A Motion Planning Method and System for Vibration Suppression

Abstract

The present application provides a motion planning method and system capable of suppressing vibration. The historical motion data set is decomposed into gradual motion data and abrupt motion data; multiple tracking errors are obtained based on the gradual motion data, a motion smoothing factor is determined through all the tracking errors, and the gradual motion control amount of the target machine is determined by combining the motion smoothing factor with the environmental parameters; the vibration interference characteristics during abrupt motion are extracted according to the time response data to obtain a vibration interference factor, and the abrupt motion control amount is determined by the abrupt motion data and the vibration interference factor; the vibration suppression coefficient at different rotation angles during the motion of the target machine is determined through the gradual motion control amount and the abrupt motion control amount; when the target machine has a rotation angle during the motion, the motion planning path of the target machine is vibration-suppressed by the vibration suppression coefficient. By adopting the solution of the present application, global vibration suppression can be achieved during the motion planning process to reduce the non-smooth motion planning path.

Description

Technical Field

[0001] This application relates to the technical field of motion planning. More specifically, this application relates to a motion planning method and system that can suppress vibrations. Background Art

[0002] Motion planning is an important task in the fields of robotics, automatic control, artificial intelligence, and mechanical engineering. Its goal is to determine how a robot or system generates a suitable trajectory or sequence of actions in a given environment to complete a specific task. Motion planning can involve path planning for mobile robots, motion control for industrial robots, and trajectory planning for unmanned aerial vehicles, etc. Motion planning that can suppress vibrations refers to designing control strategies in a mechanical system to reduce or suppress the vibrations generated when the system executes a motion task.

[0003] During the process of motion planning, there is a problem of path smoothness. Path smoothness refers to the continuity and smoothness of the path generated by motion planning in space. Generally, it is desired that the path generated by motion planning is continuous and smooth to ensure stability and comfort during the motion process. Sudden turns or sharp changes in the path will cause the system to vibrate or oscillate. Especially for high-speed motion or sensitive systems, it will affect the performance and stability of the system. However, in the prior art, some vibration suppression methods for motion planning are only effective within a local range and cannot globally suppress vibrations, resulting in vibrations still existing in some parts. Especially in high-degree-of-freedom mechanical systems, sudden turns or discontinuities caused by non-smooth motion planning paths lead to friction and impact between components, thus resulting in wear and damage of mechanical components in high-degree-of-freedom mechanical systems. Therefore, how to achieve global vibration suppression during the motion planning process to reduce non-smooth motion planning paths has become a difficult problem faced by the industry. Summary of the Invention

[0004] This application provides a motion planning method and system that can suppress vibrations, which can achieve global vibration suppression during the motion planning process to reduce non-smooth motion planning paths.

[0005] In a first aspect, this application provides a motion planning method that can suppress vibrations, including the following steps:

[0006] Obtain the historical motion data set of the target machine;

[0007] Based on the motion characteristics of the target machine during motion, decompose the historical motion data set into gradual motion data and sudden motion data;

[0008] Perform trajectory tracking on the target machine based on the gradual motion data, and then obtain multiple tracking errors. Determine the motion smoothing factor of the target machine through all the tracking errors, and determine the gradual motion control amount of the target machine by combining the motion smoothing factor with the environmental parameters in the current motion process;

[0009] Obtain the time response data of the target machine during sudden motion, and then extract the vibration interference characteristics during sudden motion according to the time response data to obtain the vibration interference factor. Determine the sudden motion control amount of the target machine from the sudden motion data and the vibration interference factor;

[0010] Determine the vibration suppression coefficient of the target machine at different rotation angles during motion through the gradual motion control amount and the sudden motion control amount;

[0011] When the target machine has a rotation angle during motion, suppress the vibration of the motion planning path of the target machine by the vibration suppression coefficient.

[0012] In some embodiments, decomposing the historical motion data set into gradual motion data and sudden motion data based on the motion characteristics of the target machine during motion specifically includes:

[0013] Screen out the relative rotation angles of each motion of the target machine in the historical motion data set, and all the screened relative rotation angles are the motion characteristics of the target machine during motion;

[0014] Set the rotation amplitude threshold of the target machine according to all the relative rotation angles;

[0015] Form the sudden motion data from all the relative rotation angles greater than or equal to the rotation amplitude threshold in the historical motion data set;

[0016] Form the gradual motion data from all the relative rotation angles less than the rotation amplitude threshold in the historical motion data set.

[0017] In some embodiments, determining the motion smoothing factor of the target machine through all the tracking errors specifically includes:

[0018] Determine the corner tracking extreme difference of the target machine from all the tracking errors;

[0019] Determine the trajectory smoothness of the target machine during trajectory tracking;

[0020] Determine the motion smoothing factor of the target machine according to the corner tracking extreme difference and the trajectory smoothness.

[0021] In some embodiments, determining the gradual motion control amount of the target machine by combining the motion smoothing factor with the environmental parameters in the current motion process specifically includes:

[0022] Obtain the environmental parameters during the current movement of the target machine;

[0023] Determine the environmental impact coefficient of the target machine based on the environmental parameters;

[0024] Determine the gradual movement control amount of the target machine according to the environmental impact coefficient and the movement smoothing factor.

[0025] In some embodiments, determining the mutation movement control amount of the target machine from the mutation movement data and the vibration interference factor specifically includes:

[0026] Determine the suppression and interference adjustment value of each relative rotation angle according to each relative rotation angle in the mutation movement data and the vibration interference factor;

[0027] Furthermore, determine the mutation movement control amount of the target machine from all the suppression and interference adjustment values.

