Mobile air conditioner and path planning method thereof, and computer-readable storage medium

Abstract

The present invention discloses a path planning method for a mobile air conditioner, comprising: obtaining target movement parameters for the mobile air conditioner; determining a target optimization model corresponding to an initial curve function; the initial curve function representing the correspondence between time and position during the movement of the mobile air conditioner, the conversion parameters between time and position in the initial curve function being parameters whose values ​​are to be determined, the target optimization model being a function that optimizes the conversion parameters with the goal of minimizing the change in jerk of the mobile air conditioner; determining a target value for the conversion parameter based on the target movement parameters and the target optimization model; and determining the initial curve function with the conversion parameter at the target value as the target curve function representing the target path. The present invention also discloses a mobile air conditioner and a computer-readable storage medium. The present invention aims to improve the mechanical performance and lifespan of a mobile air conditioner.

Description

Technical Field

[0001] The present invention relates to the technical field of air conditioning, and in particular to a path planning method, a mobile air conditioner and a computer-readable storage medium. Background Art

[0002] With the development of economy and technology, air conditioners are becoming more and more widely used, and their performance is constantly being optimized. Among them, some mobile air conditioners have autonomous mobility functions. They obtain a map of their environment, plan a path based on set rules on the map, and then move autonomously along the planned path.

[0003] Currently, when a mobile air conditioner performs path planning, it generally obtains a grid map of its environment and searches for a path based on the scene status represented by each grid on the grid map. The searched path is obtained by connecting grids that meet the traffic requirements by line segments. The path is generally a broken line. When the mobile air conditioner is controlled to operate according to the planned path, poor operation smoothness can easily cause the internal components of the mobile air conditioner to loosen or malfunction, affecting the mechanical performance and life of the mobile air conditioner. Summary of the Invention

[0004] The main purpose of the present invention is to provide a path planning method, a mobile air conditioner and a computer-readable storage medium, aiming to improve the mechanical performance and life of the mobile air conditioner.

[0005] To achieve the above object, the present invention provides a path planning method for a mobile air conditioner, the path planning method comprising the following steps:

[0006] Obtaining target movement parameters of the mobile air conditioner;

[0007] Determining a target optimization model corresponding to an initial curve function; the initial curve function represents the corresponding relationship between time and position during the movement of the mobile air conditioner, the conversion parameter between the time and the position in the initial curve function is a parameter whose value is to be determined, and the target optimization model is a function that optimizes the conversion parameter with the goal of minimizing the change in the acceleration of the mobile air conditioner;

[0008] determining a target value of the conversion parameter according to the target movement parameter and the target optimization model;

[0009] The initial curve function whose conversion parameter is the target value is determined as a target curve function, and the target curve function represents a target path planned by the mobile air conditioner.

[0010] Optionally, the target movement parameter includes a target total duration for the mobile air conditioner to move along the target path, and the step of determining the target optimization model corresponding to the initial curve function includes:

[0011] calculating a fourth-order derivative of the initial curve function with respect to the time, wherein the fourth-order derivative represents a quantitative relationship between a change in the jerk and the time;

[0012] The target optimization model is determined according to the target total duration and the fourth-order derivative.

[0013] Optionally, the target path includes multiple sub-paths, the initial curve function includes multiple sub-curve functions, the sub-paths correspond to the sub-curve functions one-to-one, the sub-curve functions represent the corresponding relationship between time and position of the mobile air conditioner during movement of the corresponding sub-path, the fourth-order derivative includes a sub-fourth-order derivative of each sub-curve function, and the step of determining the target optimization model based on the target total duration and the fourth-order derivative includes:

[0014] Determine a target time period for each sub-path movement according to the target total duration and the number of the sub-paths;

[0015] The target optimization model is determined according to the plurality of target time periods and their corresponding fourth-order sub-derivatives.

[0016] Optionally, before the step of determining the target time period for each sub-path to move according to the total duration and the number of the sub-paths, the method further includes:

[0017] Obtaining obstacle information of the space where the mobile air conditioner is located;

[0018] The number of the sub-paths is determined according to the obstacle information.

[0019] Optionally, the conversion parameters include sub-conversion parameters between time and position in each of the sub-curve functions, and the step of determining target values ​​of the conversion parameters according to the target movement parameters and the target optimization model includes:

[0020] Determining the equality constraint relationship corresponding to the target optimization model according to the target movement parameters;

[0021] The target optimization model is solved by a quadratic programming algorithm with the equality constraint relationship as a constraint to obtain a sub-target value corresponding to each sub-conversion parameter.

[0022] Optionally, the target movement parameters further include a target position of an endpoint of each subpath, a speed, an acceleration, and / or a jerk of each target position, and the step of determining the equality constraint relationship corresponding to the target optimization model based on the target movement parameters includes:

[0023] Taking the target position, the velocity, the acceleration and / or the jerk as known quantities of derivatives of target orders of corresponding sub-curve functions, a first equality constraint relationship is obtained;

[0024] Based on the target positions, velocities, accelerations, and / or jerks corresponding to endpoints connected by two adjacent subpaths being equal, an optimization result of a quantitative relationship between derivatives of target orders of sub-curve functions corresponding to two adjacent subpaths is established to obtain a second equality constraint relationship;

[0025] The first equality constraint relationship and the second equality constraint relationship are combined to obtain the equality constraint relationship.

