Master-slave teleoperation method based on adaptive signal and dynamic control optimization

Abstract

The invention particularly relates to a master-slave teleoperation method based on adaptive signals and dynamic control optimization, which comprises the following steps: acquiring a master end signal, and performing Kalman filtering on the master end signal to obtain a filtered master end signal; constructing a buffer signal sequence based on the filtered main end signal, and smoothing the buffer signal sequence to obtain a smoothed main end signal; and the smoothed master end signal passes through a slave end proportional-differential controller to generate an acceleration control signal, integration is carried out on the acceleration control signal, meanwhile, saturation constraint is carried out on the acceleration control signal, and a displacement instruction used for controlling the mechanical arm to move is obtained. Under the condition of unstable time delay signals, the high-frequency servo precision, the trajectory tracking performance and the dynamic response stability of the slave end mechanical arm are remarkably improved, and technical support is provided for stable and efficient operation of the master-slave teleoperation system.

Description

Technical Field

[0001] The invention belongs to the technical field of robot teleoperation control, and in particular relates to a master-slave teleoperation method based on adaptive signal and dynamic control optimization. Background Art

[0002] Master-slave teleoperation systems are widely used in medical surgery, remote maintenance, and hazardous environment operations. The system controls the slave robotic arm through the operation signal of the master end to perform precise operation tasks. However, in practical applications, the slave robotic arm is usually required to have high-frequency servo accuracy to ensure that it can effectively cope with complex dynamic tasks. Due to the jitter and unevenness of the master end signal, directly transmitting it to the slave end for control may cause the system response to be unstable, or even lead to dynamic instability.

[0003] In the prior art, the irregularity of the master-side signal is mainly due to the delay and instability of the communication link, which causes the signal to fluctuate irregularly during transmission and cannot be transmitted to the slave side in real time at uniform time intervals. This signal irregularity directly affects the servo accuracy and dynamic response performance of the slave-side manipulator, especially when performing high-frequency dynamic tasks, which may lead to increased trajectory tracking errors and instability of dynamic responses.

[0004] To solve this problem, existing solutions usually use signal filtering technology to smooth the master-side signal. Commonly used filtering methods, such as weighted moving average, median filtering or Kalman filtering, can effectively suppress noise and fluctuations in the signal, but these methods do not fully consider the requirements of the slave end for high-frequency servo accuracy when they are designed. In addition, when the slave-side controller responds to extreme signals, the system may exhibit nonlinear responses, which in turn affects the robustness and stability of the system.

[0005] Therefore, how to design a strategy that can comprehensively consider the real-time filtering of the master-side signal and the efficient control of the slave-side to improve the servo accuracy and dynamic response performance of the slave-side manipulator under irregular signal conditions has become a key issue that needs to be urgently solved in the current master-slave teleoperation system field. Summary of the invention

[0006] The present invention proposes a master-slave teleoperation method based on adaptive signal and dynamic control optimization, aiming to solve the problem that the master-end signal cannot be evenly and real-time transmitted to the slave-end manipulator due to the instability and delay of the communication link. In particular, when the slave-end manipulator performs high-frequency dynamic tasks, accurate servo control and response performance must be guaranteed. The present invention introduces a buffer sequence to smooth the master-end signal, and combines the proportional-differential (PD) control algorithm to optimize the motion performance of the slave-end manipulator, significantly improving the trajectory tracking accuracy and the stability of the dynamic response.

[0007] The technical means adopted by the present invention are as follows:

[0008] A master-slave remote operation method based on adaptive signal and dynamic control optimization, comprising the following steps:

[0009] S1. Obtain a master signal, perform Kalman filtering on the master signal, and obtain a filtered master signal;

[0010] S2. Based on the filtered master signal, a buffered signal sequence is constructed, and the buffered signal sequence is smoothed to obtain a smoothed master signal;

[0011] S3. The smoothed master-end signal is passed through the slave-end proportional-differential controller to generate an acceleration control signal, which is integrated and saturated to obtain a displacement command for controlling the movement of the robotic arm.

[0012] Furthermore, the filtered master-end signal is obtained based on the following formula:

[0013]

[0014] Among them, K k is the Kalman gain, z k is the observed value of the master signal at time k, H is the observation matrix, is the observed value of the filtered master signal at time k-1, is the observed value of the filtered master signal at time k.

[0015] Further, based on the filtered master-end signal, a buffered signal sequence is constructed, including:

[0016] A buffer sequence with a length of M is constructed, and the filtered master-end signal is stored in the buffer sequence to obtain a buffer signal sequence. The calculation formula of the buffer signal sequence is as follows:

[0017]

[0018] in, To buffer the signal sequence, is the observed value of the filtered master signal at time k, is the observed value of the filtered master signal at time k-M+1, is the observed value of the filtered master signal at time k-M+2.

