device in the front-end application, determines the corresponding collision probability and / or missed scanning probability according to the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters set by the user, and performs cleaning of the target area according to the collision probability and / or missed scanning probability, which meets the user's various personalized and differentiated needs, and realizes the refined satisfaction of the user's needs to avoid collisions in certain areas as much as possible and not miss scanning in certain areas as much as possible. On the premise of ensuring the cleaning quality, it greatly saves cleaning time and improves the utilization rate of the self-propelled walking device, and the algorithm is simple and practical.

[0106] FIG2 is a flow chart showing a control method for a self-propelled device according to a second embodiment of the present application. As can be seen from FIG2 , this embodiment includes at least steps S210 to S220:

[0107] Step S210: Read the historical cleaning log generated by the self-propelled device when cleaning at least a portion of the target area.

[0108] As previously mentioned, the present application provides a self-propelled device with configurable cleaning and obstacle avoidance modes and / or cleaning and obstacle avoidance parameters. Specifically, in some embodiments, the self-propelled device itself has a display screen, virtual buttons, or physical buttons. On the display screen, the self-propelled device can display options for cleaning and obstacle avoidance modes and / or cleaning and obstacle avoidance parameters for the user to set. If the user does not set them, the default mode can be used. In other embodiments, the self-propelled device is a smart device that is usually connected to a front-end application for communication. The user can control the self-propelled device through the front-end application, that is, the front-end application displays options for cleaning and obstacle avoidance modes and / or cleaning and obstacle avoidance parameters for the user to set.

[0109] This application provides multiple configuration options. For example, in some embodiments, certain control parameters are abstracted into different cleaning and obstacle avoidance modes. The user only needs to specify a certain level of cleaning and obstacle avoidance mode, and the autonomous vehicle will then clean the target area in that mode. For example, in some embodiments, cleaning and obstacle avoidance modes include but are not limited to: cautious obstacle avoidance mode and relaxed obstacle avoidance mode. More levels of cleaning and obstacle avoidance modes can be set as needed, and this application does not limit this.

[0110] In other embodiments, the cleaning obstacle avoidance parameters can be directly displayed, and the cleaning obstacle avoidance parameters include but are not limited to: at least one of the following parameters: wall collision level parameter, obstacle avoidance collision level parameter, and obstacle-dense area collision level parameter; wherein, the wall collision level parameter includes a wall edge collision level parameter and a head-on wall collision level parameter. The wall collision level parameter characterizes the probability of collision of the self-propelled walking device along the wall, mainly referring to the possibility of collision against the wall edge and the possibility of collision against the head-on wall. The obstacle avoidance collision level parameter characterizes the possibility of collision against low obstacles, such as shoes, slippers, and scales. The obstacle-dense area collision level parameter characterizes the possibility of collision against table and chair arrays, sofa and coffee table areas, and the like.

[0111] In some embodiments, to facilitate user operation, the obstacle avoidance parameters for cleaning can be configured as levels. Users only need to specify a level without having to fill in specific parameters. Each of the wall collision level parameter, obstacle avoidance collision level parameter, and obstacle dense area collision level parameter can be set to multiple levels to meet different user needs.

[0112] Compared with the one-button setting mode, this method is slightly more cumbersome, but it is more suitable for some special scenarios. In a target area, the areas along the wall are relatively dirty, while the open area in the middle is relatively clean. In this way, by setting the wall collision level parameters relatively strictly and the obstacle avoidance collision level parameter point cloud relatively loosely, the self-propelled walking device will spend more time cleaning along the wall, and the obstacle avoidance requirements in the open area in the middle will be relaxed, thus achieving simple cleaning.

[0113] In other embodiments, the cleaning obstacle avoidance mode and the cleaning obstacle avoidance parameters can be combined together. For example, not only can the user be allowed to set different levels of cleaning obstacle avoidance modes, but also some parameters of a set cleaning obstacle avoidance mode can be set. This can not only meet the differentiated needs of users, but also facilitate user operation. For example, the user can set a loose obstacle dense area collision level parameter in the cautious obstacle avoidance mode. In this way, strict cleaning of a large area is achieved, and the narrow space between multiple obstacles can be ignored, thereby saving cleaning time and improving cleaning efficiency. The way of setting the mode and parameters at the same time can greatly simplify the user's operation.

[0114] Step S220: Automatically adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device according to the historical cleaning log, wherein the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are default or determined according to user setting instructions.

[0115] In addition to supporting manual adjustment of the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters by the user, this application also supports automatic adjustment of the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters. Specifically, the application obtains the logs generated by the self-propelled device during the cleaning of a certain area within a historical period, records them as historical cleaning logs, and then adaptively adjusts the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters based on the historical cleaning logs.