[0026] Optionally, the step of solving the target optimization model by a quadratic programming algorithm with the equality constraint relationship as a constraint to obtain a sub-target value corresponding to each sub-conversion parameter includes:

[0027] Inputting the equality constraint relationship and the target optimization model into a preset algorithm model, wherein the preset algorithm model is an operation model of the quadratic programming algorithm constructed according to the size of the mobile air conditioner;

[0028] The result output by the preset algorithm model is obtained as the target value.

[0029] Optionally, the step of obtaining the target movement parameter of the mobile air conditioner includes:

[0030] Obtaining the air outlet direction of the mobile air conditioner and the position of a human body within the active space of the mobile air conditioner;

[0031] The target movement parameter is determined according to the air outlet direction and the human body position.

[0032] In addition, in order to achieve the above-mentioned purpose, the present application also proposes a mobile air conditioner, which includes: a memory, a processor, and a path planning program stored on the memory and runnable on the processor. When the path planning program is executed by the processor, the steps of the path planning method described in any one of the above items are implemented.

[0033] In addition, in order to achieve the above-mentioned purpose, the present application also proposes a computer-readable storage medium, on which a path planning program is stored. When the path planning program is executed by a processor, the steps of the path planning method described in any one of the above items are implemented.

[0034] The present invention proposes a path planning method for a mobile air conditioner. The method converts an initial curve function, which characterizes the correspondence between time and position during the movement of the mobile air conditioner and has undetermined conversion parameters, into a target optimization model that optimizes the conversion parameters with the goal of minimizing the change in jerk. The target movement parameters of the mobile air conditioner and the target optimization model are then combined to determine the target values ​​of the conversion parameters. The initial curve function with the conversion parameters as the target values ​​is used as the target path for characterizing the planned mobile air conditioner. In this process, based on the movement path represented by the initial curve function as a curve, the movement path of the mobile air conditioner is optimized by an optimization method with the goal of minimizing jerk in combination with actual target movement parameters. This minimizes the change in jerk during the movement of the mobile air conditioner, ensures that the speed of the mobile air conditioner does not undergo a sudden change due to a sudden change in the path direction during the movement, and thus ensures that the obtained target path is continuous and smooth. Compared with a broken line path, the smoothness of the mobile air conditioner's operation can be effectively improved, loosening or failure of internal components of the mobile air conditioner can be avoided, and the mechanical performance and life of the mobile air conditioner can be effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a schematic diagram of the hardware structure involved in the operation of an embodiment of a mobile air conditioner of the present invention;

[0036] Figure 2 This is a flow chart of an embodiment of a path planning method of the present invention;

[0037] Figure 3 A schematic flow chart of another embodiment of the path planning method of the present invention;

[0038] Figure 4 FIG. 4 is a flow chart of another embodiment of the path planning method of the present invention.

[0039] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0040] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0041] The main solution of an embodiment of the present invention is: obtaining the target moving parameters of the mobile air conditioner; determining the target optimization model corresponding to the initial curve function; the initial curve function represents the correspondence between time and position during the movement of the mobile air conditioner, the conversion parameter between the time and the position in the initial curve function is a parameter whose value is to be determined, and the target optimization model is a function that optimizes the conversion parameter with the goal of minimizing the change value of the acceleration of the mobile air conditioner; determining the target value of the conversion parameter based on the target moving parameters and the target optimization model; determining the initial curve function with the conversion parameter as the target value as the target curve function, and the target curve function represents the target path planned by the mobile air conditioner.

[0042] In the prior art, when a mobile air conditioner performs path planning, a grid map of its environment is generally obtained first, and a path is searched based on the scene status represented by each grid on the grid map. The searched path is obtained by connecting grids that meet the traffic requirements by line segments. The path is generally a broken line. When the mobile air conditioner is controlled to operate according to the planned path, poor operation smoothness can easily cause loosening or failure of internal components of the mobile air conditioner, affecting the mechanical performance and life of the mobile air conditioner.

[0043] The present invention provides the above-mentioned solution, aiming to improve the mechanical performance and life of the mobile air conditioner.

[0044] An embodiment of the present invention provides a mobile air conditioner, which is a mobile device that uses a heat pump system to regulate air temperature.

[0045] In this embodiment, referring to Figure 1 The mobile air conditioner includes a control device, which includes a processor 1001 (e.g., a CPU), a memory 1002, and the like. The memory 1002 can be a high-speed RAM memory or a non-volatile memory such as a disk drive. The memory 1002 can also be a storage device independent of the processor 1001.

