Sweeping robot operation processing method, sweeping robot and virtual device

Abstract

The invention provides a sweeping robot operation processing method, a sweeping robot and a virtual device, and is applied to the sweeping robot. Comprising the steps that operation data of the sweeping robot in the current time period are collected, and the operation data comprise position coordinates, acceleration and angular acceleration of the sweeping robot; calling a pre-constructed sweeping robot motion model, speed constraint and angular speed constraint; determining a combined operation state of the multiple groups of sweeping robots based on the speed constraint and the angular speed constraint, wherein the combined operation state comprises an operation speed and an operation angular speed; based on the sweeping robot motion model, the operation data and the operation state of each group of combination, obtaining each group of predicted operation tracks corresponding to the operation state of each group of combination; and determining a target predicted moving trajectory in the multiple groups of predicted moving trajectories, and controlling the sweeping robot to operate in the next time period according to a target combined operating state corresponding to the target predicted moving trajectory. The sweeping robot can be controlled to operate efficiently and safely.

Description

Technical Field

[0001] The present invention relates to the field of smart home technology, and in particular to a sweeping robot operation processing method, a sweeping robot and a virtual device. Background Art

[0002] Currently, autonomous mobile devices are showing unprecedented application potential in many industrial fields and daily life, especially in the field of household robots. Intelligent devices such as household cleaning robots and household care robots have gradually become an indispensable part of modern families. They provide great convenience to users through efficient path planning and navigation technology.

[0003] However, when faced with complex and changing environments, traditional path planning methods often ignore the robot's current speed state and real-time information of the surrounding environment, and thus cannot control the robot to operate in real time and efficiently.

[0004] Therefore, finding a sweeping robot operation processing method that can control the sweeping robot to operate efficiently and safely in real time has become a current research hotspot. Summary of the invention

[0005] The present invention provides a sweeping robot operation processing method, a sweeping robot and a virtual device, which can control the sweeping robot to operate efficiently and safely.

[0006] The present invention provides a sweeping robot operation processing method, which is applied to a sweeping robot; the method comprises: collecting operation data of the sweeping robot in a current time period, wherein the operation data at least includes the position coordinates, acceleration and angular acceleration of the sweeping robot; retrieving a pre-built sweeping robot motion model, a speed constraint on the sweeping robot, and an angular velocity constraint on the sweeping robot, wherein the sweeping robot motion model is a model characterizing the operation state and position information of the sweeping robot; based on the speed constraint on the sweeping robot and the angular velocity constraint on the sweeping robot, determining a plurality of groups of combined operation states of the sweeping robot, wherein the combined operation states include an operation speed and an operation angular velocity; based on the sweeping robot motion model, the operation data and each group of the combined operation states, obtaining each group of predicted operation trajectories corresponding to each group of the combined operation states; determining a target predicted operation trajectory from the plurality of groups of the predicted operation trajectories, and controlling the operation of the sweeping robot in the next time period according to the target combined operation state corresponding to the target predicted operation trajectory.

[0007] According to a sweeping robot operation processing method provided by the present invention, the sweeping robot motion model is constructed in the following manner: determine the robot angular orientation of the sweeping robot and the position coordinates of the sweeping robot in the current time period; determine a first change relationship between the position coordinates of the sweeping robot and time based on the running speed of the sweeping robot, the position coordinates, and the robot angular orientation; determine a second change relationship between the running speed of the sweeping robot and time based on the acceleration of the sweeping robot; determine a third change relationship between the robot angular orientation of the sweeping robot and time based on the angular velocity of the sweeping robot; determine a fourth change relationship between the angular velocity of the sweeping robot and time based on the angular acceleration of the sweeping robot; and construct the sweeping robot motion model based on the first change relationship, the second change relationship, the third change relationship, and the fourth change relationship.

[0008] According to a sweeping robot operation processing method provided by the present invention, the sweeping robot is used to clean an area to be cleaned, and there are obstacles in the area to be cleaned; the speed constraint of the sweeping robot is constructed in the following manner: a preset minimum operating speed value is obtained, and a preset maximum operating speed value is obtained, and a first speed sub-constraint is constructed based on the preset minimum operating speed value and the preset maximum operating speed value; the maximum acceleration of the sweeping robot and the initial operating speed of the sweeping robot in the current time period are obtained, and a second speed sub-constraint is constructed based on the maximum acceleration and the initial operating speed; the distance information between the sweeping robot and the obstacle is obtained, and a third speed sub-constraint is constructed based on the distance information, the maximum acceleration, and the preset minimum operating speed value; the speed constraint of the sweeping robot is constructed based on the first speed sub-constraint, the second speed sub-constraint, and the third speed sub-constraint.

[0009] According to a sweeping robot operation processing method provided by the present invention, the angular velocity constraint of the sweeping robot is constructed in the following manner: obtaining a preset minimum operating angular velocity value, and obtaining a preset maximum operating angular velocity value, and constructing a first angular velocity sub-constraint based on the preset minimum operating angular velocity value and the preset maximum operating angular velocity value; obtaining the maximum angular acceleration of the sweeping robot and the initial operating angular velocity of the sweeping robot in the current time period, and constructing a second angular velocity sub-constraint based on the maximum angular acceleration and the initial operating angular velocity; obtaining the distance information between the sweeping robot and the obstacle, and constructing a third angular velocity sub-constraint based on the distance information, the maximum angular acceleration, and the preset minimum operating angular velocity value; constructing an angular velocity constraint on the sweeping robot based on the first angular velocity sub-constraint, the second angular velocity sub-constraint, and the third angular velocity sub-constraint.

[0010] According to a sweeping robot operation processing method provided by the present invention, based on the sweeping robot motion model, the operation data and each group of the combined operation states, each group of predicted operation trajectories corresponding to each group of the combined operation states are obtained, which specifically includes: substituting the operation data and each group of the combined operation states into the sweeping robot motion model to obtain each group of predicted operation trajectories corresponding to each group of the combined operation states.

[0011] According to a sweeping robot operation processing method provided by the present invention, a target predicted operation trajectory is determined from a plurality of groups of predicted operation trajectories, which is implemented in the following manner: based on each group of the predicted operation trajectories, a trajectory evaluation score corresponding to each group of the predicted operation trajectories is determined; and the predicted operation trajectory corresponding to the highest trajectory evaluation score is used as the target predicted operation trajectory.

