WO2022198995A1

WO2022198995A1 - Gait trajectory planning method and apparatus, computer readable storage medium, and robot

Info

Publication number: WO2022198995A1
Application number: PCT/CN2021/124621
Authority: WO
Inventors: 郭宜劼; 赵明国; 熊友军
Original assignee: 深圳市优必选科技股份有限公司
Priority date: 2021-03-26
Filing date: 2021-10-19
Publication date: 2022-09-29
Also published as: CN113110423A; CN113110423B

Abstract

A gait trajectory planning method and apparatus, a computer readable storage medium, and a robot (7). The method comprises: acquiring a standard gait trajectory library of a robot (7) (S101), the standard gait trajectory library comprising a plurality of standard gait trajectories, and each standard gait trajectory corresponding to a preset standard travel speed; determining the current travel speed of the robot (7) (S102); and performing interpolation calculation in a standard gait trajectory in the standard gait trajectory library according to the current travel speed to obtain a target gait trajectory corresponding to the current travel speed (S103). According to the method, a target gait trajectory corresponding to the current travel speed can be obtained just by performing interpolation calculation in a standard gait trajectory, thereby effectively ensuring high time relevancy of gait trajectory planning.

Description

Gait trajectory planning method, device, computer-readable storage medium, and robot

This application claims the priority of the Chinese Patent Application No. 202110324996.1 filed with the Chinese Patent Office on March 26, 2021, the entire contents of which are incorporated herein by reference.

technical field

The present application belongs to the field of robotics, and in particular, relates to a gait trajectory planning method, device, computer-readable storage medium, and robot.

Background technique

Humanoid robots are complex systems with multiple degrees of freedom. At present, when planning the gait trajectory of humanoid robots, the full dynamic model of the robot combined with model predictive control and other optimization methods can be used to comprehensively consider the multiple degrees of freedom and constraints of the robot. In theory, this is a perfect solution for gait trajectory planning, which can not only consider all the dynamics of the robot, but also provide real-time feedback and re-planning for future information. However, because the optimization problems generated by this method are often highly nonlinear and cannot guarantee convexity, a feasible solution may not be found in real-time calculation. Although the current computer computing power has developed rapidly, it still cannot meet the high real-time requirements of such methods. sexual needs.

technical problem

In view of this, the embodiments of the present application provide a gait trajectory planning method, device, computer-readable storage medium, and robot to solve the problem that high real-time gait trajectory planning cannot be performed in the prior art.

technical solutions

A first aspect of the embodiments of the present application provides a gait trajectory planning method, which may include:

obtaining a standard gait trajectory library of the robot; the standard gait trajectory library includes several standard gait trajectories, and each standard gait trajectory corresponds to a preset standard traveling speed;

Determine the current travel speed of the robot;

According to the current traveling speed, an interpolation calculation is performed in the standard gait track of the standard gait track library to obtain a target gait track corresponding to the current traveling speed.

Further, performing interpolation calculation in the standard gait trajectory of the standard gait trajectory library according to the current travel speed to obtain a target gait trajectory corresponding to the current travel speed may include:

The interpolation calculation is performed in the standard gait trajectory of the standard gait trajectory library according to the following formula:

Among them, n is the serial number of the standard travel speed, 1≤n≤N, N is the number of standard travel speeds, vn is the nth standard travel speed, and v _n ≤ v _n+1 ,

is the standard gait trajectory corresponding to vn in the standard gait trajectory library,

is the current traveling speed, and gait(t) is the target gait trajectory corresponding to the current traveling speed.

Further, after obtaining the target gait trajectory corresponding to the current travel speed, the gait trajectory planning method may further include:

Determine the current gait trajectory of the robot;

Perform trajectory fitting according to the current gait trajectory and the target gait trajectory to obtain a fitted gait trajectory that smoothly transitions from the current gait trajectory to the target gait trajectory.

Further, performing trajectory fitting according to the current gait trajectory and the target gait trajectory may include:

constructing a fitting trajectory expression with undetermined coefficients corresponding to the fitting gait trajectory;

Determine the boundary constraints of the fitting trajectory expression according to the current gait trajectory and the target gait trajectory;

Selecting several designated time points within a preset trajectory fitting period, and calculating the value of the target gait trajectory at each designated time point;

Constructing an optimization target corresponding to the fitting trajectory expression according to the values of the target gait trajectory at each specified time point;

Various undetermined coefficients of the fitting trajectory expression are determined according to the optimization objective and the boundary constraints, so as to obtain the fitting gait trajectory.

