Robot speed planning method and device and robot

Abstract

The invention discloses a speed planning method and device of a robot and the robot. The method comprises the following steps: acquiring kinematics constraint information and intrinsic mode frequency of a robot; determining a first time constant of the first filter bank according to the kinematics constraint information, and determining a second time constant of the second filter bank according to the intrinsic mode frequency; inputting the planned path length of the to-be-planned path into a first filter bank, and processing the planned path length by using the first filter bank according to a first time constant to obtain a first processing result; and inputting the first processing result into a second filter bank, and processing the first processing result by using the second filter bank according to a second time constant to obtain speed planning information of the robot. According to the invention, the technical problem that the working precision and stability of the robot are affected due to unnecessary vibration caused by resonance of the structural part of the robot during speed planning of the robot in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of robot control, in particular to a robot speed planning method and device and a robot. BACKGROUND

[0002] In the automation manufacturing and logistics industry, the application of robot technology is increasingly widespread, and the motion control performance of the robot directly affects the production efficiency and product quality. Especially in precise operation tasks such as electronic assembly, medical surgery assistance, etc., the control accuracy of the robot is extremely high, and any slight vibration or deviation may cause irreversible effects. Therefore, the development of high-performance motion control strategies is the key to the development of robot technology.

[0003] Acceleration and deceleration control is a core component of the robot motion control system, which determines the smoothness and safety of the robot during startup, stop and movement when performing tasks. Currently, commonly used speed planning algorithms mainly include linear speed planning, trapezoidal speed planning and S-type speed planning. These methods have their own advantages, but also have some limitations:

[0004] 1) Linear speed planning: Although simple to implement, it will have sharp inflection points when the speed changes, resulting in excessive impact forces during movement, which is not suitable for applications in scenarios requiring precise control.

[0005] 2) Trapezoidal speed planning: Smooths the speed change by controlling the slope of the speed rise and fall, but still has a sudden change in jerk, which may cause vibration of the robot, especially at high speeds.

[0006] 3) S-type speed planning: By introducing more transition segments, it realizes continuous change of jerk, which can theoretically reduce vibration. However, this method usually relies on complex mathematical models and calculations, making it difficult to adjust in real time to adapt to changing working environments, and for some robots sensitive to inherent frequencies, it may still cause resonance.

[0007] In robot motion control, frequency constraints are an important consideration. This is because all physical systems, including robots, have their inherent dynamic characteristics, which manifest as inherent frequencies within a certain range. If the speed planning contains components similar to the inherent modal frequency of the robot, it may cause resonance of the structural parts of the robot, thereby producing unnecessary vibration, affecting the accuracy and stability of the robot's work. However, most speed planning algorithms on the market do not fully consider this limitation, especially those based on trigonometric functions, although they perform well in the time domain, their control ability in the frequency domain is insufficient, and problems may arise under high-speed heavy-load working modes.

[0008] At present, no effective solution has been proposed for the above problems. SUMMARY

[0009] The embodiments of the present application provide a robot speed planning method and device and robot, so as to at least solve the technical problem that resonance of structural parts of the robot may occur when the robot is speed planned in the related art, and thus unnecessary vibration is generated, affecting the precision and stability of the robot work.

[0010] According to an aspect of the embodiments of the present application, a robot speed planning method is provided, comprising: obtaining kinematic constraint information of a to-be-planned path of a robot and an inherent modal frequency of the robot; determining a first time constant of a first filter set according to the kinematic constraint information, and determining a second time constant of a second filter set according to the inherent modal frequency, wherein the first filter set comprises a plurality of kinematic constraint sliding filters, and the second filter set comprises a plurality of frequency constraint filters; inputting a planning path length of the to-be-planned path into the first filter set, processing the planning path length according to the first time constant by using the first filter set, and obtaining a first processing result; inputting the first processing result into the second filter set, processing the first processing result according to the second time constant by using the second filter set, and obtaining speed planning information of the robot.

[0011] Optionally, the second filter set is connected in series behind the first filter set, the plurality of kinematic constraint sliding filters are connected in series in turn, and the plurality of frequency constraint filters are connected in series in turn.

[0012] Optionally, determining the first time constant of the first filter set according to the kinematic constraint information comprises: determining a third time constant of each kinematic constraint sliding filter in the first filter set according to the kinematic constraint information and a time optimization condition; and adjusting the time constant of each kinematic constraint sliding filter according to the third time constant, to obtain the first time constant.

[0013] Optionally, after determining the first time constants of the first filter set according to the kinematic constraint information and determining the second time constants of the second filter set according to the natural modal frequencies, the robot velocity planning method further comprises: judging whether each of the first time constants and each of the second time constants satisfies a time optimal condition in a backward-to-forward order according to a serial order of the first filter set and the second filter set, to obtain a judgment result; when the judgment result indicates that each of the first time constants and each of the second time constants satisfies the time optimal condition, performing the robot velocity planning operation; and when the judgment result indicates that each of the first time constants and each of the second time constants does not satisfy the time optimal condition, adjusting the first time constants and the second time constants until the first time constants and the second time constants satisfy the time optimal condition.

[0014] Optionally, when the judgment result indicates that each of the first time constants and each of the second time constants does not satisfy the time optimal condition, adjusting the first time constants and the second time constants comprises: reducing the kinematic constraint information by a predetermined coefficient to increase the first time constants and the second time constants to satisfy the time optimal condition, wherein the kinematic constraint and the reduced kinematic constraint satisfy the kinematic constraint, the reduced kinematic constraint, and a is the predetermined coefficient, i represents an i th time constant, and the first time constants and the second time constants before adjustment and the first time constants and the second time constants after adjustment satisfy and T i the i th time constant before modification, the i th time constant after modification.

[0015] Optionally, the predetermined coefficient is calculated by a formula n represents a number of time constants.

[0016] Optionally, determining the second time constants of the second filter set according to the natural modal frequencies comprises: calculating the second time constants of the second filter set according to the natural modal frequencies by a formula wherein T i represents an i th second time constant, represents the natural modal.