[0116] Specifically, in some embodiments, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device are automatically adjusted based on the historical cleaning log, including: if it is determined according to the historical cleaning log that the number of collisions with any obstacle is greater than a preset first threshold, then the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are adjusted to achieve a lower collision probability.

[0117] For example, for an obstacle in the target area, if the self-propelled vehicle has collided with the obstacle multiple times in the historical period, when the number of collisions exceeds a threshold, such as 10 times, the obstacle avoidance mode and / or obstacle avoidance parameters will be adjusted to a more stringent level, further reducing the collision probability, thereby reducing collisions with the obstacle in the area in the future.

[0118] In some other embodiments, the method further includes: if the current collision probability is less than a preset second threshold, not performing the step of adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device.

[0119] That is to say, when the collision probability of the self-propelled walking device in a certain area through the cleaning obstacle avoidance mode and / or the cleaning obstacle avoidance parameters is more relaxed than a certain threshold, it means that the current collision mode is already quite relaxed, and the cleaning obstacle avoidance mode and / or the cleaning obstacle avoidance parameters are not adjusted.

[0120] It can be seen from the method shown in Figure 2 that the present application supports adaptive adjustment of the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled walking device, which not only saves the user from operation, but also meets the user's various personalized and differentiated needs, and realizes the refined satisfaction of the user's needs to avoid collisions in certain areas as much as possible and not miss cleaning certain areas as much as possible. On the premise of ensuring the cleaning quality, it greatly saves cleaning time and improves the utilization rate of the self-propelled walking device. The algorithm is simple and practical.

[0121] FIG3 shows a schematic structural diagram of a control device for a self-propelled vehicle according to a third embodiment of the present application. As can be seen from FIG3 , the control device 200 for a self-propelled vehicle includes:

[0122] The receiving unit 210 is configured to receive a setting instruction for a cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters from a user via a front-end application;

[0123] A probability hit unit 220 is used to determine the corresponding collision probability and / or missed scan probability according to the setting instruction;

[0124] The execution unit 230 is configured to execute cleaning of the target area according to the collision probability and / or the missed scanning probability.

[0125] In some embodiments of the present application, in the above-mentioned device, the cleaning obstacle avoidance parameter includes at least one of the following: a wall collision level parameter, an obstacle avoidance collision level parameter, and an obstacle-dense area collision level parameter.

[0126] In some embodiments of the present application, in the above-mentioned device, the wall collision parameter includes a wall edge collision level parameter and a head-on wall collision level parameter.

[0127] In some embodiments of the present application, in the above-mentioned device, the sweeping obstacle avoidance mode includes: a cautious obstacle avoidance mode and a relaxed obstacle avoidance mode. The cautious obstacle avoidance mode corresponds to a lower collision probability and a higher missed sweep probability than the relaxed obstacle avoidance mode.

[0128] In some embodiments of the present application, in the above-mentioned device, the cautious obstacle avoidance mode and the relaxed obstacle avoidance mode respectively include multiple levels of obstacle avoidance levels.

[0129] In some embodiments of the present application, in the above-mentioned device, the execution unit 230 is used to: determine corresponding cleaning parameters according to the collision probability and / or the missed scanning probability, wherein the cleaning parameters include: at least one of the distance along the wall, the turning amplitude along the wall, the forward travel along the wall, and the distance from the opposite wall after turning; wherein, the lower the collision probability and the higher the missed scanning probability correspond to the longer distance along the wall, the larger the turning amplitude, the longer the forward travel along the wall, and the longer the distance from the opposite wall after turning; and the target area is cleaned according to the cleaning parameters.

[0130] In some embodiments of the present application, in the above-mentioned device, the execution unit 230 is used to: determine the corresponding cleaning parameters based on the collision probability and / or the missed scanning probability, wherein the cleaning parameters include: obstacle avoidance range, and at least one of the number of obstacle avoidance range point clouds, wherein a lower collision probability and a higher missed scanning probability correspond to a larger obstacle avoidance range and a smaller number of obstacle avoidance range point clouds; and the target area is cleaned according to the cleaning parameters.

[0131] In some embodiments of the present application, in the above-mentioned device, the execution unit 230 is used to: determine the corresponding cleaning parameters based on the collision probability and / or the missed scanning probability, wherein the cleaning parameters include: the number of dense area point clouds, the size of the accessible space, the priority of traveling through the dense area, and at least one of the dense area cleaning coverage rate, wherein the lower the collision probability and the higher the missed scanning probability correspond to the fewer dense area point clouds, the larger the size of the accessible space, the lower the priority of traveling through the dense area, and the smaller the dense area cleaning coverage rate; according to the cleaning parameters, the target area is cleaned.