Further, the constructing a fitting trajectory expression with undetermined coefficients corresponding to the fitting gait trajectory may include:

Construct the fitted trajectory expression as follows:

where t is the time variable,

is the fitting trajectory expression, a _i is an undetermined coefficient, 0≤i≤5.

Further, determining the boundary constraints of the fitting trajectory expression according to the current gait trajectory and the target gait trajectory may include:

Determine boundary constraints as follows:

in,

is the current gait trajectory,

is the target gait trajectory, t ₀ is the start time of the fitted gait trajectory, and T is the end moment of the fitted gait trajectory.

Further, described according to the value of the target gait trajectory at each specified time point to construct the optimization target corresponding to the fitting trajectory expression, can include:

Build an optimization objective as follows:

Among them, t _m is the mth specified time point, 0≤m≤M, and M is the number of specified time points.

A second aspect of the embodiments of the present application provides a gait trajectory planning device, which may include:

The gait trajectory library acquisition module is used to acquire the standard gait trajectory library of the robot; the standard gait trajectory library includes several standard gait trajectories, and each standard gait trajectory corresponds to a preset standard travel speed;

The speed determination module is used to determine the current travel speed of the robot;

An interpolation calculation module, configured to perform interpolation calculation in the standard gait trajectory of the standard gait trajectory library according to the current travel speed to obtain a target gait trajectory corresponding to the current travel speed.

Further, the interpolation calculation module is specifically used to perform interpolation calculation in the standard gait trajectory of the standard gait trajectory library according to the following formula:

Further, the gait trajectory planning device may also include:

The current gait trajectory determination module is used to determine the current gait trajectory of the robot;

A trajectory fitting module, configured to perform trajectory fitting according to the current gait trajectory and the target gait trajectory, to obtain a fitted gait trajectory that smoothly transitions from the current gait trajectory to the target gait trajectory.

Further, the trajectory fitting module may include:

a fitted trajectory expression construction unit, used for constructing a fitted trajectory expression with undetermined coefficients corresponding to the fitted gait trajectory;

a boundary constraint condition determining unit, configured to determine the boundary constraint condition of the fitting trajectory expression according to the current gait trajectory and the target gait trajectory;

A designated time point selection unit, used to select several designated time points within a preset trajectory fitting period, and calculate the value of the target gait trajectory at each designated time point;

An optimization target construction unit for constructing an optimization target corresponding to the fitting trajectory expression according to the value of the target gait trajectory at each specified time point;

An undetermined coefficient solving unit, configured to determine each undetermined coefficient of the fitting trajectory expression according to the optimization objective and the boundary constraints, so as to obtain the fitting gait trajectory.

Further, the fitting trajectory expression building unit is specifically used to construct the fitting trajectory expression shown in the following formula:

where t is the time variable,

Further, the boundary constraint determination unit is specifically used to determine the boundary constraint shown in the following formula:

in,

is the current gait trajectory,

Further, the optimization target construction unit is specifically used to construct the optimization target shown in the following formula:

where t is the time variable,

is the target gait trajectory, t _m is the mth specified time point, 0≤m≤M, and M is the number of specified time points.

A third aspect of the embodiments of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, implements any of the above-mentioned gait trajectory planning methods step.

A fourth aspect of the embodiments 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, and the processor implements the computer program when the processor executes the computer program. The steps of any of the above gait trajectory planning methods.

A fifth aspect of the embodiments of the present application provides a computer program product, which, when the computer program product runs on a robot, causes the robot to execute the steps of any of the above gait trajectory planning methods.

beneficial effect

The beneficial effects of the embodiments of the present application compared with the prior art are: the embodiments of the present application acquire a standard gait trajectory library of the robot; the standard gait trajectory library includes several standard gait trajectories, and each standard gait trajectory The gait trajectories all correspond to a preset standard travel speed; determine the current travel speed of the robot; perform interpolation calculation in the standard gait trajectory of the standard gait trajectory library according to the current travel speed, and obtain a The target gait trajectory corresponding to the travel speed. Through the embodiment of the present application, the target gait trajectory corresponding to the current traveling speed can be obtained only by the interpolation calculation of the standard gait trajectory, which effectively ensures the high real-time performance of the gait trajectory planning.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present application more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only for the present application. In some embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.