[0017] According to another aspect of the embodiments of the present application, a speed planning device of a robot is provided, comprising: a first obtaining unit configured to obtain kinematic constraint information of a path to be planned of the robot and a natural modal frequency of the robot; a determining unit configured to determine a first time constant of a first filter bank according to the kinematic constraint information and a second time constant of a second filter bank according to the natural modal frequency, wherein the first filter bank comprises a plurality of kinematic constraint sliding filters and the second filter bank comprises a plurality of frequency constraint filters; a first processing unit configured to input a planning path length of the path to be planned into the first filter bank, process the planning path length according to the first time constant by using the first filter bank, and obtain a first processing result; and a second processing unit configured to input the first processing result into the second filter bank, process the first processing result according to the second time constant by using the second filter bank, and obtain speed planning information of the robot.

[0018] Optionally, the second filter bank is connected in series behind the first filter bank, the plurality of kinematic constraint sliding filters are connected in series in sequence, and the plurality of frequency constraint filters are connected in series in sequence.

[0019] Optionally, the determining unit comprises: a first determining module configured to determine a third time constant of each of the kinematic constraint sliding filters in the first filter bank according to the kinematic constraint information and a time optimal condition; and an adjusting module configured to adjust the time constant of each of the kinematic constraint sliding filters according to the third time constant to obtain the first time constant.

[0020] Optionally, the speed planning device of the robot further comprises: a second obtaining unit configured to, after determining the first time constant of the first filter bank according to the kinematic constraint information and determining the second time constant of the second filter bank according to the natural modal frequency, judge whether each of the first time constants and each of the second time constants satisfies a time optimal condition in sequence from back to front according to a series connection order of the first filter bank and the second filter bank, and obtain a judgment result; a third processing unit configured to, when the judgment result indicates that each of the first time constants and each of the second time constants satisfies the time optimal condition, perform a speed planning operation of the robot; and an adjusting unit configured to, when the judgment result indicates that each of the first time constants and each of the second time constants does not satisfy the time optimal condition, adjust the first time constant and the second time constant until the first time constant and the second time constant satisfy the time optimal condition.

[0021] Optionally, the adjusting unit comprises an increasing module configured to reduce the kinematic constraint information by a predetermined coefficient to increase the first time constant and the second time constant to satisfy the time optimal condition, wherein the kinematic constraint and the reduced kinematic constraint satisfy represents the kinematic constraint, represents the reduced kinematic constraint, a is the predetermined coefficient, i represents the ith time constant, and the first time constant and the second time constant before adjustment and the first time constant and the second time constant after adjustment satisfy and T i represents the ith time constant before modification, represents the ith time constant after modification.

[0022] Optionally, the predetermined coefficient is calculated by a formula , wherein n represents the number of time constants.

[0023] Optionally, the determining unit comprises a calculating module configured to calculate the second time constant of the second filter set according to the inherent mode by a formula , wherein T i represents the ith second time constant, represents the inherent mode.

[0024] According to another aspect of the embodiments of the present application, there is also provided a robot, which uses the speed planning method of the robot according to any one of the above.

[0025] According to another aspect of the embodiments of the present application, there is also provided a computer readable storage medium comprising a stored program, wherein the program performs the speed planning method of the robot according to any one of the above.

[0026] According to another aspect of the embodiments of the present application, there is also provided a processor configured to run a program, wherein the program performs the speed planning method of the robot according to any one of the above.

[0027] According to another aspect of the embodiments of the present application, there is also provided a computer program product comprising computer instructions configured to perform the speed planning method of the robot according to any one of the above when executed by a processor.

[0028] In this embodiment of the invention, kinematic constraint information of the robot's planned path and the robot's natural modal frequencies are obtained; a first time constant of a first filter group is determined based on the kinematic constraint information, and a second time constant of a second filter group is determined based on the natural modal frequencies. The first filter group includes multiple kinematic constraint sliding filters, and the second filter group includes multiple frequency constraint filters. The planned path length of the planned path is input into the first filter group, and the first filter group processes the planned path length according to the first time constant to obtain a first processing result. The first processing result is input into the second filter group, and the second filter group processes the first processing result according to the second time constant to obtain the robot's velocity planning information. Through the technical solution provided by this embodiment of the invention, the time constant is calculated based on kinematic constraint information and the robot's natural modal frequencies, which serves as the basis for velocity planning using filter groups. This allows for effective control of frequency characteristics while satisfying kinematic constraints, achieving the dual effect of velocity planning and vibration suppression. This improves the accuracy and stability of the robot's operation and solves the technical problem in related technologies where velocity planning of a robot may lead to resonance in the robot's structural parts, resulting in unnecessary vibrations and affecting the accuracy and stability of the robot's operation. Attached Figure Description

[0029] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0030] Figure 1 This is a hardware structure block diagram of a mobile terminal for a robot speed planning method according to an embodiment of the present invention.

[0031] Figure 2 This is a flowchart of a robot speed planning method according to an embodiment of the present invention;

[0032] Figure 3 This is a flowchart of an optional robot speed planning method according to an embodiment of the present invention;

[0033] Figure 4 This is a schematic diagram of a filter bank according to an embodiment of the present invention;

[0034] Figure 5 This is a flowchart of the time constant calculation for processing kinematic constraints according to an embodiment of the present invention;

[0035] Figure 6 This is a schematic diagram of the amplitude-frequency response curve of a sliding filter according to an embodiment of the present invention;

[0036] Figure 7is a schematic diagram of a kinematic curve before optimization according to an embodiment of the present application;

[0037] Figure 8 is a schematic diagram of a kinematic curve before optimization according to an embodiment of the present application;

[0038] Figure 9 is a schematic diagram of a speed planning curve after processing frequency constraints according to an embodiment of the present application;

[0039] Figure 10 is a flow chart of another optional speed planning method of a robot according to an embodiment of the present application;

[0040] Figure 11 is a schematic diagram of a speed planning device of a robot according to an embodiment of the present application.