[0028] In some embodiments, when the target machine has a rotation angle during movement, vibration suppression of the movement planning path of the target machine by the vibration suppression coefficient specifically includes:

[0029] Obtain the time point when the target machine has a rotation angle during movement;

[0030] Determine the movement planning parameter sequence at the time point through the vibration suppression coefficient;

[0031] Generate a movement control instruction for the target machine from the movement planning parameter sequence;

[0032] The target machine executes movement according to the movement control instruction at the time point, thereby completing the vibration suppression of the movement planning path of the target machine.

[0033] In some embodiments, the historical movement data set is a set of all movement data of the target machine in the past month.

[0034] In a second aspect, the present application provides a movement planning system capable of suppressing vibration, including:

[0035] An acquisition module, configured to acquire the historical movement data set of the target machine;

[0036] A processing module, configured to decompose the historical movement data set into gradual movement data and mutation movement data based on the movement characteristics of the target machine during movement;

[0037] The processing module is further configured to perform trajectory tracking on the target machine based on the gradual motion data, and then obtain multiple tracking errors. The motion smoothing factor of the target machine is determined by all the tracking errors, and the gradual motion control amount of the target machine is determined by combining the motion smoothing factor with the environmental parameters in the current motion process;

[0038] The processing module is further configured to obtain the time response data of the target machine during sudden motion, and then extract the vibration interference characteristics during sudden motion according to the time response data to obtain a vibration interference factor. The sudden motion control amount of the target machine is determined by the sudden motion data and the vibration interference factor;

[0039] The processing module is further configured to determine the vibration suppression coefficient of the target machine at different rotation angles during motion through the gradual motion control amount and the sudden motion control amount;

[0040] The execution module is configured to, when the target machine has a rotation angle during motion, suppress the vibration of the motion planning path of the target machine by the vibration suppression coefficient.

[0041] In a third aspect, the present application provides a computer device, which includes a memory and a processor. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned motion planning method capable of suppressing vibration.

[0042] In a fourth aspect, the present application provides a computer-readable storage medium, in which instructions or codes are stored. When the instructions or codes are run on a computer, the computer is enabled to execute the above-mentioned motion planning method capable of suppressing vibration.

[0043] The technical solutions provided by the disclosed embodiments of the present application have the following beneficial effects:

[0044] In this application, a historical motion data set of the target machine is obtained; based on the motion characteristics of the target machine during motion, the historical motion data set is decomposed into gradual motion data and abrupt motion data; the target machine is subjected to trajectory tracking based on the gradual motion data, and then a plurality of tracking errors are obtained. The motion smoothing factor of the target machine is determined by all the tracking errors, and the gradual motion control amount of the target machine is determined by combining the motion smoothing factor with the environmental parameters during the current motion process; the time response data of the target machine during abrupt motion is obtained, and then the vibration interference characteristics during abrupt motion are extracted according to the time response data to obtain a vibration interference factor. The abrupt motion control amount of the target machine is determined by the abrupt motion data and the vibration interference factor; the vibration suppression coefficient of the target machine at different rotation angles during motion is determined by the gradual motion control amount and the abrupt motion control amount; when the target machine has a rotation angle during motion, the motion planning path of the target machine is vibration-suppressed by the vibration suppression coefficient.

[0045] It can be seen that in this application, the vibration suppression coefficient of the target machine at different rotation angles during movement is determined by the gradual movement control quantity and the sudden movement control quantity. When the target machine has a rotation angle during movement, the vibration suppression coefficient is used to suppress the vibration of the movement planning path of the target machine, thereby completing the vibration suppression of the movement planning path of the target machine. Among them, the gradual movement control quantity is used to control the degree of change required for the movement posture of the target machine when performing a small rotation action. The gradual movement control quantity is determined by the smoothness of the movement trajectory of the target machine during movement (i.e., the movement smoothness factor) and the influence degree of the environmental parameters on the movement state of the target machine, which can provide a basis for suppressing vibration for the small rotation action during the movement process of the target machine, so as to formulate a targeted vibration suppression strategy subsequently. Moreover, the sudden movement control quantity is used to control the degree of change required for the movement posture of the target machine when performing a large rotation action. The sudden movement control quantity is determined by the degree of interference caused by vibration to the movement of the target machine (i.e., the vibration interference factor) and all large rotation actions of the target machine, which can enable the target machine to more effectively suppress vibration when there is vibration interference during the sudden movement process, thereby improving the stability and safety of the machine movement. Finally, the vibration suppression coefficient (i.e., the coefficient for suppressing the vibration interference during the execution of the movement by the target machine) is determined by the gradual movement control quantity and the sudden movement control quantity. Considering the vibration suppression of both large and small rotation actions of the target machine can provide a quantitative reference for vibration suppression under different movement conditions of the machine, reduce the interference of vibration on the machine movement, and thus achieve global vibration suppression. When the target machine has a rotation angle during movement, the movement actuator of the target machine executes corresponding movement actions according to the movement control instruction generated by the vibration suppression coefficient, which can ensure that the target machine remains stable throughout the movement process, thereby achieving smoother and more accurate trajectory tracking. In summary, this solution realizes global vibration suppression during the movement planning process, thereby reducing the non-smooth movement planning path. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0047] Figure 1 is an exemplary flowchart of a motion planning method capable of suppressing vibration according to some embodiments of the present application;

[0048] Figure 2An exemplary flowchart for determining a gradual motion control amount as shown in some embodiments of the present application;

[0049] Figure 3 An exemplary flowchart for determining a vibration interference factor as shown in some embodiments of the present application;

[0050] Figure 4 A schematic diagram of exemplary hardware and / or software of a motion planning system capable of suppressing vibration as shown in some embodiments of the present application;

[0051] Figure 5 A schematic structural diagram of a computer device for implementing a motion planning method capable of suppressing vibration as shown in some embodiments of the present application. Detailed implementation manners

[0052] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present application.

