Robot smooth path planning method, electronic equipment and storage medium

Abstract

The invention discloses a robot smooth path planning method, electronic equipment and a storage medium, and the robot smooth path planning method comprises the steps: obtaining smooth point parameters and re-parameters corresponding to the smooth point parameters, the re-parameters being parameters obtained by re-parameterizing a to-be-smoothed part in a front path and / or a rear path; based on the heavy parameters, a turning-out axis vector of a target turning-out point and a turning-in axis vector of a target turning-in point in the axis space are determined, the target turning-out point is a turning-out point of the front section path, and the target turning-in point is a turning-in point of the rear section path; and by means of the target function meeting the parameter continuity condition, the inflection-out axis vector, the inflection-in axis vector and the heavy parameter, the axis position of a smooth path is determined so that the robot can be controlled to operate based on the axis position of the smooth path, and the smooth path is a path corresponding to the part, needing to be smoothed, between the front-section path and the rear-section path. According to the scheme, the operation efficiency of the robot can be improved.

Description

Technical Field

[0001] The present application relates to the field of robotics technology, and in particular to a robot smooth path planning method, electronic equipment, and storage medium. Background Art

[0002] In robot trajectory planning, if the robot's starting and ending positions are known, the corresponding axis positions at the starting and ending points can be calculated. The robot's trajectory shape is not important; only the starting and ending positions need to be interpolated. This type of trajectory planning is done in the robot's axis space and is called axis-space trajectory planning. When the robot performs a single segment of axis-space motion, its initial and final velocities are both 0. If the robot needs to complete multiple consecutive segments of axis-space motion, the velocity will drop to 0 at the end of each segment, significantly reducing work efficiency. Frequent acceleration and deceleration will also shorten the life of the motor and reducer.

[0003] In view of the existing technical defects, how to provide a solution to improve the operating efficiency of robots is a technical problem that needs to be urgently solved by those skilled in the art. Summary of the Invention

[0004] The present application at least provides a robot smooth path planning method, electronic device and storage medium.

[0005] The first aspect of the present application provides a robot smooth path planning method, including: obtaining smooth point parameters and re-parameters corresponding to the smooth point parameters, the smooth point parameters including smooth turning point parameters of the front path and smooth turning point parameters of the rear path, the front path is the current moving path of the robot, and the rear path is the moving path that the robot will enter, and the re-parameters are parameters obtained by re-parameterizing the parts that need to be smoothed in the front path and / or the rear path; based on the re-parameters, determining the turning-out axis vector and the turning-in axis vector of the target turning point in the axis space, the target turning-out point is the turning-out point of the front path, and the target turning point is the turning-in point of the rear path; using the objective function, the turning-out axis vector, the turning-in axis vector and the re-parameters that meet the parameter continuity conditions, determining the axis position of the smooth path so as to control the robot to operate based on the axis position of the smooth path, the smooth path is the path corresponding to the part that needs to be smoothed between the front path and the rear path.

[0006] A second aspect of the present application provides an electronic device, which includes a memory and a processor coupled to each other, and the processor is used to execute program instructions stored in the memory to implement the robot smooth path planning method in the above-mentioned first aspect.

[0007] A third aspect of the present application provides a computer-readable storage medium having program instructions stored thereon, which, when executed by a processor, implements the robot smooth path planning method in the first aspect.

[0008] In the above scheme, the present application utilizes the re-parameters obtained by re-parameterizing the parts that need to be smoothed in the front path and / or the rear path. The re-parameters are only the information for re-parameterizing the position information and do not carry speed information, so that the axis position of the smooth path determined based on the re-parameters can reduce the coupling effect of speed and path. In addition, the axis position of the smooth path determined by the objective function that meets the parameter continuity condition is continuous in multiple dimensions for the curves corresponding to the parts that need to be smoothed in the front path and the rear path, which can make the control robot run smoother based on the axis position of the smooth path, thereby improving the operation efficiency of the robot.

[0009] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The drawings herein are incorporated into and constitute a part of the specification. These drawings illustrate embodiments consistent with the present application and, together with the specification, are used to illustrate the technical solutions of the present application.

[0011] Figure 1 This is a first flow chart of an embodiment of a method for smooth path planning of a robot according to the present application;

[0012] Figure 2 yes Figure 1 The sub-process diagram of step S12 in the robot smooth path planning method is shown;

[0013] Figure 3a This is a second flow chart of an embodiment of the robot smooth path planning method of the present application;

[0014] Figure 3b is the path intention of an embodiment of the robot smooth path planning method of the present application;

[0015] Figure 4 This is a schematic diagram of the framework of an embodiment of the robot smooth path planning device of the present application;

[0016] Figure 5 This is a schematic diagram of the framework of an embodiment of the electronic device of the present application;

[0017] Figure 6 It is a schematic diagram of a framework of an embodiment of the computer-readable storage medium of the present application. DETAILED DESCRIPTION

[0018] The following describes the embodiments of the present application in detail with reference to the accompanying drawings.

[0019] In the following description, for the purpose of explanation rather than limitation, specific details such as specific system structures, interfaces, and technologies are provided to facilitate a thorough understanding of the present application.

[0020] The term "and / or" in this article is simply a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects are in an "or" relationship. In addition, "many" in this article means two or more than two. In addition, the term "at least one" in this article means any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0021] In the present application, the execution entity for implementing the robot smooth path planning method described in the present application may be a robot smooth path planning device, an electronic device, etc. For example, the robot smooth path planning device may be provided in the robot or in an electronic device or server or other processing device that establishes a communication connection with the robot, wherein the electronic device may be a numerical control device, a user equipment (UE), a handheld device, a computing device, a vehicle-mounted device, etc. In some possible implementations, the robot smooth path planning method may be implemented by a processor calling computer-readable instructions stored in a memory.

[0022] See also Figure 1 , Figure 1 This is a first flow chart of an embodiment of the robot smooth path planning method of the present application. Specifically, it may include the following steps:

[0023] Step S11: Obtain smoothing point parameters and weight parameters corresponding to the smoothing point parameters.

[0024] This application takes the robot as the execution subject of the robot smooth path planning method as an example, and the calculation logic is specifically executed by the controller or processor in the robot. The smoothing point parameters include the smoothing inflection point parameters of the front path and the smoothing inflection point parameters of the rear path. The front path is the current moving path of the robot. The rear path is the moving path that the robot will enter. The path corresponding to the part that needs to be smoothed between the front path and the rear path is the smooth path. The smoothing point parameters are used to represent the specified parameters of the smoothing inflection point and / or the smoothing inflection point in the smooth path. The smoothing point parameters can characterize the degree of smoothness expected for the front path and / or the rear path. In some application scenarios, the degree of smoothness expected for the front path and the rear path can be the same or different. The smoothing inflection point parameters characterize the degree of smoothness expected for the front path. The smoothing inflection point parameters characterize the degree of smoothness expected for the rear path.