[0012] According to a sweeping robot operation processing method provided by the present invention, the trajectory evaluation score corresponding to each group of predicted operation trajectories is determined based on each group of predicted operation trajectories, specifically including: based on each group of predicted operation trajectories, each angle formed between each group of predicted operation trajectories and the sweeping robot is obtained, and according to each angle, each angle evaluation score corresponding to each angle is obtained; based on each group of predicted operation trajectories, each distance formed between each group of predicted operation trajectories and the area target point of the area to be cleaned is obtained, and according to each distance, each distance evaluation score corresponding to each distance is obtained; based on each group of predicted operation trajectories, each operation speed corresponding to each group of predicted operation trajectories is obtained, and according to each operation speed, each speed evaluation score corresponding to each operation speed is obtained; based on each angle evaluation score, each distance evaluation score, and each speed evaluation score, a trajectory evaluation score corresponding to each group of predicted operation trajectories is determined.

[0013] The present invention further provides a sweeping robot, comprising: a sweeping robot body, and a processor, wherein the processor is used to execute any one of the sweeping robot operation processing methods.

[0014] The present invention also provides a sweeping robot operation processing virtual device, which is applied to the sweeping robot; the virtual device comprises: a collection module, which is used to collect the operation data of the sweeping robot in the current time period, wherein the operation data at least includes the position coordinates, acceleration and angular acceleration of the sweeping robot; a calling module, which is used to call a pre-built sweeping robot motion model, a speed constraint on the sweeping robot, and an angular velocity constraint on the sweeping robot, wherein the sweeping robot motion model is a model that characterizes the operation status and position information of the sweeping robot; a determination module, which is used to determine the operation status and position information of the sweeping robot based on the relevant information; Based on the speed constraint of the sweeping robot and the angular velocity constraint of the sweeping robot, a plurality of groups of combined operating states of the sweeping robot are determined, wherein the combined operating state includes an operating speed and an operating angular velocity; a processing module is used to obtain each group of predicted operating trajectories corresponding to each group of the combined operating states based on the sweeping robot motion model, the operating data and each group of the combined operating states; a control module is used to determine a target predicted operating trajectory from the plurality of groups of the predicted operating trajectories, and control the operation of the sweeping robot in the next time period according to the target combined operating state corresponding to the target predicted operating trajectory.

[0015] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the sweeping robot operation processing method described in any one of the above methods is implemented.

[0016] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the cleaning robot operation processing method described in any one of the above is implemented.

[0017] The present invention also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the computer program implements any of the above-mentioned sweeping robot operation processing methods.

[0018] The sweeping robot operation processing method, sweeping robot and virtual device provided by the present invention are applied to the sweeping robot; the method comprises: collecting the operation data of the sweeping robot in the current time period, wherein the operation data at least includes the position coordinates, acceleration and angular acceleration of the sweeping robot; calling the pre-built sweeping robot motion model, the speed constraint on the sweeping robot, and the angular velocity constraint on the sweeping robot; determining the combined operation states of multiple groups of sweeping robots based on the speed constraint on the sweeping robot and the angular velocity constraint on the sweeping robot, wherein the combined operation states include the operation speed and the operation angular velocity; obtaining each group of predicted operation trajectories corresponding to each group of combined operation states based on the sweeping robot motion model, the operation data and each group of combined operation states; determining the target predicted operation trajectory from the multiple groups of predicted operation trajectories, and controlling the operation of the sweeping robot in the next time period according to the target combined operation state corresponding to the target predicted operation trajectory. The method realizes the ability to determine the target combined operation state of the sweeping robot in the next time period according to the real-time operation data of the sweeping robot, thereby enabling the operation of the sweeping robot to be efficiently and safely controlled. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is a schematic diagram of the hardware environment of a graded cleaning method according to an embodiment of the present application.

[0021] Figure 2 It is a flow chart of the sweeping robot operation processing method provided by the present invention.

[0022] Figure 3 It is a schematic diagram of the process of constructing a sweeping robot motion model provided by the present invention.

[0023] Figure 4It is a schematic diagram of the flow of constructing the speed constraint of the sweeping robot provided by the present invention.

[0024] Figure 5 It is a schematic diagram of the process of constructing the angular velocity constraint of the sweeping robot provided by the present invention.

[0025] Figure 6 It is a flow chart of determining the trajectory evaluation score corresponding to each group of predicted running trajectories based on each group of predicted running trajectories provided by the present invention.

[0026] Figure 7 It is a structural diagram of the sweeping robot operation processing virtual device provided by the present invention.

[0027] Figure 8 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] According to one aspect of an embodiment of the present application, a method for processing the operation of a sweeping robot is provided. The method for processing the operation of a sweeping robot is widely used in smart home, smart home, smart home device ecology, smart house ecology and other whole-house intelligent digital control application scenarios. Optionally, in this embodiment, the above-mentioned method for processing the operation of a sweeping robot can be applied to Figure 1 In the hardware environment composed of the terminal device 102 and the server 104 shown in FIG. Figure 1 As shown, the server 104 is connected to the terminal device 102 via a network, and can be used to provide services (such as application services, etc.) for the terminal or a client installed on the terminal. A database can be set on the server or independently of the server to provide data storage services for the server 104. Cloud computing and / or edge computing services can be configured on the server or independently of the server to provide data computing services for the server 104.

[0030] The network may include but is not limited to at least one of the following: wired network, wireless network. The wired network may include but is not limited to at least one of the following: wide area network, metropolitan area network, local area network, and the wireless network may include but is not limited to at least one of the following: WIFI (Wireless Fidelity), Bluetooth. The terminal device 102 may be but is not limited to a PC, a mobile phone, a tablet computer, a smart air conditioner, a smart range hood, a smart refrigerator, a smart oven, a smart stove, a smart washing machine, a smart water heater, a smart washing equipment, a smart dishwasher, a smart projection equipment, a smart TV, a smart clothes drying rack, a smart curtain, a smart audio and video, a smart socket, a smart speaker, a smart speaker, a smart fresh air equipment, a smart kitchen and bathroom equipment, a smart bathroom equipment, a smart sweeping robot, a smart window cleaning robot, a smart mopping robot, a smart air purification equipment, a smart steamer, a smart microwave oven, a smart kitchen treasure, a smart purifier, a smart water dispenser, a smart door lock, etc.

[0031] In another embodiment, the robot vacuum cleaner operation processing method provided in the present application can be applied to smart home appliances. Among them, smart home appliances refer to home appliances formed by introducing microprocessors, sensor technology, and network communication technology into home appliances, which have the function of automatically sensing the state of residential space, the state of the home appliances themselves, and the state of home appliance services, and can automatically control and receive control instructions from residential users in the home or remotely. It can be understood that smart home appliances are a component of smart homes.

[0032] The sweeping robot operation processing method provided in the present application can determine the target combined operation state of the sweeping robot in the next time period based on the real-time operation data of the sweeping robot, thereby being able to efficiently and safely control the operation of the sweeping robot.

[0033] The sweeping robot operation processing method provided in the present application can obtain an optimal motion trajectory to avoid obstacles based on the obstacle map, the robot's motion status, and the target point given to the robot, and provide control of the robot's speed, direction, etc. that follows the trajectory to achieve real-time obstacle avoidance.