[0053] The embodiments of the present application provide a motion planning method and system capable of suppressing vibration. The core is to obtain a historical motion data set of a target machine; decompose the historical motion data set into gradual motion data and sudden motion data based on the motion characteristics of the target machine during the motion process; perform trajectory tracking on the target machine based on the gradual motion data, and then obtain a plurality of tracking errors. Determine the motion smoothing factor of the target machine through all the tracking errors, and determine the gradual motion control amount of the target machine by combining the motion smoothing factor with the environmental parameters in the current motion process; obtain the time response data of the target machine during sudden motion, and then extract the vibration interference characteristics during sudden motion according to the time response data to obtain a vibration interference factor. Determine the sudden motion control amount of the target machine from the sudden motion data and the vibration interference factor; determine the vibration suppression coefficient at different rotation angles of the target machine during motion through the gradual motion control amount and the sudden motion control amount; when the target machine has a rotation angle during motion, suppress the vibration of the motion planning path of the target machine by the vibration suppression coefficient; global vibration suppression can be achieved during the motion planning process to reduce non-smooth motion planning paths.

[0054] To better understand the above technical solutions, the above technical solutions will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners. Refer to Figure 1, This figure is an exemplary flowchart of a motion planning method for suppressing vibration according to some embodiments of the present application. The motion planning method 100 for suppressing vibration mainly includes the following steps:

[0055] In step 101, obtain the historical motion data set of the target machine.

[0056] Specifically, a database management tool can be used to extract the motion data of the target machine during motion in the past month from the operation record database, and all the extracted motion data is composed of the historical motion data set of the target machine. Among them, the database management tool can be Structured Query Language (SQL). In other embodiments, other methods can also be used to obtain it, which is not specifically limited here.

[0057] It should be noted that the operation record database in the present application records various data generated during motion according to the motion planning path formulated for the target machine in the past period of time, and all the generated data is regarded as motion data; in some embodiments, the motion data includes: the time point of each motion, the relative rotation angle of each motion rotation, the time used for each rotation angle, the energy consumed for each rotation angle, the speed of each motion, the acceleration of each motion, the position point of each motion, the distance of each motion, the wind speed in the surrounding environment during each motion, the temperature in the surrounding environment during each motion, the humidity in the surrounding environment during each motion, etc. Among them, each operation refers to each basic action unit when the target machine executes motion. The action units are, for example: moving to a specific position, rotating a specific angle, grasping an object, etc., which will not be elaborated here.

[0058] In addition, it should be noted that the historical motion data set in the present application represents the set of all motion data of the target machine in the past month.

[0059] In step 102, decompose the historical motion data set into gradual change motion data and mutation motion data based on the motion characteristics of the target machine during motion.

[0060] In some embodiments, decomposing the historical motion data set into gradual change motion data and mutation motion data based on the motion characteristics of the target machine during motion can be implemented by the following steps:

[0061] Screen out the relative rotation angle of each motion of the target machine in the historical motion data set. All the screened relative rotation angles are the motion characteristics of the target machine during motion;

[0062] Set the rotation amplitude threshold of the target machine according to all the relative rotation angles;

[0063] All relative rotation angles in the historical motion dataset that are greater than or equal to the rotation amplitude threshold are composed into mutation motion data;

[0064] All relative rotation angles in the historical motion dataset that are less than the rotation amplitude threshold are composed into gradual change motion data.

[0065] It should be noted that the relative rotation angle in this application represents the angle by which the target machine rotates relative to the end of the previous motion after the current motion ends. As a preferred embodiment, filtering out the relative rotation angle of each motion of the target machine in the historical motion dataset can be achieved in the following manner, that is: the relative rotation angle of each motion of the target machine can be filtered out from the historical motion dataset through structured query language. In other embodiments, other methods can also be used to achieve this, which is not limited here.

[0066] Specifically, when implemented, the rotation amplitude threshold in this application is a boundary value used to distinguish large rotation actions and small rotation actions of the target machine in the historical motion dataset. Setting the rotation amplitude threshold of the target machine according to all relative rotation angles can be achieved in the following manner, that is: the average value of all relative rotation angles can be taken, and then the result of adding the standard deviation of all relative rotation angles to this average value can be used as the rotation amplitude threshold of the target machine. In other embodiments, it can also be set in other ways, which is not limited here.

[0067] It should be noted that the gradual change motion in this application represents the small rotation action of the target machine, and the gradual change motion data represents the set of all small rotation actions of the target machine in the historical motion dataset; in addition, the mutation motion represents the large rotation action of the target machine, and the mutation motion data represents the set of all large rotation actions of the target machine in the historical motion dataset, which will not be elaborated here.

[0068] In step 103, based on the gradual change motion data, trajectory tracking is performed on the target machine, and then multiple tracking errors are obtained. The motion smoothing factor of the target machine is determined through all the tracking errors, and the gradual change motion control amount of the target machine is determined by combining the motion smoothing factor with the environmental parameters in the current motion process.

[0069] In some embodiments, performing trajectory tracking on the target machine based on the gradual change motion data and then obtaining multiple tracking errors can be achieved through the following steps:

[0070] Determine the expected rotation angles corresponding to each relative rotation angle in the gradual change motion data in the motion planning path of the target machine;

[0071] Determine multiple tracking errors of the target machine during the motion trajectory tracking process according to all the expected rotation angles and the gradual change motion data.