[0025] In some application scenarios, the smoothing point parameters may be obtained by receiving user-entered smoothing point parameter values or directly using preset smoothing point parameters. In other application scenarios, the smoothing point parameters may be obtained by using historical smoothing point parameters at a certain moment as the smoothing point parameters, or by using the statistical value of historical smoothing parameters at several moments as the smoothing point parameters. These statistical values may be mean, mode, variance, standard deviation, etc. A historical moment is a moment before the current moment.

[0026] The reparameters are parameters obtained by reparameterizing the portion of the reference path that requires smoothing. The reference path includes the front segment and / or the back segment. Specifically, the reparameters are parameters obtained by reparameterizing the portion of the front segment and / or the back segment that requires smoothing. In some application scenarios, the reparameters can be obtained by calculating the reparameters based on the smoothing point parameters. In other application scenarios, the reparameters can be obtained by obtaining a pre-established correspondence between the smoothing point parameters and the reparameters, and then searching the reparameters based on the smoothing point parameters from the correspondence.

[0027] Exemplarily, when a parameterized function corresponding to a reference path in an axis space is obtained, the independent variables in the parameterized function corresponding to the reference path are reparameterized to obtain reparameters. The independent variables in the parameterized function corresponding to the reference path are reparameterized functions. The parameterized function corresponding to the reference path includes a front-segment parameterized function corresponding to the front-segment path and / or a back-segment parameterized function corresponding to the back-segment path.

[0028] In some application scenarios, the front-end path that needs to be smoothed is at least a portion of the path in the front-end path. The front-end path that needs to be smoothed is reparameterized, that is, the independent variable in the front-end parameterization function corresponding to the front-end path is reparameterized to obtain the reparameter. The independent variable in the front-end parameterization function corresponding to the front-end path is a function of the reparameter. In other application scenarios, the front-end path that needs to be smoothed is at least a portion of the path in the front-end path. The front-end path that needs to be smoothed is reparameterized, that is, the independent variable in the front-end parameterization function corresponding to the front-end path is reparameterized to obtain the reparameter. The independent variable in the front-end parameterization function corresponding to the front-end path is a function of the reparameter.

[0029] For example, the independent variable in the parameterized function of the preceding segment can be expressed as s1. The smooth inflection point parameter of the preceding segment path can be expressed as s 1z The independent variable in the parameterized function of the latter part can be expressed as s2. The smooth inflection point parameter of the latter part of the path can be expressed as s 2z The weight parameter can be denoted as t.

[0030] Based on the weight parameters, the axis vector of the reference point of the reference path in the axis space is determined. The reference point of the reference path includes the target inflection point and / or the target inflection point in the axis space. The axis vector of the reference point includes the inflection-out axis vector of the target inflection point and / or the inflection-in axis vector of the target inflection point. The axis vector of the reference point can represent the axis position in the axis space, and each component is an axis position. Exemplarily, in the case where the robot is a four-axis robot, the axis vector of the reference point can be a four-dimensional vector. In the case where the robot is a six-axis robot, the axis vector of the reference point can be a six-dimensional vector. It can be understood that the above-mentioned smoothing point parameters are values input into the interpolation / interpolation link.

[0031] Step S12: Based on the weight parameters, determine the turn-out axis vector of the target turn-out point and the turn-in axis vector of the target turn-in point in the axis space.

[0032] The target inflection point is the inflection point of the front path. It is understandable that when the target inflection point is on the front path, the target inflection point coincides with the inflection point of the front path. When the target inflection point is on a smooth path, the target inflection point coincides with the smooth inflection point of the smooth path. The target inflection point is the inflection point of the rear path. It is understandable that when the target inflection point is on the rear path, the target inflection point coincides with the inflection point of the rear path. When the target inflection point is on a smooth path, the target inflection point coincides with the smooth inflection point of the smooth path. Specifically, the inflection axis vector of the target inflection point can represent the axis position of the robot at the target inflection point in the axis space, and each component is an axis position. The inflection axis vector of the target inflection point can represent the axis position of the robot at the target inflection point in the axis space, and each component is an axis position.

[0033] In some application scenarios, the above step S12 may be to respectively calculate the turning-out axis vector of the target turning-out point and the turning-in axis vector of the target turning-in point based on the weight parameters. In other application scenarios, the above step S12 may be to obtain the correspondence between the pre-established weight parameters and the turning-out axis vector of the target turning-out point and the turning-in axis vector of the target turning-in point, and to find the turning-out axis vector of the target turning-out point and the turning-in axis vector of the target turning-in point from the correspondence based on the weight parameters. In other application scenarios, the above step S12 may be to determine the turning-out axis vector of the target turning-out point and / or the turning-in axis vector of the target turning-in point based on the weight parameters, the front-segment parameterized function corresponding to the front-segment path and / or the back-segment parameterized function corresponding to the back-segment path.

[0034] It can be understood that the turning-out axis vector of the target turning-out point and / or the turning-in axis vector of the target turning-in point are axis vectors that satisfy the front-end parameterized function corresponding to the front-end path and / or the back-end parameterized function corresponding to the back-end path.

[0035] For example, the target inflection point can be represented as s1. The inflection axis vector of the target inflection point can be represented as j1(s1). The target inflection point can be represented as s2. The inflection axis vector of the target inflection point can be represented as j2(s2).

[0036] Step S13: Determine the axis position of the smooth path using the objective function, the turn-out axis vector, the turn-in axis vector, and the weight parameter that satisfy the parameter continuity condition.

[0037] Using the objective function, the exit axis vector, the entry axis vector, and the weight parameters that satisfy the parameter continuity condition, the axis positions of the smooth path are determined so that the robot can be controlled to operate based on the axis positions of the smooth path. The smooth path corresponds to the path between the previous path and the next path that requires smoothing.

[0038] The parameter continuity condition is related to the selected re-parameters, and different parameter representations may result in different parameter continuity. Parameter continuity involves the parametric representation of the curve, focusing on how corresponding points change when the re-parameters change. Parameter continuity conditions include at least one of zero-order parameter continuity, first-order parameter continuity, and second-order parameter continuity. Specifically, zero-order parameter continuity requires that when the parameter is continuous at a certain point, the points on the curve also transition smoothly without sudden jumps. In addition to zero-order continuity, first-order parameter continuity also requires that the first-order derivative of the curve is also continuous when the parameter changes, that is, the tangent is continuous. Second-order parameter continuity further requires that the second-order derivative of the curve is also continuous when the parameter changes, that is, the curvature is continuous. The objective function is related to the re-parameters, and the objective function can represent the continuity of the points, tangents, and curvatures on the curve corresponding to each portion requiring smoothing in the preceding and / or succeeding path. It is understood that the multi-dimensionality on the curve corresponding to each portion requiring smoothing can be the points, tangents, and curvatures on the curve.