[0034] Figure 2 It is a flow chart of the sweeping robot operation processing method provided by the present invention.

[0035] The following will be combined Figure 2 The process of the sweeping robot operation processing method provided by the present invention is described.

[0036] In an exemplary embodiment of the present invention, the cleaning robot operation processing method can be applied to the cleaning robot. Figure 2 It can be seen that the sweeping robot operation processing method may include steps 210 to 250, and each step will be introduced below.

[0037] In step 210, the operation data of the cleaning robot in the current time period is collected, wherein the operation data at least includes the position coordinates, acceleration and angular acceleration of the cleaning robot.

[0038] In one embodiment, the operation data of the sweeping robot in the current time period can be collected. In one example, the operation data may include at least the position coordinates, acceleration and angular acceleration of the sweeping robot. Among them, the position coordinates of the sweeping robot in the current time period can be expressed as (x0, y0), and the mobile robot can be positioned by combining image data, depth camera data, lidar data, IMU data, etc., with positioning algorithms and SLAM mapping algorithms; the positioning algorithm and SLAM mapping algorithm can be implemented by relevant technical personnel. In this embodiment, the method for obtaining the position coordinates of the sweeping robot in the current time period is not limited.

[0039] In another example, the acceleration and angular acceleration of the sweeping robot in the current time period are collected, where the acceleration of the sweeping robot in the current time period can be expressed as a(0), and the angular acceleration of the sweeping robot in the current time period can be expressed as α(0). Since the acceleration also exists in the direction of the x and y axes, the corresponding values ​​are ax(0), ay(0). The acceleration a is collected by an accelerometer, and the accelerations ax, ay, and az in the three directions of x, y, and z can be collected. The angular acceleration can be collected and calculated by a gyroscope, and the calculation method is α = (ω1-ω0) / Δt, where ω is the collected angular velocity. Since the rotation angle is required, the angular velocity around the z axis is selected for calculation.

[0040] In step 220, a pre-built motion model of the cleaning robot, a speed constraint of the cleaning robot, and an angular velocity constraint of the cleaning robot are retrieved.

[0041] In another embodiment, a pre-built sweeping robot motion model, a speed constraint on the sweeping robot, and an angular velocity constraint on the sweeping robot may be retrieved. The sweeping robot motion model may be a model that characterizes the operating state and position information of the sweeping robot. It is understandable that the sweeping robot motion model may be used to calculate how the robot should walk, and based on the sweeping robot motion model, possible trajectories within a suitable range of υ and ω (operating speed and operating angular velocity) within a Δt time period may be simulated.

[0042] In step 230 , based on the speed constraint on the cleaning robot and the angular velocity constraint on the cleaning robot, a plurality of groups of combined operating states of the cleaning robot are determined, wherein the combined operating state includes an operating speed and an operating angular velocity.

[0043] In step 240, based on the sweeping robot motion model, the operation data, and the various groups of combined operation states, the various groups of predicted operation trajectories corresponding to the various groups of combined operation states are obtained.

[0044] In another exemplary embodiment of the present invention, based on the sweeping robot motion model, the operation data and each group of the combined operation states, each group of predicted operation trajectories corresponding to each group of the combined operation states is obtained, which can be implemented in the following manner: The operation data and each group of combined operation states are substituted into the sweeping robot motion model to obtain each group of predicted operation trajectories corresponding to each group of combined operation states.

[0045] In another embodiment, the speed constraint of the sweeping robot and the angular velocity constraint of the sweeping robot can be used as the definition domain to determine multiple groups of combined operating states (υ, ω) of the sweeping robots, wherein the combined operating state can include the operating speed and the operating angular velocity. Further, the operating data of the sweeping robot in the current time period collected in step 110 and each group of combined operating states are substituted into the sweeping robot motion model, so that each group of predicted operating trajectories corresponding to each group of combined operating states can be obtained.

[0046] In step 250, a target predicted running trajectory is determined from the multiple groups of predicted running trajectories, and the operation of the sweeping robot in the next time period is controlled according to the target combined running state corresponding to the target predicted running trajectory.

[0047] In another embodiment, a target predicted running trajectory can be determined from multiple groups of predicted running trajectories, that is, an optimal predicted running trajectory is determined, and the target combined running state corresponding to the target predicted running trajectory, that is, the optimal group (υ, ω) is selected as the translation speed and rotation speed at the next time, and the controller is informed of it, and the controller controls the movement of the robot. It is achieved that the target combined running state of the sweeping robot in the next time period can be determined according to the real-time running data of the sweeping robot, so that the operation of the sweeping robot can be efficiently and safely controlled.

[0048] The sweeping robot operation processing method provided by the present invention is applied to the sweeping robot; the method comprises: collecting the operation data of the sweeping robot in the current time period, wherein the operation data at least includes the position coordinates, acceleration and angular acceleration of the sweeping robot; calling the pre-built sweeping robot motion model, the speed constraint on the sweeping robot, and the angular velocity constraint on the sweeping robot; determining the combined operation states of multiple groups of sweeping robots based on the speed constraint on the sweeping robot and the angular velocity constraint on the sweeping robot, wherein the combined operation states include the operation speed and the operation angular velocity; obtaining each group of predicted operation trajectories corresponding to each group of combined operation states based on the sweeping robot motion model, the operation data and each group of combined operation states; determining the target predicted operation trajectory from the multiple groups of predicted operation trajectories, and controlling the operation of the sweeping robot in the next time period according to the target combined operation state corresponding to the target predicted operation trajectory. The method realizes the ability to determine the target combined operation state of the sweeping robot in the next time period according to the real-time operation data of the sweeping robot, thereby enabling the operation of the sweeping robot to be efficiently and safely controlled.

[0049] Figure 3 It is a schematic diagram of the process of constructing a sweeping robot motion model provided by the present invention.

[0050] The following will be combined Figure 3 The process of building a sweeping robot motion model is described.

[0051] In an exemplary embodiment of the present invention, Figure 3 It can be seen that constructing the sweeping robot motion model may include steps 310 to 360, and each step will be introduced below.

[0052] In step 310 , the robot angle orientation of the cleaning robot and the position coordinates of the cleaning robot in the current time period are determined.

[0053] In one embodiment, the robot angle orientation θ of the sweeping robot can be determined, wherein the robot angle orientation θ can be located by combining image data, depth camera data, laser radar data, IMU data, etc., with positioning algorithms and SLAM mapping algorithms, etc. for positioning the mobile robot; the positioning algorithms and SLAM mapping algorithms are implemented by relevant technical personnel and are not limited here. In another embodiment, the position coordinates (x0, y0) of the sweeping robot in the current time period can also be determined.

