CN111993411A - Robot motion planning method and device, robot and storage medium - Google Patents
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Abstract
The application is applicable to the technical field of communication, and provides a robot motion planning method, a device, a robot and a computer readable storage medium, wherein the method comprises the following steps: acquiring current physical state parameters, target physical state parameters and motion planning conditions of the robot; inputting the current physical state parameter, the target physical state parameter and the motion planning condition into a preset motion planning model to obtain a motion control parameter of the robot; the preset motion planning model is a motion planning model established by an exhaustion method, the motion planning model is a motion planning model with continuous physical parameters, and the physical parameters comprise speed, angular speed, moment or position; and controlling the robot according to the motion control parameters. The embodiment provided by the application can reduce the end jitter.
Description
Technical Field
The present application relates to the field of robot technology, and in particular, to a method and an apparatus for planning robot motion, a robot, and a computer-readable storage medium.
Background
A robot is an intelligent machine that can work semi-autonomously or fully autonomously. It can accept human command, run the program programmed in advance, and also can operate according to the principle outline action made by artificial intelligence technology.
In a mobile robot, a plurality of motion units exist. Such as a chassis motion unit, an arm motion unit, a head motion unit, etc. All motion processes can be simplified to a change from state a to state B, which may be physical state parameters such as torque, speed, position, etc.
In the current motion planning scheme, a T-type or cubic polynomial acceleration and deceleration method is mostly adopted for motion planning, and the terminal jitter phenomenon is serious in the state switching process.
Disclosure of Invention
The embodiment of the application provides a robot motion planning method and device, a robot and a storage medium, which can solve at least part of technical problems in the related art.
In a first aspect, an embodiment of the present application provides a robot motion planning method, including:
acquiring current physical state parameters, target physical state parameters and motion planning conditions of the robot;
inputting the current physical state parameter, the target physical state parameter and the motion planning condition into a preset motion planning model to obtain a motion control parameter of the robot; the preset motion planning model is a motion planning model established by an exhaustion method, the motion planning model is a motion planning model with continuous physical parameters, and the physical parameters comprise speed, angular speed, moment or position;
and controlling the robot according to the motion control parameters.
On one hand, the embodiment of the first aspect considers the motion planning condition, and ensures small jitter and high smoothness; on the other hand, a motion planning model with continuous physical parameters is preset, so that the continuity of the physical parameters is met, and the control effect of small jitter is achieved; on the other hand, the preset motion planning model is used for motion planning, so that the computational cost is reduced, and the scheme is simple and easy to implement.
In a second aspect, an embodiment of the present application provides a robot motion planning apparatus, including:
the acquisition unit is used for acquiring the current physical state parameter, the target physical state parameter and the motion planning condition of the robot;
the calculation unit is used for inputting the current physical state parameter, the target physical state parameter and the motion planning condition into a preset motion planning model to obtain a motion control parameter of the robot; the preset motion planning model is a motion planning model established by an exhaustion method, the motion planning model is a motion planning model with continuous physical parameters, and the physical parameters comprise speed, angular speed, moment or position;
and the control execution unit is used for controlling the robot according to the motion control parameters.
In a third aspect, an embodiment of the present application provides a robot, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor, when executing the computer program, implements the robot motion planning method according to the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the robot motion planning method according to the first aspect.
In a fifth aspect, an embodiment of the present application provides a computer program product, which when running on a robot, causes an electronic device to execute the robot motion planning method according to the first aspect.
It is understood that the beneficial effects of the second aspect to the fifth aspect can be referred to the related description of the first aspect, and are not described herein again.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic structural diagram of a robot to which a robot motion planning method provided in an embodiment of the present application is applied;
fig. 2 is a schematic flowchart of a robot motion planning method according to an embodiment of the present disclosure;
FIG. 3A is a schematic diagram of an exercise planning model provided in an embodiment of the present application;
FIG. 3B is another schematic diagram of an exercise planning model provided by an embodiment of the present application;
fig. 4 is a schematic structural diagram of a robot motion planning apparatus according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a robot motion planning apparatus according to another embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
The terminology used in the following examples is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
It should also be understood that in the embodiments of the present application, "one or more" means one, two, or more than two; "and/or" describes the association relationship of the associated objects, indicating that three relationships may exist; for example, a and/or B, may represent: a alone, both A and B, and B alone, where A, B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
The robot motion planning method provided by the embodiment of the application can be applied to robots. Fig. 1 is a schematic structural diagram of a robot according to an embodiment of the present application. As shown in fig. 1, the robot 1 of this embodiment includes: at least one processor 10 (only one is shown in fig. 1), a memory 11, and a computer program 12 stored in the memory 11 and executable on the at least one processor 10, wherein the processor 10, when executing the computer program 12, implements the steps in each of the robot motion planning method embodiments provided by the embodiments of the present application. Or the functions of each unit in each robot motion planning device embodiment provided by the embodiment of the present application are realized.