[0039] The objective function can be a curve that can characterize the smooth path between the front path and the back path, and the independent variable in the objective function is a heavy parameter. The axis position of the smooth path can be the axis vector of the robot traveling on the smooth path in the axis space when the above-mentioned smooth point parameters are input in the interpolation / interpolation link. For example, the axis position of the smooth path can be expressed as j m .

[0040] In some application scenarios, step S13 may involve pre-establishing a correspondence between the weight parameter and the axis position of the smoothed path based on the objective function, and then searching for the axis position of the smoothed path based on the weight parameter. In other application scenarios, the turn-out axis vector, the turn-in axis vector, and the weight parameter are input into the objective function, and the resulting value of the objective function is used as the axis position of the smoothed path.

[0041] In some application scenarios, after the above step S13, when the robot enters the smooth path, the robot is controlled to move the axis position j based on the smooth path. m Run. At this time, the curve that the robot runs on the smooth path satisfies geometric continuity and parametric continuity. Geometric continuity includes at least one of zero-order geometric continuity, first-order geometric continuity and second-order geometric continuity. Specifically, zero-order geometric continuity means that the curve is connected at a certain point without breaks. In addition to zero-order continuity, first-order geometric continuity also requires that the tangents of the curve at this point are the same. Second-order geometric continuity further requires that the curvature of the curve at this point is also the same. Geometric continuity is not affected by the selection of parameters. Even if the parameter representation changes, as long as the above conditions are met, the curve still maintains the same geometric continuity.

[0042] This application takes into account that if the front path and the rear path are directly superimposed by vectors to form a smooth path, it depends on the speed of the original trajectory (for example, the front path and the rear path), and the speed curve of the original trajectory is changed while the trajectory is smoothed, resulting in a coupling effect between the speed and the path. When the vectors are superimposed, the paths and speeds of the front and back segments are superimposed separately. The speed of the trajectory is affected by the path (for example, the speed when going through a curve must be less than the speed of a straight line). After the path is smoothed, the smooth path is no longer a straight line but a smooth curve, and the speed is still superimposed according to the previously planned vectors, resulting in coupling, and the smooth path obtained in this way is low-order continuous.

[0043] The re-parameters of the present application are only information for re-parameterizing the position information and do not carry speed information, so that the axis position of the smooth path determined based on the re-parameters can reduce the coupling effect between the speed and the path.

[0044] In the above scheme, the present application utilizes the re-parameters obtained by re-parameterizing the parts that need to be smoothed in the front path and / or the rear path. The re-parameters are only the information for re-parameterizing the position information and do not carry speed information, so that the axis position of the smooth path determined based on the re-parameters can reduce the coupling effect of speed and path. In addition, the axis position of the smooth path determined by the objective function that meets the parameter continuity condition is continuous in multiple dimensions for the curves corresponding to the parts that need to be smoothed in the front path and the rear path, which can make the control robot run smoother based on the axis position of the smooth path, thereby improving the operation efficiency of the robot.

[0045] See also Figure 2 , Figure 2 yes Figure 1 The sub-process diagram of step S12 in the robot smooth path planning method is shown.

[0046] In some embodiments, step S12 may include the following steps: Step S21: Obtaining a front-segment parameterized function corresponding to the front-segment path and a back-segment parameterized function corresponding to the back-segment path in the axis space. Step S22: Determining a target inflection point and a target inflection point based on the weight parameter. Step S23: Determining an inflection axis vector of the target inflection point using the front-segment parameterized function and the target inflection point. Step S24: Determining an inflection axis vector of the target inflection point using the back-segment parameterized function and the target inflection point.

[0047] The front-end parameterization function is used to represent the parametric expression function of the front-end path. The back-end parameterization function is used to represent the parametric expression function of the back-end path. The independent variables in the front-end parameterization function and the back-end parameterization function are different. For example, given two parametric paths in the axial space, they are the front-end parameterization function j1(s1) and the back-end parameterization function j2(s2). In the front-end parameterization function, the independent variable is s1, and the value of the independent variable s1 is s1∈[0,1]. In the back-end parameterization function, the independent variable is s2, and the value of the independent variable s2 is s2∈[0,1].

[0048] The above step S21 may be to obtain the parameterized path of the front segment path and / or the back segment path input by the user in the axis space.

[0049] The above-mentioned step S22 can be based on the correlation between the weight parameter and the target inflection point and / or the target inflection point, and determine the target inflection point corresponding to the smooth inflection point parameter and / or the target inflection point corresponding to the smooth inflection point parameter. In some application scenarios, after the above-mentioned step S22, the above-mentioned step S23 can be directly using the target inflection point as the independent variable in the front-end parameterized function, obtaining the value of the front-end parameterized function, and using the value of the front-end parameterized function as the inflection axis vector of the target inflection point. In other application scenarios, after the above-mentioned step S22, the above-mentioned step S23 can be pre-processing the target inflection point to obtain a new target inflection point, using the new target inflection point as the independent variable in the front-end parameterized function, obtaining the value of the front-end parameterized function, and using the value of the front-end parameterized function as the inflection axis vector of the target inflection point. Among them, the pre-processing can be to calibrate and / or modify the target inflection point to obtain a new target inflection point. The modification process can be to increase or decrease the value of the target inflection point according to a preset correction value. The preset correction value can be determined according to the smoothing accuracy requirement. The above target inflection point and the new target inflection point can be the same or different.

[0050] In some application scenarios, after step S22, step S24 may be performed by directly using the target inflection point as the independent variable in the back-end parameterized function to obtain the value of the back-end parameterized function, and using the value of the back-end parameterized function as the inflection axis vector of the target inflection point. In other application scenarios, after step S22, step S24 may be performed by pre-processing the target inflection point to obtain a new target inflection point, using the new target inflection point as the independent variable in the back-end parameterized function to obtain the value of the back-end parameterized function, and using the value of the back-end parameterized function as the inflection axis vector of the target inflection point. The pre-processing may be performed by correcting and / or revising the target inflection point to obtain a new target inflection point. The correction process may be performed by increasing or decreasing the value of the target inflection point according to a preset correction value. The preset correction value may be determined according to the smoothing accuracy requirement. The target inflection point and the new target inflection point may be the same or different.

[0051] It can be considered that only using heavy parameters that do not involve speed information to determine the turning-out axis vector to the target turning-out point and the turning-in axis vector to the target turning-in point also does not involve speed information, thereby enabling the axis position of the smooth path subsequently determined based on the heavy parameters to reduce the coupling effect of speed and path.

[0052] In some embodiments, step S22 may include the following steps: first, obtaining a front-segment smoothing function and a back-segment smoothing function. The front-segment smoothing function is used to represent the association between the front-segment path and the smooth inflection point parameter, and the back-segment smoothing function is used to represent the association between the back-segment path and the smooth inflection point parameter. Based on the weight parameter and the front-segment smoothing function, a target inflection point is determined. Based on the weight parameter and the back-segment smoothing function, a target inflection point is determined.

