CN111515958B - Network delay estimation and compensation method of robot remote control system - Google Patents
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Abstract
The invention relates to a network delay estimation and compensation method of a robot remote control system, belonging to the technical field of robot remote control. Aiming at the problem of network delay of a robot remote control system, the method is characterized in that all negative influences caused by the network delay are summarized into a network interference torque, an extended active observer IEAOB is adopted at a main robot end to carry out online real-time estimation on the network interference torque and parameters of a slave robot dynamics model, the model parameters obtained through estimation are used for obtaining a prepared slave robot dynamics model, and meanwhile, the influences caused by the estimated network interference on the network delay are used for compensating. The method can be used for efficiently estimating and compensating the network delay under the condition that the robot dynamic model parameters are difficult to accurately obtain.
Description
Technical Field
The invention belongs to the technical field of robot remote control, and relates to a network delay estimation and compensation method of a robot remote control system.
Background
The robot remote control system is a remote operation control system which is used for remotely operating machines in environments which are difficult to access due to long distance or harm to people and completing relatively complex and accurate operation. Due to the characteristics, the robot remote control system has wide application prospect in many fields. The application of the robot remote control system in new operation fields such as deep sea exploration, deep stratum, outer space, strong radiation and the like brings hope for solving the problems. However, the problem of network delay is a very important problem faced in implementing a robot remote control system. Network delays can cause the teleoperated robot to be unstable and difficult to operate. Furthermore, IP network based delays are typically time varying, which makes control of the robot remote control system more cumbersome. Therefore, how to solve the problem of network delay of the robot remote control system becomes a research focus. The network delay control methods proposed at present mainly include the following: the control method based on passivity, the control method based on a virtual internal model, the control method based on a network communication interference observer (CDOB), the control method based on an H infinity theory and the control method based on a Lyapunov-like function.
Among these methods, a control method based on a network Communication Disturbance Observer (CDOB) is advantageous in that it does not rely on a model of network delay and is receiving increasing attention. The core idea of the control method is to classify all negative influences caused by network delay into a network interference item (NB), estimate the network interference item on line by designing CDOB, and then compensate the influences caused by the network delay by the estimated network interference. Kenji et al propose a method for constructing CDOB using a conventional interference observer (DOB) for network delay estimation and compensation, however this method is based on perfect interference suppression from the robot side, where the interference includes: internal disturbances (uncertain parameters from the robot-end robot dynamics model) and external disturbances (frictional effects and environmental noise, etc.). Not only does this require the CDOB designed by this method to finally get the estimated network interference through a low-pass filter, but the estimated network interference of the CDOB can only be equal to the actual value if the cut-off frequency of the low-pass filter is chosen to be infinite, which obviously does not apply to the actual situation. Therefore, how to construct a CDOB is a problem to be solved, which can accurately estimate network interference while efficiently suppressing the influence of various interferences.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a method for estimating and compensating network delay of a robot remote control system, which resolves all negative effects caused by network delay into a network interference torque, performs online real-time estimation on the network interference torque and parameters of a robot dynamics model by using an extended active observer (IEAOB) at a host robot end, obtains a prepared robot dynamics model by using the estimated model parameters, and compensates for the effects caused by network delay by using the estimated network interference.
In order to achieve the purpose, the invention provides the following technical scheme:
a network delay estimation and compensation method of a robot remote control system specifically comprises the following steps:
s1: delaying time according to the concept of network interferenceAll negative effects of T are summarized in the disturbance torque T d Performing the following steps;
s2: estimating parameters of a slave robot model and external environment torque T by adopting an extended active observer IEAOB at a slave robot end to obtain an accurate slave robot dynamic model;
s3: using control torque T at the main robot end m And fed back slave robot position signals with network delay
On-line estimation of network disturbance torque by IEAOB
And from the robot dynamics model parameters;
s4: acquiring an estimated slave robot dynamics model at the master robot end by using the slave robot model parameters obtained in the step S3;
s5: and obtaining a corresponding position signal by the estimated network interference torque through the estimated slave robot model, and then superposing the position signal and a fed back slave robot position signal with network delay to obtain a position signal without the influence of the network delay, thereby realizing the network delay compensation.