[0072] In specific implementation, before the target machine in the present application executes a motion, a corresponding motion planning path will be formulated. The motion planning path consists of various expected rotation angles and other motion postures. The expected rotation angle in the motion planning path represents the preset rotation angle of the target machine during the process from the previous motion to the next motion in the formulated motion planning path. The following method can be used to determine the expected rotation angles corresponding to the respective relative rotation angles in the gradient motion data in the motion planning path of the target machine, that is: taking the preset rotation angles at the same time point of the respective relative rotation angles in the gradient motion data in the motion planning path formulated by the target machine as the expected rotation angles corresponding to the respective relative rotation angles in the motion planning path of the target machine. In other embodiments, other methods can also be used to determine, which will not be specifically limited here; the following method can be used to determine multiple tracking errors of the target machine during the motion trajectory tracking according to all the expected rotation angles and the gradient motion data, that is: selecting a relative rotation angle in the gradient motion data, obtaining the expected rotation angle corresponding to this relative rotation angle in the motion planning path of the target machine, and then taking the difference between this relative rotation angle and the expected rotation angle as the tracking error of the target machine corresponding to this relative rotation angle. Repeat the above steps to obtain the tracking errors corresponding to the remaining relative rotation angles in the gradient motion data of the target machine. In other embodiments, it can also be determined by other methods, which will not be limited here.

[0073] It should be noted that the tracking error in the present application reflects the deviation degree between the actual rotation angle and the expected rotation angle of the target machine during motion execution. The larger the tracking error, the greater the deviation degree between the actual rotation angle and the expected rotation angle of the target machine during motion execution. On the contrary, the smaller the tracking error, the smaller the deviation degree between the actual rotation angle and the expected rotation angle of the target machine during motion execution.

[0074] In some embodiments, the following steps can be used to determine the motion smoothing factor of the target machine based on all the tracking errors:

[0075] Determine the corner tracking extreme difference value of the target machine from all the tracking errors;

[0076] Determine the trajectory smoothness of the target machine during the motion trajectory tracking;

[0077] Determine the motion smoothing factor of the target machine according to the corner tracking extreme difference value and the trajectory smoothness.

[0078] In specific implementation, the corner tracking extreme difference in this application reflects the deviation degree between the maximum tracking error and the minimum tracking error of the target machine. The corner tracking extreme difference of the target machine determined by all tracking errors can be implemented in the following manner, that is: taking the absolute value of the difference between the maximum tracking error and the minimum tracking error among all tracking errors as the corner tracking extreme difference. In other embodiments, other methods can also be used to determine it, which is not limited here; the trajectory smoothness reflects the change degree of the trajectory curve during the motion trajectory tracking of the target machine. The higher the trajectory smoothness, the more gentle the change of the trajectory curve during the motion trajectory tracking of the target machine. On the contrary, the lower the trajectory smoothness, the more drastic the change of the trajectory curve during the motion trajectory tracking of the target machine. The trajectory smoothness of the target machine during the motion trajectory tracking can be implemented in the following manner, that is: first calculating the curvature of each point on the trajectory curve during the motion trajectory tracking of the target machine by numerical methods or differential geometry methods, and then comprehensively evaluating all the obtained curvatures, and further taking the result obtained from the comprehensive evaluation as the trajectory smoothness of the target machine during the motion trajectory tracking. Among them, the comprehensive evaluation may include: integrating or averaging all the curvatures. In other embodiments, it can also be determined by other methods, which is not limited here; the motion smooth factor of the target machine can be determined according to the corner tracking extreme difference and the trajectory smoothness in the following manner, that is: taking the ratio of the corner tracking extreme difference to the trajectory smoothness as the motion smooth factor of the target machine. In other embodiments, it can also be determined by other methods, which is not limited here.

[0079] It should be noted that the motion smooth factor in this application is used to control the smoothness of the motion trajectory of the target machine during the motion process. The greater the smoothness of the motion trajectory, the smaller the motion error of the target machine during the motion process. On the contrary, the greater the motion error of the target machine during the motion process. This will not be elaborated here.

[0080] In some embodiments, referring to Figure 2 As shown, this figure is an exemplary flowchart for determining the gradual motion control amount in some embodiments of this application. In this embodiment, the gradual motion control amount of the target machine determined by combining the motion smooth factor with the environmental parameters during the current motion process can be implemented by the following steps:

[0081] First, in step 1031, obtain the environmental parameters during the current motion process of the target machine;

[0082] Secondly, in step 1032, determine the environmental influence coefficient of the target machine through the environmental parameters;

[0083] Finally, in step 1033, determine the gradual motion control amount of the target machine according to the environmental impact coefficient and the motion smoothing factor.

[0084] It should be noted that the environmental parameters in this application include, but are not limited to: the distance and position of surrounding obstacles, the slope and curvature of the terrain, wind speed and wind direction, etc. In some embodiments, the environmental data during the current movement of the target machine can be obtained through various sensors and environmental perception devices, and all the obtained environmental data are combined into the environmental parameters during the current movement of the target machine. Among them, the various sensors and environmental perception devices are, for example: distance sensors, lidar, tilt sensors, wind speed sensors, anemometers, and wind direction meters, etc. In other embodiments, the environmental parameters can also be obtained through other methods, which will not be specifically limited here.

