Control method for obstacle movement of cleaning robot and cleaning robot

Abstract

The application discloses a control method and device for movement of a cleaning robot along an obstacle, a cleaning robot and a storage medium. The control method for movement of the cleaning robot along the obstacle comprises the following steps: acquiring detection data of an obstacle detector on the cleaning robot; identifying an obstacle type in front of the cleaning robot according to the detection data; determining a movement model corresponding to the obstacle type, wherein the movement model is constructed in advance according to a position relationship between the cleaning robot and the obstacle and the obstacle type; and controlling the cleaning robot to move along an edge of the obstacle according to the movement model and the detection data. Compared with the prior art, the application can improve the movement ability of the robot along the obstacle, thereby realizing the efficient and autonomous edge cleaning function of the cleaning robot.

Description

Technical Field

[0001] This application belongs to the field of home appliance technology, and in particular relates to a control method, device, cleaning robot and storage medium for the movement of a cleaning robot along obstacles. Background Technology

[0002] Robotic vacuum cleaners, also known as automatic cleaning machines, smart vacuum cleaners, or cleaning robots, are a type of smart home appliance that uses artificial intelligence to automatically clean floors in a room. They are increasingly becoming essential smart helpers in people's lives.

[0003] The ability to move along obstacles is the most basic capability of a robotic vacuum cleaner. Existing robotic vacuum cleaners use a single sensor, or infrared or lidar, to control the robot's movement along obstacles. Limited by the detection capabilities of a single sensor, in environments containing certain special obstacles, such as environments with obstacles with large curvature changes (e.g., table legs), or environments beyond the measurement range of a single sensor, the ability of the robotic vacuum cleaner to move along obstacles will deteriorate or be lost. This will affect the basic performance of the robotic vacuum cleaner, such as its ability to clean corners and edges and its cleaning coverage. Summary of the Invention

[0004] In view of this, embodiments of this application provide a control method, device, cleaning robot, and storage medium for the movement of a cleaning robot along obstacles, so as to improve the robot's ability to move along obstacles, thereby realizing the efficient and autonomous edge cleaning function of the cleaning robot.

[0005] The first aspect of this application provides a control method for a cleaning robot to move along an obstacle, including:

[0006] Acquire detection data from the obstacle detector on the cleaning robot;

[0007] Based on the detection data, the type of obstacle in front of the cleaning robot is identified;

[0008] Determine the motion model corresponding to the obstacle type, wherein the motion model is pre-constructed based on the positional relationship between the cleaning robot and the obstacle and the obstacle type;

[0009] Based on the motion model and the detection data, the cleaning robot is controlled to move along the edge of the obstacle.

[0010] The first aspect of this application describes a method for controlling the movement of a cleaning robot along obstacles. This method involves acquiring detection data from an obstacle detector on the cleaning robot; identifying the type of obstacle in front of the cleaning robot based on the detection data; determining a motion model corresponding to the obstacle type, wherein the motion model is pre-constructed based on the positional relationship between the cleaning robot and the obstacle, as well as the obstacle type; and controlling the cleaning robot to move along the edge of the obstacle based on the motion model and the detection data. Compared to existing technologies, this application improves the robot's ability to move along obstacles, thereby enabling the cleaning robot to perform efficient and autonomous edge cleaning.

[0011] In some embodiments of this application, determining the motion model corresponding to the obstacle type includes:

[0012] Based on the fact that the obstacle type is a continuous wall, the corresponding motion model is determined to be a small curvature motion model;

[0013] Based on the fact that the obstacle type is an isolated columnar type, the corresponding motion model is determined to be a high curvature motion model.

[0014] In some embodiments of this application, the process of constructing the small curvature motion model is as follows:

[0015]

[0016] Where, d W denoted by v, representing the distance between the cleaning robot and the obstacle as the robot moves along the edge of the obstacle; v represents the linear velocity of the cleaning robot; w represents the angular velocity of the cleaning robot; θ is the angle between the cleaning robot and the parallel direction of the wall; θ0 is the angle between the upper edge laser and the perpendicular line of the wall; and d0 represents the distance from the center of mass of the cleaning robot to the wall.