[0054] In step 320 , based on the running speed, position coordinates, and angular orientation of the cleaning robot, a first change relationship between the position coordinates of the cleaning robot and time is determined.

[0055] In one embodiment, based on the running speed, position coordinates, and angular orientation of the cleaning robot, the first change relationship of the position coordinates of the cleaning robot over time can be determined using formulas (1)-(2): x(t) = x(0) + υx(0).Δt.cos(θ(0))-υy(0).Δt.sin(θ(0)) (1) y(t) = y(0) + υx(0)Δtsin(θ(0))+υy(0)Δtcos(θ(0)) (2) Among them, x(t) and y(t) represent the first change relationship of the position coordinates of the sweeping robot with time; that is, x(t) represents the x-coordinate position of the robot at time t; y(t) represents the y-coordinate position of the robot at time t; x(0) represents the x-coordinate position of the robot at the initial moment (i.e. t=0), that is, the x-coordinate position of the position coordinates of the sweeping robot in the current time period; y(0) represents the y-coordinate position of the robot at the initial moment (i.e. t=0), that is, the y-coordinate position of the position coordinates of the sweeping robot in the current time period; υx(0) represents the translation speed of the robot in the x-axis direction at the initial moment, that is, the component speed of the running speed of the sweeping robot in the x-axis direction; Δt represents the running time; θ(0) represents the orientation angle of the robot at the initial moment (corresponding to the current moment); υy(0) represents the translation speed of the robot in the y-axis direction at the initial moment, that is, the component speed of the running speed of the sweeping robot in the y-axis direction.

[0056] In step 330 , based on the acceleration of the cleaning robot, a second variation relationship between the running speed of the cleaning robot and time is determined.

[0057] In another embodiment, based on the acceleration of the cleaning robot, the second variation relationship between the running speed of the cleaning robot and time can be determined by using formulas (3)-(4): υx(t) = υx(0) + ax(0).Δt (3) υy(t) = υy(0) + ay(0).Δt (4) Among them, υx(t) and υy(t) represent the second variation relationship of the running speed of the sweeping robot with time, that is, υx(t) represents the translation speed of the robot in the x-axis direction at time t; υy(t) represents the translation speed of the robot in the y-axis direction at time t; ax(0) represents the acceleration of the robot in the x-axis direction at the initial moment; ay(0) represents the acceleration of the robot in the y-axis direction at the initial moment. It should be noted that the initial moment represented in this embodiment can be considered as the current time period.

[0058] In step 340 , based on the angular velocity of the cleaning robot, a third change relationship of the robot angular orientation of the cleaning robot over time is determined.

[0059] In another embodiment, based on the angular velocity of the cleaning robot, the third change relationship of the robot angle orientation of the cleaning robot over time can be determined by formula (5): θ(t) = θ(0) + ω(0).Δt (5) Among them, θ(t) represents the third change relationship of the robot angle orientation of the sweeping robot with time, that is, the orientation angle of the robot at time t; ω(0) represents the rotation speed (that is, angular velocity) of the robot at the initial moment.

[0060] In step 350 , based on the angular acceleration of the cleaning robot, a fourth variation relationship between the angular velocity of the cleaning robot and time is determined.

[0061] In yet another embodiment, based on the angular acceleration of the cleaning robot, the fourth variation relationship of the angular velocity of the cleaning robot over time can be determined by formula (6): ω(t) = ω(0) + α(0).Δt (6) Among them, ω(t) represents the fourth change relationship of the angular velocity of the sweeping robot with time, that is, it represents the rotation speed (ie angular velocity) of the robot at time t; α(0) represents the angular acceleration of the robot at the initial moment.

[0062] In step 360, a motion model of the sweeping robot is constructed based on the first change relationship, the second change relationship, the third change relationship, and the fourth change relationship.

[0063] In another embodiment, based on the first change relationship, the second change relationship, the third change relationship, and the fourth change relationship, the motion model of the sweeping robot can be expressed as the aforementioned formulas (1)-(6), that is: x(t) = x(0) + υx(0).Δt.cos(θ(0))-υy(0).Δt.sin(θ(0)) (1) y(t) = y(0) + υx(0)Δtsin(θ(0))+υy(0)Δtcos(θ(0)) (2) υx(t) = υx(0) + ax(0) .Δt (3) υy(t) = υy(0) + ay(0) .Δt (4) θ(t) = θ(0) + ω(0) .Δt (5) ω(t) = ω(0) + α(0) .Δt (6) Figure 4 It is a schematic diagram of the flow of constructing the speed constraint of the sweeping robot provided by the present invention.

[0064] The following will be combined Figure 4 The process of building the speed constraint of the sweeping robot is explained.

[0065] In an exemplary embodiment of the present invention, a cleaning robot is used to clean an area to be cleaned, wherein obstacles exist in the area to be cleaned. Figure 4 It can be seen that constructing the speed constraint on the sweeping robot may include steps 410 to 440, and each step will be introduced below.

[0066] In step 410 , a preset minimum operating speed value and a preset maximum operating speed value are obtained, and a first speed sub-constraint is constructed based on the preset minimum operating speed value and the preset maximum operating speed value.

[0067] In one embodiment, since multiple sets of υ and ω need to be simulated, the range of these two values ​​needs to be determined. According to the hardware conditions and environmental restrictions of the mobile robot, during the application process, the limit of υ can be set to (υmin,υmax) (representing that the range of the running speed should be υmin to υmax). Among them, υmin can represent the preset minimum running speed value; υmax can represent the preset maximum running speed value. Among them, the first speed sub-constraint can be expressed as formula (7): [υmin , υmax] (7) It should be noted that the specific values ​​of υmin and υmax can be adjusted according to actual conditions and are not specifically limited in this embodiment.

[0068] In step 420, the maximum acceleration of the cleaning robot and the initial running speed of the cleaning robot in the current time period are obtained, and a second speed sub-constraint is constructed based on the maximum acceleration and the initial running speed.

[0069] In another embodiment, the limitation of the driving motor of the mobile robot needs to be considered. Therefore, the linear acceleration and angular acceleration of the mobile robot are both subject to boundary limitations. If the maximum acceleration and the maximum deceleration are the same, the limitation of υ is (υ(0) - amax.Δt,υ(0) + amax.Δt), where amax can represent the maximum acceleration; υ(0) represents the initial running speed. The second speed sub-constraint can be expressed as formula (8): [υ(0) - amax . Δt , υ(0) + amax .Δt] (8) Among them, Δt is the time for simulating the trajectory. The specific value of Δt can be set according to the relevant scenario and the actual situation of the robot, and there is no restriction here.

[0070] In step 430, the distance information between the cleaning robot and the obstacle is obtained, and based on the distance information, the maximum acceleration, and the preset minimum running speed value, a third speed sub-constraint is constructed.