[0041] Wherein, the above figures include the following reference signs:

[0042] 102, processor; 104, memory; 106, transmission device; 108, input and output device. DETAILED DESCRIPTION

[0043] In order to make the personnel in the art better understand the present application scheme, the technical scheme in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0044] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0045] As described in the background section, related technologies may cause resonance in the robot's structural parts during speed planning, leading to unnecessary vibrations and affecting the robot's accuracy and stability. This invention provides a robot speed planning method and apparatus, a robot, a computer-readable storage medium, a processor, and a computer program product.

[0046] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0047] The methods and embodiments provided in this invention can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a robot speed planning method according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0048] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the robot speed planning method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the aforementioned networks may include wireless networks provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0049] Example 1

[0050] According to an embodiment of the present invention, a method embodiment for robot speed planning is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0051] Figure 2 This is a flowchart of a robot speed planning method according to an embodiment of the present invention, such as... Figure 2 As shown, the robot's speed planning method includes the following steps:

[0052] Step S202: Obtain the kinematic constraint information of the robot's planned path and the robot's natural modal frequencies.

[0053] Optionally, the robot's natural modal frequencies refer to the specific vibration frequencies that naturally form in the robot's mechanical structure under free vibration. These frequencies are often parameters that require special attention during robot design, because their presence may cause input signals at certain specific frequencies to resonate in the mechanical structure, thereby generating unwanted vibrations.

[0054] Optionally, the kinematic constraint information includes a series of restrictions that the robot must follow during motion planning, such as maximum speed, maximum acceleration, maximum jerk, etc., as well as the geometric properties of the path, such as the length of the path to be planned. These constraints are to ensure that the robot completes the specified task safely and efficiently.

[0055] In step S204, the first time constant of the first filter bank is determined according to the kinematic constraint information, and the second time constant of the second filter bank is determined according to the natural modal frequency, wherein the first filter bank includes a plurality of kinematic constraint sliding filters, and the second filter bank includes a plurality of frequency constraint filters.

[0056] Optionally, the time constant of the filter is used to describe the speed of the filter's response to the input signal, or in other words, the length of time required for the filter to transition to a stable state. In the field of electronic engineering and signal processing, the time constant is closely related to the dynamic characteristics of the filter, which is reflected in the following aspects:

[0057] 1) Response speed: The smaller the time constant, the faster the filter responds to the input signal, and the shorter the transient process of the signal, i.e. the filter can reach a steady state response faster. Conversely, the larger the time constant, the slower the response speed of the filter, and the longer the time for the signal to pass through the filter.

[0058] 2) Smoothness: A filter with a larger time constant has a better smoothing effect on the signal, and can better filter out high-frequency noise, but this may also cause the details and rapid changes of the signal to be excessively suppressed. A filter with a smaller time constant has better followability to the signal, and can retain more detailed information, but its noise resistance is relatively weak.

[0059] 3) Frequency response: For a low-pass filter, the time constant is inversely proportional to its cutoff frequency (i.e. the frequency point at which the filter begins to significantly attenuate the input signal). This means that the size of the time constant directly affects the frequency selection characteristics of the filter, i.e. which frequency components will be retained or filtered out more.

[0060] In the context of robot speed planning, the time constant of the filter is used to adjust the smoothing degree and frequency characteristics of the speed signal to ensure the smoothness of the robot motion and that the control signal does not contain frequency components that may cause the robot structure to vibrate. By optimizing the time constant of the filter, a balance between the dynamic response speed and the smoothing degree of the speed planning can be achieved, so that the kinematic constraints (such as speed and acceleration limits) are met while avoiding oscillation or instability phenomena during robot operation.

[0061] Optionally, the moving average filter, as the signal processing unit, can control the smoothing degree of the filter to the input signal by adjusting its time constant, thereby affecting the kinematic characteristics of the output speed planning trajectory. In the present application, by optimizing the time constant, it is ensured that the output trajectory meets the constraints such as the upper limit of speed and the upper limit of acceleration, while the duration of the trajectory is shortened as much as possible to achieve time optimality. The moving average filter has frequency response characteristics and can suppress the signal components in a certain frequency band. By calculating the time constant matching the natural modal frequency of the robot, a filter that can effectively suppress the frequency components can be designed. Adding such a filter to the speed planning algorithm can ensure that the planned speed information does not excite the vibration mode of the robot, avoiding resonance and vibration during movement.

[0062] Optionally, the first time constant and the second time constant refer to a parameter of the moving average filter when processing signals, which determines the response speed and frequency selectivity of the filter to the input signal. In the embodiment of the present application, the first time constant corresponds to the first filter group processing kinematic constraints, and the second time constant corresponds to the second filter group processing frequency constraints.

[0063] Optionally, the moving average filter is a low-pass filter that removes high-frequency noise and specific frequency components by averaging the input signal to smooth the signal. It has a wide range of applications in the field of signal processing, especially in cases where specific frequency components need to be suppressed.

[0064] In this embodiment, in the robot control system, first, the kinematic constraint information of the robot needs to be collected or pre-set, including but not limited to path length, speed upper limit, acceleration upper limit, and other key parameters. At the same time, the natural modal frequency of the robot is identified. This frequency is usually known during the design stage of the robot, or is empirical data obtained through experiments and tests. For example, the path length is set to 10 meters, the maximum speed is 3 m / s, and the maximum acceleration is 0.4 m / s 2 , and the natural modal frequency of the robot is determined to be 33 Hz.

[0065] Then, according to the above kinematic constraint information, the first time constant of each filter in the first filter group is calculated using mathematical models or formulas in control theory. Similarly, according to the natural modal frequency of the robot, the second time constant of each filter in the second filter group is determined. These two time constants are indicators of filter response speed, which directly determine the processing effect of the filter to the signal.

[0066] Step S206, input the planning path length of the path to be planned into the first filter group, and process the planning path length according to the first time constant using the first filter group to obtain a first processing result.