[0017] In some embodiments of this application, the process of constructing the large curvature motion model is as follows:

[0018] The distances to the upper, middle, and lower obstacles were determined from the detection data.

[0019] The sum of the cleaning robot's radius and the preset obstacle avoidance distance is determined as the positional relationship threshold;

[0020] The relative positional relationship between the cleaning robot and the obstacle is determined based on the upper obstacle bypass distance, middle obstacle bypass distance, lower obstacle bypass distance and the positional relationship threshold;

[0021] Based on the relative positional relationship and at least two preset rotational motion states, the cleaning robot is controlled to move along the edge of the obstacle. Different rotational motion states correspond to different linear velocities and angular velocities.

[0022] In some embodiments of this application, controlling the cleaning robot to move along the edge of an obstacle based on the relative positional relationship and at least two preset rotational motion states includes:

[0023] Determine the target rotational motion state corresponding to the relative positional relationship;

[0024] Control the cleaning robot to move according to the target rotational motion state;

[0025] Obtain the new relative positional relationship, and repeat the above steps according to the new relative positional relationship until the cleaning robot completes the obstacle along the edge.

[0026] The control device for the cleaning robot to move along an obstacle according to the second aspect embodiment of this application includes:

[0027] The acquisition module is used to acquire detection data from the obstacle detectors on the cleaning robot;

[0028] The identification module is used to identify the type of obstacle in front of the cleaning robot based on the detection data;

[0029] A determination module is used to determine the motion model corresponding to the obstacle type. The motion model is pre-constructed based on the positional relationship between the cleaning robot and the obstacle, as well as the obstacle type.

[0030] The control module is used to control the cleaning robot to move along the edge of the obstacle based on the motion model and the detection data.

[0031] The control device for a cleaning robot moving along an obstacle according to a second aspect of this application acquires detection data from an obstacle detector on the cleaning robot; identifies the type of obstacle in front of the cleaning robot based on the detection data; determines a motion model corresponding to the obstacle type, the motion model being pre-constructed based on the positional relationship between the cleaning robot and the obstacle and the obstacle type; and controls the cleaning robot to move along the edge of the obstacle based on the motion model and the detection data. Compared with the prior art, this application can improve the robot's ability to move along obstacles, thereby realizing the efficient and autonomous edge cleaning function of the cleaning robot.

[0032] In some embodiments of this application, the determining module is specifically used for:

[0033] Based on the fact that the obstacle type is a continuous wall, the corresponding motion model is determined to be a small curvature motion model;

[0034] Based on the fact that the obstacle type is an isolated columnar type, the corresponding motion model is determined to be a high curvature motion model.

[0035] In some embodiments of this application, the control module is further used to construct a small curvature motion model, and the small curvature motion model construction process is as follows:

[0036]

[0037] Where, d W denoted by v, representing the distance between the cleaning robot and the obstacle as the robot moves along the edge of the obstacle; v represents the linear velocity of the cleaning robot; w represents the angular velocity of the cleaning robot; θ is the angle between the cleaning robot and the parallel direction of the wall; θ0 is the angle between the upper edge laser and the perpendicular line of the wall; and d0 represents the distance from the center of mass of the cleaning robot to the wall.

[0038] In some embodiments of this application, the control module is further used for constructing a large curvature motion model, the process of which is as follows:

[0039] The distances to the upper, middle, and lower obstacles were determined from the detection data.

[0040] The sum of the cleaning robot's radius and the preset obstacle avoidance distance is determined as the positional relationship threshold;

[0041] The relative positional relationship between the cleaning robot and the obstacle is determined based on the upper obstacle bypass distance, middle obstacle bypass distance, lower obstacle bypass distance and the positional relationship threshold;

[0042] Based on the relative positional relationship and at least two preset rotational motion states, the cleaning robot is controlled to move along the edge of the obstacle. Different rotational motion states correspond to different linear velocities and angular velocities.

[0043] In some embodiments of this application, the control module is specifically used for:

[0044] Obtain the ambient humidity at multiple locations at preset distances along the boundary of the target area;

[0045] Calculate the average ambient humidity at the multiple locations to obtain the average humidity of the target area.