[0053] The front-end smoothing function may be an expression function obtained by linearly pre-transforming the portion of the front-end path that needs to be smoothed. The back-end smoothing function may be an expression function obtained by linearly pre-transforming the portion of the back-end path that needs to be smoothed.

[0054] Specifically, the form of the front-end smoothing function can refer to formula (1), and the form of the back-end smoothing function can refer to formula (2):

[0055] s1(t)=(1-s 1z )×t+s 1z Formula (1);

[0056] s2(t)=s 2z ×t formula (2);

[0057] Among them, the linear domain transformation is performed on the parts that need to be smoothed in the front path and the back path respectively to obtain the above formulas (1) and (2). 1zIt can represent the smooth inflection point parameter, s1∈[s 1z ,1]. t can represent a heavy parameter, parameter t∈[0,1]. s1(t) can represent the value of the previous smoothing function, that is, the smoothing inflection point parameter is s 1z When , the value of the target inflection point is taken. At this time, s1(t) refers to s1. 2z It can represent the smooth inflection point parameter, s2∈[0,s 2z ]. s2(t) can represent the value of the latter smoothing function, that is, the smoothing inflection point parameter is s 2z When , the value of the target inflection point is . In this case, s2(t) refers to s2. In some application scenarios, the front path that needs to be smoothed is reparameterized, that is, s1 is a function of t. Among them, the value of s1 is within the first range, for example, the value of the first range can be [s 1z ,1]. In other application scenarios, the back path that needs to be smoothed is reparameterized, that is, s2 is also a function of t. The value of s2 is in the second range, for example, the second range can be [0,s 2z It can be understood that, using the weight parameter t, the front path that needs to be smoothed (s1 takes [s 1z ,1]) and the latter path (s2 takes [0,s 2z ]) is reparameterized to obtain the front-end smoothing function and the back-end smoothing function. In the front-end smoothing function, the target inflection point s1 is a function of the reparameter t. In the back-end smoothing function, the target inflection point s2 is also a function of t. The front-end smoothing function and the back-end smoothing function need to satisfy: when the value range of the reparameter t is [0,1], the value range of s1 is [s 1z ,1], so the above formula (1) is obtained. When the value range of the weight parameter t is [0,1], the value range of s2 is [0,s 2z ], so we have the above formula (2).

[0058] In some application scenarios, the target inflection point can be determined by directly using the weight parameter and the smooth inflection parameter to input the front-segment smoothing function to obtain the value of the front-segment smoothing function, and using the value of the front-segment smoothing function as the value of the target inflection point. In other application scenarios, the target inflection point can be determined by preprocessing the value of the front-segment smoothing function to obtain a new value of the front-segment smoothing function, and using the new value of the front-segment smoothing function as the value of the target inflection point. The preprocessing can be to calibrate and / or correct the value of the front-segment smoothing function to obtain the new value of the front-segment smoothing function. The correction process can be to increase or decrease the value of the front-segment smoothing function according to a preset correction value. The preset correction value can be determined according to the smoothing accuracy requirement. The value of the above-mentioned front-segment smoothing function and the value of the new front-segment smoothing function can be the same or different.

[0059] In some application scenarios, the target inflection point can be determined by directly using the weight parameter and the smoothing out parameter to input the posterior smoothing function to obtain the value of the posterior smoothing function, and using the value of the posterior smoothing function as the value of the target inflection point. In other application scenarios, the target inflection point can be determined by preprocessing the value of the posterior smoothing function to obtain a new value of the posterior smoothing function, and using the new value of the posterior smoothing function as the value of the target inflection point. The preprocessing can be to calibrate and / or correct the value of the posterior smoothing function to obtain the new value of the posterior smoothing function. The correction process can be to increase or decrease the value of the posterior smoothing function according to a preset correction value. The preset correction value can be determined according to the smoothing accuracy requirement. The value of the posterior smoothing function and the value of the new posterior smoothing function can be the same or different.

[0060] It can be considered that only using the re-parameters that do not involve speed information to determine the values of the target inflection point and the target inflection point does not involve the influence of speed information, thereby enabling the subsequent axis position of the smooth path determined based on the re-parameters to reduce the coupling effect of speed and path.

[0061] See also Figure 3a , Figure 3a This is a second flow chart of an embodiment of the robot smooth path planning method of the present application.

[0062] In some embodiments, before step S13, the robot smooth path planning method may further include the following steps: Step S31: Obtaining a superposition function. The superposition function is a polynomial function with multiple parameters and satisfies the parameter continuity condition. Step S32: Constructing an objective function based on the superposition function, the front-end parameterized function, and the back-end parameterized function.

[0063] The independent variable in the superposition function is a multi-parameter polynomial function that satisfies a parameter continuity condition. At least a portion of the objective function includes the superposition function. The objective function can be determined based on the superposition function. The parameter continuity condition can be that the derivative of the axis position / axis vector corresponding to the objective function determined based on the superposition function satisfies third-order parameter continuity. The derivatives of the axis position / axis vector corresponding to the objective function are the first-order derivative, the second-order derivative, and the third-order derivative, respectively.

[0064] In some application scenarios, the above-mentioned step S31 may be to use a preset superposition function that meets the requirements as the above-mentioned superposition function. In other application scenarios, the above-mentioned step S31 may be a superposition function whose number of terms is constructed based on re-parameters and whose coefficients meet the parameter continuity conditions. In some application scenarios, the above-mentioned step S32 may be to determine the objective function by utilizing the relationship between the superposition function, the front-end parameterization function and the back-end parameterization function. The objective function includes at least the superposition function, the front-end parameterization function and the back-end parameterization function. In other application scenarios, the objective function includes at least part of the superposition function, at least part of the front-end parameterization function and at least part of the back-end parameterization function.

[0065] For example, the objective function can be expressed as m (t). The parameterized function of the first part can be expressed as j1(s1). The parameterized function of the second part can be expressed as j2(s2). The superposition function can be expressed as p(t).

[0066] In some embodiments, step S11 may include the following steps: first, obtaining a path parameter function of the smoothed path. The path parameter function is an expression function obtained by reparameterizing the smoothed path. Then, determining a reparameter based on the path parameter function and the smoothing point parameters.

[0067] In some application scenarios, the weight parameter may be determined based on a path parameter function and a smooth inflection point parameter. In some application scenarios, the weight parameter may be determined based on a path parameter function and a smooth inflection point parameter. In some application scenarios, the weight parameter may be determined based on a path parameter function and a smooth inflection point parameter. In some application scenarios, the weight parameter may be determined based on a path parameter function, a front-segment smoothing function, and a rear-segment smoothing function. In some application scenarios, the weight parameter may be determined based on a path parameter function, a front-segment smoothing function, a rear-segment smoothing function, and a smooth inflection point parameter.