[0071] In another embodiment, since the ability to avoid obstacles in real time is required, the surrounding obstacles need to be considered, so the range of υ under the restriction of no collision with obstacles is: (υmin, (2.dist(υ,ω).amax) ½), where dist(υ,ω) is the shortest distance between the corresponding simulation trajectory and the obstacle at the current speed. In another example, the third speed sub-constraint can be expressed by formula (9): [υmin , (2.dist(υ,ω) .amax)½] (9) Among them, υmin represents the preset minimum operating speed value; dist(υ,ω) represents the distance information between the sweeping robot and the obstacle.

[0072] In this embodiment, the maximum speed is the maximum speed at which the robot can stop in front of an obstacle, which is derived from the formula Vt^2 -V0^2 = 2.ax. Dist(υ,ω) calculates the shortest distance between the trajectory and the obstacle. However, due to the existence of angular velocity, the robot does not move in a straight line, but its motion trajectory is an arc. Therefore, when calculating the distance to the obstacle, the arc length can be calculated. The specific calculation method is not limited here.

[0073] In step 440 , a speed constraint for the cleaning robot is constructed based on the first speed sub-constraint, the second speed sub-constraint, and the third speed sub-constraint.

[0074] In another embodiment, the speed constraint of the sweeping robot can be expressed by the formulas (7) to (9) mentioned above, that is, as follows: [υmin , υmax] (7) [υ(0) - amax.Δt , υ(0) + amax.Δt] (8) [υmin , (2. dist(υ,ω) . amax)½] (9) Figure 5 It is a schematic diagram of the process of constructing the angular velocity constraint of the sweeping robot provided by the present invention.

[0075] The following will be combined Figure 5 The process of constructing the angular velocity constraint of the sweeping robot is explained.

[0076] In another exemplary embodiment of the present invention, Figure 5 It can be seen that constructing the angular velocity constraint of the cleaning robot may include steps 510 to 540, and each step will be introduced below.

[0077] In step 510, a preset minimum operating angular velocity value and a preset maximum operating angular velocity value are obtained, and a first angular velocity sub-constraint is constructed based on the preset minimum operating angular velocity value and the preset maximum operating angular velocity value.

[0078] In one embodiment, since multiple sets of υ and ω need to be simulated, the range of these two values ​​needs to be determined. According to the hardware conditions and environmental restrictions of the mobile robot, in the application process, the limit of ω can be set to (ωmin, ωmax) (representing that the range of the operating angular velocity should be ωmin to ωmax). Among them, ωmin can represent the preset minimum operating angular velocity value; ωmax can represent the preset maximum operating angular velocity value. Among them, the first angular velocity sub-constraint can be expressed as formula (10): [(ωmin , (ωmax] (10) It should be noted that the specific values ​​of ωmin and ωmax can be adjusted according to actual conditions and are not specifically limited in this embodiment.

[0079] In step 520, the maximum angular acceleration of the cleaning robot and the initial operating angular velocity of the cleaning robot in the current time period are obtained, and a second angular velocity sub-constraint is constructed based on the maximum angular acceleration and the initial operating angular velocity.

[0080] In another embodiment, the limitation of the driving motor of the mobile robot needs to be considered. Therefore, the linear acceleration and angular acceleration of the mobile robot are both subject to boundary limitations. If the maximum acceleration and the maximum deceleration are the same, the limitation of ω is (ω (0) - αmax.Δt, ω (0) + αmax.Δt), where ω(0) represents the initial running angular velocity; αmax represents the maximum angular acceleration. The second speed sub-constraint can be expressed as formula (11): [ω(0) - αmax .Δt , ω(0) + αmax .Δt] (11) Among them, Δt is the time for simulating the trajectory. The specific value of Δt can be set according to the relevant scenario and the actual situation of the robot, and there is no restriction here.

[0081] In step 530, the distance information between the cleaning robot and the obstacle is obtained, and a third angular velocity sub-constraint is constructed based on the distance information, the maximum angular acceleration, and the preset minimum operating angular velocity value.

[0082] In another embodiment, since the ability to avoid obstacles in real time is required, the surrounding obstacles need to be considered, so the range of ω without collision with obstacles is: (ωmin, (2. dist(υ, ω) . αmax) ½), where dist(υ, ω) is the shortest distance between the corresponding simulation trajectory and the obstacle at the current speed. In another example, the third angular velocity sub-constraint can be expressed by formula (12): [ωmin , (2. dist(υ,ω) . αmax)½] (12) Among them, ωmin represents the preset minimum operating angular velocity value; dist(υ,ω) represents the distance information between the sweeping robot and the obstacle.

[0083] In step 540, an angular velocity constraint for the cleaning robot is constructed based on the first angular velocity sub-constraint, the second angular velocity sub-constraint, and the third angular velocity sub-constraint.

[0084] In another embodiment, the angular velocity constraint of the cleaning robot can be expressed by the formulas (10)-(12) mentioned above, that is, as follows: [(ωmin , (ωmax] (10) [ω(0) - αmax .Δt , ω(0) + αmax.Δt] (11) [ωmin , (2. dist(υ,ω) . αmax)½] (12) In another exemplary embodiment of the present invention, continuing with the above Figure 2 The above embodiment is used as an example for explanation, wherein determining a target predicted running trajectory from a plurality of groups of predicted running trajectories can be implemented in the following manner: Based on each group of predicted running trajectories, determining a trajectory evaluation score corresponding to each group of predicted running trajectories; The predicted running trajectory corresponding to the highest trajectory evaluation score is taken as the target predicted running trajectory.

[0085] In one embodiment, the trajectory evaluation scores corresponding to each group of predicted running trajectories may be determined respectively. Further, the predicted running trajectory with the highest trajectory evaluation score is determined in each group of predicted running trajectories, and the predicted running trajectory with the highest trajectory evaluation score is used as the target predicted running trajectory, that is, the optimal predicted running trajectory.

[0086] Figure 6 It is a flow chart of determining the trajectory evaluation score corresponding to each group of predicted running trajectories based on each group of predicted running trajectories provided by the present invention.

[0087] The following will be combined Figure 6 A process of determining a trajectory evaluation score corresponding to each group of the predicted operation trajectories based on each group of the predicted operation trajectories will be described.

[0088] In another exemplary embodiment of the present invention, Figure 6 It can be seen that, based on each group of predicted running trajectories, determining the trajectory evaluation score corresponding to each group of predicted running trajectories may include steps 610 to 640, and each step will be introduced below.

[0089] In step 610, based on each group of predicted running trajectories, each angle formed between each group of predicted running trajectories and the cleaning robot is obtained, and according to each angle, each angle evaluation score corresponding to each angle is obtained.