[0067] In this embodiment, the length of the path to be planned is taken as the input signal, which is sequentially processed by a first filter bank consisting of kinematic constraint filters, each of which adjusts the input signal according to its first time constant to meet the kinematic constraint conditions in the speed planning. Then, the output signal of the first filter bank is input to a second filter bank consisting of frequency constraint filters, which further process the signal according to its second time constant to suppress frequency components matching the inherent modal frequency of the robot. Finally, the speed planning information output by the second filter bank is a planned trajectory that takes into account both time optimality and frequency constraints.

[0068] In step S208, the first processing result is input to the second filter bank, and the second filter bank is used to process the first processing result according to a second time constant to obtain the speed planning information of the robot.

[0069] Figure 3 is a flowchart of an optional speed planning method for a robot according to an embodiment of the present application, as shown in Figure 3 After obtaining the path to be planned, the kinematic constraint filter bank is processed, followed by the frequency constraint filter bank, and finally the planning information is obtained.

[0070] It is worth noting that in the embodiment of the present application, the input signal is processed by the carefully designed filter bank, which ensures that the speed planning trajectory not only complies with the kinematic constraints, but also completes the planning path in the shortest time, greatly improving the efficiency of the robot in the task execution process. At the same time, by suppressing frequency components matching the inherent modal frequency of the robot, the speed planning information will not cause resonance of the robot, even at high speed and complex path planning, it can maintain good motion stability and control accuracy. Combined with the time optimality and frequency constraint control strategy, the method of the present application not only improves the efficiency of robot speed planning, but also effectively avoids vibration caused by improper frequency matching, which is crucial for robots in precision manufacturing, medical surgery, electronic assembly and other high-precision application scenarios, greatly improving the applicability and competitiveness of robots in these fields.

[0071] From the above, in the embodiment of the present application, the kinematic constraint information of the path to be planned of the robot and the inherent modal frequency of the robot are obtained; the first time constant of the first filter bank is determined according to the kinematic constraint information, and the second time constant of the second filter bank is determined according to the inherent modal frequency, wherein the first filter bank comprises a plurality of kinematic constraint sliding filters, and the second filter bank comprises a plurality of frequency constraint filters; the planning path length of the path to be planned is input into the first filter bank, the planning path length is processed according to the first time constant by using the first filter bank, and a first processing result is obtained; the first processing result is input into the second filter bank, the first processing result is processed according to the second time constant by using the second filter bank, and the speed planning information of the robot is obtained, which realizes that the time constant is calculated according to the kinematic constraint information and the inherent modal frequency of the robot, and the time constant is used as the basis of the filter bank for speed planning, so that the frequency characteristics can be effectively controlled on the premise of meeting the kinematic constraint, and the purpose of double effect of speed planning and vibration suppression is achieved, and the precision and stability of the robot work are improved.

[0072] Therefore, by the above technical solution provided by the embodiment of the present application, the technical problem that the structure of the robot may resonate and unnecessary vibration is generated when the speed of the robot is planned in the related art, thereby affecting the precision and stability of the robot work is solved.

[0073] According to the above embodiment of the present application, the second filter bank is connected in series behind the first filter bank, the plurality of kinematic constraint sliding filters are connected in series, and the plurality of frequency constraint filters are connected in series.

[0074] In the embodiment of the present application, all the kinematic constraint sliding filters and the frequency constraint filters are connected in series. For example, the filters in the first filter bank are arranged in the order of (τ1), (τ2), and the filters in the second filter bank are arranged in the order of (τ3). This series connection structure ensures the continuity and hierarchy of signal processing, which is beneficial to the step-by-step optimization of the signal.

[0075] Figure 4 is a schematic diagram of the filter bank according to the embodiment of the present application, as shown in Figure 4 The filter bank for processing kinematic constraint (i.e., the first filter bank) includes filter 1, filter 2, and filter 3 connected in series. The filter bank for processing frequency constraint includes filter 4 and filter 5.

[0076] The series connection structure of the above filters enables the speed planning process to be carried out systematically and hierarchically, which not only realizes time optimality, but also effectively processes frequency constraint, avoids vibration and instability caused by inherent modal frequency, and improves the overall performance and reliability of the robot.

[0077] According to the above embodiment of the present application, the determining the first time constants of the first filter set according to the kinematic constraint information comprises: determining the third time constants of each kinematic constraint sliding filter in the first filter set according to the kinematic constraint information and the time optimal condition; and adjusting the time constants of each kinematic constraint sliding filter according to the third time constants to obtain the first time constants.

[0078] In this embodiment, the time constants of each kinematic constraint sliding filter in the first filter set are determined according to the kinematic constraint information (such as the upper limit of speed and the upper limit of acceleration) and the time optimal condition. For example, the initially calculated time constants are (\tau_1^*=0.03s) and (\tau_2^*=0.08s), but they may not satisfy the optimal condition. Through adjustment, the finally determined time constants are (\tau_1=0.05s) and (\tau_2=0.1s).

[0079] Here, the optimal adjustment of the time constants ensures that the robot can achieve the minimum duration in time while satisfying the kinematic constraints, thereby improving the response speed and work efficiency of the robot in a dynamic environment.

[0080] According to the above embodiment of the present application, after determining the first time constants of the first filter set according to the kinematic constraint information and determining the second time constants of the second filter set according to the inherent modal frequency, the speed planning method of the robot further comprises: judging whether each first time constant and each second time constant satisfy the time optimal condition in a backward-to-forward order according to the serial connection order of the first filter set and the second filter set to obtain a judgment result; when the judgment result indicates that each first time constant and each second time constant satisfy the time optimal condition, performing the speed planning operation of the robot; and when the judgment result indicates that each first time constant and each second time constant do not satisfy the time optimal condition, adjusting the first time constants and the second time constants until the first time constants and the second time constants satisfy the time optimal condition.