[0085] Specifically, the environmental impact coefficient in this application reflects the degree of influence of environmental parameters on the motion state of the target machine. The larger the environmental impact coefficient, the greater the degree of influence of environmental parameters on the motion state of the target machine. Conversely, the smaller the environmental impact coefficient, the smaller the degree of influence of environmental parameters on the motion state of the target machine. The environmental impact coefficient of the target machine can be determined through the environmental parameters in the following way, that is: first, the degree of influence of each environmental data in the environmental parameters on the motion state of the target machine can be evaluated through machine learning or evaluation algorithms, and then the obtained evaluation values are averaged and weighted and summed, and then the obtained result is used as the environmental impact coefficient of the target machine. In other embodiments, it can also be realized through other methods, which will not be elaborated here; the gradual motion control amount of the target machine can be determined according to the environmental impact coefficient and the motion smoothing factor in the following way, that is: the product value of the environmental impact coefficient and the motion smoothing factor can be used as the gradual motion control amount of the target machine. In other embodiments, it can also be determined through other methods, which will not be limited here.

[0086] It should be noted that the gradual motion control amount in this application is used to control the degree of change required for the motion posture of the target machine during a small rotation action. Among them, the motion postures are, for example: the rotation angle, angular velocity, angular acceleration, force, and torque of the target machine, etc., which will not be elaborated here.

[0087] In step 104, obtain the time response data of the target machine during the sudden motion, and then extract the vibration interference characteristics during the sudden motion according to the time response data to obtain the vibration interference factor. Determine the sudden motion control amount of the target machine from the sudden motion data and the vibration interference factor.

[0088] When specifically implemented, the time response data of the target machine during mutation motion can be obtained in the following manner, that is: the time taken for each relative rotation angle in the mutation motion data can be extracted from the historical motion data set of the target machine through Structured Query Language, and the time taken for each relative rotation angle is used as the response time corresponding to each relative rotation angle. Furthermore, all the extracted response times are combined to form the time response data of the target machine during mutation motion. In other embodiments, it can also be obtained by other methods, which are not limited here.

[0089] It should be noted that the time response data in this application represents the set of response times corresponding to all mutation motions during the motion of the target machine. Among them, one mutation motion corresponds to one response time, which will not be elaborated here.

[0090] In some embodiments, as shown in Figure 3 This figure is an exemplary flowchart for determining the vibration interference factor in some embodiments of this application. In this embodiment, the vibration interference characteristics during mutation motion are extracted based on the time response data, and the vibration interference factor can be obtained through the following steps:

[0091] First, in step 1041, a response time in the time response data is selected;

[0092] Secondly, in step 1042, the vibration interference amount in the mutation motion corresponding to this response time is determined from this response time and the relative rotation angle corresponding to this response time;

[0093] Then, in step 1043, the rotation angle stability corresponding to this response time is determined according to the vibration interference amount;

[0094] Again, in step 1044, the above steps are repeated to obtain the rotation angle stabilities corresponding to the remaining response times in the time response data;

[0095] Finally, in step 1045, the vibration interference factor of the target machine during the mutation motion process is further determined through all the rotation angle stabilities.

[0096] It should be noted that since vibration will cause additional fluctuations or jitters when the target machine rotates, and the fluctuations or jitters caused by vibration will make the changes in acceleration and angular velocity during the rotation process more complex, thereby prolonging the time required for the rotation angle to reach the target value, that is, increasing the response time of the relative rotation angle. Therefore, the longer the response time of the relative rotation angle, the greater the vibration interference received during the corresponding response time, and the lower the stability of the relative rotation angle corresponding to the response time, which will not be elaborated here.

[0097] In specific implementation, the vibration interference amount in the present application represents the degree of vibration interference received during the corresponding response time in the sudden motion. To determine the vibration interference amount in the sudden motion corresponding to a certain response time from the corresponding response time and the relative rotation angle corresponding to this response time, the following method can be adopted, that is: the ratio of the relative rotation angle corresponding to this response time to this response time can be used as the vibration interference amount in the sudden motion corresponding to this response time. In other embodiments, it can also be determined by other methods, which is not limited herein; the rotation angle stability reflects the resistance ability of the corresponding relative rotation angle to external interference (i.e., vibration interference). The higher the rotation angle stability, the stronger the resistance ability of the corresponding relative rotation angle to external interference (i.e., vibration interference). On the contrary, the lower the rotation angle stability, the weaker the resistance ability of the corresponding relative rotation angle to external interference (i.e., vibration interference). To determine the rotation angle stability corresponding to this response time according to the vibration interference amount, the following method can be adopted, that is: first, the energy consumed by the relative rotation angle corresponding to this response time can be obtained from the historical motion dataset of the target machine through Structured Query Language, then the energy consumed by this relative rotation angle is multiplied by the vibration interference amount, and then the reciprocal of the obtained product value is used as the rotation angle stability corresponding to this response time. In other embodiments, it can also be determined by other methods, which is not limited herein; to determine the vibration interference factor of the target machine during the sudden motion from all the rotation angle stabilities, the following method can be adopted, that is: the reciprocal of the average value of all rotation angle stabilities is used as the vibration interference factor of the target machine during the sudden motion. In other embodiments, it can also be determined by other means, which is not limited herein.

[0098] It should be noted that the vibration interference factor in the present application reflects the degree of interference caused by vibration to the motion of the target machine. The larger the vibration interference factor, the greater the degree of interference caused by vibration to the motion of the target machine. On the contrary, the smaller the vibration interference factor, the smaller the degree of interference caused by vibration to the motion of the target machine.

[0099] In some embodiments, to determine the sudden motion control amount of the target machine from the sudden motion data and the vibration interference factor, the following steps can be adopted:

[0100] Determine the anti-interference adjustment value of each relative rotation angle according to each relative rotation angle in the sudden motion data and the vibration interference factor;

[0101] Furthermore, determine the sudden motion control amount of the target machine from all the anti-interference adjustment values.

