CN113021349A - Remote operation control method, device, system, equipment and storage medium - Google Patents
Remote operation control method, device, system, equipment and storage medium Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J13/00—Controls for manipulators
- B25J13/08—Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
- B25J13/087—Controls for manipulators by means of sensing devices, e.g. viewing or touching devices for sensing other physical parameters, e.g. electrical or chemical properties
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1612—Programme controls characterised by the hand, wrist, grip control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1661—Programme controls characterised by programming, planning systems for manipulators characterised by task planning, object-oriented languages
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1679—Programme controls characterised by the tasks executed
- B25J9/1689—Teleoperation
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Abstract
The invention relates to the field of remote operation control, and discloses a remote operation control method, a device, a system, equipment and a computer readable storage medium. The method comprises the steps that surface electromyographic data and inertial measurement data are collected through a control end, the surface electromyographic data and the inertial measurement data are preprocessed respectively to obtain a posture parameter and a posture motion parameter, a target posture motion parameter value is determined according to an interval range to which the posture motion parameter value belongs after the posture motion parameter is obtained, an operation instruction is determined according to the posture parameter, the target posture motion parameter value and a mapping relation between a preset parameter and the operation instruction, and then the operation instruction is sent to an execution end; the execution end receives the operation instruction sent by the control end, and then controls the robot to execute corresponding actions according to the operation instruction; the problem of among the correlation technique remote operation control robot accuracy low is solved.
Description
Technical Field
The present invention relates to the field of remote operation control, and in particular, to a remote operation control method, apparatus, system, device, and computer-readable storage medium.
Background
At present, the development trend of the robot is rapid in a plurality of industrial fields, the robot has good commercial prospect, and along with diversification of application scenes, the robot is urgently required to be controlled by remote operation to complete related operations in special application scenes. In recent years, a series of researches have been conducted on teleoperation control robots, such as telemedicine surgical operation systems based on Virtual Reality technology (VR), control strategy systems based on force/touch technology, and interactive systems based on data gloves, etc. In the related art, the robot is remotely controlled by using the acquired inertial measurement data, but the accuracy of the method is low.
Therefore, how to improve the accuracy of the remote operation control robot is an urgent problem to be solved.
Disclosure of Invention
The invention mainly aims to provide a remote operation control method, a device, a system, equipment and a computer readable storage medium, aiming at improving the accuracy of a remote operation control robot.
In order to achieve the above object, the present invention provides a remote operation control method applied to a control terminal, the remote operation control method comprising the steps of:
collecting surface electromyogram data and inertial measurement data;
preprocessing the surface electromyogram data to obtain a posture parameter;
preprocessing the inertia measurement data to obtain a posture motion parameter, and determining a target posture motion parameter value according to an interval range to which the posture motion parameter value belongs;
determining an operation instruction according to the posture parameter, the target posture motion parameter value and a preset parameter and operation instruction mapping relation; a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values respectively are preset in the preset parameter and operation instruction mapping relation;
and sending the operation instruction to an execution end so that the execution end controls the robot to execute a corresponding action according to the operation instruction.
Optionally, the step of preprocessing the surface electromyography data to obtain a posture parameter includes:
denoising the surface electromyography data to obtain first surface electromyography data; performing feature extraction on the first surface electromyographic data to obtain second surface electromyographic data; performing pattern recognition on the second surface electromyography data to obtain third surface electromyography data, and taking the third surface electromyography data as a posture parameter corresponding to the surface electromyography data;
and/or the presence of a gas in the gas,
the step of preprocessing the inertial measurement data to obtain the posture motion parameters comprises:
performing preset element number conversion on the inertia measurement data to obtain first inertia measurement data; and compensating the first inertia measurement data according to a filtering algorithm to obtain second inertia measurement data, and taking the second inertia measurement data as the posture motion parameters corresponding to the inertia measurement data.
Optionally, the step of determining the target posture motion parameter value according to the interval range to which the posture motion parameter value belongs includes:
acquiring a plurality of interval ranges;
searching the interval range to which the gesture motion parameter value belongs in the plurality of interval ranges;
and acquiring a target value corresponding to the range of the belonged interval, and determining the target value as a target posture motion parameter value.
Optionally, the step of sending the operation instruction to the execution end includes:
judging whether a Bluetooth communication link is established with the execution end;
and if a Bluetooth communication link is established with the execution end, the operation instruction is sent to the execution end through the Bluetooth communication link.
In order to achieve the above object, the present invention provides a remote operation control method applied to an execution end, the remote operation control method including the steps of:
receiving an operation instruction sent by a control end; the operation instruction is that the control end acquires surface electromyogram data and inertial measurement data, the surface electromyogram data is preprocessed to obtain posture parameters, the inertial measurement data is preprocessed to obtain posture motion parameters, target posture motion parameter values are determined according to the range of the posture motion parameter values, and the target posture motion parameter values are determined according to the posture parameters, the target posture motion parameter values and a preset parameter and operation instruction mapping relation, wherein a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values are preset in the preset parameter and operation instruction mapping relation;
and controlling the robot to execute corresponding actions according to the operation instruction.
Optionally, after the step of controlling the robot to execute the corresponding action according to the operation instruction, the remote operation control method further includes:
monitoring whether the robot executes the corresponding action;
if the robot finishes executing the corresponding action, generating execution completion information;
and sending the execution completion information to the control end.