[0068] In some embodiments, the step of obtaining a path parameter function for a smooth path may include the following steps: first, taking the difference between the preceding smoothing function and the smoothing inflection point parameter as a first difference, and the difference between the succeeding smoothing function and the preceding smoothing function as a second difference. Then, taking the sum of the preset value and the second difference as a first sum, and multiplying the superposition function and the first sum as a target product. Next, taking the sum of the first difference and the target product as a second sum, and constructing a path parameter function based on the second sum.

[0069] The independent variable in the path parameter function of the smooth path may be a heavy parameter. The step of constructing the path parameter function based on the second sum may be determining the second sum as the value of the path parameter function.

[0070] Specifically, the path parameter function of the smooth path can refer to formula (3):

[0071] s m (t)=s1(t)+p(t)×(s2(t)+X-s1(t))-s 1z Formula (3);

[0072] The smooth path is transformed into a path parameter function. The range of the parameter is t∈[0,1]. m (t) can represent the path parameter function of the smooth path. p(t) can represent the superposition function. 1z It can represent the smooth inflection point parameter. s1(t) can represent the front-end smoothing function. s2(t) can represent the back-end smoothing function. X can represent a preset value, for example, the preset value can be 1.

[0073] In some embodiments, step S31 may include the following steps: First, based on the path parameter function, a first constraint condition of the superposition function is determined. The first constraint condition is used to represent the value of the superposition function when the weight parameter takes the maximum value. Then, based on the parameter continuity condition, a second constraint condition of the superposition function is determined. The second constraint condition is used to represent the value of the superposition function when the superposition function satisfies the parameter continuity condition. Subsequently, based on the first constraint condition and the second constraint condition, the values of the number of terms and coefficients in the superposition function are determined.

[0074] At least a portion of the path parameter function includes an overlay function. There is an association between the path parameter function and the overlay function. The independent variables in both the path parameter function and the overlay function are re-parameters. When the re-parameters are at their maximum values, the first constraint condition is related to the value of the path parameter function. The maximum values of the re-parameters include the minimum and / or maximum values of the re-parameters. The first constraint condition includes the values of the path parameter function and the overlay function when the re-parameters are at their maximum values.

[0075] Among them, the superposition function is a polynomial function, and the path parameter function s m ∈[0,1-s 1z +s 2z ], the first constraint condition can satisfy the following formulas (4), (5), (6) and (7):

[0076] s m (0)=0 formula (4);

[0077] s m (1) = 1-s1z +s 2z Formula (5);

[0078] p(0)=0 Formula (6);

[0079] p(1)=1 Formula (7);

[0080] It can be understood that by substituting the above formulas (1) to (3) into the above formulas (4) and (5), the above formulas (6) and (7) can be obtained. The above formula (4) can represent the value of the path parameter function when the independent variable re-parameter in the path parameter function takes the minimum value, that is, when the re-parameter takes 0. The specific value of the path parameter function is s m (0) is 0. The above formula (5) can express the value of the path parameter function when the independent variable re-parameter in the path parameter function takes the maximum value, that is, when the re-parameter takes 1. The specific value of the path parameter function is s m (1) is 1-s 1z +s 2z The above formula (6) can express the value of the superposition function when the independent variable re-parameter in the superposition function takes the minimum value, that is, when the re-parameter takes 0, and the specific value of the superposition function p(0) is 0. The above formula (7) can express the value of the superposition function when the independent variable re-parameter in the superposition function takes the maximum value, that is, when the re-parameter takes 1, and the specific value of the superposition function p(1) is 1.

[0081] In some embodiments, step S32 may include the following steps: first, taking the difference between the second-stage parameterized function and the first-stage parameterized function as a candidate difference. Then, multiplying the candidate difference by the superposition function as a candidate product. Next, taking the sum of the first-stage parameterized function and the candidate product as a candidate sum. Subsequently, defining a target function based on the candidate sum and the axis position of the smoothed path.

[0082] Specifically, the objective function can refer to formula (8):

[0083] j m (t) = j1(s1) + p(t) × (j2(s2) - j1(s1)) Formula (8);

[0084] Among them, the objective function can be expressed as j m(t). The parameterized function of the front segment can be expressed as j1(s1). The parameterized function of the back segment can be expressed as j2(s2). The superposition function can be expressed as p(t). The objective function can be the result of polynomial vector superposition of the front segment path and the back segment path. It can be understood that the vector superposition method interpolates the smooth path by adding space vectors between the smooth turning point of the front segment path and the smooth turning point of the back segment path in the two paths to be smoothed, and the final smooth path will form an arc in space.

[0085] It can be argued that using only re-parameters that don't involve velocity information to determine the objective function also eliminates the influence of velocity information, allowing the axis positions of the smooth path subsequently determined based on the re-parameters to reduce the effects of velocity-path coupling. Furthermore, the re-parameters in the objective function can satisfy parameter continuity. Consequently, the axis positions of the smooth path determined using this objective function are continuous in multiple dimensions for the curves corresponding to the smoothed portions of the preceding and subsequent paths. This allows the robot to operate more smoothly based on the axis positions of the smooth path, thereby improving its operational efficiency.

[0086] The parametric continuity condition indicates that the smoothed path and the reference path must satisfy third-order parametric continuity at the connection point. The reference path is a non-smooth path, that is, the aforementioned front-end path and / or the aforementioned back-end path. The derivatives of the axis position / axis vector corresponding to the objective function determined by the superposition function satisfy third-order parametric continuity. In some application scenarios, the first-order, second-order, and third-order derivatives of the axis position / axis vector corresponding to the objective function satisfy third-order parametric continuity.

[0087] Specifically, the parameter continuity conditions can refer to the following formulas (9) to (16):

[0088] j m (t)| t＝＝ =j1(s1(t))| t＝0 Formula (9);

[0089]

[0090] j m (t)| t＝1 =j2(s2(t))| t＝1 Formula (13);

[0091]

[0092] Wherein, s1(t) can be the value of the target inflection point obtained by the above formula (1). j1(s1(t)) can be the inflection axis vector of the above target inflection point. s2(t) can be the value of the target inflection point obtained by the above formula (2). j2(s2(t)) can be the inflection axis vector of the above target inflection point. m (t) can represent the objective function or the value of the objective function, that is, the axis position of the smooth path. It can be understood that the parameters in the above formulas (9) to (16) can refer to the parameter diagrams in the above formulas (1) to (8), and will not be repeated here. The parameter continuity condition is also the third-order continuity condition, that is, the above formulas (9) to (16) can obtain several values of the superposition function in the second constraint condition. The several values can be the value of the superposition function when the multi-parameter corresponding to the independent variable in the superposition function takes an extreme value, the first-order derivative of the superposition function with respect to the multi-parameter, the second-order derivative of the superposition function with respect to the multi-parameter, and the third-order derivative of the superposition function with respect to the multi-parameter. The several values can be p(0)=0, p′(0)=0, p″(0)=0, p″′(0)=0, p(1)=1, p′(1)=1, p″(1)=1, p″′(1)=1. The second constraint condition satisfies both the above formula (6) and the above formula (7), and the superposition function p(t) is a seventh-order polynomial. Specifically, the expression of the superposition function can refer to formula (17):