[0046] Those skilled in the art will understand that Figure 1 The device structure shown in the figure does not constitute a limitation of the device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0047] like Figure 1 As shown, the memory 1002 as a computer readable storage medium may include a path planning program. Figure 1 In the device shown, the processor 1001 can be used to call the path planning program stored in the memory 1002 and execute the relevant steps of the path planning method in the following embodiments.

[0048] Specifically, refer to Figure 1 The mobile air conditioner may include a heat pump device 1 and a motion device 2. The heat pump device 1 includes components such as a compressor, a heat exchanger, and a throttling device. The motion device 2 includes related structures required for the movement of the mobile device, such as casters, a drive motor, and a transmission structure connecting the casters and the drive motor. The heat pump device 1 and the motion device 2 are both connected to a control device. The control device can control the operation of the heat pump device 1 to achieve ambient air conditioning, and the control device can control the operation of the motion device 2 to control the movement of the mobile air conditioner in whole or in part.

[0049] In one embodiment, the heat pump device 1 and the motion device 2 can be integrated and installed in the same housing to form an air conditioner in which the heat pump device 1 and the motion device 2 are movable as a whole. In another embodiment, the heat pump module and the motion device 2 can be separately provided to form an air conditioner in which the motion device 2 can be moved independently of the heat pump module. For example, when the air conditioner includes a fixed main unit equipped with a heat pump system and a movable sub-unit with air treatment functions (such as purification, sterilization, aromatherapy, humidification, heating, dehumidification and / or cleaning, etc.), the sub-unit in the air conditioner can serve as the motion device 2 here, and the main unit can serve as the heat pump device 1.

[0050] Furthermore, in another embodiment of the mobile air conditioner, the detection module 3 is used to collect scene information of the space where the mobile air conditioner is located, and to construct a map of the space where the mobile air conditioner is located based on the collected scene information. In this embodiment, the detection module 3 is a light detection module 3 (such as a lidar). In other embodiments, the detection module 3 can also be configured as another type of detection module 3, such as a camera, based on actual needs. The aforementioned control device can be connected to the detection module 3 to construct a map of the space where the mobile air conditioner is located based on the detection information provided by the detection module 3.

[0051] Furthermore, in another embodiment of the mobile air conditioner, the mobile air conditioner may further include a navigation module 4, which is specifically configured to locate the mobile air conditioner and provide location data support for the movement of the mobile air conditioner. The aforementioned control device may be connected to the navigation module 4 to obtain the location of the mobile air conditioner based on the positioning information of the navigation module 4, and may also control the mobile air conditioner to operate along a planned route based on the positioning information of the navigation module 4.

[0052] Furthermore, in yet another embodiment of the mobile air conditioner, the mobile air conditioner may further include an air processing module 5 (e.g., a purification module, an aromatherapy module, a sterilization module, a humidification module, a heating module, and / or a dehumidification module). The air processing module 5 may be used to condition the air. The aforementioned control device may be connected to the air processing module 5 to control the operation of the air processing module 5.

[0053] An embodiment of the present invention further provides a path planning method, which is applied to the above-mentioned mobile air conditioner to plan the path of the mobile air conditioner.

[0054] Reference Figure 2 , an embodiment of the path planning method of the present application is proposed. In this embodiment, the path planning method includes:

[0055] Step S10, obtaining target movement parameters of the mobile air conditioner;

[0056] The target movement parameter here specifically refers to the target value that the movement parameter of the mobile air conditioner needs to reach when it moves along the target path obtained in the subsequent plan.

[0057] The movement parameters specifically include the total time, speed, acceleration, jerk and / or one or more spatial positions required to complete the target path movement, etc.

[0058] The target movement parameter may be a preset parameter, a parameter determined based on the actual operation of the mobile air conditioner, or a parameter determined based on a user control instruction.

[0059] Step S20: determining a target optimization model corresponding to an initial curve function; the initial curve function represents the correspondence between time and position during movement of the mobile air conditioner; a conversion parameter between time and position in the initial curve function is a parameter whose value is to be determined; and the target optimization model is a function that optimizes the conversion parameter with the goal of minimizing a change in the jerk of the mobile air conditioner;

[0060] The initial curve function is a curve function with time as the independent variable and the position of the mobile air conditioner as the dependent variable. This curve function can represent the movement path formed by connecting the positions of the mobile air conditioner at different times during its movement. Because it is a curve function, the movement path of the mobile air conditioner represented by it is a curved path.

[0061] The conversion parameter is specifically a parameter in the initial curve function used to determine the position of the mobile air conditioner corresponding to a time. The conversion parameter can have an initial value or an unknown number. There can be one or more conversion parameters.

[0062] The initial curve function can be a pre-set fixed curve function or a curve function determined based on scene information of the space in which the mobile air conditioner is located. In this embodiment, the initial curve function is a multi-order polynomial, and the conversion parameters are the coefficients of each term in the multi-order polynomial. Specifically, in this embodiment, the initial curve function is as follows:

[0063]

[0064] Among them, pi is a conversion parameter whose value is to be determined, t is time, and p(t) represents the position of the mobile air conditioner over time, that is, the path of the mobile air conditioner.