The robot 1 may include, but is not limited to, a processor 10, a memory 11. It will be appreciated by those skilled in the art that fig. 1 is merely an example of the robot 1 and does not constitute a limitation of the robot 1, and that the robot may include more or less components than those shown, or some components may be combined, or different components may include, for example, input and output devices, network access devices, motors, chassis, sensors, etc.
The Processor 10 may be a Central Processing Unit (CPU), and the Processor 10 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 11 may in some embodiments be an internal storage unit of the robot 1, such as a hard disk or a memory of the robot 1. In other embodiments, the memory 11 may also be an external storage device of the robot 1, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, provided on the robot 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the robot 1. The memory 11 is used for storing an operating system, an application program, a BootLoader (BootLoader), data, and other programs, such as program codes of a computer program. The memory 11 may also be used to temporarily store data that has been output or is to be output.
A robot motion planning method provided in an embodiment of the present application is described below.
Fig. 2 shows a schematic flowchart of a robot motion planning method provided by the present application. The method is executed by a robot motion planning device, which can be configured to the robot and can be implemented by software and/or hardware. As shown in fig. 2, the method includes steps S210 to S230, and the implementation process and principle of each step are as follows.
And S210, acquiring the current physical state parameters, the target physical state parameters and the motion planning conditions of the robot.
In some embodiments of the present application, motion planning may be performed for a chassis of a robot, one or more motors (or servomotors). It should be understood that each joint of the robot is correspondingly provided with a motor, and the rotation of the motor is controlled so as to drive the rotation of the joint. The chassis of the robot is controlled to move or rotate, and the whole robot can be controlled to move or rotate. Therefore, the motion planning scheme provided by the embodiment of the application can be applied to chassis motion planning, such as chassis speed and/or position; but also to motor motion planning, such as speed and/or position of the motor, etc.
In some embodiments of the present application, a motion planning scheme may be started after obtaining a control command for a change in robot state. The state change control command indicates a command for controlling a physical state parameter of a joint or a chassis of the robot to change from a first state to a second state. The first state is a current physical state parameter and the second state is a target physical state parameter. Physical state parameters include, but are not limited to: speed, torque, or position, etc. The speed may be a linear speed or an angular speed.
In some embodiments of the present application, the robot may autonomously initiate control instructions for state changes. For example, after a work task, such as a material taking work task, is received by the robot arm, motion planning needs to be performed on each joint, including but not limited to planning one or more physical state parameters of speed, torque, position, and the like of a motor corresponding to each joint.
In other embodiments of the present application, a control instruction for a robot state change may be initiated by a user. As a non-limiting example, the user may initiate at the robot or at other electronic devices communicatively coupled to the robot before transmitting to the robot. This is not limited by the present application.
In the embodiment of the present application, the motion planning condition refers to a limitation condition of the motion planning. The motion planning conditions can be set by the default of the robot system; or can be set by the user in a self-defined way; the settings may also be partly set by the robot system default and partly by the user customization. The default motion planning conditions for the robot system may be determined by the hardware and/or software attributes of the robot. For example, when the robot is manufactured, the factory sets a maximum possible moving speed and a maximum possible acceleration, etc.
The exercise planning conditions include, but are not limited to: one or more of a distance of movement, a length of movement time, a maximum acceleration, a maximum speed of movement, and the like.
In the embodiment of the application, in the motion planning for changing from the first state to the second state, the motion planning conditions, such as an acceleration limit value and the like, are considered, so that the robot does not exceed the allowed maximum acceleration, and the small jitter and the high smoothness are ensured.
And S220, inputting the current physical state parameter, the target physical state parameter and the motion planning condition into a preset motion planning model to obtain the motion control parameter of the robot.
In the embodiment of the application, the robot presets the motion planning model, and the motion planning model can be stored in a memory of the robot and called when in use. The motion planning model is a motion planning model with continuous physical parameters. The motion planning model is a model taking the current physical state parameter, the target physical state parameter and the motion planning condition as variables.