[0132] In some embodiments of the present application, in the above-mentioned device, the execution unit 230 is also used to intelligently identify the current scene of the target area, and match the corresponding cleaning parameters based on the scene recognition results, combined with the collision probability and / or the missed scanning probability, to perform cleaning of the target area.

[0133] In some embodiments of the present application, in the above-mentioned device, the execution unit 230 is also used to receive a user's designated instruction for a target area based on a pre-built map; if it is determined through intelligent recognition that the target area has been entered, the step of performing cleaning of the target area according to the collision probability and / or the missed scanning probability is executed.

[0134] In some embodiments of the present application, in the above-mentioned device, the execution unit 230 is further used to read at least part of the historical cleaning log in the target area; and automatically adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters according to the historical cleaning log.

[0135] In some embodiments of the present application, in the above-mentioned device, 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 if it is determined, based on the historical cleaning log, that the number of collisions with any obstacle is greater than a preset first threshold.

[0136] In some embodiments of the present application, in the above-mentioned device, the execution unit 230 is further configured to not execute the step of adjusting the sweeping obstacle avoidance mode and / or sweeping obstacle avoidance parameters if the current collision probability is less than a preset second threshold.

[0137] It should be noted that the control device 200 of the self-propelled device can implement the control method of the self-propelled device shown in Figure 1 one by one, and the technical features that are the same as the control method of the self-propelled device shown in Figure 1 are not repeated here.

[0138] FIG4 shows a schematic structural diagram of a control device for a self-propelled vehicle according to a fourth embodiment of the present application. As can be seen from FIG4 , the control device 300 for the self-propelled vehicle includes:

[0139] A reading unit 310 is configured to read a historical cleaning log generated by the self-propelled device when cleaning at least a portion of the target area;

[0140] The adjustment unit 320 is used to automatically adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device according to the historical cleaning log, wherein the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are default or determined according to the user's setting instructions.

[0141] Optionally, in the above-mentioned 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 is determined based on the historical cleaning log that the number of collisions with any obstacle is greater than a preset first threshold.

[0142] Optionally, in the above-mentioned device, the adjustment unit 320 is further used to not 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.

[0143] It should be noted that the control device 300 for the self-propelled device described above can implement the control method for the self-propelled device shown in FIG. 2 , and the technical features that are the same as those in the control method for the self-propelled device shown in FIG. 2 are not described in detail here. The fifth embodiment of the present application is a computer-readable storage medium having computer program instructions stored therein. The computer program instructions are loaded and executed by a processor to implement the operations performed by the method described in the first embodiment described above.

[0144] The sixth embodiment of the present application is a self-propelled walking device, including a processor and a memory, wherein the memory stores computer program instructions that can be executed by the processor, and when the processor executes the computer program instructions, the instructions of the method described above are implemented. The above-mentioned device corresponds to the method embodiment and has the same technical effect as the method embodiment. For specific descriptions, please refer to the method embodiment. The device embodiment is obtained based on the method embodiment. For specific descriptions, please refer to the method embodiment section and will not be repeated here. It can be understood by those skilled in the art that the accompanying drawings are only schematic diagrams of one embodiment, and the modules or processes in the accompanying drawings are not necessarily required to implement this application.

[0145] Those skilled in the art will appreciate that the modules in the apparatuses of the embodiments may be distributed in the apparatuses of the embodiments as described in the embodiments, or may be located in one or more apparatuses different from the embodiments with corresponding changes. The modules in the above embodiments may be combined into one module or further divided into multiple sub-modules.

[0146] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A control method for a self-propelled walking device, characterized in that: include: Receiving a user's instruction to set a cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters; Determine the corresponding collision probability and / or missed scanning probability according to the setting instruction; The target area is cleaned according to the collision probability and / or the missed scanning probability.

2. The method according to claim 1, characterized in that The cleaning obstacle avoidance parameter includes at least one of the following: a wall 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 collision level parameters include wall side collision level parameters and head-on wall collision level parameters.

4. The method according to claim 1, characterized in that: The sweeping obstacle avoidance mode includes: a cautious obstacle avoidance mode and a relaxed obstacle avoidance mode. The cautious obstacle avoidance mode corresponds to a lower collision probability and / or a higher missed sweep probability relative to the relaxed obstacle avoidance mode.