[0090] In step 620, based on each group of predicted running trajectories, each distance formed between each group of predicted running trajectories and the area target point of the area to be cleaned is obtained, and according to each distance, each distance evaluation score corresponding to each distance is obtained.

[0091] In step 630, based on each group of predicted running trajectories, each running speed corresponding to each group of predicted running trajectories is obtained, and according to each running speed, each speed evaluation score corresponding to each running speed is obtained.

[0092] In step 640 , based on the angle evaluation scores, the distance evaluation scores, and the speed evaluation scores, the trajectory evaluation scores corresponding to the groups of predicted running trajectories are determined.

[0093] In one embodiment, for example, to obtain the target predicted running trajectory, multiple aspects can be evaluated, and the three points of the angle between the predicted running trajectory and the current robot, the distance between the target trajectory and the obstacle, and the speed that the predicted running trajectory can reach can be selected as evaluation indicators, that is, each angle evaluation score corresponding to each angle, each distance evaluation score corresponding to each distance, and each speed evaluation score corresponding to each running speed can be obtained respectively. Therefore, based on each angle evaluation score, each distance evaluation score, and each speed evaluation score, the trajectory evaluation score corresponding to each group of predicted running trajectories can be determined.

[0094] In another embodiment, the trajectory evaluation score corresponding to each group of predicted running trajectories can be expressed as formula (13): G(υ,ω)=σ(a⋅h(υ,ω)+b⋅d(υ,ω)+c⋅v(υ,ω)) (13) Among them, G(υ,ω) can represent the trajectory evaluation score corresponding to each group of predicted running trajectories; h(υ,ω) is the angle between the predicted trajectory end point and the target point, that is, the angle evaluation score corresponding to each angle; a is the weight value of the evaluation index; d(υ,ω) is the distance between the predicted trajectory and the obstacle, that is, the distance evaluation score corresponding to each distance; b is the weight value of the evaluation index; v(υ,ω) is the speed that the predicted trajectory can reach, that is, the speed evaluation score corresponding to each running speed; c is the weight value of the evaluation index; σ is the normalization of the three evaluation indicators to ensure that the indicators are at the same percentage.

[0095] Among them, for h(υ,ω), that is, the angle between the predicted end point of the trajectory and the target point, in order to make the robot consume less energy by rotating at a large angle, we set the angle here to be no more than 110° different from the current angle θ. If it exceeds this value, the trajectory will be cleared.

[0096] The normalized σ operation method can be the sum of all predicted values ​​of a single indicator / single evaluation indicator. Since the units of angle, speed, and obstacle distance are not the same, the above operation is performed on each indicator, converted into a percentage, and then multiplied by the corresponding weight.

[0097] According to the foregoing description, the sweeping robot operation processing method provided by the present invention determines a sampling speed space that satisfies the hardware constraints of the mobile robot in the speed space (v, ω) according to the current position state and speed state of the mobile robot, and then calculates the trajectory (multiple trajectories) of the mobile robot moving within a certain period of time under these speed conditions, and evaluates the trajectory through an evaluation function, and finally selects the speed corresponding to the best evaluated trajectory as the movement speed of the mobile robot, and gives the speed to the controller to control the robot to move along the planned trajectory. The purpose is to provide a path that is optimal and not prone to encounter obstacles to the target point. The method of the present invention improves the real-time response capability of the sweeping robot and its robustness in uncertain environments.

[0098] The following is a description of the sweeping robot operation processing virtual device provided by the present invention. The sweeping robot operation processing virtual device described below and the sweeping robot operation processing method described above can be referenced to each other.

[0099] Figure 7 It is a structural diagram of the sweeping robot operation processing virtual device provided by the present invention.

[0100] The following will be combined Figure 7The structure of the sweeping robot operation processing virtual device provided by the present invention is described.

[0101] In an exemplary embodiment of the present invention, the cleaning robot operation processing virtual device can be applied to the cleaning robot. Figure 7 It can be seen that the sweeping robot operation processing virtual device may include a collection module 710, a retrieval module 720, a determination module 730, a processing module 740, and a control module 750, and each module will be introduced below.

[0102] The collection module 710 may be configured to collect the operation data of the cleaning robot in the current time period, wherein the operation data at least includes the position coordinates, acceleration and angular acceleration of the cleaning robot; The retrieval module 720 may be configured to retrieve a pre-built sweeping robot motion model, a velocity constraint on the sweeping robot, and an angular velocity constraint on the sweeping robot, wherein the sweeping robot motion model is a model that characterizes the operating state and position information of the sweeping robot; The determination module 730 may be configured to determine a plurality of groups of combined operating states of the cleaning robot based on a speed constraint on the cleaning robot and an angular velocity constraint on the cleaning robot, wherein the combined operating state includes an operating speed and an operating angular velocity; The processing module 740 may be configured to obtain each group of predicted operation trajectories corresponding to each group of the combined operation states based on the motion model of the cleaning robot, the operation data and each group of the combined operation states; The control module 750 may be configured to determine a target predicted operation trajectory from the plurality of groups of predicted operation trajectories, and control the operation of the sweeping robot in the next time period according to a target combined operation state corresponding to the target predicted operation trajectory.

[0103] In an exemplary embodiment of the present invention, the retrieval module 720 can construct the sweeping robot motion model in the following manner: Determine the robot angle orientation of the cleaning robot and the position coordinates of the cleaning robot in the current time period; Determine a first change relationship between the position coordinates of the cleaning robot and time based on the running speed of the cleaning robot, the position coordinates, and the angular orientation of the robot; Determining a second variation relationship between the running speed of the cleaning robot and time based on the acceleration of the cleaning robot; Determining a third change relationship of the robot angle orientation of the cleaning robot over time based on the angular velocity of the cleaning robot; Based on the angular acceleration of the cleaning robot, determining a fourth change relationship of the angular velocity of the cleaning robot over time; Based on the first change relationship, the second change relationship, the third change relationship, and the fourth change relationship, a motion model of the sweeping robot is constructed.

[0104] In an exemplary embodiment of the present invention, the cleaning robot is used to clean an area to be cleaned, and there are obstacles in the area to be cleaned; the calling module 720 can implement the construction of the speed constraint of the cleaning robot in the following manner: Acquire a preset minimum operating speed value and a preset maximum operating speed value, and construct a first speed sub-constraint based on the preset minimum operating speed value and the preset maximum operating speed value; Acquire the maximum acceleration of the cleaning robot and the initial running speed of the cleaning robot in the current time period, and construct a second speed sub-constraint based on the maximum acceleration and the initial running speed; Acquire distance information between the cleaning robot and the obstacle, and construct a third speed sub-constraint based on the distance information, the maximum acceleration, and the preset minimum running speed value; Based on the first speed sub-constraint, the second speed sub-constraint, and the third speed sub-constraint, a speed constraint for the cleaning robot is constructed.