[0046] A cleaning robot according to a third aspect of this application includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor runs the computer program, it executes a control method for moving the cleaning robot along an obstacle according to a first aspect of this application.

[0047] A computer-readable storage medium according to a fourth aspect of this application stores computer-readable instructions that can be executed by a processor to implement a control method for a cleaning robot to move along an obstacle according to a first aspect of this application. Attached Figure Description

[0048] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0049] Appendix Figure 1 A flowchart illustrating a control method for a cleaning robot to move along an obstacle, according to an embodiment of this application, is shown.

[0050] Appendix Figure 2 A schematic diagram of the six laser beam data used in the embodiments of this application is shown;

[0051] Appendix Figure 3 A schematic diagram of the detection process for constructing a small curvature motion model in an embodiment of this application is shown;

[0052] Appendix Figure 4 A schematic diagram illustrating the state transition between two rotational motion states in an embodiment of this application is shown;

[0053] Appendix Figure 5 A schematic diagram of a control device for a cleaning robot moving along an obstacle, according to an embodiment of this application, is shown.

[0054] Appendix Figure 6 A schematic diagram of a cleaning robot according to an embodiment of this application is shown;

[0055] Appendix Figure 7 A schematic diagram of a computer-readable storage medium according to an embodiment of this application is shown.

[0056] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0058] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0059] Furthermore, in this invention, descriptions involving "first," "second," etc., are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0060] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0061] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are feasible for those skilled in the art. If the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0062] This application proposes a control method, device, cleaning robot, and storage medium for the movement of a cleaning robot along obstacles. The method involves acquiring detection data from an obstacle detector on the cleaning robot, which can be a line laser detector or a lidar sensor, etc. Based on the detection data, the type of obstacle in front of the cleaning robot is identified. A motion model corresponding to the obstacle type is determined, which is pre-constructed based on the positional relationship between the cleaning robot and the obstacle, as well as the obstacle type. Based on the motion model and the detection data, the cleaning robot is controlled to move along the edge of the obstacle. Compared to existing technologies, this application improves the robot's ability to move along obstacles, thereby achieving efficient and autonomous edge cleaning functionality for the cleaning robot.

[0063] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, specific embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0064] Example 1

[0065] Figure 1 This is a flowchart illustrating a control method for a cleaning robot moving along an obstacle, as provided in an embodiment of this application. Figure 1 As shown, the control method for the cleaning robot to move along obstacles includes:

[0066] Step S101: Obtain the detection data from the obstacle detector on the cleaning robot.

[0067] In this embodiment, the obstacle detector can be a line laser detector or a lidar sensor, that is, the detection data can be laser data or laser ranging data.

[0068] Figure 2 A schematic diagram of the six laser beams used in this embodiment is shown, as follows: Figure 2 As shown, the data from the six laser beams includes three edge-guided lasers and three barrier-circling lasers: the lower edge laser (signal range: -11° to -9°), the upper edge laser (signal range: 9° to 11°), the middle edge laser (signal range: -11° to 11°), the lower barrier-circling laser (signal range: -5° to -1°), the middle barrier-circling laser (signal range: -1° to 1°), and the upper barrier-circling laser (signal range: 1° to 5°).

[0069] It should be understood that the edge-to-edge laser corresponds to the edge-to-edge distance; the obstacle-around laser corresponds to the obstacle-around distance. The signal range of the 6 laser beams can be calibrated according to the actual situation, and both the edge-to-edge distance and the obstacle-around distance are the minimum distances within the signal range.

[0070] Step S102: Based on the detection data, identify the type of obstacle in front of the cleaning robot.

[0071] In practical applications, cleaning robots are often located indoors, where there are many obstacles, such as walls, tables, and chairs. Therefore, obstacle types can include continuous wall surfaces (such as the front or the top of a standing cabinet) and isolated columnar surfaces (such as table legs or chair legs).

[0072] Step S103: Determine the motion model corresponding to the obstacle type. The motion model is pre-constructed based on the positional relationship between the cleaning robot and the obstacle, as well as the obstacle type.