1 is a flowchart of an embodiment of a gait trajectory planning method in an embodiment of the present application;

Fig. 2 is the schematic diagram of the state trajectory of the robot workspace;

Fig. 3 is a schematic diagram of the mutation of gait trajectory;

4 is a schematic flow chart of trajectory fitting according to the current gait trajectory and the target gait trajectory;

Fig. 5 is the schematic diagram of fitting gait trajectory;

6 is a structural diagram of an embodiment of a gait trajectory planning device in an embodiment of the present application;

FIG. 7 is a schematic block diagram of a robot in an embodiment of the present application.

Embodiments of the present invention

In order to make the purpose, features and advantages of the invention of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the following The described embodiments are only some, but not all, embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

It is to be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described feature, integer, step, operation, element and/or component, but does not exclude one or more other features , whole, step, operation, element, component and/or the presence or addition of a collection thereof.

It should also be understood that the terminology used in the specification of the application herein is for the purpose of describing particular embodiments only and is not intended to limit the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural unless the context clearly dictates otherwise.

It should also be further understood that, as used in this specification and the appended claims, the term "and/or" refers to and including any and all possible combinations of one or more of the associated listed items .

As used in this specification and the appended claims, the term "if" may be contextually interpreted as "when" or "once" or "in response to determining" or "in response to detecting" . Similarly, the phrases "if it is determined" or "if the [described condition or event] is detected" may be interpreted, depending on the context, to mean "once it is determined" or "in response to the determination" or "once the [described condition or event] is detected. ]" or "in response to detection of the [described condition or event]".

In addition, in the description of the present application, the terms "first", "second", "third", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

Referring to FIG. 1, an embodiment of a gait trajectory planning method in the embodiment of the present application may include:

Step S101 , obtaining a standard gait trajectory library of the robot.

Wherein, the standard gait trajectory library includes several standard gait trajectories, and each standard gait trajectory corresponds to a preset standard traveling speed.

The gait trajectory in this embodiment of the present application may refer to a certain single state trajectory, or may refer to a combination of multiple state trajectories. Figure 2 shows a schematic diagram of the state trajectory of some robot workspaces, including but not limited to the pitch angle θ _t (t) and roll angle γ _t (t) of the upper body posture, the forward position x of the upper body relative to the support feet _t (t), lateral position y _t (t) and height h _t (t), and forward position x _f (t), lateral position y _f (t) of the swing foot relative to the waist, and the swing foot relative to the ground Height z _f (t), where t is a time variable. Preferably, the gait trajectory in this embodiment of the present application may be a combination of the above state trajectories, namely:

gait(t)=[θt(t),γt( _t ), _xt ( _t ),yt( _t ),ht( _t ),xf( _t ), _yf ( _t ),zf (t)]

For any standard travel speed, the gait trajectory under a preset gait cycle (marked as T) can be generated in advance through the full dynamic model of the robot, and this gait trajectory can be used as the corresponding standard travel speed. Standard gait trajectory.

The number of standard traveling speeds to be set and the specific value of each standard traveling speed can be set according to actual conditions, which are not specifically limited in this embodiment of the present application.

Step S102, determining the current traveling speed of the robot.

For a certain time t during the robot's traveling process, the measured value of the forward speed of the robot's waist at this time can be taken as the current traveling speed, which is recorded as

Step S103: Perform interpolation calculation in the standard gait trajectory of the standard gait trajectory library according to the current travel speed to obtain a target gait trajectory corresponding to the current travel speed.

Specifically, interpolation calculation can be performed in the standard gait trajectory of the standard gait trajectory library according to the following formula:

is the standard gait trajectory corresponding to vn in the standard gait trajectory library, and gait(t) is the target gait trajectory corresponding to the current traveling speed.

For example, assuming that the number of standard travel speeds is 4, which are 0m/s, 0.3m/s, 0.6m/s, and 0.9m/s, the corresponding standard gait trajectories are gait ^v0 , gait ^v0.3 , and gait ^v0 , respectively ^.6 and gait ^v0.9 , the interpolation calculation can be performed according to the following formula:

In this way, the robot can select the gait trajectory most suitable for the current speed in real time even if it is disturbed by the speed during the traveling process, so as to ensure its own stability.