Further, in step S1, the time delay t is t ═ t 1 +t 2 Wherein t is 1 Network communication delay from a master robot end to a slave robot end, namely control channel delay; t is t 2 The method comprises the steps of delaying network communication from a robot end to a main robot end, namely delaying a feedback channel;
the disturbance torque T d ＝T c (1-e -ts )，T c For input of the control torque, s is a laplace frequency domain transform symbol.
Further, in step S2, the IEAOB is used at the slave robot end to match the parameters of the robot kinetic model
And external environment moment T e And estimating, wherein the specific steps of estimating comprise:
s21: the slave robot dynamics model was determined to be:
wherein, theta s Is the inertial parameter of the robot and is,
q s acceleration, velocity and position signals, M s (q s ,q s ) In order to be the inertia, the inertia is set,
coriolis force and centripetal force, g s (q s ,θ s ) In order to be a gravitational torque,
in order to be a friction force, the friction force,
T s in order to control the moment from the robot,
is a function of the coulomb friction coefficient,
is a viscous friction coefficient;
s22: by expanding the system state vector
The slave robot dynamics model is extended to:
wherein, Y s For system output, G s Is an identity matrix, H s ＝[I 0 0 0 0 0]In order to observe the matrix for the states,
and
respectively process noise and measurement noise,
and
respectively representing the change rates of the external environment force, the friction coefficient and the model parameter;
s23: will be derived from the robot dynamics model parameters
And external environment moment T e The variation process of (2) is simulated into a random walk process, namely a Gaussian-Markov chain, and the IEAOB is adopted to estimate the random walk process as follows:
wherein,
wherein,
a corresponding covariance matrix is represented,
representing the corresponding estimate;
wherein,
s24: the external environment torque estimated in the step S23
And from robot dynamics model parameters
The feedback acts on the slave robot model to obtain an accurate slave robot dynamics model of
Wherein
Further, in step S3, an IEAOB is used to disturb the network torque T at the main robot end d And from robot dynamics model parameters
The estimation is performed, the specific steps are similar to steps S21, S22, S23 and S24, except that the estimation of the external environment torque in step S23 is changed to the estimation of the network disturbance torque, and finally the estimated network disturbance torque is obtained as
Further, in step S5, the network disturbance torque estimated in step S3 is processed to obtain a corresponding position signal from the robot dynamics model estimated in step S4
Slave robot position signal with network delay for combining it with feedback
Are superposed to obtain the final feedback position signal of
I.e. to compensate for the adverse effects of network delays.
The invention has the beneficial effects that: compared with the existing network delay control method, the method does not need to rely on a network delay model; meanwhile, the invention also considers the influence of model uncertainty and external environmental noise in the actual robot remote control system, effectively inhibits the influence of the environmental noise, and simultaneously carries out online estimation on system model parameters and realizes accurate estimation and compensation on adverse effects brought by network delay.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention may be realized and attained by the means of the instrumentalities and combinations particularly pointed out hereinafter.
Drawings
For the purposes of promoting a better understanding of the objects, aspects and advantages of the invention, reference will now be made to the following detailed description taken in conjunction with the accompanying drawings in which:
FIG. 1 is a schematic flow chart of a network delay estimation and compensation method of a robot remote control system according to the present invention;
FIG. 2 is a schematic diagram of a network delay estimation and compensation method of the robot remote control system according to the present invention;
FIG. 3 is a conceptual diagram of network disturbance torque in an embodiment of the present invention;
FIG. 4 is a graph of network delay in an embodiment of the present invention;
FIG. 5 is a graph of a parameter estimation from a robot dynamics model in an embodiment of the present invention;
fig. 6 is a graph of position and force estimation and tracking for a robotic remote control system in an embodiment of the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention in a schematic way, and the features in the following embodiments and examples may be combined with each other without conflict.