[0081] In this embodiment, the time constants of the filters are judged in a backward-to-forward order whether they satisfy the time optimal condition. If not, the time constants are adjusted using a predetermined coefficient until all the time constants satisfy the time optimal condition. For example, if (\tau_1=0.05s) and (\tau_2=0.1s) do not satisfy the optimal condition, the values of (\tau_1) and (\tau_2) are adjusted until they satisfy the optimal condition.

[0082] Here, the ability to dynamically adjust the time constants enables the present technical solution to adapt to the specific needs of different robots and different tasks, thereby improving the versatility and adaptability of the speed planning method.

[0083] According to the above embodiment of the present application, when the judgment result indicates that each first time constant and each second time constant does not satisfy the time optimal condition, adjusting the first time constant and the second time constant comprises: reducing the kinematic constraint information by a predetermined coefficient to increase the first time constant and the second time constant to satisfy the time optimal condition, wherein the kinematic constraint and the reduced kinematic constraint satisfy represents the kinematic constraint, represents the reduced kinematic constraint, a is a predetermined coefficient, i represents the i-th time constant, the first time constant and the second time constant before adjustment and the first time constant and the second time constant after adjustment satisfy and T i represents the i-th time constant before modification, represents the i-th time constant after modification.

[0084] This adjustment strategy based on a predetermined coefficient can achieve a dynamic balance between the kinematic constraint and the time constant, and ensure the optimal performance of the robot speed planning.

[0085] Figure 5 is a flow chart of the time constant calculation of the kinematic constraint processing according to the embodiment of the present application, as shown in Figure 5 First, the time constants of all filters are calculated according to the kinematic constraint. Second, whether the optimal condition is satisfied is judged from back to front according to the series order of the filters, and if the optimal condition is not satisfied, the third step is entered. Third, the time constants T j and T j+1 are adjusted according to the calculation formula of the coefficient a (i.e., the predetermined coefficient), and the loop index is reset. Fourth, the time constants of all filters satisfy the optimal condition and are output.

[0086] As described above, in the embodiment of the present application, it mainly includes two parts of processing the kinematic constraint and processing the frequency constraint, and the filter group processing the frequency constraint is connected behind the filter group processing the kinematic constraint. In the filter group processing the kinematic constraint, the time constant T i of the kinematic constraint sliding average filter is calculated according to the kinematic constraint of the path to be planned; and the time constant of each filter is adjusted according to the time optimal condition . In the filter group processing the frequency constraint, the time constant of the frequency constraint filter is calculated according to the set robot inherent modal frequency. The length of the path to be planned is input to the filter groups processing the kinematic constraint and the frequency constraint, and the output planning signal satisfies the shortest duration and does not contain the set suppression frequency.

[0087] The principle of processing the kinematic constraint is as follows: the length h of the path to be planned, the speed upper limit Acceleration upper limit accelerometer limit The input signal for processing the kinematically constrained filter bank is a step signal containing path length information. The calculation of the time constant of each filter satisfies Where i = 0, ..., n. When the time constant of a filter does not satisfy the optimal condition... Then, the time constant of each filter is recalculated. The derivation of the specific method is as follows. It should be noted here that the time constant T of each filter... i Both represent the current kinematic constraint q (i-1) use arrive The shortest duration; the duration of the entire velocity planning is the sum of the time constants of all filters; if the time constant of the current filter is greater than or equal to the sum of the time constants of all subsequent filters, the optimal condition is met, and the duration of the entire velocity planning trajectory is optimal.

[0088] kinematic constraints Substitute the optimal conditions You can get .when When the time-optimal condition is not met, use the coefficient Reduce kinematic constraints Increase the time constant Make it satisfy the optimal condition, that is ,in To reduce the kinematic constraints, the modified time constant and the unmodified time constant must satisfy the following relationship: and Substitute these two relations into The correlation coefficient can be obtained. equation Solving the equation yields the analytical expression for the coefficients as follows: .

[0089] The process of substituting kinematic constraints into the optimal conditions is as follows:

[0090] 1) Design the kinematic constraints for the entire velocity planning trajectory target: trajectory length, upper limit of velocity, upper limit of acceleration, upper limit of jerk, etc.;

[0091] 2) Determine the number of filters to use based on the number of kinematic constraints and the number of frequency domain constraints. For example, if the number of kinematic constraints is n and the number of frequency domain constraints is m, the total number of filters used is n+m-1.

[0092] 3) Calculate the time constants of all filters. and

[0093] 4) Determine whether the time constant of the filter handling kinematic constraints meets the time-optimal condition. If it does not meet the time-optimal condition, perform optimization. and

[0094] 5) Use the optimized filter bank for speed planning.

[0095] Furthermore, it should be noted that in the embodiments of the present invention, a transfer function is used. Velocity planning is performed using a series sliding filter structure, T i Let be the time constant of the filter (the transfer function is defined as the ratio of the Laplace transform of the output to the Laplace transform of the input under zero initial conditions). To achieve trajectory time optimization, the time constant of each filter in the cascaded array must satisfy . When the kinematic constraints are not set properly, the time constant of the filter may not meet the above conditions, resulting in a longer duration of the entire trajectory and failure to meet the time optimality requirement.

[0096] Therefore, in this embodiment of the invention, the time constants of each filter calculated based on kinematic constraints are recalculated, such that each time constant is determined by satisfying... To achieve optimal speed planning time.

[0097] Furthermore, in this embodiment of the invention, the principle of frequency constraint is as follows: the amplitude response function of the sliding filter used is... Among them, cutoff frequency The graph of the function is as follows Figure 6 ( Figure 6 This is a schematic diagram of the amplitude-frequency response curve of a sliding filter according to an embodiment of the present invention. The horizontal axis represents frequency, and the vertical axis represents the gain or attenuation amplitude of the input filter signal. The amplitude response function describes the effect of the filter on the signal amplitude at different frequencies. The filter cutoff frequency refers to the frequency point at which the filter begins to significantly attenuate the input signal. Figure 6 It can be seen that when the input signal frequency ω is the cutoff frequency ω i When the amplitude is an integer multiple of the value, the filter amplitude is zero. Based on the above relationship, the robot's natural mode frequency can be used. Set the time constant T of the moving average filter i inhibition The two satisfy the relation After the planned speed information is passed through the aforementioned moving average filter, the robot's inherent modal frequencies are filtered out. This satisfies the frequency constraints and solves the vibration problem caused by this reason during the movement.