However, when the robot is disturbed, there is often a sudden change in speed. Therefore, when the gait trajectory planning is carried out in the above way, it will also bring about a sudden change in the gait trajectory, which will also cause the robot to walk unstable. FIG. 3 is a schematic diagram of the sudden change of the gait trajectory, in which the forward position x _f (t) of the swinging foot relative to the waist is used as an example for illustration. Assuming that the traveling speed of the robot is 0m/s, that is, the gait of walking on the spot, at the 0.1s moment of the gait cycle, it is suddenly disturbed, resulting in the sudden change of the traveling speed to 0.6m/s, and the gait from 0m/s is required. The trajectory is switched to the gait trajectory of 0.6m/s, which causes the instability of the robot's walking.

In response to this problem, in the embodiment of the present application, on the premise of determining the current gait trajectory of the robot and calculating the target gait trajectory, trajectory fitting can be performed according to the current gait trajectory and the target gait trajectory , to obtain a fitted gait trajectory that smoothly transitions from the current gait trajectory to the target gait trajectory.

As shown in Figure 4, the process of trajectory fitting may specifically include the following steps:

Step S401 , constructing a fitting trajectory expression with undetermined coefficients corresponding to the fitting gait trajectory.

The specific expression used can be set according to the actual situation, including but not limited to high-order polynomials and Bezier curves. For example, using a polynomial of degree 6, the fitted trajectory expression can be constructed as follows:

in,

For the fitting trajectory expression, a _i is an undetermined coefficient, 0≤i≤5, that is, there are altogether 6 undetermined coefficients a ₀ , a ₁ , a ₂ , a ₃ , a ₄ , and a ₅ .

The corresponding velocity expression can be obtained by taking the derivative of it, namely:

Step S402: Determine boundary constraints of the fitting trajectory expression according to the current gait trajectory and the target gait trajectory.

The time range under one gait cycle is [0, T], and the fitting gait trajectory needs to connect the position of the current gait trajectory at the current time t ₀ and the target gait trajectory at the final time T position, and at the same time satisfy the velocity continuity, that is, it is required to determine the boundary constraints shown in the following formula:

in,

is the current gait trajectory,

For example, if a 6th order polynomial is used, the corresponding boundary constraints are:

Step S403: Select several designated time points within a preset trajectory fitting period, and calculate the value of the target gait trajectory at each designated time point.

The trajectory fitting period is [t ₀ , T], and the number of specified time points can be set according to the actual situation. Preferably, two specified time points t ₁ and t ₂ can be selected as follows:

After selecting the specified time point, the value of the target gait trajectory at each specified time point can be calculated separately, that is,

and

Step S404 , constructing an optimization target corresponding to the fitting trajectory expression according to the values of the target gait trajectory at each specified time point.

Specifically, the optimization objective can be constructed as follows:

That is, the fitting trajectory is as close as possible to the target gait trajectory, and the deviation between the two is minimized, wherein t _m is the mth specified time point, 0≤m≤M, and M is the specified time point number of.

For example, if a 6th-order polynomial is used and only two specified time points t ₁ and t ₂ are selected, the corresponding optimization objective is:

Step S405: Determine each undetermined coefficient of the fitting trajectory expression according to the optimization objective and the boundary constraint condition to obtain the fitting gait trajectory.

For example, common optimization tools such as qpOASES can be used to analyze this optimization problem, and various undetermined coefficients of the fitted trajectory expression can be solved, thereby obtaining the fitted gait trajectory. Figure 5 shows the fitted gait trajectory corresponding to the example in Figure 3. Through this fitted gait trajectory, a smooth and continuous switching from the current trajectory to the new trajectory is realized. The above trajectory fitting process is repeated at each moment, that is, rolling trajectory fitting is performed.

It should be noted that the above description only takes the forward position x _f (t) of the swinging foot relative to the waist as an example for description, and other state trajectories can be processed by referring to the above method, which will not be repeated here.