[0019] Further, the buffered signal sequence is smoothed to obtain a smoothed master end signal, including:

[0020] The buffered signal sequence is input into the buffered sequence module. The historical filtered master-end signal for a period of time is stored through the sliding window technology. The historical filtered master-end signal is reconstructed through the linear interpolation algorithm to obtain the smoothed master-end signal. The calculation formula of the smoothed master-end signal is as follows:

[0021]

[0022] in, is the observed value of the smoothed master signal at time k, is the observed value of the filtered master signal at time k+1, is the observed value of the filtered master signal at time k-1, t is the current time point, t k-1 is the time point k-1, t k+1 is the time point k+1.

[0023] Furthermore, the smoothed master-end signal is passed through a slave-end proportional-differential controller to generate an acceleration control signal, including:

[0024] The smoothed master-end signal is transmitted to the slave-end, and the smoothed master-end signal is inversely solved to obtain the joint angle, which is input into the slave-end proportional-differential controller. Through the deep coupling method, the error between the buffered master-end signal and the current position of the slave-end is calculated to obtain the acceleration control signal used to adjust the control output. The acceleration control signal calculation formula is as follows:

[0025]

[0026] Among them, a k is the acceleration control signal at time k, x desired is the joint angle, is the target speed, x k is the position of the slave end at time k, is the speed of the slave end at time k, K p is the proportional gain, K d is the differential gain.

[0027] Furthermore, the acceleration control signal is integrated to obtain the speed command and displacement command. The calculation formula of the speed command is as follows:

[0028]

[0029] in, is the speed of the slave end at time k, is the speed of the slave end at time k-1, a k is the acceleration control signal at time k, Δt is the time step between time k and time k-1,

[0030] The calculation formula of displacement instruction is as follows:

[0031]

[0032] in, is the speed of the slave end at time k, x k is the displacement from the end at time k, x k-1 is the displacement of the slave end at time k-1, and Δt is the time step between time k and time k-1.

[0033] Furthermore, the formula for saturation constraint on the acceleration control signal is as follows:

[0034]

[0035] in, is the speed at the end at time k, is the acceleration from end k at time instant, is the acceleration limit, For speed limit.

[0036] Compared with the prior art, the present invention has the following advantages:

[0037] 1. The present invention utilizes an online filter to smooth the irregular signal transmitted by the master end in real time, eliminate signal jitter and noise interference, and provide a more stable input signal for the slave end.

[0038] 2. In the present invention, the slave-end robot arm adopts a deeply coupled proportional-differential (PD) control algorithm, which effectively improves the adaptability to complex dynamic tasks and the servo accuracy.

[0039] 3. In the present invention, in order to prevent extreme behavior of system response, an integral saturation term is introduced to constrain the speed and acceleration, thereby improving the stability and robustness of the system.

[0040] Based on the above reasons, the present invention can be widely promoted in the fields of robot remote operation control, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0042] Figure 1 This is the overall control block diagram of the remote operation of the present invention;

[0043] Figure 2The position diagram of the irregular signal trajectory tracking from the slave controller of the present invention

[0044] Figure 3 This is a speed curve diagram of the slave controller tracking the irregular signal trajectory of the present invention.

[0045] Figure 4 The present invention provides an acceleration curve diagram for tracking the irregular signal trajectory by the slave controller. DETAILED DESCRIPTION

[0046] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0047] like Figure 1 As shown, the present invention provides a master-slave remote operation method based on adaptive signal and dynamic control optimization, the steps specifically include:

[0048] S1. Acquire a master-end signal, and perform Kalman filtering on the master-end signal to obtain a filtered master-end signal.

[0049] In the master-slave teleoperation system, the master signal s k Affected by the instability and delay of the communication link and the shaking of human hands, irregularities and noise occur during the transmission process. To this end, the present invention designs a real-time signal smoothing method based on a buffer sequence to reduce signal fluctuations caused by communication delays and noise. The Kalman filter can perform real-time smoothing of the master-end signal in the presence of noise through a recursive estimation process and a measurement process, thereby obtaining a more accurate and stable signal.

[0050] First, let the discretization of the master signal be s k , where k represents the discrete sampling time. The master end filters the master end signal through the Kalman filter algorithm to obtain the filtered master end signal. The calculation formula of the filtered master end signal is as follows:

[0051]

[0052] Among them, K k is the Kalman gain, z k is the observed value of the master signal at time k, H is the observation matrix, is the observed value of the filtered master signal at time k-1, is the observed value of the filtered master signal at time k.

[0053] The present invention uses an adaptive Kalman filter algorithm to adjust the parameters of the filter (such as the covariance matrix) in real time and automatically adapt to different noise levels according to changes in the signal.