[0098] According to the above embodiments of the present invention, the predetermined coefficient is determined by the formula The calculation shows that n represents the number of time constants.

[0099] Optionally, the predetermined coefficient is the coefficient α of the time constant of the optimized filter. Its physical meaning is a scaling ratio of the filter time constant. For time constants that do not meet the optimal conditions, the scaling is performed, and a new time constant is calculated to meet the optimal conditions, which significantly reduces the duration of the entire velocity planning trajectory.

[0100] Here, the adjustment coefficient is calculated using precise mathematical formulas, ensuring the accuracy of the time constant adjustment and helping to achieve optimal performance in speed planning.

[0101] According to the above embodiments of the present invention, determining the second time constant of the second filter bank based on the inherent mode frequency includes: determining the second time constant based on the inherent mode frequency using the formula... The second time constant of the second filter bank is calculated, where T i Represents the i-th second time constant. Indicates the intrinsic mode.

[0102] By adjusting the time constant directly related to the intrinsic modal frequency, the signal components that match the vibration frequency of the robot structure are effectively suppressed, improving the control accuracy of frequency characteristics during speed planning, thereby reducing vibration and improving the smoothness and accuracy of robot operation.

[0103] The following is a specific implementation method, where the length of the path to be planned is set to 10, and the speed limit is set. The maximum acceleration is 3. The maximum accelerometer value is 0.4. The value is 0.4, and the upper limit of the derivative of the jerk is 5. (This is derived from the formula...) The time parameters of each filter were calculated as follows: Time constant T1 < T2 + T3 + T4, duration T tot =11.9133, which does not meet the optimal conditions, and its kinematic curve is as follows. Figure 7 ( Figure 7 This is a schematic diagram of the kinematic curves before optimization according to an embodiment of the present invention. The horizontal axis represents time, and the vertical axis q(t) represents displacement. (1) (t) represents velocity, and the ordinate is q. (2) (t) represents acceleration, and the ordinate is q. (3) (t) represents jerk, q (4) (t) represents the derivative of the jerk. After using the optimization method, the time constant T1 = 5.5961, the time constant T2 = 4.4891, and the duration T tot= 11.1382, the time is reduced by -6.5%. The optimized kinematic curve is shown in Fig. 6. Figure 8 Figure 8 Fig. 6 is a schematic diagram of a kinematic curve before optimization according to an embodiment of the present application, the horizontal coordinate represents time, the vertical coordinate q(t) represents displacement, the vertical coordinate q (1) (t) represents velocity, the vertical coordinate q (2) (t) represents acceleration, the vertical coordinate q (3) (t) represents jerk, and the vertical coordinate q (4) (t) represents jerk derivative.

[0104] Suppose the robot inherent modal frequency to be suppressed is 33, the time constant of the filter is calculated as 33, the time constant of the filter is calculated as The velocity planning curve obtained after processing the frequency constraint filter in series is shown in Fig. 7. Figure 9 Figure 9 Fig. 7 is a schematic diagram of a velocity planning curve after processing the frequency constraint according to an embodiment of the present application, the horizontal coordinate represents time, the vertical coordinate q(t) represents displacement, the vertical coordinate q (1) (t) represents velocity, the vertical coordinate q (2) (t) represents acceleration, the vertical coordinate q (3) (t) represents jerk, and the vertical coordinate q (4) (t) represents jerk derivative.

[0105] It should be noted that the technical scheme provided by the embodiment of the present application can be applied to the velocity planning of the motion control system of the robot, and acts on the robot motion process. Figure 10 Fig. 8 is a flow chart of another optional velocity planning method of the robot according to an embodiment of the present application, as shown in Fig. 8, first, the kinematic constraint and the frequency constraint of the path to be planned can be input, then the filter time constant for processing the kinematic constraint is calculated for optimization calculation processing; then the filter time constant for processing the frequency constraint is calculated; finally, the velocity planning information is output. Figure 10 Through the above technical scheme provided by the embodiment of the present application, the sliding average filter is used for velocity planning, the time constant of the filter is adjusted, the planning trajectory duration is optimized, the vibration of the robot caused by the inherent modal frequency during the motion is suppressed, and the working precision and stability of the robot are improved.

[0106]

[0107] ​​​It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all described as a combination of a series of actions, but those skilled in the art should know that the present application is not limited to the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0108] Those skilled in the art can clearly understand from the description of the foregoing embodiments that the method according to the foregoing embodiments can be implemented by means of software and a necessary general hardware platform, and of course, it can also be implemented by hardware, but in many cases, the former is a better implementation. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as a ROM / RAM, a magnetic disk, or an optical disk) and includes a plurality of instructions for causing a terminal device (which can be a mobile phone, a computer, a server, or a network device) to execute the methods described in the various embodiments of the present application.

[0109] Embodiment 2

[0110] According to the embodiments of the present application, a robot speed planning device for implementing the robot speed planning method described above is also provided, Figure 11 is a schematic diagram of a robot speed planning device according to an embodiment of the present application, as Figure 11 shown, the device includes a first acquisition unit 1101, a determination unit 1103, a first processing unit 1105, and a second processing unit 1107. The robot speed planning device will be described in detail below.

[0111] The first acquisition unit 1101 is configured to acquire kinematic constraint information of a path to be planned of a robot and a natural modal frequency of the robot.

[0112] The determination unit 1103 is configured to determine a first time constant of a first filter bank according to the kinematic constraint information, and determine a second time constant of a second filter bank according to the natural modal frequency, wherein the first filter bank includes a plurality of kinematic constraint sliding filters, and the second filter bank includes a plurality of frequency constraint filters.