The motion planning model may be one or more, and the motion planning model includes, but is not limited to, a linear motion planning model, a curvilinear motion planning model, or a combination of linear and curvilinear motion planning models. The motion planning model is not particularly limited by the present application.
In the motion planning of the state change provided by the embodiment of the application, the continuity, smoothness or continuous rule of physical parameters is met, the higher requirement on the motion planning is met, and the control effect of small jitter is achieved.
And inputting the current physical state parameter, the target physical state parameter and the motion planning condition into a preset motion planning model to obtain the motion control parameter of the robot.
In some implementations of the present application, if there is one preset motion planning model, the current physical state parameter, the target physical state parameter, and the motion planning condition are input into the preset motion planning model to obtain the motion control parameter of the robot.
In some implementation manners of the present application, if a plurality of preset motion planning models are provided, the current physical state parameter, the target physical state parameter and the motion planning condition are input into the preset motion planning models to obtain the calculation results of each motion planning model, and the calculation results meeting the actual conditions are used as the motion control parameters of the robot.
In some implementations of the present application, the motion planning model is preset in an exhaustive manner.
The explanation is given by taking the example of planning the physical state parameter of speed by using a linear motion planning model, and the motion planning model comprises a two-section linear planning model and a three-section linear planning model.
In practical application, the current physical state parameter, the target physical state parameter and the motion planning condition are input into a preset two-section linear planning model and a preset three-section linear planning model, and respective solutions of the two models are obtained. Then, the solutions calculated by the two models are judged, and if the solutions of the two linear planning models meet the actual condition, namely the engineering practice condition, the solution of the model is adopted as the motion control parameter; and if the solution of the three-section linear programming model accords with the actual condition, the solution of the model is used as the motion control parameter.
And S230, controlling the robot according to the motion control parameters.
Step S220 obtains motion control parameters, such as motion control parameters of the chassis or the motor. In step S230, the chassis or the motor of the robot is controlled according to the obtained motion control parameters, thereby completing the motion planning.
In the embodiment of the application, on one hand, the motion planning condition is considered, and the small jitter and high smoothness are ensured; on the other hand, a motion planning model with continuous physical parameters is preset, so that the continuity of the physical parameters is met, and the control effect of small jitter is achieved; on the other hand, the preset motion planning model is used for motion planning, so that the computational cost is reduced, and the scheme is simple and easy to implement.
Next, the technical solution of the embodiment of the present application will be described in detail by taking an example of a plan for linear motion of the chassis from the first speed to the second speed.
As an example, the current chassis speed v0I.e. initial velocity v0The target speed is 0, i.e., the final speed is 0. Furthermore, the chassis speed does not exceed the speed value v according to the robot system settingsmI.e. maximum velocity vmThe maximum acceleration value is a; and determining that the speed of the robot is just 0 after the robot moves for a distance s according to the movement distance s input by the user. In addition, considering the working efficiency of the robot, the shortest time is required to be satisfied to calculate the optimal velocity plan, and the maximum acceleration value a is adopted for acceleration in the linear motion plan according to the input of the user or the system setting of the robot.
Analysis by exhaustion, different initial velocities v0，vmThere are 14 cases of linear motion planning, as shown in fig. 3A and 3B, 6 of which are shown in fig. 3A and 8 of which are shown in fig. 3B. In fig. 3A and 3B, the horizontal axis represents time T, the vertical axis represents velocity V, and the linear motion distanceThe distance is s. Using case 3 in FIG. 3A as an example, the initial chassis velocity v0Elapsed time t1Accelerate to vnThen from vnSlowing down to 0 for a total duration of t2. S1 and S2 respectively indicate two straight lines of speed. Using case 7 in FIG. 3B as an example, the initial chassis velocity v0Elapsed time t1Is decelerated to vmThen with vmMove at a constant speed until t2Finally to 0 for a total duration of t3. S1, S2, and S3 represent three straight lines of speed, respectively.
Meanwhile, according to 14 kinds of rectilinear motion planning situations, the following two planning models can be generalized.
First, a two-segment line planning model.
Referring to cases 3 to 6 in fig. 3A, these four cases can be summarized as a two-segment line planning model, which is a motion planning model with continuous velocity. The two-segment linear programming model is characterized in that: the slope signs of the two straight lines are opposite, and the value is the maximum acceleration value a; chassis speed can only reach vnCan not reach vmValue vnLess than vm. Known initial velocity v0In the two-segment linear programming model, the integral of the velocity V over time is the distance s.