[0073] In some embodiments of this application, step S103 can be specifically implemented as follows:

[0074] Based on the obstacle type being a continuous wall surface, the corresponding motion model is determined to be a small curvature motion model;

[0075] Based on the obstacle type being an isolated columnar type, the corresponding motion model is determined to be a high curvature motion model.

[0076] Specifically, continuous wall surfaces exhibit smaller curvature changes, therefore a small curvature motion model is selected. Isolated columnar surfaces exhibit larger curvature changes, therefore a large curvature motion model is selected.

[0077] The process of constructing the small curvature motion model is as follows:

[0078]

[0079] Where, d W denoted by , v represents the distance between the cleaning robot and the obstacle as the robot moves along the edge of the obstacle; v represents the linear velocity of the cleaning robot; w represents the angular velocity of the cleaning robot; θ represents the angle between the cleaning robot and the parallel direction of the wall; θ0 represents the angle between the upper edge laser and the perpendicular line of the wall; d0 represents the distance from the center of mass of the cleaning robot to the wall.

[0080] The relative position information of the cleaning robot with respect to obstacles with small curvature is constructed using three edge-guided laser beams. The specific detection process involves... Figure 3 As shown.

[0081] Figure 3 In the diagram, the distance from the center of mass of the cleaning robot to the wall is d0, and the shortest distance from the upper edge laser to the wall is d. U The closest distance from the lower edge of the laser to the wall is d. L When the cleaning robot is parallel to the wall, the angle between the upper edge laser beam and the perpendicular line of the wall is θ0, and the angle difference between the direction in which the cleaning robot is parallel to the wall is θ. Here, it is defined that the angle difference is positive when rotating counterclockwise and negative when rotating clockwise. Based on the above definition, we can obtain:

[0082] d U cos(θ0+θ)=d0

[0083] d L cos(θ0-θ)=d0 (1)

[0084] Define the distance between the cleaning robot and an obstacle with small curvature as:

[0085] d W =d U -d L +d0 (2)

[0086] Let the linear velocity of the cleaning robot be v, and its angular velocity be w. According to the kinematic model of the robot, we can obtain:

[0087]

[0088]

[0089] According to (1)-(3), we can obtain:

[0090]

[0091] The above formula can be simplified to:

[0092]

[0093] Equation (4) is a model for controlling the movement of a machine along an obstacle with small curvature by using the distance constructed from the data of three edge-mounted laser beams.

[0094] The construction of the large curvature motion model will be introduced below.

[0095] The process of constructing the large curvature motion model is as follows:

[0096] The distances to the upper, middle, and lower obstacles were determined from the detection data.

[0097] The sum of the cleaning robot's radius and the preset obstacle avoidance distance is determined as the positional relationship threshold;

[0098] The relative positional relationship between the cleaning robot and the obstacle is determined based on the upper obstacle bypass distance, middle obstacle bypass distance, lower obstacle bypass distance and the positional relationship threshold;

[0099] Based on the relative positional relationship and at least two preset rotational motion states, the cleaning robot is controlled to move along the edge of the obstacle. Different rotational motion states correspond to different linear velocities and angular velocities.

[0100] The step of controlling the cleaning robot to move along the edge of the obstacle based on the relative positional relationship and at least two preset rotational motion states includes:

[0101] Determine the target rotational motion state corresponding to the relative positional relationship;

[0102] Control the cleaning robot to move according to the target rotational motion state;

[0103] Obtain the new relative positional relationship, and repeat the above steps according to the new relative positional relationship until the cleaning robot completes the obstacle along the edge.

[0104] Specifically, through Figure 3 The three obstacle-around laser data in the table are used to construct the relative position of the cleaning robot with respect to obstacles with large curvature. The specific construction method is shown in Table 1. In Table 1, D = cleaning robot radius + obstacle-around distance.

[0105] Table 1

[0106]

[0107]

[0108] While moving along the edge of the obstacle, the cleaning robot, based on the relative positional relationship between the cleaning robot and the obstacle with large curvature as shown in Table 1, switches between different rotational motion states (i.e., rotational trajectories with different curvatures, such as...). Figure 4(As shown) Approaching the outer contour of the obstacle.