[0113] The first processing unit 1105 is configured to input a planning path length of the path to be planned into the first filter bank, and process the planning path length according to the first time constant by using the first filter bank to obtain a first processing result.

[0114] The second processing unit 1107 is configured to input the first processing result into the second filter set, and process the first processing result according to the second time constant by using the second filter set, to obtain the speed planning information of the robot.

[0115] It should be noted that the first obtaining unit 1101, the determining unit 1103, the first processing unit 1105 and the second processing unit 1107 correspond to steps S202 to S208 in the above embodiment, and the four units have the same examples and application scenarios as the corresponding steps, but are not limited to the content disclosed in the above embodiment.

[0116] As can be seen from the above, in the scheme described in the above embodiment, the kinematic constraint information of the to-be-planned path of the robot and the inherent modal frequency of the robot can be obtained by using the first obtaining unit; then the first time constant of the first filter set is determined according to the kinematic constraint information, and the second time constant of the second filter set is determined according to the inherent modal frequency, wherein the first filter set includes a plurality of kinematic constraint sliding filters, and the second filter set includes a plurality of frequency constraint filters; the planning path length of the to-be-planned path is input into the first filter set by using the first processing unit, and the planning path length is processed according to the first time constant by using the first filter set, to obtain the first processing result; then the first processing result is input into the second filter set by using the second processing unit, and the first processing result is processed according to the second time constant by using the second filter set, to obtain the speed planning information of the robot, which realizes that the time constant is calculated according to the kinematic constraint information and the inherent modal frequency of the robot, and the time constant is used as the basis for speed planning of the filter set, so that the frequency characteristics can be effectively controlled on the premise of meeting the kinematic constraint, and the purpose of double effect of speed planning and vibration suppression is achieved, and the precision and stability of the robot work are improved.

[0117] Therefore, by using the above technical scheme provided in the embodiment of the present application, the technical problem that the structure of the robot may resonate and unnecessary vibration may be generated when the speed of the robot is planned in the related art, thereby affecting the precision and stability of the robot work is solved.

[0118] Optionally, the second filter set is connected in series behind the first filter set, the plurality of kinematic constraint sliding filters are connected in series, and the plurality of frequency constraint filters are connected in series.

[0119] Optionally, the determining unit includes: a first determining module, configured to determine the third time constant of each kinematic constraint sliding filter in the first filter set according to the kinematic constraint information and the time optimal condition; and an adjusting module, configured to adjust the time constant of each kinematic constraint sliding filter according to the third time constant, to obtain the first time constant.

[0120] Optionally, the speed planning device of the robot further comprises: a second acquisition unit, configured to determine the first time constants of the first filter set according to the kinematic constraint information, and determine the second time constants of the second filter set according to the natural modal frequencies, and then determine whether each first time constant and each second time constant satisfy the time optimal condition in a backward order from the last to the first according to the series connection order of the first filter set and the second filter set, to obtain a determination result; a third processing unit, configured to execute the speed planning operation of the robot when the determination result indicates that each first time constant and each second time constant satisfy the time optimal condition; and an adjustment unit, configured to adjust the first time constants and the second time constants until the first time constants and the second time constants satisfy the time optimal condition when the determination result indicates that each first time constant and each second time constant do not satisfy the time optimal condition.

[0121] Optionally, the adjustment unit comprises: an increasing module, configured to reduce the kinematic constraint information by a predetermined coefficient to increase the first time constants and the second time constants to satisfy the time optimal condition, wherein the kinematic constraint and the reduced kinematic constraint satisfy represents the kinematic constraint, represents the reduced kinematic constraint, α is the predetermined coefficient, i represents the i th time constant, and the first time constants and the second time constants before adjustment and the first time constants and the second time constants after adjustment satisfy and T i represents the i th time constant before modification, represents the i th time constant after modification.

[0122] Optionally, the predetermined coefficient is calculated by a formula , and n represents the number of time constants.

[0123] Optionally, the determination unit comprises: a calculation module, configured to calculate the second time constants of the second filter set according to the natural modal frequencies by a formula , wherein T i represents the i th second time constant, represents the natural modal frequency.

[0124] According to another aspect of the embodiments of the present application, a robot is also provided, which uses the speed planning method of the robot according to any one of the above.

[0125] According to another aspect of the embodiments of the present application, a processor is also provided, which is used to run a program, wherein the program executes the speed planning method of the robot according to any one of the above when the program is run.

[0126] According to another aspect of the embodiments of the present application, a computer program product including computer instructions is provided, which, when executed by a processor, performs the robot speed planning method of any one of the above.

[0127] According to another aspect of the embodiments of the present application, a computer readable storage medium is provided, which includes a stored program, wherein the program performs the robot speed planning method of any one of the above.

[0128] Optionally, in the embodiment, the computer readable storage medium can be located in any one of a group of computer terminals in a computer network, or in any one of a group of communication devices.

[0129] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: obtaining kinematic constraint information of a path to be planned for a robot and inherent modal frequency of the robot; determining a first time constant of a first filter set according to the kinematic constraint information, and determining a second time constant of a second filter set according to the inherent modal frequency, wherein the first filter set includes a plurality of kinematic constraint sliding filters, and the second filter set includes a plurality of frequency constraint filters; inputting a planning path length of the path to be planned into the first filter set, processing the planning path length according to the first time constant by using the first filter set to obtain a first processing result; inputting the first processing result into the second filter set, processing the first processing result according to the second time constant by using the second filter set to obtain speed planning information of the robot.

[0130] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: determining a third time constant of each kinematic constraint sliding filter in the first filter set according to the kinematic constraint information and a time optimal condition; and adjusting the time constant of each kinematic constraint sliding filter according to the third time constant to obtain the first time constant.