The first straight line S1 passes (0, v)0) At point, the second straight line S2 passes (t)20), the equations of the two straight lines can be set as:
S1：y＝kx+v0；
S2：y＝-kx+kt2。
unknown parameters are k, t1,t2. According to the characteristics of the two-segment linear programming model, namely the known conditions, 3 solving equations can be listed as follows:
①k2-a2＝0；
②kt1+v0＝-kt1+kt2；
solving the equation can obtain four groups of k, t1,t2Each group of the analytic solutions is k, t from top to bottom in sequence1,t2：
Wherein,
in application, v is0After the values of a and s are substituted, according to t1>0，t2>t1The three groups of solutions which do not meet the actual conditions or the engineering practical conditions can be excluded. When eq1 is calculated to be 0, the first and second set of solutions are equal; alternatively, when eq2 is calculated to be 0, the third and fourth set of solutions are equal and the two projected straight lines degenerate into one straight line, corresponding to case 1 and case 2 in fig. 3A. Therefore, the parameters of the actual planning linear equation of the cases 1 to 6, i.e., the control parameters of the chassis, can be solved in an inductive manner according to the above method.
And the second type is a three-section straight line planning model.
Referring to cases 7 to 12 in fig. 3B, these four cases can be summarized as a three-segment line plan model. The three-section straight line planning model is characterized in that: the chassis speed can reach v in the second straight line S2mThe value is obtained. Known initial velocity v0In the three-segment linear programming model, the integral of the velocity V over time is the distance s.
The first straight line S1 passes (0, v)0) Point, constant velocity v of the second straight line S2mThe third straight line S3 passes (t)20), the equations of three straight lines can be set as:
S1：y＝k1x+v0；
S2：y＝vm；
S3：y＝k2x-k2t3。
unknown parameter k1,k2,t1,t2,t3. According to the characteristics of the three-segment linear programming model, namely the known conditions, 5 solving equations can be listed as follows:
①k1 2-a2＝0；
②k2 2-a2＝0；
③k1t1+v0＝vm；
④k2t2-k2t3＝vm；
solving the equations can obtain four groups of k1,k2,t1,t2,t3Analytic solutions, each group of analytic solutions is k from top to bottom in sequence1,k2,t1,t2,t3：
In application, v is0,a,s,vmAccording to t1>0，t2>t1，t3>t2The three groups of solutions which do not meet the actual conditions or the engineering practical conditions can be excluded. When v is0And vmAre equal, t1The three planned straight lines degenerate into two straight lines, corresponding to cases 13 and 14 in fig. 3B, 0. Therefore, the parameters of the actual planning straight line equation of the cases 7 to 14, i.e., the control parameters of the chassis, can be solved in an inductive manner according to the above method.
At this point, the process of presetting the motion planning model by an exhaustive method or an enumeration method is completed. Two linear motion planning models, namely a two-section linear planning model and a three-section linear planning model, are established.
In practical application, it is necessary to determine which motion planning model is used for motion planning, and specifically, the determination may be performed by the following method: by applying actual values, e.g. v0,a,s,vmThe numerical value of (c) is brought into a two-segment linear programming model, if the numerical value meets the actual condition or the engineering practical condition, the numerical value meets t1>0，t2>t1And (4) planning the motion of the chassis by using the two sections of linear planning models. And conversely, performing motion planning on the chassis by using a three-section linear planning model.
The method can be used for planning the chassis motion (speed, position and the like) straight line. In addition, the method can be used for linear planning or rotary planning of the movement (speed, position and the like) of the servo motor, smooth switching of physical states is achieved, and jitter of the tail end is small. It should be understood that in the example of a rotation plan, the velocity is angular velocity, the acceleration is angular acceleration, and the movement distance s is replaced by a rotation angle.
In addition, the analytic solution is calculated through the two types of planning models, so that the scheme is easier to realize in programming.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Fig. 4 shows a block diagram of a robot motion planning apparatus provided in the embodiment of the present application, which corresponds to the robot motion planning method described in the above embodiment, and only shows portions related to the embodiment of the present application for convenience of description.