[0109] like Figure 4 As shown, the state transition relationship between rotational motion state 1 and rotational motion state 2 is illustrated. The state transition is based on the relative positional relationship between the cleaning robot and the obstacle.

[0110] According to some embodiments of this application, more state transition relationships between rotational motion states can also be set, and this application does not limit this.

[0111] Step S104: Based on the motion model and the detection data, control the cleaning robot to move along the edge of the obstacle.

[0112] For details on the control process, please refer to the construction process of the large curvature motion model described above.

[0113] The control method for a cleaning robot to move along obstacles according to embodiments of this application involves acquiring detection data from an obstacle detector on the cleaning robot; identifying the type of obstacle in front of the cleaning robot based on the detection data; determining a motion model corresponding to the obstacle type, wherein the motion model is pre-constructed based on the positional relationship between the cleaning robot and the obstacle and the obstacle type; and controlling the cleaning robot to move along the edge of the obstacle based on the motion model and the detection data. Compared with the prior art, this application can improve the robot's ability to move along obstacles, thereby realizing the efficient and autonomous edge cleaning function of the cleaning robot.

[0114] Example 2

[0115] This application provides a control device for a cleaning robot to move along an obstacle. This control device corresponds to the control method for a cleaning robot to move along an obstacle in Embodiment 1. For relevant details, please refer to the description in Embodiment 1. The method embodiments described below are merely illustrative.

[0116] Figure 5 This is a schematic diagram of a control device for a cleaning robot to move along an obstacle, as provided in an embodiment of this application. Figure 5 As shown, the device 10 includes:

[0117] The acquisition module 101 is used to acquire the detection data of the obstacle detector on the cleaning robot;

[0118] The identification module 102 is used to identify the type of obstacle in front of the cleaning robot based on the detection data;

[0119] The determination module 103 is used to determine the motion model corresponding to the obstacle type. The motion model is pre-constructed based on the positional relationship between the cleaning robot and the obstacle and the obstacle type.

[0120] The control module 104 is used to control the cleaning robot to move along the edge of the obstacle according to the motion model and the detection data.

[0121] In some embodiments of this application, the determining module 103 is specifically used for:

[0122] Based on the fact that the obstacle type is a continuous wall, the corresponding motion model is determined to be a small curvature motion model;

[0123] Based on the fact that the obstacle type is an isolated columnar type, the corresponding motion model is determined to be a high curvature motion model.

[0124] In some embodiments of this application, the control module 104 is further used to construct a small curvature motion model, and the small curvature motion model construction process is as follows:

[0125]

[0126] Where, d W denoted by v, representing the distance between the cleaning robot and the obstacle as the robot moves along the edge of the obstacle; v represents the linear velocity of the cleaning robot; w represents the angular velocity of the cleaning robot; θ is the angle between the cleaning robot and the parallel direction of the wall; θ0 is the angle between the upper edge laser and the perpendicular line of the wall; and d0 represents the distance from the center of mass of the cleaning robot to the wall.

[0127] In some embodiments of this application, the control module 104 is further used for constructing a large curvature motion model, the process of which is as follows:

[0128] Determine the distances to the top edge, middle edge, and bottom edge from the detection data;

[0129] The sum of the cleaning robot's radius and the preset obstacle avoidance distance is determined as the positional relationship threshold;

[0130] The relative positional relationship between the cleaning robot and the obstacle is determined based on the upper obstacle bypass distance, middle obstacle bypass distance, lower obstacle bypass distance and the positional relationship threshold;

[0131] Based on the relative positional relationship and at least two preset rotational motion states, the cleaning robot is controlled to move along the edge of the obstacle. Different rotational motion states correspond to different linear velocities and angular velocities.

[0132] In some embodiments of this application, the control module 104 is specifically used for:

[0133] Obtain the ambient humidity at multiple locations at preset distances along the boundary of the target area;

[0134] Calculate the average ambient humidity at the multiple locations to obtain the average humidity of the target area.