[0105] In an exemplary embodiment of the present invention, the calling module 720 may construct the angular velocity constraint of the cleaning robot in the following manner: Acquire a preset minimum running angular velocity value, and acquire a preset maximum running angular velocity value, and construct a first angular velocity sub-constraint based on the preset minimum running angular velocity value and the preset maximum running angular velocity value; Acquire the maximum angular acceleration of the cleaning robot and the initial operating angular velocity of the cleaning robot in the current time period, and construct a second angular velocity sub-constraint based on the maximum angular acceleration and the initial operating angular velocity; Acquire distance information between the cleaning robot and the obstacle, and construct a third angular velocity sub-constraint based on the distance information, the maximum angular acceleration, and the preset minimum operating angular velocity value; Based on the first angular velocity sub-constraint, the second angular velocity sub-constraint, and the third angular velocity sub-constraint, an angular velocity constraint for the cleaning robot is constructed.

[0106] In an exemplary embodiment of the present invention, the processing module 740 can obtain each group of predicted operation trajectories corresponding to each group of the combined operation states based on the sweeping robot motion model, the operation data and each group of the combined operation states in the following manner: The operation data and each group of the combined operation states are substituted into the motion model of the sweeping robot to obtain each group of predicted operation trajectories corresponding to each group of the combined operation states.

[0107] In an exemplary embodiment of the present invention, the control module 750 may determine the target predicted running trajectory from the plurality of groups of predicted running trajectories in the following manner: Based on the predicted running trajectories of each group, determining a trajectory evaluation score corresponding to the predicted running trajectories of each group; The predicted running trajectory corresponding to the highest trajectory evaluation score is used as the target predicted running trajectory.

[0108] In an exemplary embodiment of the present invention, the control module 750 may determine the trajectory evaluation score corresponding to each group of the predicted running trajectories based on each group of the predicted running trajectories in the following manner: Based on each group of the predicted running trajectories, each angle formed between each group of the predicted running trajectories and the sweeping robot is obtained, and according to each of the angles, each angle evaluation score corresponding to each of the angles is obtained; Based on each group of predicted running trajectories, obtaining each distance formed between each group of predicted running trajectories and the regional target point of the area to be cleaned, and obtaining each distance evaluation score corresponding to each distance according to each distance; Based on each group of the predicted running trajectories, each running speed corresponding to each group of the predicted running trajectories is obtained, and according to each of the running speeds, each speed evaluation score corresponding to each of the running speeds is obtained; Based on the various angle evaluation scores, the various distance evaluation scores, and the various speed evaluation scores, a trajectory evaluation score corresponding to each group of the predicted operating trajectories is determined.

[0109] Based on the same inventive concept, the present invention also provides a sweeping robot, and the structure of the sweeping robot will be described below in conjunction with the following embodiments.

[0110] In an exemplary embodiment of the present invention, the sweeping robot may include: a sweeping robot body, and a processor, wherein the processor is used to execute the sweeping robot operation processing method described in any of the above embodiments. Through this embodiment, it is possible to determine the target combined operation state of the sweeping robot in the next time period based on the real-time operation data of the sweeping robot, thereby enabling efficient and safe control of the operation of the sweeping robot.

[0111] Figure 8 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 8 As shown, the electronic device may include: a processor (processor) 810, a communication interface (Communications Interface) 820, a memory (memory) 830 and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other through the communication bus 840. The processor 810 can call the logic instructions in the memory 830 to execute the sweeping robot operation processing method, which is applied to the sweeping robot; the method includes: collecting the operation data of the sweeping robot in the current time period, wherein the operation data at least includes the position coordinates, acceleration and angular acceleration of the sweeping robot; calling the pre-built sweeping robot motion model, the speed constraint on the sweeping robot, and the angular velocity constraint on the sweeping robot, wherein the sweeping robot motion model is a model that characterizes the operation state and position information of the sweeping robot; based on the speed constraint on the sweeping robot and the angular velocity constraint on the sweeping robot, determining multiple groups of combined operation states of the sweeping robot, wherein the combined operation state includes an operation speed and an operation angular velocity; based on the sweeping robot motion model, the operation data and each group of the combined operation states, obtaining each group of predicted operation trajectories corresponding to each group of the combined operation states; determining a target predicted operation trajectory from the multiple groups of the predicted operation trajectories, and controlling the operation of the sweeping robot in the next time period according to the target combined operation state corresponding to the target predicted operation trajectory.

[0112] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0113] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the sweeping robot operation processing method provided by the above methods, and the method is applied to the sweeping robot; the method includes: collecting the operation data of the sweeping robot in the current time period, wherein the operation data at least includes the position coordinates, acceleration and angular acceleration of the sweeping robot; calling a pre-built sweeping robot motion model, a speed constraint on the sweeping robot, and an angular velocity constraint on the sweeping robot, wherein the The motion model of the sweeping robot is a model that characterizes the operating state and position information of the sweeping robot; based on the speed constraint of the sweeping robot and the angular velocity constraint of the sweeping robot, multiple groups of combined operating states of the sweeping robot are determined, wherein the combined operating state includes an operating speed and an operating angular velocity; based on the sweeping robot motion model, the operating data and each group of the combined operating states, each group of predicted operating trajectories corresponding to each group of the combined operating states is obtained; a target predicted operating trajectory is determined from the multiple groups of predicted operating trajectories, and the operation of the sweeping robot in the next time period is controlled according to the target combined operating state corresponding to the target predicted operating trajectory.

[0114] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the sweeping robot operation processing method provided by the above-mentioned methods, and the method is applied to a sweeping robot; the method comprises: collecting operation data of the sweeping robot in a current time period, wherein the operation data at least includes the position coordinates, acceleration and angular acceleration of the sweeping robot; calling a pre-built sweeping robot motion model, a speed constraint on the sweeping robot, and an angular velocity constraint on the sweeping robot, wherein the sweeping robot motion model is a method for characterizing the sweeping robot. A model of the running state and position information of the sweeping robot; based on the speed constraint of the sweeping robot and the angular velocity constraint of the sweeping robot, determining multiple groups of combined running states of the sweeping robot, wherein the combined running state includes the running speed and the running angular velocity; based on the sweeping robot motion model, the running data and each group of the combined running states, obtaining each group of predicted running trajectories corresponding to each group of the combined running states; determining a target predicted running trajectory from the multiple groups of the predicted running trajectories, and controlling the operation of the sweeping robot in the next time period according to the target combined running state corresponding to the target predicted running trajectory.

[0115] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0116] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention 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 invention.