[0093] p(t)=a+bt+ct 2 +dt 3 +et 4 +ft 5 +gt 6 +ht 7 Formula (17);

[0094] Among them, p(t) can represent a superposition function. t can represent a weight parameter. a, b, c, d, e, f, g, h represent the coefficients of the zeroth power, first power, second power, third power, fourth power, fifth power, sixth power and seventh power of the weight parameter t, respectively. In some application scenarios, after iterating the above formula (1) to the above formula (16), the number of terms and the coefficients of each power of the above formula (17) are calculated. For example, the values of a, b, c, and d are all 0. The values of e, f, g, and h are 35, -84, 70, and -20, respectively. Specifically, the above formula (17), that is, the superposition function, can be expressed as: p(t) = 35×t 4 -84×t 5 +70×t 6 -20×t 7 .

[0095] See also Figure 3b , Figure 3bThis is the path intention of an embodiment of the robot smooth path planning method of the present application.

[0096] like Figure 3b As shown in Figure 2, the robot's path at a certain moment includes the non-smooth part r1(s) in the front path, the non-smooth part r2(s) in the back path, and the smooth path r(s). The part that needs to be smoothed in the latter part of the path It is understandable that if Figure 3b For the remaining parameters shown, please refer to the above content and will not be repeated here. For example, the smooth path is interpolated, and the parameterized path construction in response to the smooth path is completed, that is, the objective function is constructed. The parameterized paths of the two axis spaces are known, namely j1(s1) and j2(s2), s1, s2∈[0,1]. The user specifies the smooth distance of the front and back paths to obtain the parameters corresponding to the smooth inflection points of the two paths: s1=s 1z , s2=s 2z . Construct a connection j1(s 1z )、j2(s 2z ) path curve j m (s m ), where s m ∈[0,1-s 1z +s 2z ], it is necessary to satisfy the third-order continuity of the parameters of the smooth segment path and the two non-smooth segments before and after. The objective function of the parameterized curve in the axis space is expressed as j m (s m ), path interpolation is to determine j by smoothing point parameters m (s m ) in the independent variable s m ∈[0,1-s 1z +s 2z ], calculate the axis position of the path point corresponding to the smoothing point parameter in the axis space. From the above formulas (1), (2), (3) and (17), it can be seen that the path point parameter s of the smoothing path is m is an octave polynomial with weight parameter t, and when weight parameter t∈[0,1], the path point parameter s of the smooth path is m It is monotonically increasing with respect to t, so the path point parameter s can be solved using the bisection method or Newton iteration method. mThe corresponding weight parameter t. The above formulas (1) and (2) can be used to calculate the values of the target inflection point parameter s1 in the front path and the target inflection point parameter s2 in the back path, thereby obtaining the front path axis position vector j1(s1) corresponding to s1 and the back path axis position vector j2(s2) corresponding to s2. The seventh-order polynomial corresponding to the weight parameter t can be calculated by the above formula (17), which is also the value of the superposition function p(t). Finally, the front path axis position vector j1(s1), the back path axis position vector j2(s2), and the value of the superposition function p(t) are substituted into the above formula (8) to obtain the axis vector of the path point of the smooth path / the axis position of the smooth path.

[0097] It can be understood that, first, the parameterized paths in the two axis spaces are input as the front-end parameterized function j1(s1) and the back-end parameterized function j2(s2), s1, s2∈[0,1]. The smooth inflection point parameter s of the front-end path specified by the user is 1z , and the smooth inflection point parameter s of the subsequent path 2z Then, the front and back paths that need to be smoothed are transformed into linear domains by the above formulas (1) and (2), that is, after parameter transformation, the paths j1 and j2 are functions of the weight parameter t. Then, the path of the smooth segment is transformed into domains by the above formula (3), that is, after parameter transformation, the path j m is a function of the parameter t. The parameter transformation form is the above formula (3), which needs to satisfy the above formulas (4) and (5), and then derive the polynomial function, that is, the conditions that the superposition function p(t) needs to satisfy, namely the above formulas (6) and (7). Then, the part of the front path that needs to be smoothed and the part of the back path that needs to be smoothed are superimposed by polynomial vectors to obtain the smoothed path segment, and the superposition form is the above formula (8), where the superposition function is still a polynomial function. The above formula (8) is the same as the superposition function in the above formula (3). Then, the smoothed path segment, that is, the smoothed path and the non-smooth part of the front path and the non-smooth part of the back path, needs to satisfy the third-order continuity of parameters (parameter continuity conditions) at the connection point, namely the above formulas (9) to (16), and then derive the eight conditions that the polynomial function superposition function p(t) needs to satisfy, including the above formulas (6) to (7). Therefore, it is determined that the superposition function p(t) is a seventh-order polynomial, and its eight coefficients are calculated, namely formula (17).

[0098] After the objective function is constructed, the objective function of the smooth path segment is finally obtained as the above formula (8). m ∈[0,1-s 1z +s 2z ] The process of obtaining the axis position is as follows: According to the above formula (3), the path parameter function s mand the smoothing point parameter calculation re-parameter t; according to the above formulas (1) to (2), the target inflection point s1 and the target inflection point s2 are calculated by the re-parameter t; according to the input parameterized path, that is, the front-end parameterized function and the back-end parameterized function, the target inflection point s1 and the target inflection point s2 are used to obtain the inflection axis vector j1(s1) of the target inflection point and the inflection axis vector j2(s2) of the target inflection point; according to the above formula (8), the axis position j of the smoothing path is calculated by the inflection axis vector j1(s1) of the target inflection point and the inflection axis vector j2(s2) of the target inflection point and the re-parameter t m , which is the axis position of the smooth segment.