5. The method according to claim 4, characterized in that The cautious obstacle avoidance mode and the relaxed obstacle avoidance mode each include multiple obstacle avoidance levels.

6. The method according to claim 1, characterized in that The performing cleaning of the target area according to the collision probability and / or the missed scanning probability includes: Determine a corresponding cleaning parameter according to the collision probability and / or the missed scanning probability, wherein the cleaning parameter includes at least one of: a distance along the wall, a turning amplitude along the wall, a forward travel along the wall, and a distance from the opposite wall after turning; wherein a lower collision probability and / or a higher missed scanning probability corresponds to a longer distance along the wall, a larger turning amplitude, a longer forward travel along the wall, and a longer distance from the opposite wall after turning; The target area is cleaned according to the cleaning parameters.

7. The method according to claim 1, characterized in that The performing cleaning of the target area according to the collision probability and / or the missed scanning probability includes: Determine a corresponding cleaning parameter according to the collision probability and / or the missed scanning probability, the cleaning parameter including: an obstacle avoidance range, and at least one of the number of point clouds in the obstacle avoidance range, wherein a lower collision probability and / or a higher missed scanning probability corresponds to a greater obstacle avoidance and a smaller number of point clouds in the obstacle avoidance range; The target area is cleaned according to the cleaning parameters.

8. The method according to claim 1, characterized in that The performing cleaning of the target area according to the collision probability and / or the missed scanning probability includes: Determine corresponding cleaning parameters according to the collision probability and / or the missed scanning probability, wherein the cleaning parameters include: at least one of the number of dense area point clouds, the size of the accessible space, the priority of dense area travel, and the dense area cleaning coverage rate, wherein a lower collision probability and / or a higher missed scanning probability corresponds to a smaller number of dense area point clouds, a larger size of the accessible space, a lower priority of dense area travel, and a smaller dense area cleaning coverage rate; The target area is cleaned according to the cleaning parameters.

9. The method according to any one of claims 1 to 8, characterized in that: Also includes: The current scene of the target area is intelligently identified, and corresponding cleaning parameters are matched according to the scene identification result in combination with the collision probability and / or the missed scanning probability to perform cleaning of the target area.

10. The method according to any one of claims 1 to 8, further comprising at least one of the following: receiving a user's designated instruction for the target area based on a pre-built map; It is determined by intelligent identification whether the self-propelled device has entered the target area. If so, it is determined to execute the step of performing cleaning of the target area according to the collision probability and / or the missed scanning probability.

11. The method according to any one of claims 1 to 8, characterized in that: Also includes: Reading at least a portion of the historical cleaning logs in the target area; The cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are automatically adjusted according to the historical cleaning log.

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

13. The method according to claim 11 or 12, characterized in that: Also includes: If the current collision probability is less than the preset second threshold, the step of adjusting the sweeping obstacle avoidance mode and / or sweeping obstacle avoidance parameters is not performed.

14. A control device for a self-propelled device, characterized in that: include: A receiving unit, used to receive a setting instruction of a cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters from a user through a front-end application; A probability hit unit, used to determine the corresponding collision probability and / or missed scan probability according to the setting instruction; An execution unit is used to execute cleaning of the target area according to the collision probability and / or the missed scanning probability.

15. A control method for a self-propelled device, characterized in that: include: Reading a historical cleaning log generated by a self-propelled device cleaning at least a portion of a target area; According to the historical cleaning log, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device are automatically adjusted, wherein the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are default or determined according to the setting instructions of the user.

16. The method according to claim 15, characterized in that The automatically adjusting the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device according to the historical cleaning log includes: If it is determined according to the historical cleaning log that the number of collisions with any obstacle is greater than a preset first threshold, the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are adjusted to achieve a lower collision probability.

17. The method according to claim 15 or 16, characterized in that Also includes: 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 of the self-propelled device is not performed.

18. A control device for a self-propelled device, characterized in that: The device comprises: A reading unit, configured to read a historical cleaning log generated by the self-propelled device cleaning at least a portion of the target area; An adjustment unit is used to automatically adjust the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters of the self-propelled device according to the historical cleaning log, wherein the cleaning obstacle avoidance mode and / or cleaning obstacle avoidance parameters are default or determined according to the user's setting instructions.

19. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, which are loaded and executed by a processor to implement the operations performed by the method according to any one of claims 1-13 or 15-17.

20. A self-propelled walking device, comprising a processor and a memory, characterized in that: The memory stores computer program instructions that can be executed by the processor, and when the processor executes the computer program instructions, the method according to any one of claims 1-13 or 15-17 is implemented.

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