[0054] S2. Based on the filtered master-end signal, a buffer signal sequence is constructed, and the buffer signal sequence is smoothed to obtain a smoothed master-end signal.

[0055] Construct a buffer sequence of length M The filtered master-end signal is stored in the buffer sequence to obtain the buffer signal sequence. The calculation formula of the buffer signal sequence is as follows:

[0056]

[0057] in, To buffer the signal sequence, is the observed value of the filtered master signal at time k, is the observed value of the filtered master signal at time k-M+1, is the observed value of the filtered master signal at time k-M+2.

[0058] The buffered signal sequence is input into the buffered sequence module. The historical filtered master-end signal for a period of time is stored through the sliding window technology. The historical filtered master-end signal is reconstructed through the linear interpolation algorithm to obtain the smoothed master-end signal. The calculation formula of the smoothed master-end signal is as follows:

[0059]

[0060] in, is the observed value of the smoothed master signal at time k, is the observed value of the filtered master signal at time k+1, is the observed value of the filtered master signal at time k-1, t is the current time point, t k-1 is the time point k-1, t k+1 is the time point k+1.

[0061] By buffering the smoothed signal, the delay problem that may be caused by communication delay is eliminated. The buffer module stores and gradually updates the signal to ensure the continuity and consistency of the signal received from the end, and reduce the signal irregularity caused by unstable communication link. The update of the signal in the buffer sequence follows the "first in, first out" rule to ensure that the latest signal is gradually added and the historical signal is removed in sequence.

[0062] S3. The smoothed master-end signal is passed through the slave-end proportional-differential controller to generate an acceleration control signal, which is integrated and saturated to obtain a displacement command for controlling the movement of the robotic arm.

[0063] The smoothed master-end signal is transmitted to the slave-end, and the smoothed master-end signal is inversely solved to obtain the joint angle, which is then input into the proportional-differential (PD) controller. Through the deep coupling method, the error between the buffered master-end signal and the current position of the slave-end manipulator is calculated, and the execution action of the slave-end is adjusted in real time to ensure high-precision trajectory tracking and stable dynamic response, thereby obtaining the PD control formula and acceleration control signal. The acceleration control signal calculation formula is as follows:

[0064]

[0065] Among them, a k is the acceleration control signal at time k, x desired is the joint angle, is the target speed, x k and are the position and velocity of the slave manipulator at time k, K p and K d are proportional gain and differential gain respectively.

[0066] The target speed here is generally 0, and the target of the master-slave teleoperation is the stop state.

[0067] The acceleration control signal is integrated to obtain the speed command and displacement command, and the displacement command is used to control the movement of the robotic arm to improve the dynamic response and control accuracy of the system.

[0068] The calculation formula of speed command is as follows:

[0069]

[0070] in, is the speed of the slave robot arm at time k, is the speed of the slave robot arm at time k-1, a k is the acceleration control signal at time k, Δt is the time step between time k and time k-1, and the calculation formula of the displacement command is as follows:

[0071]

[0072] in, is the speed of the slave robot arm at time k, x k is the displacement of the slave robot at time k, x k-1is the displacement of the slave manipulator at time k-1, and Δt is the time step between time k and time k-1.

[0073] In order to prevent the system from responding too quickly or excessively, the acceleration control signal is saturated to limit the maximum value of acceleration and speed to ensure that the system response does not exceed the preset safety range. The calculation formula of the saturation constraint is as follows:

[0074]

[0075] in, is the speed of the slave robot at time k, is the acceleration of the slave manipulator at time k, is the acceleration limit, For speed limit.

[0076] Due to the introduction of saturation terms in the control system, the PD control system is transformed from a traditional second-order linear system to a system with nonlinear characteristics. This transformation directly affects the dynamic behavior and response characteristics of the system, which is mainly manifested in the limitation of acceleration and speed, thereby effectively preventing the system from responding too fast or excessively. In order to better achieve the tracking effect of the nonlinear system, the response time, maximum speed and maximum acceleration constraints of the above system are judged below.

[0077] Assume that the system equation of slave-side PD control plus normal integration is:

[0078]

[0079] Where x(t) is the actual position of the system at time t, is the position x(t), is the velocity of the system at time t, is the position x(t), is the acceleration of the system at time t, ζ is the damping ratio, ω n is the natural angular frequency, x desired (t) is the target position of the system at time t.

[0080] The approximate characteristic calculation formula of the proportional-derivative controller after the saturation constraint is introduced is as follows:

[0081]

[0082] Among them, T r is the approximate response time of the system, is the acceleration under limiting, is the speed under the limit, x desired is the joint angle, is the acceleration limit, is the speed limit, Δt is the discrete time interval of the discrete system, ω nis the natural angular frequency, ζ is the damping ratio, x is the actual position of the system, is the time speed.