To sum up, in this embodiment of the present application, the standard gait trajectory library of the robot is obtained; the standard gait trajectory library includes several standard gait trajectories, and each standard gait trajectory corresponds to a preset standard travel speed; determine the current travel speed of the robot; perform interpolation calculation in the standard gait trajectory of the standard gait trajectory library according to the current travel speed to obtain a target gait trajectory corresponding to the current travel speed. Through the embodiment of the present application, the target gait trajectory corresponding to the current traveling speed can be obtained only by the interpolation calculation of the standard gait trajectory, which effectively ensures the high real-time performance of the gait trajectory planning.

It should be understood that the size of the sequence numbers of the steps in the above embodiments does not mean the sequence of execution, and the execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

Corresponding to a gait trajectory planning method described in the above embodiment, FIG. 6 shows a structural diagram of an embodiment of a gait trajectory planning apparatus provided by an embodiment of the present application.

In this embodiment, a gait trajectory planning device may include:

The gait trajectory library acquisition module 601 is used to acquire the standard gait trajectory library of the robot; the standard gait trajectory library includes several standard gait trajectories, and each standard gait trajectory corresponds to a preset gait trajectory standard travel speed;

a speed determination module 602, used to determine the current travel speed of the robot;

The interpolation calculation module 603 is configured to perform interpolation calculation in the standard gait trajectory of the standard gait trajectory library according to the current travel speed to obtain a target gait trajectory corresponding to the current travel speed.

Further, the gait trajectory planning device may also include:

Further, the trajectory fitting module may include:

a fitting trajectory expression construction unit, used for constructing a fitting trajectory expression with undetermined coefficients corresponding to the fitted gait trajectory;

an optimization target construction unit, configured to construct an optimization target corresponding to the fitting trajectory expression according to the values of the target gait trajectory at each specified time point;

where t is the time variable,

in,

is the current gait trajectory,

Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described devices, modules and units can be referred to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

In the foregoing embodiments, the description of each embodiment has its own emphasis. For parts that are not described or described in detail in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

FIG. 7 shows a schematic block diagram of a robot provided by an embodiment of the present application. For convenience of description, only parts related to the embodiment of the present application are shown.

As shown in FIG. 7 , the robot 7 of this embodiment includes a processor 70 , a memory 71 , and a computer program 72 stored in the memory 71 and executable on the processor 70 . When the processor 70 executes the computer program 72 , the steps in each of the above embodiments of the gait trajectory planning method are implemented, for example, steps S101 to S103 shown in FIG. 1 . Alternatively, when the processor 70 executes the computer program 72, the functions of the modules/units in the above device embodiments, for example, the functions of the modules 601 to 603 shown in FIG. 6 are implemented.

Exemplarily, the computer program 72 may be divided into one or more modules/units, and the one or more modules/units are stored in the memory 71 and executed by the processor 70 to complete the this application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 72 in the robot 7 .

Those skilled in the art can understand that FIG. 7 is only an example of the robot 7, and does not constitute a limitation to the robot 7. It may include more or less components than the one shown, or combine some components, or different components, such as The robot 7 may also include input and output devices, network access devices, buses, and the like.

The processor 70 may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), Field-Programmable Gate Array (FPGA) 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 71 may be an internal storage unit of the robot 7 , such as a hard disk or a memory of the robot 7 . The memory 71 can also be an external storage device of the robot 7, such as a plug-in hard disk equipped on the robot 7, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, Flash card (Flash Card) and so on. Further, the memory 71 may also include both an internal storage unit of the robot 7 and an external storage device. The memory 71 is used to store the computer program and other programs and data required by the robot 7 . The memory 71 may also be used to temporarily store data that has been output or will be output.

Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. Module completion, that is, dividing the internal structure of the device into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated in one processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit, and the above-mentioned integrated units may adopt hardware. It can also be realized in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing from each other, and are not used to limit the protection scope of the present application. For the specific working processes of the units and modules in the above-mentioned system, reference may be made to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of this application.

In the embodiments provided in this application, it should be understood that the disclosed apparatus/robot and method may be implemented in other ways. For example, the device/robot embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or Components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.

The integrated modules/units, if implemented in the form of software functional units and sold or used as independent products, may be stored in a computer-readable storage medium. Based on this understanding, the present application can implement all or part of the processes in the methods of the above embodiments, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer When the program is executed by the processor, the steps of the foregoing method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form, and the like. The computer-readable storage medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM, Read-Only Memory) ), random access memory (RAM, Random Access Memory), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content contained in the computer-readable storage medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, computer-readable Storage media exclude electrical carrier signals and telecommunications signals.