Referring to fig. 4, the robot motion planning apparatus includes:
an obtaining unit 41, configured to obtain a current physical state parameter, a target physical state parameter, and a motion planning condition of the robot;
a calculating unit 42, configured to input the current physical state parameter, the target physical state parameter, and the motion planning condition into a preset motion planning model to obtain a motion control parameter of the robot; the preset motion planning model is a motion planning model established by an exhaustion method, the motion planning model is a motion planning model with continuous physical parameters, and the physical parameters comprise speed, angular speed, moment or position;
and a control execution unit 43 for controlling the robot according to the motion control parameters.
Optionally, as shown in fig. 5, the robot motion planning apparatus further includes:
a building unit 40 for building the motion planning model by an exhaustive method.
Optionally, the establishing unit 40 is specifically configured to:
and establishing a motion planning model among the current physical state parameters, the target physical state parameters, the motion planning conditions and the motion control parameters by an exhaustion method.
Optionally, the motion planning model comprises: a linear motion planning model, a curvilinear motion planning model, or a combination of linear and curvilinear motion planning models.
Optionally, the motion planning model is a linear motion planning model, and the linear motion planning model includes a two-segment linear planning model and a three-segment linear planning model.
Optionally, the computing unit 42 is specifically configured to:
inputting the current physical state parameter, the target physical state parameter and the motion planning condition into a preset motion planning model to obtain an analytic solution of the motion planning model, and if the analytic solution meets a preset condition, taking the analytic solution meeting the preset condition as a motion control parameter.
Optionally, the preset condition is an engineering practice condition.
It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Embodiments of the present application further provide a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program may implement each step in the robot motion planning method embodiment.
The embodiment of the present application provides a computer program product, which when running on a robot, enables the robot to implement various steps in the robot motion planning method embodiment when executing the computer program product.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a network terminal, recording medium, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, and software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/device and method may be implemented in other ways. For example, the above-described apparatus/device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A robot motion planning method, comprising:
acquiring current physical state parameters, target physical state parameters and motion planning conditions of the robot;
inputting the current physical state parameter, the target physical state parameter and the motion planning condition into a preset motion planning model to obtain a motion control parameter of the robot; the preset motion planning model is a motion planning model established by an exhaustion method, the motion planning model is a motion planning model with continuous physical parameters, and the physical parameters comprise speed, angular speed, moment or position;
and controlling the robot according to the motion control parameters.
2. A robot motion planning method according to claim 1, wherein the motion planning model comprises: a linear motion planning model, a curvilinear motion planning model, or a combination of linear and curvilinear motion planning models.
3. A robot motion planning method according to claim 1 or 2, wherein the motion planning model is established by an exhaustive method comprising:
and establishing a motion planning model among the current physical state parameters, the target physical state parameters, the motion planning conditions and the motion control parameters by an exhaustion method.
4. A robot motion planning method according to claim 1 or 2, wherein the motion planning model is a linear motion planning model comprising a two-segment linear planning model and a three-segment linear planning model.
5. The robot motion planning method according to claim 1 or 2, wherein the step of inputting the current physical state parameter, the target physical state parameter and the motion planning condition into a preset motion planning model to obtain the motion control parameter of the robot comprises:
inputting the current physical state parameter, the target physical state parameter and the motion planning condition into a preset motion planning model to obtain an analytic solution of the motion planning model, and if the analytic solution meets a preset condition, taking the analytic solution meeting the preset condition as a motion control parameter.
6. A robot motion planning method according to claim 5 in which the preset conditions are engineering practice conditions.
7. A robot motion planning apparatus, comprising:
the acquisition unit is used for acquiring the current physical state parameter, the target physical state parameter and the motion planning condition of the robot;
the calculation unit is used for inputting the current physical state parameter, the target physical state parameter and the motion planning condition into a preset motion planning model to obtain a motion control parameter of the robot; the preset motion planning model is a motion planning model established by an exhaustion method, the motion planning model is a motion planning model with continuous physical parameters, and the physical parameters comprise speed, angular speed, moment or position;
and the control execution unit is used for controlling the robot according to the motion control parameters.
8. The robot motion planning apparatus of claim 7 wherein the computing unit is specifically configured to:
inputting the current physical state parameter, the target physical state parameter and the motion planning condition into a preset motion planning model to obtain an analytic solution of the motion planning model, and if the analytic solution meets a preset condition, taking the analytic solution meeting the preset condition as a motion control parameter.