[0083] Example

[0084] In order to prove the feasibility of the above invention, a simulation experiment of the master-slave teleoperation method based on adaptive signal and dynamic control optimization is further established. In the simulation experiment, the maximum acceleration limit of the slave arm is set to 15 rad / s 2 The maximum speed limit is 3rad / s, and the master end signal is a segmented irregular signal. The simulation tracking experiment results are as follows Figure 2-Figure 4 As shown, the slave end is controlled to follow the following joint trajectory:

[0085]

[0086] Among them, u d (t) is the piecewise function of the main end position signal including irregular signals, is the corresponding velocity function, is the corresponding acceleration function.

[0087] like Figures 2 to 4 As shown in the figure, simulation verification shows that the introduction of the saturation term improves the stability and robustness of the system, while also improving the smoothness of the dynamic response, ensuring the high-frequency servo accuracy and trajectory tracking performance of the slave robot under unstable time delay and signal jitter conditions.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A master-slave remote operation method based on adaptive signal and dynamic control optimization, characterized in that the steps include: S1. Obtain a master signal, perform Kalman filtering on the master signal, and obtain a filtered master signal; S2. Based on the filtered master signal, a buffered signal sequence is constructed, and the buffered signal sequence is smoothed to obtain a smoothed master signal; S3. The smoothed master-end signal is passed through the slave-end proportional-differential controller to generate an acceleration control signal, which is integrated and saturated to obtain a displacement command for controlling the movement of the robotic arm.

2. The master-slave remote operation method based on adaptive signal and dynamic control optimization according to claim 1 is characterized in that: The filtered master signal is obtained based on the following formula: Among them, K k is the Kalman gain, z k is the observed value of the master signal at time k, H is the observation matrix, is the observed value of the filtered master signal at time k-1, is the observed value of the filtered master signal at time k.

3. The master-slave remote operation method based on adaptive signal and dynamic control optimization according to claim 1 is characterized in that: Based on the filtered master signal, a buffered signal sequence is constructed, including: A buffer sequence with a length of M is constructed, and the filtered master-end signal is stored in the buffer sequence to obtain a buffer signal sequence. The calculation formula of the buffer signal sequence is as follows: in, To buffer the signal sequence, is the observed value of the filtered master signal at time k, is the observed value of the filtered master signal at time k-M+1, is the observed value of the filtered master signal at time k-M+2.

4. The master-slave remote operation method based on adaptive signal and dynamic control optimization according to claim 1 is characterized in that: The buffered signal sequence is smoothed to obtain a smoothed master end signal, including: The buffered signal sequence is input into the buffered sequence module. The historical filtered master-end signal for a period of time is stored through the sliding window technology. The historical filtered master-end signal is reconstructed through the linear interpolation algorithm to obtain the smoothed master-end signal. The calculation formula of the smoothed master-end signal is as follows: in, is the observed value of the smoothed master signal at time k, is the observed value of the filtered master signal at time k+1, is the observed value of the filtered master signal at time k-1, t is the current time point, t k-1 is the time point k-1, t k+1 is the time point k+1.

5. The master-slave remote operation method based on adaptive signal and dynamic control optimization according to claim 1 is characterized in that: The smoothed master-end signal is passed through the slave-end proportional-differential controller to generate an acceleration control signal, including: The smoothed master-end signal is transmitted to the slave-end, and the smoothed master-end signal is inversely solved to obtain the joint angle, which is input into the slave-end proportional-differential controller. Through the deep coupling method, the error between the buffered master-end signal and the current position of the slave-end is calculated to obtain the acceleration control signal used to adjust the control output. The acceleration control signal calculation formula is as follows: Among them, a k is the acceleration control signal at time k, x desired is the joint angle, is the target speed, x k is the position of the slave end at time k, is the speed at the kth moment from the end, K p is the proportional gain, K d is the differential gain.

6. The master-slave remote operation method based on adaptive signal and dynamic control optimization according to claim 1 is characterized in that: Integrate the acceleration control signal to obtain the speed command and displacement command. The calculation formula of the speed command is as follows: in, is the speed of the slave end at time k, is the speed of the slave end at time k-1, a k is the acceleration control signal at time k, Δt is the time step between time k and time k-1, The calculation formula of displacement instruction is as follows: in, is the speed of the slave end at time k, x k is the displacement from the end at time k, x k-1 is the displacement of the slave end at time k-1, and Δt is the time step between time k and time k-1.

7. The master-slave remote operation method based on adaptive signal and dynamic control optimization according to claim 1 is characterized in that: The formula for saturation constraint on the acceleration control signal is as follows: in, is the speed at the end at time k, is the acceleration from end k at time instant, is the acceleration limit, For speed limit.

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