Referring to fig. 1 to 6, fig. 1 is a flowchart illustrating a method for estimating and compensating a network delay of a robot remote control system, the method including: the first step, generalizing all negative effects caused by time delay to a disturbance moment according to the concept of network disturbance; secondly, estimating parameters of the slave robot model and external environment torque by adopting an IEAOB at the slave robot end to obtain an accurate slave robot dynamic model; thirdly, estimating a network interference torque and a slave robot dynamic model parameter on line by using the IEAOB at the master robot end by using the control torque and a fed back slave robot position signal with network delay; fourthly, acquiring an estimated slave robot dynamics model at the master robot end by utilizing the slave robot model parameters obtained by the IEAOB in the third step; and fifthly, obtaining a corresponding position signal through the estimated network interference torque by the estimated slave robot model, and superposing the position signal and a fed back slave robot position signal with network delay to obtain a position signal without the influence of the network delay, thereby realizing the network delay compensation.
As shown in fig. 2, the network delay estimation and compensation method specifically includes the steps of:
step 1: as shown in FIG. 3, all negative effects of the time delay T are summarized in a disturbance torque T d ：
T d ＝T c (1-e -ts )
Wherein, T c To input a control torque;
step 2: considering the slave robot end, estimating the slave robot dynamic model and the external environment moment by using the IEAOB, and specifically comprising the following steps:
1) determining a robot dynamics model as follows:
wherein
q s For acceleration, velocity and position signals, M s (q s ,θ s ) In order to be the inertia, the inertia is set,
coriolis force and centripetal force, g s (q s ,θ s ) In order to be a gravitational torque,
in order to be a friction force, the friction force,
T s controlling the moment for the slave robot;
2) by expanding the system state vector
The robot dynamics model is extended as:
wherein, Y s For system output, G s Is an identity matrix, H s ＝[I 0 0 0 0 0]In order to observe the matrix for the states,
and
respectively the process noise and the measurement noise,
and
representing the ambient force, the coefficient of friction, and the rate of change of the model parameters.
3) Using robot dynamics model parameters
And external environment moment T e The course of variation of (c) is modeled as a random walk (a gaussian-markov chain) which is estimated using IEAOB as follows:
wherein,
wherein,
a corresponding covariance matrix is represented,
representing the corresponding estimate;
wherein,
4) the external environment torque estimated in the step 3) is used
And learning model parameters
The feedback acts on the slave robot model to obtain an estimated slave robot dynamics model of
Wherein
And step 3: adopting IEAOB to interfere the network torque T at the main robot end d And from robot dynamics model parameters
The estimation is carried out, the specific execution steps are similar to the step (2), and only the outside world is treated in the step (2)Ambient moment T e Is changed to a disturbance torque T on the network d Finally, the estimated network disturbance torque is obtained
And 4, step 4: obtaining an estimated slave robot dynamics model at the master robot end by using the robot model parameters obtained by IEAOB in the step 3, and obtaining corresponding position signals by passing the estimated network interference torque through the slave robot
And 5: subjecting the product obtained in step (4)
Position signal with network delay and feedback
Are superposed to obtain the final feedback position signal of
I.e. to compensate for the adverse effects of network delays.
Example (b):
the network delay estimation and compensation method of the robot remote control system provided by the invention is applied to the robot remote control system with single degree of freedom, namely, the master robot and the slave robot are all one-degree-of-freedom mechanical arm equipment, wherein the slave robot dynamics parameter theta is s ＝M s ＝5.0e-3kgm 2 Coefficient of friction
When the IEAOB of the main robot end is initialized, the dynamic parameters and the initial values of the friction coefficient of the robot are set to be actual values, and when the IEAOB of the slave robot end is initialized, the dynamic parameters and the initial values of the friction coefficient of the robot are set to be 80% of the actual values, namely theta s ＝M s ＝4.0e-3kgm 2 ,
While the environmental object is placed at an angular velocity of 0.2rad/s from the initial origin of the robot. The network delay is chosen as shown in figure 4. By selecting IEAOB parameters as in table 1, the resulting estimated curves from the robot dynamics model parameters and the estimated and tracked curves of the position and force of the robot remote control system are shown in fig. 5 and 6.