[0065] Based on this, the above initial curve function can be written in the following vector form: p(t) = [t1, t2, ..., tn]·p.

[0066] Furthermore, the jerk is specifically a change in acceleration per unit time, and the change value of the jerk is the change in the jerk per unit time.

[0067] Specifically, the initial curve function is determined according to a preset conversion rule as a target optimization model with minimizing the change in jerk as the optimization objective. The target optimization model is specifically used to optimize the values ​​of the conversion parameters in the initial curve function to obtain target values ​​of the conversion parameters, such that the target values ​​of the conversion parameters minimize the change in jerk during movement of the mobile air conditioner.

[0068] The preset conversion rules herein are not specifically limited; any rule that can convert an initial curve function into a target optimization model can be used as the preset conversion rule herein. The preset conversion rule can be determined based on, for example, the function type of the initial curve function and / or the type of optimization algorithm employed by the target optimization model.

[0069] Step S30, determining a target value of the conversion parameter according to the target movement parameter and the target optimization model;

[0070] The target movement parameter can be used as another target of the target optimization model in the process of optimizing the numerical value of the conversion parameter. The determined target value can minimize the change value of the acceleration during the movement of the mobile air conditioner, and at the same time make the actual movement parameter of the mobile air conditioner consistent with the target movement parameter when it moves according to the planned target path.

[0071] For example, known quantities or constraints (such as equality constraints or inequality constraints) of a target optimization model can be determined based on the target motion parameters. By substituting the known quantities into the target optimization model, the value of the conversion parameter that minimizes the change in the jerk of the mobile air conditioner is determined as the target value of the conversion parameter. Alternatively, the value of the conversion parameter that simultaneously satisfies the constraints and minimizes the change in the jerk of the mobile air conditioner can be used as the target value of the conversion parameter.

[0072] Step S40 : determining the initial curve function whose conversion parameter is the target value as a target curve function, where the target curve function represents the target path planned by the mobile air conditioner.

[0073] After the target curve function is determined, the mobile air conditioner may be controlled to move according to the target curve function so that the moving path of the mobile air conditioner is the target path.

[0074] An embodiment of the present invention provides a path planning method for a mobile air conditioner. The method converts an initial curve function, which represents the correspondence between time and position during the movement of the mobile air conditioner and has undetermined conversion parameters, into a target optimization model that optimizes the conversion parameters with the goal of minimizing jerk changes. The target values ​​of the conversion parameters are then determined by combining the target movement parameters of the mobile air conditioner with the target optimization model. The initial curve function, with the conversion parameters as the target values, is used as the target path for the mobile air conditioner. In this process, based on the movement path represented by the initial curve function as a curve, the movement path of the mobile air conditioner is optimized using an optimization method with the goal of minimizing jerk combined with actual target movement parameters. This minimizes the jerk changes during the movement of the mobile air conditioner, ensures that the speed of the mobile air conditioner does not undergo abrupt changes due to sudden changes in the path direction, and ensures that the resulting target path is continuous and smooth. Compared to a broken line path, the method can effectively improve the smoothness of the mobile air conditioner's operation, prevent loosening or failure of internal components of the mobile air conditioner, and effectively improve the mechanical performance and lifespan of the mobile air conditioner.

[0075] Furthermore, the process of determining the initial curve parameters is as follows: the mobile air conditioner can be controlled to move and scene information of the space where it is located can be collected. A grid map corresponding to the space can be constructed based on the collected scene information. The current location of the mobile air conditioner is used as the starting location, and the spatial location that the mobile air conditioner needs to reach is used as the end location. The shortest path between the starting location and the end location is planned based on the grid map (the shortest path avoids obstacles in the space). The determined shortest path can be a broken line connected by multiple line segments. The path function corresponding to the broken line path is curve fitted according to pre-set rules, and the fitted curve function can be used as the initial curve function.

[0076] Furthermore, in the above embodiment, the target movement parameter includes a target total movement time of the mobile air conditioner along the target path. The target total movement time may be obtained based on user-set parameters, or may be determined based on the actual operation of the mobile air conditioner and / or the monitored indoor scene conditions. For example, when the mobile air conditioner needs to turn on the air conditioning function while moving along the target path, the environmental parameters corresponding to the air conditioning function (e.g., the ambient humidity corresponding to the dehumidification or humidification function, the ambient pollutant concentration corresponding to the purification function, the ambient temperature corresponding to the heat exchange function or heating function, etc.) may be obtained, and the target total movement time is determined based on the environmental parameters. This ensures that the mobile air conditioner's air conditioning effect is maintained when the mobile air conditioner moves along the target path and the air conditioning function is turned on, thereby effectively balancing indoor environmental comfort and smooth mobile operation.

[0077] Based on the target total duration, the step of determining the target optimization model corresponding to the initial curve function includes:

[0078] Step S21, calculating the fourth-order derivative of the initial curve function with respect to the time, wherein the fourth-order derivative represents the quantitative relationship between the change value of the acceleration and the time;

[0079] For example, when the initial curve function is p(t) above, its fourth-order derivative with respect to time is p 4 (t).