[0135] The control device for the cleaning robot's movement along obstacles in this embodiment acquires detection data from the obstacle detector on the cleaning robot; identifies the type of obstacle in front of the cleaning robot based on the detection data; determines the motion model corresponding to the obstacle type, which is pre-constructed based on the positional relationship between the cleaning robot and the obstacle and the obstacle type; and controls the cleaning robot to move along the edge of the obstacle based on the motion model and the detection data. Compared with the prior art, this application can improve the robot's ability to move along obstacles, thereby realizing the cleaning robot's efficient and autonomous edge cleaning function.

[0136] Example 3

[0137] like Figure 6 As shown, this application embodiment also provides a cleaning robot 20, including: a memory 201, a processor 202, and a computer program stored in the memory and executable on the processor. When the processor 202 runs the computer program, it executes a control method for moving the cleaning robot along an obstacle in any of the embodiments of the first embodiment.

[0138] Specifically, the cleaning robot may include: a processor, a memory, a bus, and a communication interface, wherein the processor, the communication interface, and the memory are connected via the bus; the memory stores a computer program that can run on the processor, and when the processor runs the computer program, it executes the control method for the cleaning robot to move along obstacles provided in any of the foregoing embodiments of this application.

[0139] The memory may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk drive. Communication between this system network element and at least one other network element is achieved through at least one communication interface (wired or wireless), which can use the Internet, wide area network, local area network, metropolitan area network, etc.

[0140] The bus can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The memory is used to store the program, and the processor executes the program after receiving an execution instruction. The control method for the cleaning robot's movement along obstacles disclosed in any of the foregoing embodiments of this application can be applied to the processor, or implemented by the processor.

[0141] The processor may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed through integrated logic circuits in the processor's hardware or through software instructions. The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application-Specific Integrated Circuit (ASIC), an Off-the-shelf Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0142] The cleaning robot provided in this application embodiment and the control method for the cleaning robot to move along obstacles provided in this application embodiment are based on the same inventive concept and have the same beneficial effects as the methods used, operated or implemented.

[0143] Example 4

[0144] This application also provides a computer-readable storage medium, please refer to... Figure 7 The computer-readable storage medium shown is an optical disc 30, on which computer-readable instructions (i.e., program products) are stored, which can be executed by a processor to implement the control method for the movement of the cleaning robot along obstacles in any embodiment of the first embodiment.

[0145] Examples of the computer-readable storage medium may also include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which will not be described in detail here.

[0146] The computer-readable storage medium provided in the above embodiments of this application and the control method for the movement of a cleaning robot along obstacles provided in the embodiments of this application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the applications stored therein.

[0147] It should be noted that:

[0148] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0149] Similarly, it should be understood that, in order to simplify this application and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of this application, various features of this application are sometimes grouped together into a single embodiment, figure, or description thereof. However, this method of disclosure should not be construed as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this application.

[0150] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0151] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.

[0152] The various component embodiments of this application can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components in the virtual machine creation apparatus according to embodiments of this application. This application can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such an implementation of this application can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0153] It should be noted that the above embodiments are illustrative of this application and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. This application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0154] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made under the concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A control method for a cleaning robot moving along an obstacle, characterized in that, include: Acquire detection data from the obstacle detector on the cleaning robot; Based on the detection data, the type of obstacle in front of the cleaning robot is identified; Determine the motion model corresponding to the obstacle type, wherein the motion model is pre-constructed based on the positional relationship between the cleaning robot and the obstacle and the obstacle type; Based on the motion model and the detection data, the cleaning robot is controlled to move along the edge of the obstacle; The step of determining the motion model corresponding to the obstacle type includes: determining the corresponding motion model as a large curvature motion model based on the obstacle type being an isolated columnar type; The process of constructing the large curvature motion model is as follows: The distances to the upper, middle, and lower obstacles were determined from the detection data. The sum of the cleaning robot's radius and the preset obstacle avoidance distance is determined as the positional relationship threshold; The relative positional relationship between the cleaning robot and the obstacle is determined based on the upper obstacle bypass distance, middle obstacle bypass distance, lower obstacle bypass distance and the positional relationship threshold; Based on the relative positional relationship and at least two preset rotational motion states, the cleaning robot is controlled to move along the edge of the obstacle. Different rotational motion states correspond to different linear velocities and angular velocities.