Claims

1. A method for processing the operation of a sweeping robot, characterized in that: The method is applied to a sweeping robot; the method comprises: Collecting operation data of the cleaning robot in the current time period, wherein the operation data at least includes the position coordinates, acceleration and angular acceleration of the cleaning robot; Retrieving a pre-built sweeping robot motion model, a velocity constraint on the sweeping robot, and an angular velocity constraint on the sweeping robot, wherein the sweeping robot motion model is a model that characterizes the operating state and position information of the sweeping robot; Based on the speed constraint on the cleaning robot and the angular velocity constraint on the cleaning robot, determining a plurality of groups of combined operating states of the cleaning robot, wherein the combined operating states include operating speeds and operating angular velocities; Based on the sweeping robot motion model, the operation data and the groups of combined operation states, obtaining groups of predicted operation trajectories corresponding to the groups of combined operation states; A target predicted running trajectory is determined from the multiple groups of predicted running trajectories, and the operation of the sweeping robot in the next time period is controlled according to the target combined running state corresponding to the target predicted running trajectory.

2. The sweeping robot operation processing method according to claim 1, characterized in that: The sweeping robot motion model is constructed in the following way: Determine the robot angle orientation of the cleaning robot and the position coordinates of the cleaning robot in the current time period; Determine a first change relationship between the position coordinates of the cleaning robot and time based on the running speed of the cleaning robot, the position coordinates, and the angular orientation of the robot; Determining a second variation relationship between the running speed of the cleaning robot and time based on the acceleration of the cleaning robot; Determining a third change relationship of the robot angle orientation of the cleaning robot over time based on the angular velocity of the cleaning robot; Based on the angular acceleration of the cleaning robot, determining a fourth change relationship of the angular velocity of the cleaning robot over time; Based on the first change relationship, the second change relationship, the third change relationship, and the fourth change relationship, a motion model of the sweeping robot is constructed.

3. The sweeping robot operation processing method according to claim 1, characterized in that: The sweeping robot is used to sweep an area to be swept, and there are obstacles in the area to be swept. The speed constraint of the sweeping robot is constructed in the following manner: Acquire a preset minimum operating speed value and a preset maximum operating speed value, and construct a first speed sub-constraint based on the preset minimum operating speed value and the preset maximum operating speed value; Acquire the maximum acceleration of the cleaning robot and the initial running speed of the cleaning robot in the current time period, and construct a second speed sub-constraint based on the maximum acceleration and the initial running speed; Acquire distance information between the cleaning robot and the obstacle, and construct a third speed sub-constraint based on the distance information, the maximum acceleration, and the preset minimum running speed value; Based on the first speed sub-constraint, the second speed sub-constraint, and the third speed sub-constraint, a speed constraint for the cleaning robot is constructed.

4. The sweeping robot operation processing method according to claim 3, characterized in that: The angular velocity constraint of the sweeping robot is constructed in the following manner: Acquire a preset minimum running angular velocity value, and acquire a preset maximum running angular velocity value, and construct a first angular velocity sub-constraint based on the preset minimum running angular velocity value and the preset maximum running angular velocity value; Acquire the maximum angular acceleration of the cleaning robot and the initial operating angular velocity of the cleaning robot in the current time period, and construct a second angular velocity sub-constraint based on the maximum angular acceleration and the initial operating angular velocity; Acquire distance information between the cleaning robot and the obstacle, and construct a third angular velocity sub-constraint based on the distance information, the maximum angular acceleration, and the preset minimum operating angular velocity value; Based on the first angular velocity sub-constraint, the second angular velocity sub-constraint, and the third angular velocity sub-constraint, an angular velocity constraint for the cleaning robot is constructed.

5. The sweeping robot operation processing method according to any one of claims 1 to 4, characterized in that: The obtaining, based on the sweeping robot motion model, the operation data and each group of the combined operation states, each group of predicted operation trajectories corresponding to each group of the combined operation states specifically includes: The operation data and each group of the combined operation states are substituted into the motion model of the sweeping robot to obtain each group of predicted operation trajectories corresponding to each group of the combined operation states.

6. The sweeping robot operation processing method according to any one of claims 1 to 4, characterized in that: Determining a target predicted running trajectory from a plurality of groups of predicted running trajectories is achieved in the following manner: Based on the predicted running trajectories of each group, determining a trajectory evaluation score corresponding to the predicted running trajectories of each group; The predicted running trajectory corresponding to the highest trajectory evaluation score is used as the target predicted running trajectory.

7. The sweeping robot operation processing method according to claim 6, characterized in that: The determining, based on each group of the predicted running trajectories, a trajectory evaluation score corresponding to each group of the predicted running trajectories specifically includes: Based on each group of the predicted running trajectories, each angle formed between each group of the predicted running trajectories and the sweeping robot is obtained, and according to each of the angles, each angle evaluation score corresponding to each of the angles is obtained; Based on each group of predicted running trajectories, obtaining each distance formed between each group of predicted running trajectories and the regional target point of the area to be cleaned, and obtaining each distance evaluation score corresponding to each distance according to each distance; Based on each group of the predicted running trajectories, each running speed corresponding to each group of the predicted running trajectories is obtained, and according to each of the running speeds, each speed evaluation score corresponding to each of the running speeds is obtained; Based on the various angle evaluation scores, the various distance evaluation scores, and the various speed evaluation scores, a trajectory evaluation score corresponding to each group of the predicted operating trajectories is determined.

8. A sweeping robot, characterized in that: The sweeping robot comprises: The robot vacuum cleaner, and A processor, wherein the processor is used to execute the sweeping robot operation processing method according to any one of claims 1 to 7.

9. A sweeping robot operation processing virtual device, characterized in that: The virtual device is applied to a sweeping robot; The virtual device comprises: A collection module, used to collect the operation data of the cleaning robot in the current time period, wherein the operation data at least includes the position coordinates, acceleration and angular acceleration of the cleaning robot; A calling module, used to call a pre-built sweeping robot motion model, a speed constraint on the sweeping robot, and an angular velocity constraint on the sweeping robot, wherein the sweeping robot motion model is a model that characterizes the operating state and position information of the sweeping robot; A determination module, configured to determine a plurality of groups of combined operating states of the cleaning robot based on a speed constraint on the cleaning robot and an angular velocity constraint on the cleaning robot, wherein the combined operating states include an operating speed and an operating angular velocity; A processing module, configured to obtain each group of predicted operation trajectories corresponding to each group of the combined operation states based on the motion model of the sweeping robot, the operation data and each group of the combined operation states; The control module is used to determine a target predicted running trajectory from the multiple groups of predicted running trajectories, and control the operation of the sweeping robot in the next time period according to the target combined running state corresponding to the target predicted running trajectory.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the cleaning robot operation processing method according to any one of claims 1 to 7 is implemented.

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