[0080] Step S22: determining the target optimization model according to the target total duration and the fourth-order derivative.

[0081] Specifically, the target optimization algorithm required for the target optimization mode can be obtained, and the fourth-order derivative can be transformed into an optimization model corresponding to the target optimization algorithm to obtain the target optimization model. For example, the fourth-order derivative can be modeled as a constrained optimization problem, and the target optimization model can have the following form:

[0082] Min[f (4) (t)] 2s.t.Aeqp＝beq ;

[0083] Where f(t) is a multi-order polynomial, Aeq is a matrix consisting of the coefficients of the polynomial, and bep is also a matrix consisting of the position and its derivative.

[0084] The target total duration can be used as the target range of the allowable variation corresponding to time in the target optimization model, so as to limit the variation range of time as an independent variable in the target optimization model.

[0085] In this embodiment, since the initial curve function represents the correspondence between position and time, its fourth-order derivative with respect to time can accurately represent the change value of the acceleration at different times during the movement of the mobile air conditioner. Based on this, the target optimization model is determined by the fourth-order derivative, which can ensure that the target value of the conversion parameter determined based on the target optimization model can accurately ensure that the change value of the acceleration during the movement of the air conditioner is minimized. On this basis, the target optimization model is determined in combination with the target total time, which can effectively exempt the target optimization model from the data analysis process within the time range corresponding to the target total time, so as to shorten the time for obtaining the target value of the conversion parameter based on the target optimization model, thereby ensuring that the target value of the conversion parameter can be quickly and accurately determined based on the target optimization model, thereby improving the path planning efficiency of the mobile air conditioner.

[0086] Furthermore, based on the above embodiment, another embodiment of the path planning method of the present application is proposed. In this embodiment, the target path includes multiple sub-paths, which are connected at the end to form the target path. The number of sub-paths can be a preset fixed number or a number determined based on the actual operating conditions of the mobile air conditioner. The initial curve function includes multiple sub-curve functions, and the sub-paths correspond one-to-one to the sub-curve functions. The sub-curve functions represent the corresponding relationship between time and position of the mobile air conditioner during the movement of the corresponding sub-path.

[0087] In this embodiment, each sub-curve function is a multi-order polynomial, and the conversion parameters include the coefficients of each term in all sub-curve functions. For example, the initial curve function is:

[0088]

[0089] Based on this, the fourth-order derivative includes the fourth-order sub-derivative of each of the sub-curve functions. Figure 3 , the step S22 includes:

[0090] Step S221, determining a target time period for each sub-path movement according to the target total duration and the number of sub-paths;

[0091] The target time period represents the target value of the time required for the mobile air conditioner to move along the corresponding sub-path during the movement of the mobile air conditioner according to the planned target path (that is, the path formed by connecting the various sub-paths).

[0092] The number of sub-paths may be equal to the total number of target time periods.

[0093] In this embodiment, each target time period can be of equal duration, and the target total duration can be evenly distributed according to the number of sub-paths, and the result can be used as the target time period. In other embodiments, each target time period can also be of unequal duration.

[0094] Step S222: determining the target optimization model according to the plurality of target time periods and their corresponding fourth-order sub-derivatives.

[0095] If the moving path of the mobile air conditioner is represented by a function, the planned target path may not be smooth enough. Therefore, a segmented method is used to represent the entire moving path that needs to be planned. The initial curve function corresponding to the path is divided into multiple sub-curve functions based on time. Multiple sub-curve functions are used to represent the total path that the mobile air conditioner needs to move. The target optimization model is established through each time period and its corresponding sub-fourth-order function, which can ensure that the target value determined subsequently can make the target path represented by the target curve function smooth and continuous.

[0096] It should be noted that in other embodiments, the target time period may not be determined by the target total duration and the number of sub-paths, but may be a pre-set parameter or determined by obtaining user-set parameters. For example, the user may specify a target duration for one or more sub-paths, which may serve as the target time period for each sub-path.

[0097] To make it easier to understand the present embodiment, the following provides a process for determining the target optimization model involved in the present embodiment. For example, based on the initial curve function p(t), the path is divided into k segments, and the entire path is composed of k segments of fourth-order sub-functions (such as multi-order polynomials); the total time is T, and an average distribution is used here, that is, each time segment is the same, and the target time period corresponding to each fourth-order sub-derivative during calculation is 0 to t, then t = T / k, and the process of determining the target optimization model through the target time period and the fourth-order sub-derivative is as follows:

[0098]

[0099]

[0100]

[0101]

[0102]

[0103] in,

[0104]

[0105] r, c are the row and column indices of the matrix, and the index starts from 0, that is, the first row r = 0. Based on this, the target optimization model can be:

[0106]

[0107] It can be seen that the optimization process of the conversion parameters can be converted into a quadratic programming problem by combining the target time period and its corresponding sub-fourth-order function to obtain the target optimization model here, which is conducive to improving the accuracy of the determined target value of the conversion parameter.