[0131] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: after determining the first time constants of the first filter set according to the kinematic constraint information and determining the second time constants of the second filter set according to the natural modal frequency, judging in sequence from back to front whether each first time constant and each second time constant satisfy the time optimal condition in the order of series connection of the first filter set and the second filter set, to obtain a judgment result; when the judgment result indicates that each first time constant and each second time constant satisfy the time optimal condition, performing the speed planning operation of the robot; when the judgment result indicates that each first time constant and each second time constant do not satisfy the time optimal condition, adjusting the first time constant and the second time constant until the first time constant and the second time constant satisfy the time optimal condition.

[0132] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: reducing the kinematic constraint information by a predetermined coefficient to increase the first time constant and the second time constant to satisfy the time optimal condition, wherein the kinematic constraint and the reduced kinematic constraint satisfy represents the kinematic constraint, represents the reduced kinematic constraint, a is the predetermined coefficient, i represents the i th time constant, and the first time constant and the second time constant before adjustment and the first time constant and the second time constant after adjustment satisfy and T i represents the i th time constant before modification, represents the i th time constant after modification.

[0133] Optionally, in the embodiment, the computer readable storage medium is configured to store program code for performing the following steps: according to the natural modal, the second time constant of the second filter set is calculated by the formula T i represents the i th second time constant, represents the natural modal.

[0134] The above-mentioned serial numbers of the embodiments of the application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0135] In the above-mentioned embodiments of the application, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0136] In several embodiments provided in the present application, it should be understood that the disclosed technical contents can be implemented by other manners. Among them, the above-described device embodiments are only illustrative, for example, the division of the units can be a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or modules shown or discussed can be indirect coupling or communication connection between the units or modules through some interfaces, and can be electrical or other forms.

[0137] The technical features of the above-described embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above-described embodiments are not described, however, as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present disclosure.

[0138] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Part or all of the units can be selected to achieve the purpose of the embodiment scheme according to actual needs.

[0139] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0140] When the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that makes a contribution to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The foregoing storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0141] The above merely describes the preferred embodiments of the present application, and it should be pointed out that, for those skilled in the art, several improvements and refinements can be made without departing from the principles of the present application, and these improvements and refinements should also be considered as falling within the protection scope of the present application.

Claims

1. A speed planning method of a robot, characterized by, The method comprises the following steps: obtaining kinematic constraint information of a path to be planned of a robot and inherent modal frequency of the robot; determining a first time constant of a first filter set according to the kinematic constraint information and determining a second time constant of a second filter set according to the inherent modal frequency, wherein the first filter set comprises a plurality of kinematic constraint sliding filters, and the second filter set comprises a plurality of frequency constraint filters; inputting a planning path length of the path to be planned into the first filter set, processing the planning path length according to the first time constant by using the first filter set to obtain a first processing result; inputting the first processing result into the second filter set, processing the first processing result according to the second time constant by using the second filter set to obtain speed planning information of the robot.

2. The speed planning method of a robot according to claim 1, characterized in that, The second filter set is connected in series behind the first filter set, the plurality of kinematic constraint sliding filters are connected in series in turn, and the plurality of frequency constraint filters are connected in series in turn.

3. The method of velocity planning for a robot according to claim 1, wherein, The method further comprises the following steps: determining a third time constant of each kinematic constraint sliding filter in the first filter set according to the kinematic constraint information and a time optimization condition; adjusting the time constant of each kinematic constraint sliding filter according to the third time constant to obtain the first time constant.

4. The speed planning method of a robot according to claim 1, wherein After determining the first time constant of the first filter set according to the kinematic constraint information and determining the second time constant of the second filter set according to the inherent modal frequency, the method further comprises the following steps: judging whether each first time constant and each second time constant meets a time optimization condition in a sequence from back to front according to the series connection of the first filter set and the second filter set to obtain a judgment result; when the judgment result indicates that each first time constant and each second time constant meets the time optimization condition, performing a speed planning operation of the robot; when the judgment result indicates that each first time constant and each second time constant does not meet the time optimization condition, adjusting the first time constant and the second time constant until the first time constant and the second time constant meet the time optimization condition.

5. The method of velocity planning of a robot according to claim 4, wherein, When the judgment result indicates that each first time constant and each second time constant does not meet the time optimization condition, adjusting the first time constant and the second time constant comprises the following steps: reducing the kinematic constraint information by a predetermined coefficient to increase the first time constant and the second time constant to satisfy the time optimal condition, wherein the kinematic constraint and the reduced kinematic constraint satisfy representing the kinematic constraint, representing the reduced kinematic constraint, a is the predetermined coefficient, i represents an i-th time constant, the first time constant and the second time constant before adjustment and the first time constant and the second time constant after adjustment satisfy and T i representing an i-th time constant before modification, representing an i-th time constant after modification.

6. The speed planning method of a robot according to claim 5, wherein The predetermined coefficient is calculated by the formula n represents the number of time constants.

7. The method of velocity planning of a robot according to claim 1, wherein, determining the second time constant of the second filter set according to the inherent modal frequency comprises the following steps: The second filter set is calculated with a second time constant T according to the intrinsic mode i denotes the i-th second time constant, denotes the intrinsic mode.

8. A speed planning device of a robot characterized by comprising: The method comprises the following steps: a first obtaining unit is configured to obtain kinematic constraint information of a path to be planned of a robot and inherent modal frequency of the robot; a determining unit is configured to determine a first time constant of a first filter set according to the kinematic constraint information and determine a second time constant of a second filter set according to the inherent modal frequency, wherein the first filter set comprises a plurality of kinematic constraint sliding filters, and the second filter set comprises a plurality of frequency constraint filters; A first processing unit is configured to input a planned path length of the path to be planned into the first filter set, process the planned path length according to the first time constant by using the first filter set, and obtain a first processing result. A second processing unit is configured to input the first processing result into the second filter set, process the first processing result according to the second time constant by using the second filter set, and obtain the speed planning information of the robot.

9. A robot, characterized in that The robot uses the speed planning method of the robot according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises a stored program, wherein the program executes the speed planning method of the robot according to any one of claims 1 to 7.

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