2. The control method for the movement of a cleaning robot along an obstacle according to claim 1, characterized in that, The step of determining the motion model corresponding to the obstacle type further includes: Based on the fact that the obstacle type is a continuous wall, the corresponding motion model is determined to be a small curvature motion model.

3. The control method for the movement of a cleaning robot along an obstacle according to claim 2, characterized in that, The process of constructing the small curvature motion model is as follows: ； in, This indicates the distance between the cleaning robot and the obstacle as the robot moves along the edge of the obstacle. This indicates the linear velocity of the cleaning robot; This represents the angular velocity of the cleaning robot; The angle between the cleaning robot and the parallel direction of the wall; The angle between the upper edge laser and the perpendicular line of the wall; This indicates the distance from the center of mass of the cleaning robot to the wall.

4. The control method for the movement of a cleaning robot along an obstacle according to claim 1, characterized in that, The step of controlling the cleaning robot to move along the edge of the obstacle based on the relative positional relationship and at least two preset rotational motion states includes: Determine the target rotational motion state corresponding to the relative positional relationship; Control the cleaning robot to move according to the target rotational motion state; Obtain the new relative positional relationship, and repeat the above steps according to the new relative positional relationship until the cleaning robot completes the obstacle along the edge.

5. A control device for a cleaning robot to move along an obstacle, characterized in that, include: The acquisition module is used to acquire detection data from the obstacle detectors on the cleaning robot; The identification module is used to identify the type of obstacle in front of the cleaning robot based on the detection data; A determination module is used to determine the motion model corresponding to the obstacle type. The motion model is pre-constructed based on the positional relationship between the cleaning robot and the obstacle, as well as the obstacle type. The control module is used to control the cleaning robot to move along the edge of the obstacle based on the motion model and the detection data; The determining module is specifically used to: determine the corresponding motion model as a large curvature motion model based on the obstacle type being an isolated columnar type; The control module is also used for constructing a large curvature motion model, and the large curvature motion model construction process is as follows: The distances to the upper, middle, and lower obstacles were determined from the detection data. The sum of the cleaning robot's radius and the preset obstacle avoidance distance is determined as the positional relationship threshold; The relative positional relationship between the cleaning robot and the obstacle is determined based on the upper obstacle bypass distance, middle obstacle bypass distance, lower obstacle bypass distance and the positional relationship threshold; Based on the relative positional relationship and at least two preset rotational motion states, the cleaning robot is controlled to move along the edge of the obstacle. Different rotational motion states correspond to different linear velocities and angular velocities.

6. The control device for the cleaning robot to move along an obstacle according to claim 5, characterized in that, The determining module is further specifically used for: Based on the fact that the obstacle type is a continuous wall, the corresponding motion model is determined to be a small curvature motion model.

7. The control device for the cleaning robot to move along an obstacle according to claim 6, characterized in that, The control module is also used for constructing a small curvature motion model, and the process of constructing the small curvature motion model is as follows: ； in, This indicates the distance between the cleaning robot and the obstacle as the robot moves along the edge of the obstacle. This indicates the linear velocity of the cleaning robot; This represents the angular velocity of the cleaning robot; The angle between the cleaning robot and the parallel direction of the wall; The angle between the upper edge laser and the perpendicular line of the wall; This indicates the distance from the center of mass of the cleaning robot to the wall.

8. The control device for the cleaning robot to move along an obstacle according to claim 5, characterized in that, The control module is specifically used for: Obtain the ambient humidity at multiple locations at preset distances along the boundary of the target area; Calculate the average ambient humidity at the multiple locations to obtain the average humidity of the target area.

9. A cleaning robot, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method as claimed in any one of claims 1 to 4.

10. A computer-readable storage medium having stored thereon computer-readable instructions that can be executed by a processor to implement the method as described in any one of claims 1 to 4.

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