[0102] In specific implementation, the anti-interference adjustment value in the present application represents the degree of adjustment required for the corresponding relative rotation angle to counteract vibration interference. The larger the anti-interference adjustment value, the greater the adjustment required for the target machine to suppress vibration interference at the corresponding relative rotation angle, and vice versa. Determining the anti-interference adjustment value for each relative rotation angle according to each relative rotation angle and the vibration interference factor in the mutation motion data can be implemented in the following manner, that is: select a relative rotation angle in the mutation motion data, and use the product value of this relative rotation angle and the vibration interference factor as the anti-interference adjustment value for this relative rotation angle. Repeat the above steps to obtain the anti-interference adjustment values for the remaining relative rotation angles in the mutation motion data. In other embodiments, it can also be determined by other methods, which are not limited herein; determining the mutation motion control amount of the target machine from all the anti-interference adjustment values can be implemented in the following manner, that is: first calculate the difference between all the anti-interference adjustment values and each relative rotation angle in the mutation motion data, and then use the average value of all the obtained differences as the mutation motion control amount of the target machine. In other embodiments, it can also be determined by other methods, which are not limited herein.

[0103] It should be noted that the mutation motion control amount in the present application is used to control the degree of change required for the motion posture of the target machine when performing large-scale rotation actions. Among them, the motion postures include, for example: the rotation angle, angular velocity, angular acceleration, force, torque, etc. of the target machine, which will not be elaborated herein.

[0104] In step 105, determine the vibration suppression coefficient of the target machine at different rotation angles during motion based on the gradual motion control amount and the mutation motion control amount.

[0105] In some embodiments, determining the vibration suppression coefficient of the target machine at different rotation angles during motion based on the gradual motion control amount and the mutation motion control amount can be implemented in the following steps:

[0106] Determine the motion posture control sequence of the target machine according to the gradual motion control amount and the mutation motion control amount;

[0107] Determine the vibration suppression coefficient of the target machine at different rotation angles during motion from the motion posture control sequence.

[0108] It should be noted that the motion attitude control sequence in this application consists of multiple motion attitude control parameters of the target machine. Among them, the motion attitude control parameters may include: rotation angle control coefficient, angular velocity control coefficient, angular acceleration control coefficient, force control coefficient, torque control coefficient, etc. As a preferred embodiment, determining the motion attitude control sequence of the target machine according to the gradual motion control amount and the sudden motion control amount can be implemented in the following manner, that is: a fitting model can be used to fit the relationships between the rotation angle, angular velocity, angular acceleration, force, torque, etc. between the actual motion attitude and the expected motion attitude of the target machine based on the gradual motion control amount and the sudden motion control amount, and then an optimization algorithm is used to find the optimal multiple motion attitude control parameters such as the rotation angle control coefficient, angular velocity control coefficient, angular acceleration control coefficient, force control coefficient, and torque control coefficient. Furthermore, all the motion attitude control parameters are combined to form the motion attitude control sequence of the target machine. Among them, the fitting model is, for example: logistic regression model, decision tree, artificial neural network, deep learning model, etc., and the optimization algorithm is, for example: particle swarm optimization algorithm, stochastic gradient descent method, ant colony algorithm, etc. In other embodiments, other methods can also be used for determination, which is not limited here.

[0109] In specific implementation, determining the vibration suppression coefficient of the target machine at different rotation angles during motion from the motion attitude control sequence can be implemented in the following manner, that is: a machine learning method can be used to automatically adjust the motion control parameters of the target machine at different rotation angles during motion based on expert knowledge and empirical rules, and the adjusted result is used as the vibration suppression coefficient of the target machine at different rotation angles during motion. In other embodiments, other methods can also be used for implementation, which is not limited here.

[0110] It should be noted that the vibration suppression coefficient in this application is a coefficient used to suppress the vibration interference of the target machine during motion execution.

[0111] In step 106, when the target machine has a rotation angle during motion, the vibration suppression coefficient is used to suppress the vibration of the motion planning path of the target machine.

[0112] In some embodiments, when the target machine has a rotation angle during motion, suppressing the vibration of the motion planning path of the target machine by the vibration suppression coefficient can be implemented in the following steps:

[0113] Obtain the time point when the target machine has a rotation angle during motion;

[0114] Determine the motion planning parameter sequence at the time point through the vibration suppression coefficient;

[0115] Generate a motion control instruction for the target machine from the motion planning parameter sequence;

[0116] The target machine performs motion according to the motion control instruction at the time point, so as to complete the vibration suppression of the motion planning path of the target machine.

[0117] It should be noted that the motion planning parameter sequence in this application represents a sequence composed of motion attitude parameters such as the rotation angle, angular velocity, angular acceleration, force, and torque of the target machine after vibration suppression. As a preferred embodiment, the motion planning parameter sequence at the time point can be determined by the following method through the vibration suppression coefficient, that is: First, the rotation angle, angular velocity, angular acceleration, force, torque and other motion postures of the target machine at the time point can be matched from the motion planning path of the target machine through a matching algorithm, and then all the motion postures obtained by matching are arranged to form the motion posture sequence at the time point. Then, each motion posture in the motion posture sequence is multiplied by the vibration suppression coefficient respectively, and the obtained new sequence is used as the motion planning parameter sequence at the time point. Among them, the matching algorithm is, for example: the nearest neighbor matching algorithm, the least square matching algorithm, the neural network matching algorithm, etc. In other embodiments, other methods can also be used for determination, which is not limited here.