[0099] It can be considered that the execution of the above steps S11 to S13 of the present application can be regarded as the implementation of a smoothing algorithm, specifically the implementation of a smoothing algorithm in the axis space. The smoothing algorithm proposed in the present application can make the smooth segment and the non-smooth segment meet the third-order geometric continuity, so that the axis position of the smooth path meets the geometric continuity. The smoothing algorithm proposed in the present application can make the smooth segment and the non-smooth segment meet the third-order parameter continuity, so that the axis position of the smooth path meets the parameter continuity. The smoothing algorithm proposed in the present application performs a reparameterized linear domain transformation on the front and back segments of the path, and performs a reparameterized high-order domain transformation on the smooth segment path, so that the path parameter s of the smooth segment and the reparameter t meet a monotonically increasing relationship, which facilitates the reverse solution of the reparameter t from the path parameter s. The smoothing algorithm proposed in the present application uses the reparameterization method, and the path parameter is also used as the smoothing object, that is, in the axis space, the n-dimensional components of the n axes are removed, and the path parameter is used as the seventh smoothing dimension to achieve third-order parameter continuity. The axis space path smoothing algorithm proposed in the present application has good robustness, has no requirements for the original path segment to be smoothed, and the smoothing object is the axis position vector of the path point, which will not cause the problem of mutual influence between the path and speed. This application adopts the method of polynomial vector superposition (interpolation) of the path segments corresponding to the turning point of the smooth front path and the turning point of the rear path, so that the path shape of the smooth segment can be controlled, the position of each axis of the robot will not exceed the limit, and the smooth segment and the non-smooth segment can achieve not only third-order geometric continuity but also third-order parameter continuity.

[0100] In the above scheme, the present application utilizes the re-parameters obtained by re-parameterizing the parts that need to be smoothed in the front path and / or the rear path. The re-parameters are only the information for re-parameterizing the position information and do not carry speed information, so that the axis position of the smooth path determined based on the re-parameters can reduce the coupling effect of speed and path. In addition, the axis position of the smooth path determined by the objective function that meets the parameter continuity condition is continuous in multiple dimensions for the curves corresponding to the parts that need to be smoothed in the front path and the rear path, which can make the control robot run smoother based on the axis position of the smooth path, thereby improving the operation efficiency of the robot.

[0101] Those skilled in the art will understand that in the above-mentioned method of the specific implementation method, the writing order of each step does not mean a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0102] See also Figure 4 , Figure 4 It is a schematic diagram of the framework of an embodiment of the robot smooth path planning device of the present application. The robot smooth path planning device 40 includes: an acquisition module 41, a first determination module 42 and a second determination module 43; wherein the acquisition module 41 is used to obtain smoothing point parameters and re-parameters corresponding to the smoothing point parameters, the smoothing point parameters including smoothing inflection point parameters of the front path and smoothing out point parameters of the rear path, the front path is the current movement path of the robot, and the rear path is the movement path that the robot will enter, and the re-parameters are parameters obtained by re-parameterizing the parts that need to be smoothed in the front path and / or the rear path; the first determination module 42 is used to determine the turning-out axis vector and the turning-in axis vector of the target turning point in the axis space based on the re-parameters, the target turning-out point is the turning-out point of the front path, and the target turning-in point is the turning-in point of the rear path; the second determination module 43 is used to use the objective function, the turning-out axis vector, the turning-in axis vector and the re-parameters that satisfy the parameter continuity condition to determine the axis position of the smooth path so as to control the robot to operate based on the axis position of the smooth path, and the smooth path is the path corresponding to the part that needs to be smoothed between the front path and the rear path.

[0103] In some embodiments, the first determination module 42 is used to determine the turning-out axis vector of the target turning point and the turning-in axis vector of the target turning point in the axial space based on the re-parameters, including: obtaining the front-segment parameterized function corresponding to the front-segment path and the rear-segment parameterized function corresponding to the rear-segment path in the axial space; determining the target turning-out point and the target turning-in point according to the re-parameters; determining the turning-out axis vector of the target turning point using the front-segment parameterized function and the target turning-out point; and determining the turning-in axis vector of the target turning point using the rear-segment parameterized function and the target turning-in point.

[0104] In some embodiments, the first determination module 42 is used to determine the target inflection point and the target inflection point based on the weight parameters, including: obtaining a front-segment smoothing function and a rear-segment smoothing function, the front-segment smoothing function is used to represent the association relationship between the front-segment path and the smooth inflection point parameters, and the rear-segment smoothing function is used to represent the association relationship between the rear-segment path and the smooth inflection point parameters; determining the target inflection point based on the weight parameters and the front-segment smoothing function; determining the target inflection point based on the weight parameters and the rear-segment smoothing function.

[0105] In some embodiments, the robot smooth path planning device 40 also includes a third determination module (not shown). Before the second determination module 43 is used to determine the axis position of the smooth path using the objective function, turn-out axis vector, turn-in axis vector and heavy parameters that satisfy the parameter continuity condition, the third determination module is used to: obtain the superposition function, which is a polynomial function with heavy parameters and satisfies the parameter continuity condition; construct the objective function based on the superposition function, the front-end parameterized function and the back-end parameterized function.

[0106] In some embodiments, the third determination module is used to construct an objective function based on the superposition function, the front-end parameterization function and the back-end parameterization function, including: taking the difference between the back-end parameterization function and the front-end parameterization function as a candidate difference; taking the product of the candidate difference and the superposition function as a candidate product; taking the sum value between the front-end parameterization function and the candidate product as a candidate sum; and defining the candidate sum equal to the axis position of the smooth path as the objective function.

[0107] In some embodiments, the acquisition module 41 is used to obtain smooth point parameters and re-parameters corresponding to the smooth point parameters, including: obtaining a path parameter function of the smooth path, where the path parameter function is an expression function obtained by re-parameterizing the smooth path; and determining the re-parameters based on the path parameter function and the smooth point parameters.

[0108] In some embodiments, the acquisition module 41 is used to obtain the path parameter function of the smooth path, including: taking the difference between the front smooth function and the smooth inflection point parameter as the first difference, and the difference between the rear smooth function and the front smooth function as the second difference; taking the sum of the preset value and the second difference as the first sum, and taking the product between the superposition function and the first sum as the target product; taking the sum between the first difference and the target product as the second sum, and defining the second sum equal to the path parameter function.

[0109] In some embodiments, the third determination module is used to obtain the superposition function, including: determining the first constraint of the superposition function based on the path parameter function, the first constraint is used to represent the value of the superposition function when the weight parameter takes the maximum value; determining the second constraint of the superposition function based on the parameter continuity condition, the second constraint is used to represent the value of the superposition function when the superposition function satisfies the parameter continuity condition; based on the first constraint and the second constraint, determining the values of the number of terms and coefficients in the superposition function.

[0110] In the above scheme, the present application utilizes the re-parameters obtained by re-parameterizing the parts that need to be smoothed in the front path and / or the rear path. The re-parameters are only the information for re-parameterizing the position information and do not carry speed information, so that the axis position of the smooth path determined based on the re-parameters can reduce the coupling effect of speed and path. In addition, the axis position of the smooth path determined by the objective function that meets the parameter continuity condition is continuous in multiple dimensions for the curves corresponding to the parts that need to be smoothed in the front path and the rear path, which can make the control robot run smoother based on the axis position of the smooth path, thereby improving the operation efficiency of the robot.