The above-mentioned embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the above-mentioned embodiments, those of ordinary skill in the art should understand that: it can still be used for the above-mentioned implementations. The technical solutions described in the examples are modified, or some technical features thereof are equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions in the embodiments of the application, and should be included in the within the scope of protection of this application.

Claims

A gait trajectory planning method, comprising:

obtaining a standard gait trajectory library of the robot; the standard gait trajectory library includes several standard gait trajectories, and each standard gait trajectory corresponds to a preset standard traveling speed;

Determine the current travel speed of the robot;

According to the current traveling speed, an interpolation calculation is performed in the standard gait track of the standard gait track library to obtain a target gait track corresponding to the current traveling speed.
The gait trajectory planning method according to claim 1, wherein the interpolation calculation is performed in the standard gait trajectory of the standard gait trajectory library according to the current travel speed, to obtain the difference between the current travel speed and the current travel speed. The corresponding target gait trajectory, including:

The interpolation calculation is performed in the standard gait trajectory of the standard gait trajectory library according to the following formula:

Among them, n is the serial number of the standard travel speed, 1≤n≤N, N is the number of standard travel speeds, vn is the nth standard travel speed, and v n ≤ v n+1 ,
is the standard gait trajectory corresponding to vn in the standard gait trajectory library,
is the current traveling speed, and gait(t) is the target gait trajectory corresponding to the current traveling speed.
The gait trajectory planning method according to claim 1, wherein after obtaining the target gait trajectory corresponding to the current travel speed, the method further comprises:

Determine the current gait trajectory of the robot;

Perform trajectory fitting according to the current gait trajectory and the target gait trajectory to obtain a fitted gait trajectory that smoothly transitions from the current gait trajectory to the target gait trajectory.
The gait trajectory planning method according to claim 3, wherein the performing trajectory fitting according to the current gait trajectory and the target gait trajectory comprises:

constructing a fitting trajectory expression with undetermined coefficients corresponding to the fitting gait trajectory;

Determine the boundary constraints of the fitting trajectory expression according to the current gait trajectory and the target gait trajectory;

Selecting several designated time points within a preset trajectory fitting period, and calculating the value of the target gait trajectory at each designated time point;

Constructing an optimization target corresponding to the fitting trajectory expression according to the values of the target gait trajectory at each specified time point;

According to the optimization objective and the boundary constraints, each undetermined coefficient of the fitting trajectory expression is determined to obtain the fitting gait trajectory.
The gait trajectory planning method according to claim 4, wherein the constructing a fitting trajectory expression with undetermined coefficients corresponding to the fitting gait trajectory comprises:

Construct the fitted trajectory expression as follows:

where t is the time variable,
is the fitting trajectory expression, a i is an undetermined coefficient, 0≤i≤5.
The gait trajectory planning method according to claim 4, wherein the determining the boundary constraints of the fitting trajectory expression according to the current gait trajectory and the target gait trajectory comprises:

Determine boundary constraints as follows:

where t is the time variable,
is the fitted trajectory expression,
is the current gait trajectory,
is the target gait trajectory, t 0 is the start time of the fitted gait trajectory, and T is the end moment of the fitted gait trajectory.
The gait trajectory planning method according to claim 4, wherein the constructing an optimization target corresponding to the fitting trajectory expression according to the values of the target gait trajectory at each specified time point comprises:

Build an optimization objective as follows:

where t is the time variable,
is the fitted trajectory expression,
is the target gait trajectory, t m is the mth specified time point, 0≤m≤M, and M is the number of specified time points.
A gait trajectory planning device, comprising:

The gait trajectory library acquisition module is used to acquire the standard gait trajectory library of the robot; the standard gait trajectory library includes several standard gait trajectories, and each standard gait trajectory corresponds to a preset standard travel speed;

The speed determination module is used to determine the current travel speed of the robot;

An interpolation calculation module, configured to perform interpolation calculation in the standard gait trajectory of the standard gait trajectory library according to the current travel speed to obtain a target gait trajectory corresponding to the current travel speed.
A computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, the gait trajectory according to any one of claims 1 to 7 is realized Steps in the planning method.
A robot, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, when the processor executes the computer program, the implementation of claims 1 to 7 The steps of any one of the gait trajectory planning methods.