[0118] When specifically implemented, the motion control instruction of the target machine can be generated from the motion planning parameter sequence by the following method, that is: the motion planning parameters can be converted into the motion control instructions of each joint of the target machine through the inverse kinematics method. In other embodiments, it can also be determined by other methods, which is not specifically limited here.

[0119] When specifically implemented, the target machine performs motion according to the motion control instruction at the time point, so as to complete the vibration suppression of the motion planning path of the target machine can be implemented by the following method, that is: when the target machine has a corner during motion, the motion actuator of the target machine performs corresponding motion actions according to the motion control instruction to complete the vibration suppression of the motion planning path of the target machine, which will not be elaborated here.

[0120] In addition, on the other hand of this application, in some embodiments, this application provides a motion planning system capable of suppressing vibration. Refer to Figure 4 , this figure is a schematic diagram of exemplary hardware and / or software of a motion planning system capable of suppressing vibration according to some embodiments of this application. The motion planning system 400 capable of suppressing vibration includes: an acquisition module 401, a processing module 402, and an execution module 403, which are described as follows:

[0121] The acquisition module 401 is mainly used to acquire the historical motion data set of the target machine in this application;

[0122] The processing module 402. In this application, the processing module 402 is mainly used to decompose the historical motion data set into gradual motion data and sudden motion data based on the motion characteristics of the target machine during motion;

[0123] In this application, the processing module 402 is further used to perform trajectory tracking on the target machine based on the gradual motion data, and then obtain multiple tracking errors. The motion smoothing factor of the target machine is determined by all the tracking errors, and the gradual motion control amount of the target machine is determined by combining the motion smoothing factor with the environmental parameters during the current motion process;

[0124] In this application, the processing module 402 is further used to obtain the time response data of the target machine during sudden motion, and then extract the vibration interference characteristics during sudden motion according to the time response data to obtain a vibration interference factor. The sudden motion control amount of the target machine is determined by the sudden motion data and the vibration interference factor;

[0125] In this application, the processing module 402 is further used to determine the vibration suppression coefficient of the target machine at different rotation angles during motion through the gradual motion control amount and the sudden motion control amount;

[0126] The execution module 403. In this application, the execution module 403 is mainly used to suppress the vibration of the motion planning path of the target machine by the vibration suppression coefficient when the target machine has a rotation angle during motion.

[0127] The above has introduced in detail the examples of the motion planning method and system for vibration suppression provided by the embodiments of this application. It can be understood that, in order to implement the above functions, the corresponding device includes the corresponding hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, combining the units and algorithm steps of each example described in the embodiments disclosed in this article, this application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0128] In some embodiments, this application further provides a computer device, which includes a memory and a processor. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned motion planning method for vibration suppression.

[0129] In some embodiments, refer to Figure 5, the dashed lines in the figure indicate that the unit or module is optional. This figure is a schematic structural diagram of a computer device for implementing the vibration-suppressible motion planning method of the present application. The vibration-suppressible motion planning method in the above embodiments can be implemented by Figure 5 the computer device shown. The computer device 500 includes at least one processor 501, a memory 502, and at least one communication unit 505. The computer device 500 can be a terminal device, a server, or a chip.

[0130] The processor 501 can be a general-purpose processor or a special-purpose processor. For example, the processor 501 can be a central processing unit (CPU). The CPU can be used to control the computer device 500, execute software programs, and process the data of software programs. The computer device 500 can also include a communication unit 505 for implementing signal input (reception) and output (transmission).

[0131] For example, the computer device 500 can be a chip, and the communication unit 505 can be the input and / or output circuit of the chip, or the communication unit 505 can be the communication interface of the chip. The chip can be a component of a terminal device, a network device, or other devices.

[0132] Again, for example, the computer device 500 can be a terminal device or a server, and the communication unit 505 can be the transceiver of the terminal device or the server, or the communication unit 505 can be the transceiver circuit of the terminal device or the server.

[0133] The computer device 500 can include one or more memories 502 on which a program 504 is stored. The program 504 can be run by the processor 501 to generate instructions 503, enabling the processor 501 to execute the method described in the above method embodiments according to the instructions 503. Optionally, data (such as a target review model) can also be stored in the memory 502. Optionally, the processor 501 can also read the data stored in the memory 502. This data can be stored at the same storage address as the program 504, or it can be stored at a different storage address from the program 504.

[0134] The processor 501 and the memory 502 can be set separately or integrated together. For example, they can be integrated on a system on chip (SOC) of a terminal device.

[0135] It should be understood that the steps of the above method embodiments can be completed by logical circuits in the form of hardware or instructions in the form of software in the processor 501. The processor 501 can be a CPU, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, for example, discrete gates, transistor logic devices, or discrete hardware components.

[0136] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0137] For example, in some embodiments, the present application also provides a computer-readable storage medium, in which instructions or code are stored. When the instructions or code run on a computer, the computer is caused to execute the above-mentioned motion planning method capable of suppressing vibration.

[0138] In summary, in the motion planning method and system for suppressing vibration disclosed in the embodiments of the present application, a historical motion data set of a target machine is obtained; the historical motion data set is decomposed into gradual motion data and mutation motion data based on the motion characteristics of the target machine during the motion; the target machine is subjected to trajectory tracking based on the gradual motion data, and then a plurality of tracking errors are obtained. The motion smoothing factor of the target machine is determined through all the tracking errors. The gradual motion control amount of the target machine is determined by combining the motion smoothing factor with the environmental parameters in the current motion process; the time response data of the target machine during the mutation motion is obtained, and then the vibration interference characteristics during the mutation motion are extracted according to the time response data to obtain a vibration interference factor. The mutation motion control amount of the target machine is determined by the mutation motion data and the vibration interference factor; the vibration suppression coefficient of the target machine at different rotation angles during the motion is determined by the gradual motion control amount and the mutation motion control amount; when the target machine has a rotation angle during the motion, the motion planning path of the target machine is vibration-suppressed by the vibration suppression coefficient; global vibration suppression can be achieved during the motion planning process to reduce the non-smooth motion planning path.