Table 1 IEAOB parameters selected in the examples
The experimental result proves the effectiveness of the network delay estimation and compensation method of the robot remote control system, the network delay estimation and compensation method not only well estimates the parameters of the robot dynamic model and inhibits the influence caused by environmental noise, but also well estimates the network interference torque, compensates the adverse influence caused by network delay, and realizes the position tracking of the master robot and the slave robot of the robot remote control system and the tracking of artificial applied force and external environmental force. Meanwhile, the idea of the network delay estimation and compensation method of the robot remote control system can also be expanded to solve the network delay problem of other network control systems.
Finally, the above embodiments are only intended to illustrate the technical solutions of the present invention and not to limit the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions, and all of them should be covered by the claims of the present invention.
Claims (3)
1. A network delay estimation and compensation method of a robot remote control system is characterized by comprising the following steps:
s1: summarizing the time delay T to the disturbance torque T d Performing the following steps;
the time delay t ═ t 1 +t 2 Wherein t is 1 Network communication delay from a master robot end to a slave robot end, namely control channel delay; t is t 2 The method comprises the steps of delaying network communication from a robot end to a main robot end, namely delaying a feedback channel;
the disturbance torque T d ＝T c (1-e -ts )，T c For inputting control torque, s is a Laplace frequency domain transformation symbol;
s2: estimating parameters of a slave robot model and external environment torque T by adopting an extended active observer IEAOB at a slave robot end to obtain an accurate slave robot dynamic model;
in step S2, IEAOB is used at the slave robot end to match the kinetic model parameters of the slave robot
And external environment moment T e And estimating, wherein the specific steps of estimating comprise:
s21: the slave robot dynamics model was determined to be:
wherein, theta s Is the inertial parameter of the robot and is,
q s acceleration, velocity and position signals, M s (q s ,θ s ) In order to be the inertia, the inertia is,
coriolis force and centripetal force, g s (q s ,θ s ) In order to be a gravitational torque,
in order to be a friction force, the friction force,
T s in order to control the moment from the robot,
is a function of the coulomb friction coefficient,
is a viscous friction coefficient;
s22: by expanding the system state vector
The slave robot dynamics model is extended to:
wherein, Y s For system output, G s Is an identity matrix, H s ＝[I 0 0 0 0 0]In order to observe the matrix for the states,
and
respectively process noise and measurement noise,
and
respectively representing the change rates of the external environment force, the friction coefficient and the model parameter;
s23: will be derived from the robot dynamics model parameters
And external environment moment T e The variation process of (2) is simulated into a random walk process, namely a Gaussian-Markov chain, and the IEAOB is adopted to estimate the random walk process as follows:
wherein,
wherein,
a corresponding covariance matrix is represented,
representing the corresponding estimate;
wherein,
s24: the external environment torque estimated in the step S23
And from robot dynamics model parameters
The feedback acts on the slave robot model to obtain an accurate slave robot dynamics model of
Wherein
S3: using control torque T at the main robot end m And fed back slave robot position signals with network delay
On-line estimation of network disturbance torque by IEAOB
And from the robot dynamics model parameters;
s4: acquiring an estimated slave robot dynamics model at the master robot end by using the slave robot model parameters obtained in the step S3;
s5: and obtaining a corresponding position signal by the estimated network interference torque through the estimated slave robot model, and then superposing the position signal and a fed back slave robot position signal with network delay to obtain a position signal without the influence of the network delay, thereby realizing the network delay compensation.
2. The method of claim 1, wherein in step S3, IEAOB is adopted to estimate and compensate the network delay at the master robot end d And from robot dynamics model parameters
Estimating to obtain the estimated network interference torque as
3. A machine according to claim 2The network delay estimation and compensation method of the human remote control system is characterized in that in step S5, the network disturbance moment estimated in step S3 is used for obtaining a corresponding position signal from a robot dynamic model estimated in step S4
Slave robot position signal with network delay for combining it with feedback
Are superposed to obtain the final feedback position signal of
I.e. to compensate for the adverse effects of network delays.
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