9. A robot comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the control method according to any of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, implements the control method according to any one of claims 1 to 6.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112597612A (en) * | 2020-12-30 | 2021-04-02 | 深圳市优必选科技股份有限公司 | Robot optimization method and device, terminal equipment and computer-readable storage medium |
| CN112783171A (en) * | 2020-12-31 | 2021-05-11 | 上海擎朗智能科技有限公司 | Robot operation control method and device, electronic equipment and storage medium |
| CN113312777A (en) * | 2021-06-03 | 2021-08-27 | 广东博智林机器人有限公司 | Method and device for checking construction working face, electronic equipment and storage medium |
| CN115826430A (en) * | 2022-09-22 | 2023-03-21 | 宁德时代新能源科技股份有限公司 | Method, device and storage medium for modifying kinematic pair parameters |
| CN116277038A (en) * | 2023-05-23 | 2023-06-23 | 极限人工智能(北京)有限公司 | Mechanical arm track planning method and system for given time and initial and final speeds |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106346478A (en) * | 2016-11-09 | 2017-01-25 | 广州视源电子科技股份有限公司 | control method and device of mechanical arm |
| CN107030697A (en) * | 2017-04-28 | 2017-08-11 | 广州大学 | A kind of planing method of robot cartesian space smooth track |
| EP3403772A1 (en) * | 2017-05-18 | 2018-11-21 | KUKA Hungária Kft. | Robot motion planning for avoiding collision with moving obstacles |
| CN109129470A (en) * | 2018-08-02 | 2019-01-04 | 深圳市智能机器人研究院 | The method and system for planning of robot straight line path |
| CN109434831A (en) * | 2018-11-12 | 2019-03-08 | 深圳前海达闼云端智能科技有限公司 | Robot operation method and device, robot, electronic device and readable medium |
| CN110850883A (en) * | 2019-11-29 | 2020-02-28 | 上海有个机器人有限公司 | Movement control method, medium, terminal and device of robot |
-
2020
- 2020-07-07 CN CN202010645041.1A patent/CN111993411A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106346478A (en) * | 2016-11-09 | 2017-01-25 | 广州视源电子科技股份有限公司 | control method and device of mechanical arm |
| CN107030697A (en) * | 2017-04-28 | 2017-08-11 | 广州大学 | A kind of planing method of robot cartesian space smooth track |
| EP3403772A1 (en) * | 2017-05-18 | 2018-11-21 | KUKA Hungária Kft. | Robot motion planning for avoiding collision with moving obstacles |
| CN109129470A (en) * | 2018-08-02 | 2019-01-04 | 深圳市智能机器人研究院 | The method and system for planning of robot straight line path |
| CN109434831A (en) * | 2018-11-12 | 2019-03-08 | 深圳前海达闼云端智能科技有限公司 | Robot operation method and device, robot, electronic device and readable medium |
| CN110850883A (en) * | 2019-11-29 | 2020-02-28 | 上海有个机器人有限公司 | Movement control method, medium, terminal and device of robot |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112597612A (en) * | 2020-12-30 | 2021-04-02 | 深圳市优必选科技股份有限公司 | Robot optimization method and device, terminal equipment and computer-readable storage medium |
| CN112597612B (en) * | 2020-12-30 | 2023-12-15 | 深圳市优必选科技股份有限公司 | Robot optimization method, device, terminal equipment and computer readable storage medium |
| CN112783171A (en) * | 2020-12-31 | 2021-05-11 | 上海擎朗智能科技有限公司 | Robot operation control method and device, electronic equipment and storage medium |
| CN113312777A (en) * | 2021-06-03 | 2021-08-27 | 广东博智林机器人有限公司 | Method and device for checking construction working face, electronic equipment and storage medium |
| CN115826430A (en) * | 2022-09-22 | 2023-03-21 | 宁德时代新能源科技股份有限公司 | Method, device and storage medium for modifying kinematic pair parameters |
| WO2024060553A1 (en) * | 2022-09-22 | 2024-03-28 | 宁德时代新能源科技股份有限公司 | Method and apparatus for modifying parameters of kinematic pair, and storage medium |
| CN116277038A (en) * | 2023-05-23 | 2023-06-23 | 极限人工智能(北京)有限公司 | Mechanical arm track planning method and system for given time and initial and final speeds |
| CN116277038B (en) * | 2023-05-23 | 2023-10-20 | 极限人工智能(北京)有限公司 | Mechanical arm track planning method and system for given time and initial and final speeds |
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