[0139] Although the preferred embodiments of the present application have been described, additional changes and modifications can be made by those skilled in the art once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications that fall within the scope of the present application.

[0140] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present invention.

[0141] In this way, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these changes and modifications.

Claims

1. A motion planning method capable of suppressing vibrations, characterized in that, It includes the following steps: Obtain the historical motion data set of the target machine; Decompose the historical motion data set into gradual motion data and sudden motion data based on the motion characteristics of the target machine during motion; Perform trajectory tracking on the target machine based on the gradual motion data, and then obtain multiple tracking errors. Determine the motion smoothness factor of the target machine through all the tracking errors. Determine the gradual motion control amount of the target machine by combining the motion smoothness factor with the environmental parameters during the current motion process; Obtain the time response data of the target machine during sudden motion, and then extract the vibration interference characteristics during sudden motion according to the time response data to obtain the vibration interference factor. Determine the sudden motion control amount of the target machine by the sudden motion data and the vibration interference factor; Determine the vibration suppression coefficient of the target machine at different rotation angles during motion through the gradual motion control amount and the sudden motion control amount, where the vibration suppression coefficient is a coefficient for suppressing the vibration interference during the motion of the target machine; When the target machine has a rotation angle during motion, suppress the vibration of the motion planning path of the target machine by the vibration suppression coefficient; 2. The method according to claim 1, characterized in that, Specifically, decomposing the historical motion data set into gradual motion data and sudden motion data based on the motion characteristics of the target machine during motion includes: Screen out the relative rotation angles of each motion of the target machine in the historical motion data set, and all the screened relative rotation angles are the motion characteristics of the target machine during motion; Set the rotation amplitude threshold of the target machine according to all the relative rotation angles; Form the sudden motion data by all the relative rotation angles in the historical motion data set that are greater than or equal to the rotation amplitude threshold; Form the gradual motion data by all the relative rotation angles in the historical motion data set that are less than the rotation amplitude threshold; 3. The method according to claim 1, characterized in that, Specifically, determining the motion smoothness factor of the target machine through all the tracking errors includes: Determine the corner tracking extreme difference value of the target machine from all the tracking errors; Determine the trajectory smoothness during the trajectory tracking process of the target machine; Determine the motion smoothness factor of the target machine according to the corner tracking extreme difference value and the trajectory smoothness; 4. The method according to claim 1, characterized in that, Specifically, determining the gradual motion control amount of the target machine by combining the motion smoothness factor with the environmental parameters during the current motion process includes: Obtain the environmental parameters during the current motion process of the target machine; Determine the environmental influence coefficient of the target machine through the environmental parameters; Determine the gradual motion control amount of the target machine according to the environmental influence coefficient and the motion smoothness factor; 5. The method according to claim 1, wherein Specifically, determining the sudden motion control amount of the target machine by the sudden motion data and the vibration interference factor includes: Determine the interference suppression adjustment value of each relative rotation angle according to each relative rotation angle in the sudden motion data and the vibration interference factor; Then determine the sudden motion control amount of the target machine from all the interference suppression adjustment values; 6. The method according to claim 1, characterized in that, Specifically, when the target machine has a rotation angle during motion, suppressing the vibration of the motion planning path of the target machine by the vibration suppression coefficient includes: Obtain the time point when the target machine has a rotation angle during motion; Determine the motion planning parameter sequence at the time point through the vibration suppression coefficient; Generate motion control instructions for the target machine from the sequence of motion planning parameters; At the time point, the target machine executes motion according to the motion control instructions, thereby completing the vibration suppression of the motion planning path of the target machine.

7. The method according to claim 1, wherein The historical motion data set is a set of all motion data of the target machine in the past month.

8. A motion planning system capable of suppressing vibration, characterized in that, Including: An acquisition module for acquiring the historical motion data set of the target machine; A processing module for decomposing the historical motion data set into gradual motion data and abrupt motion data based on the motion characteristics of the target machine during motion; The processing module is further configured to perform trajectory tracking on the target machine based on the gradual motion data, and then obtain a plurality of tracking errors. Determine the motion smoothing factor of the target machine through all the tracking errors, and determine the gradual motion control amount of the target machine by combining the motion smoothing factor with the environmental parameters in the current motion process; The processing module is further configured to obtain the time response data of the target machine during abrupt motion, and then extract the vibration interference characteristics during abrupt motion according to the time response data to obtain a vibration interference factor, and determine the abrupt motion control amount of the target machine from the abrupt motion data and the vibration interference factor; The processing module is further configured to determine the vibration suppression coefficient of the target machine at different rotation angles during motion through the gradual motion control amount and the abrupt motion control amount, where the vibration suppression coefficient is a coefficient for suppressing the vibration interference during the motion of the target machine; An execution module for suppressing the vibration of the motion planning path of the target machine by the vibration suppression coefficient when the target machine has a rotation angle during motion.

9. A computer device, characterized in that, The computer device includes a memory and a processor. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the vibration-suppressible motion planning method according to any one of claims 1 to 7.

10. A computer-readable storage medium, in which instructions or codes are stored. When the instructions or codes are run on a computer, the computer is caused to execute the vibration-suppressible motion planning method according to any one of claims 1 to 7.

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