[0111] See also Figure 5 , Figure 5 is a schematic diagram of the framework of an embodiment of an electronic device of the present application. The electronic device 50 includes a memory 51 and a processor 52 coupled to each other. The processor 52 is configured to execute program instructions stored in the memory 51 to implement the steps of any of the aforementioned embodiments of the robot smooth path planning method. In a specific implementation scenario, the electronic device 50 may include, but is not limited to, a microcomputer and a server. Furthermore, the electronic device 50 may also include mobile devices such as laptops and tablet computers, which are not limited herein.

[0112] Specifically, the processor 52 is used to control itself and the memory 51 to implement the steps of any of the above-mentioned robot smooth path planning method embodiments. The processor 52 can also be called a CPU (Central Processing Unit). The processor 52 may be an integrated circuit chip with signal processing capabilities. The processor 52 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. In addition, the processor 52 can be implemented by an integrated circuit chip.

[0113] In the above scheme, the present application utilizes the re-parameters obtained by re-parameterizing the parts that need to be smoothed in the front path and / or the rear path. The re-parameters are only the information for re-parameterizing the position information and do not carry speed information, so that the axis position of the smooth path determined based on the re-parameters can reduce the coupling effect of speed and path. In addition, the axis position of the smooth path determined by the objective function that meets the parameter continuity condition is continuous in multiple dimensions for the curves corresponding to the parts that need to be smoothed in the front path and the rear path, which can make the control robot run smoother based on the axis position of the smooth path, thereby improving the operation efficiency of the robot.

[0114] See also Figure 6 , Figure 6 The computer-readable storage medium 60 stores program instructions 601 that can be executed by a processor, and the program instructions 601 are used to implement the steps of any of the above-mentioned robot smooth path planning method embodiments.

[0115] In the above scheme, the present application utilizes the re-parameters obtained by re-parameterizing the parts that need to be smoothed in the front path and / or the rear path. The re-parameters are only the information for re-parameterizing the position information and do not carry speed information, so that the axis position of the smooth path determined based on the re-parameters can reduce the coupling effect of speed and path. In addition, the axis position of the smooth path determined by the objective function that meets the parameter continuity condition is continuous in multiple dimensions for the curves corresponding to the parts that need to be smoothed in the front path and the rear path, which can make the control robot run smoother based on the axis position of the smooth path, thereby improving the operation efficiency of the robot.

[0116] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments. For the sake of brevity, it will not be repeated here.

[0117] The above description of the various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced with each other and will not be repeated herein for the sake of brevity.

[0118] In the several embodiments provided in this application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device implementation methods described above are only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation. For example, units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0119] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0120] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

Claims

1. A robot smooth path planning method, characterized in that: The method comprises: Obtaining smoothing point parameters and corresponding re-parameters of the smoothing point parameters, the smoothing point parameters including smoothing inflection point parameters of a front path and smoothing inflection point parameters of a rear path, the front path being the current movement path of the robot, the rear path being the movement path the robot will enter, and the re-parameters being parameters obtained by re-parameterizing portions of the front path and / or the rear path that require smoothing; Determine, based on the weight parameters, an inflection axis vector of a target inflection point and an inflection axis vector of a target inflection point in the axis space, wherein the target inflection point is the inflection point of the front path, and the target inflection point is the inflection point of the back path; Using the objective function that satisfies the parameter continuity condition, the turn-out axis vector, the turn-in axis vector and the weight parameter, the axis position of the smooth path is determined so as to control the robot to operate based on the axis position of the smooth path, and the smooth path is the path corresponding to the part that needs to be smoothed between the front path and the rear path.

2. The method according to claim 1, characterized in that The step of determining the inflection axis vector of the target inflection point and the inflection axis vector of the target inflection point in the axis space based on the weight parameter includes: Obtaining a front-segment parameterized function corresponding to the front-segment path and a back-segment parameterized function corresponding to the back-segment path in the axis space; Determining the target inflection point and the target inflection point according to the weight parameter; Determining an inflection axis vector of the target inflection point using the preceding parameterized function and the target inflection point; The inflection axis vector of the target inflection point is determined by using the latter parameterized function and the target inflection point.

3. The method according to claim 2, characterized in that The step of determining the target inflection point and the target inflection point according to the weight parameter includes: Obtaining a front-segment smoothing function and a back-segment smoothing function, wherein the front-segment smoothing function is used to represent the association relationship between the front-segment path and the smooth inflection point parameter, and the back-segment smoothing function is used to represent the association relationship between the back-segment path and the smooth inflection point parameter; Determining the target inflection point according to the weight parameter and the front-segment smoothing function; The target inflection point is determined according to the weight parameter and the latter smoothing function.

4. The method according to claim 2, characterized in that Before determining the axis position of the smooth path using the objective function that satisfies the parameter continuity condition, the turn-out axis vector, the turn-in axis vector, and the weight parameter, the method further includes: Obtaining a superposition function, where the superposition function is a polynomial function of the multiple parameters and satisfies the parameter continuity condition; The objective function is constructed based on the superposition function, the front-end parameterization function and the back-end parameterization function.

5. The method according to claim 4, characterized in that The constructing the objective function based on the superposition function, the front-end parameterized function and the back-end parameterized function includes: taking the difference between the latter parameterized function and the former parameterized function as a candidate difference; taking the product of the candidate difference value and the superposition function as a candidate product; Taking the sum of the preceding parameterized function and the candidate product as the candidate sum; The objective function is defined based on the candidate sum and the axis position of the smoothed path.

6. The method according to claim 4, characterized in that The obtaining of the smoothing point parameter and the weight parameter corresponding to the smoothing point parameter includes: Obtaining a path parameter function of the smooth path, where the path parameter function is an expression function obtained by reparameterizing the smooth path; A weight parameter is determined according to the path parameter function and the smoothing point parameter.

7. The method according to claim 6, characterized in that The path parameter function for obtaining the smooth path includes: The difference between the front-segment smoothing function and the smoothing inflection point parameter is used as a first difference, and the difference between the rear-segment smoothing function and the front-segment smoothing function is used as a second difference; using a sum of a preset value and the second difference as a first sum, and using a product of the superposition function and the first sum as a target product; A sum value between the first difference and the target product is used as a second sum, and the path parameter function is constructed based on the second sum.

8. The method according to claim 6, characterized in that The obtaining of the superposition function comprises: Determining a first constraint condition of the superposition function based on the path parameter function, wherein the first constraint condition is used to represent a value of the superposition function when the weight parameter takes a maximum value; Determining, based on the parameter continuity condition, a second constraint condition of the superposition function, where the second constraint condition is used to represent a value of the superposition function when the superposition function satisfies the parameter continuity condition; Based on the first constraint condition and the second constraint condition, the number of terms and values of coefficients in the superposition function are determined.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the memory stores program instructions, and the processor calls the program instructions from the memory to execute the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having program instructions stored thereon, characterized in that: When the program instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 8.

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