[0108] Furthermore, in this embodiment, before the step of determining the target time period for movement of each sub-path based on the total duration and the number of sub-paths, it also includes: obtaining obstacle information of the space where the mobile air conditioner is located; and determining the number of sub-paths based on the obstacle information.

[0109] Specifically, the obstacle information here may be characteristic information of obstacles within the path alternative area in the space (which may be set by the user or autonomously identified by the air conditioner based on target movement parameters).

[0110] Obstacle information may specifically include obstacle location, number of obstacles, and / or obstacle type. Different obstacle information corresponds to different numbers of sub-paths. For example, the closer the distance between two adjacent obstacles determined based on obstacle location, the more sub-paths may be used; the greater the number of obstacles, the more sub-paths may be used; if the obstacle type includes people, the number of sub-paths may be reduced, and so on.

[0111] In this embodiment, the number of sub-paths in the target path is determined in combination with obstacle information, which can ensure the smoothness of the determined sub-paths while matching the obstacle conditions in the space. This ensures that when the mobile air conditioner runs along the target path represented by the target value, it can effectively avoid obstacles while the smooth path allows the air conditioner to run smoothly. In fact, the operation of the mobile air conditioner will not have a negative impact on obstacles (such as affecting human comfort) and will not allow obstacles to affect the normal operation of the mobile air conditioner.

[0112] Furthermore, based on the above embodiment, another embodiment of the path planning method of the present application is proposed. In this embodiment, the conversion parameters include sub-conversion parameters between time and position in each of the sub-curve functions. If the sub-curve function is a multi-order polynomial, the sub-conversion parameters include the coefficients of each term in the polynomial. Based on this, referring to Figure 4 , step S30 includes:

[0113] Step S31, determining the equality constraint relationship corresponding to the target optimization model according to the target movement parameters;

[0114] Different target movement parameters may correspond to different equality constraint relationships. There may be one or more equality constraint relationships determined by the target movement parameters.

[0115] Specifically, the equality constraint relationship may be determined by combining the target movement parameters and the initial curve function. The equality constraint relationship may also be determined by combining the target movement parameters and other functions representing the movement path (e.g., a function representing a broken line path determined based on a grid map).

[0116] Step S32: using the equality constraint relationship as a constraint, solving the optimization result of the target optimization model through a quadratic programming algorithm to obtain a sub-target value corresponding to each of the sub-conversion parameters.

[0117] Specifically, in the process of solving the target optimization model through the quadratic programming algorithm, the above-determined equality constraint relationship is used as a restriction condition so that all the determined sub-target values ​​can satisfy the equality constraint condition and minimize the change value of the mobile air conditioner's acceleration.

[0118] In this embodiment, the optimization result of the target optimization model is solved by combining the equality constraint relationship determined by the target movement parameters with the quadratic programming algorithm. This ensures that when the mobile air conditioner moves along the target path represented by the target curve function corresponding to all the determined sub-target values, the actual movement parameters of the mobile air conditioner can match the target movement parameters, thereby ensuring that the mobile air conditioner can meet the operating requirements.

[0119] Specifically, in this embodiment, in addition to the above-mentioned target total duration, the target movement parameters also include the target position of the endpoint of each sub-path, the speed of each target position, the acceleration of each target position and / or the jerk of each target position. The target position here can be used to divide the sub-path. For example, if there are three target positions, the path between two adjacent target positions is determined as a sub-path. Each target position here and its corresponding speed, acceleration and jerk can be selected by the user or determined by the mobile air conditioner based on the detected scene information. Based on this, step S31 includes:

[0120] Step S311, using the target position, the velocity, the acceleration and / or the jerk as known quantities of derivatives of the target order of the corresponding sub-curve function to obtain a first equality constraint relationship;

[0121] Different types of target movement parameters correspond to different target orders.

[0122] When the target movement parameters include the target position, each target position or part of the target position can be used as a known quantity of the 0th-order derivative of the sub-curve function (ie, the sub-curve function itself) to obtain the corresponding first equality constraint relationship.

[0123] When the target movement parameters include speed, the speed of each target position or part of the target positions can be used as a known quantity of the first-order derivative of the sub-curve function to obtain the corresponding first equality constraint relationship.

[0124] When the target movement parameters include acceleration, the velocity of each target position or part of the target positions can be used as a known quantity of the second-order derivative of the sub-curve function to obtain the corresponding first equality constraint relationship.

[0125] When the target movement parameters include jerk, the velocity of each target position or part of the target positions can be used as a known quantity of the third-order derivative of the sub-curve function to obtain the corresponding first equality constraint relationship.

[0126] When the target movement parameters include the target position, the velocity, the acceleration, and the jerk, a plurality of first equality constraint relationships may be determined in the above-mentioned corresponding manners.

[0127] Step S312: establishing a quantitative relationship between the derivatives of the target order of the sub-curve functions corresponding to the two adjacent sub-paths based on the target positions, velocities, accelerations, and / or jerks corresponding to the endpoints connected by the two adjacent sub-paths being equal, to obtain a second equality constraint relationship;

[0128] Specifically, for two sub-curve functions with continuous temporal variation ranges, in the two sub-paths represented by these functions, the air conditioner is located at the connection point between the two adjacent sub-paths at the same time. Based on this, an equality relationship between the two adjacent sub-curve functions can be established using the position, velocity, acceleration, and / or jerk of the connection point, serving as the corresponding second equality constraint.

[0129] Different types of target movement parameters correspond to different target orders.

[0130] When the target movement parameter includes the target position, the corresponding second equality constraint relationship can be obtained by making the 0th-order derivatives of the two sub-curve functions corresponding to the two adjacent sub-paths equal at the positions of the connection endpoints and establishing a quantitative relationship between the two 0th-order derivatives for the corresponding target positions.

[0131] When the target movement parameter includes speed, the corresponding second equality constraint relationship can be obtained by establishing a quantitative relationship between the two first-order derivatives of the two sub-curve functions corresponding to the two adjacent sub-paths, which have equal speeds at the connection endpoints and are the speeds of the corresponding target positions.

[0132] When the target movement parameters include acceleration, the second-order derivatives of the two sub-curve functions corresponding to two adjacent sub-paths can be used to establish a quantitative relationship between the two second-order derivatives, which are equal in acceleration at the connection endpoints and are the accelerations of the corresponding target positions, to obtain the corresponding second equality constraint relationship.

[0133] When the target movement parameter includes jerk, the corresponding second equality constraint relationship can be obtained by establishing a quantitative relationship between the two third-order derivatives of the two sub-curve functions corresponding to the two adjacent sub-paths, where the jerk at the connection endpoints is equal and the jerk is the corresponding target position.

[0134] When the target movement parameters include the target position, the velocity, the acceleration, and the jerk, a plurality of second equality constraint relationships may be determined in the above-mentioned corresponding manners.

[0135] Step S313: Merge the first equality constraint relationship and the second equality constraint relationship to obtain the equality constraint relationship.

[0136] In this embodiment, combining two equality constraint relationships to determine the process for solving the target value of the constraint target optimization model can ensure that the path represented by the target curve function corresponding to the determined target value is continuous, smooth, and can match the target movement parameters.

[0137] To better understand the target value determination process mentioned in this embodiment, the following describes the process of determining the target value based on the target optimization model after converting the above p(t) into a quadratic programming problem:

[0138] The specific process of determining the first equality constraint relationship is as follows:

[0139]

[0140]

[0141]

[0142]

[0143]

[0144] The specific process of determining the second equality constraint relationship is as follows:

[0145]

[0146]

[0147]

[0148]

[0149] in, is the position, velocity, acceleration, or jerk corresponding to a target position, i is the i-th term in the polynomial, k is the derivative order, and j is the sub-curve function corresponding to the j-th sub-path. and They respectively represent the derivatives of the two adjacent sub-curve functions, and the order is determined according to the type of the target movement parameter.

[0150] Merge the two equality constraints to get the final equality constraint:

[0151]

[0152] The target optimization model with equality constraints as constraints is:

[0153]

[0154]

[0155] Based on this, calling the OOQP library can obtain the conversion parameter pi.

[0156] Furthermore, in this embodiment, the step of solving the target optimization model using a quadratic programming algorithm based on the equality constraint to obtain a sub-target value corresponding to each sub-conversion parameter includes: inputting the equality constraint and the target optimization model into a preset algorithm model, wherein the preset algorithm model is a computational model of the quadratic programming algorithm constructed based on the size of the mobile air conditioner; and obtaining the result output by the preset algorithm model as the target value. Solving the target value using the preset algorithm model helps simplify data processing, ensures a smooth path, and improves path planning efficiency. Since mobile air conditioners of different sizes have different stability during movement, constructing a preset algorithm model based on the size of the mobile air conditioner helps further improve the accuracy of the target value, thereby ensuring further improved smoothness when the mobile air conditioner operates along the target path corresponding to the target value, thereby ensuring the performance and lifespan of the air conditioner.

[0157] Furthermore, based on any of the above embodiments, another embodiment of the path planning method of the present application is proposed. In this embodiment, the step of obtaining the target movement parameters of the mobile air conditioner includes: obtaining the air outlet direction of the mobile air conditioner and the position of a human body within the mobile air conditioner's operating space; and determining the target movement parameters based on the air outlet direction and the human body position.

[0158] The air outlet direction can be specifically obtained by obtaining the air guide angle of the air guide component of the mobile air conditioner. The human body position can be specifically obtained by obtaining the human body position in the working space of the mobile air conditioner.

[0159] Different airflow directions and different body positions may correspond to different target movement parameters. For example, different airflow directions and different body positions may correspond to different target positions, target position velocities, target position accelerations, and / or target position jerk.

[0160] Based on this, it can be ensured that the air output of the mobile air conditioner can meet the comfort needs of the human body during its subsequent movement along the target path.

[0161] Specifically, when the mobile air conditioner needs to turn on the air conditioning function when moving along the target path, the environmental parameters corresponding to the air conditioning function (such as the ambient humidity corresponding to the dehumidification or humidification function, the ambient pollutant concentration corresponding to the purification function, the ambient temperature corresponding to the heat exchange function or heating function, etc.) can be obtained, and the correspondence between the air outlet direction, the human body position and the target movement parameters is obtained based on the environmental parameters. Different environmental parameters correspond to different correspondences. Based on this, in addition to ensuring that the air outlet of the mobile air conditioner can meet the comfort needs of the human body during its subsequent movement along the target path, it can also ensure that the air conditioning efficiency of the mobile air conditioner to the environment near its moving path can match the actual environmental conditions, thereby ensuring the air conditioning effect of the mobile air conditioner.

[0162] In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a path planning program is stored. When the path planning program is executed by a processor, the relevant steps of any embodiment of the above path planning method are implemented.

[0163] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0164] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0165] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, mobile air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0166] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A path planning method, characterized in that: Applied to mobile air conditioners, the path planning method includes the following steps: Obtaining the air outlet direction of the mobile air conditioner and the position of a human body within the active space of the mobile air conditioner; determining target movement parameters according to the air outlet direction and the human body position; Determine the target optimization model corresponding to the initial curve function; The target movement parameter includes a target total time duration for the mobile air conditioner to move along the target path. The step of determining a target optimization model corresponding to the initial curve function includes: Calculating a fourth-order derivative of the initial curve function with respect to time, wherein the fourth-order derivative represents a quantitative relationship between a change in the acceleration and the time; The target optimization model is determined based on the target total duration and the fourth-order derivative; the initial curve function represents the corresponding relationship between time and position during the movement of the mobile air conditioner, the conversion parameter between time and position in the initial curve function is a parameter whose value is to be determined, and the target optimization model is a function that optimizes the conversion parameter with the goal of minimizing the change in the acceleration of the mobile air conditioner; determining a target value of the conversion parameter according to the target movement parameter and the target optimization model; The initial curve function whose conversion parameter is the target value is determined as a target curve function, and the target curve function represents a target path planned by the mobile air conditioner.

2. The path planning method according to claim 1, wherein: The target path includes multiple sub-paths, the initial curve function includes multiple sub-curve functions, the sub-paths correspond to the sub-curve functions one-to-one, the sub-curve functions represent the corresponding relationship between time and position of the mobile air conditioner during the movement of the corresponding sub-path, the fourth-order derivative includes the fourth-order sub-derivative of each sub-curve function, and the step of determining the target optimization model based on the target total duration and the fourth-order derivative includes: Determine a target time period for each sub-path movement according to the target total duration and the number of the sub-paths; The target optimization model is determined according to the plurality of target time periods and their corresponding fourth-order sub-derivatives.

3. The path planning method according to claim 2, wherein: Before the step of determining the target time period for each sub-path movement according to the total duration and the number of the sub-paths, the method further includes: Obtaining obstacle information of the space where the mobile air conditioner is located; The number of the sub-paths is determined according to the obstacle information.

4. The path planning method according to claim 2, wherein: The conversion parameters include sub-conversion parameters between time and position in each of the sub-curve functions, and the step of determining target values ​​of the conversion parameters according to the target movement parameters and the target optimization model includes: Determining the equality constraint relationship corresponding to the target optimization model according to the target movement parameters; The target optimization model is solved by a quadratic programming algorithm with the equality constraint relationship as a constraint to obtain a sub-target value corresponding to each sub-conversion parameter.

5. The path planning method according to claim 4, wherein: The target movement parameters further include the target position of the endpoint of each subpath, the speed, acceleration and / or jerk of each target position, and the step of determining the equality constraint relationship corresponding to the target optimization model according to the target movement parameters includes: Taking the target position, the velocity, the acceleration and / or the jerk as known quantities of derivatives of target orders of corresponding sub-curve functions, a first equality constraint relationship is obtained; Based on the target positions, velocities, accelerations, and / or jerks corresponding to endpoints connected by two adjacent subpaths being equal, an optimization result of a quantitative relationship between derivatives of target orders of sub-curve functions corresponding to two adjacent subpaths is established to obtain a second equality constraint relationship; The first equality constraint relationship and the second equality constraint relationship are combined to obtain the equality constraint relationship.

6. The path planning method according to claim 4, wherein: The step of solving the target optimization model by a quadratic programming algorithm with the equality constraint relationship as a constraint to obtain a sub-target value corresponding to each sub-conversion parameter includes: Inputting the equality constraint relationship and the target optimization model into a preset algorithm model, wherein the preset algorithm model is an operation model of the quadratic programming algorithm constructed according to the size of the mobile air conditioner; The result output by the preset algorithm model is obtained as the target value.

7. A mobile air conditioner, characterized in that: The mobile air conditioner includes: a memory, a processor, and a path planning program stored in the memory and executable on the processor. When the path planning program is executed by the processor, the steps of the path planning method according to any one of claims 1 to 6 are implemented.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a path planning program, which, when executed by a processor, implements the steps of the path planning method according to any one of claims 1 to 6.

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