In addition, in order to achieve the above object, the present invention provides a remote operation control device applied to a control terminal, the remote operation control device including:
the acquisition module is used for acquiring surface electromyogram data and inertial measurement data;
the first processing module is used for preprocessing the surface electromyogram data to obtain a posture parameter;
the second processing module is used for preprocessing the inertia measurement data to obtain a posture motion parameter and determining a target posture motion parameter value according to an interval range to which the posture motion parameter value belongs;
the determining module is used for determining an operation instruction according to the posture parameter, the target posture motion parameter value and a preset parameter and operation instruction mapping relation; a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values respectively are preset in the preset parameter and operation instruction mapping relation;
and the sending module is used for sending the operation instruction to an execution end so that the execution end controls the robot to execute the corresponding action according to the operation instruction.
In addition, in order to achieve the above object, the present invention provides a remote operation control apparatus applied to an execution end, the remote operation control apparatus including:
the receiving module is used for receiving an operation instruction sent by the control end; the operation instruction is that the control end acquires surface electromyogram data and inertial measurement data, the surface electromyogram data is preprocessed to obtain posture parameters, the inertial measurement data is preprocessed to obtain posture motion parameters, target posture motion parameter values are determined according to the range of the posture motion parameter values, and the target posture motion parameter values are determined according to the posture parameters, the target posture motion parameter values and a preset parameter and operation instruction mapping relation, wherein a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values are preset in the preset parameter and operation instruction mapping relation;
and the control module is used for controlling the robot to execute corresponding actions according to the operation instructions.
Further, to achieve the above object, the present invention also provides a remote operation control system including:
the control end is used for acquiring surface electromyography data and inertia measurement data; preprocessing the surface electromyogram data to obtain a posture parameter; preprocessing the inertia measurement data to obtain a posture motion parameter, and determining a target posture motion parameter value according to an interval range to which the posture motion parameter value belongs; determining an operation instruction according to the posture parameter, the target posture motion parameter value and a preset parameter and operation instruction mapping relation; a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values respectively are preset in the preset parameter and operation instruction mapping relation; sending the operation instruction to an execution end;
the execution end is used for receiving the operation instruction sent by the control end; and controlling the robot to execute corresponding actions according to the operation instruction.
Further, to achieve the above object, the present invention also provides a remote operation control apparatus including: a memory, a processor and a remote operation control program stored on the memory and running on the processor, the remote operation control program when executed by the processor implementing the steps of the remote operation control method as the above control end or execution end.
Further, to achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a remote operation control program which, when executed by a processor, realizes the steps of the remote operation control method as in the above control terminal or execution terminal.
According to the technical scheme provided by the invention, surface electromyogram data and inertial measurement data are acquired through a control end, the surface electromyogram data and the inertial measurement data are respectively preprocessed to obtain a posture parameter and a posture motion parameter, the posture motion parameter is obtained and then a target posture motion parameter value is determined according to the range of the posture motion parameter value, an operation instruction is further determined according to the posture parameter, the target posture motion parameter value and the mapping relation of a preset parameter and the operation instruction, wherein the mapping relation of the preset parameter and the operation instruction is preset with a plurality of posture parameters and posture motion parameter values, and operation instructions corresponding to the posture parameters and the posture motion parameter values respectively, and then the operation instruction is sent to an execution end; the execution end receives the operation instruction sent by the control end, and then controls the robot to execute corresponding actions according to the operation instruction; the problem of among the correlation technique remote operation control robot accuracy low is solved.
That is, in the technical scheme provided by the invention, the control end combines the surface electromyogram data and the inertial measurement data to jointly determine an operation instruction, and then sends the determined operation instruction to the execution end, and the execution end controls the robot to execute the corresponding action according to the operation instruction; the professional requirement on the operator is not high, the application range is wide, and the method is particularly suitable for special crowds with partial sensory disorder or limb dysfunction; and simultaneously, after the posture motion parameters are obtained, the target posture motion parameter values are determined according to the interval range to which the posture motion parameter values belong, so that the real-time performance of the execution end is higher.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a schematic diagram of a remote operation control device in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a remote operation control method according to a first embodiment of the present invention;
FIG. 3 is a first block diagram of a first embodiment of a remote control device applied to a control end according to the present invention;
FIG. 4 is a second block diagram of the remote control device according to the first embodiment of the present invention;
FIG. 5 is a block diagram showing a first embodiment of a remote operation control apparatus for an execution terminal according to the present invention;
fig. 6 is a block diagram of the remote operation control system according to the first embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a remote operation control device in a hardware operating environment according to an embodiment of the present invention.
The remote operation control apparatus includes: at least one processor 101, a memory 102, and a remote operation control program stored on the memory and executable on the processor, the remote operation control program being configured to implement the steps of the remote operation control method of any one of the following embodiments.
In some embodiments, the remote operation control device may further include: a communication interface 103 and at least one peripheral device. The processor 101, memory 102 and communication interface 103 may be connected by a bus or signal lines. Various peripheral devices may be connected to communication interface 103 via a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of radio frequency circuitry 104, display screen 105, and power supply 106.
The communication interface 103 can be used to connect at least one peripheral device related to I/O (Input/Output) to the processor 101 and the memory 102. In some embodiments, the processor 101, memory 102, and communication interface 103 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 101, the memory 102 and the communication interface 103 may be implemented on a single chip or circuit board, which is not limited in this embodiment of the present invention.
The Radio Frequency circuit 104 is used for receiving and transmitting RF (Radio Frequency) signals, also called electromagnetic signals. The radio frequency circuitry 104 communicates with the communications network and other communicating remotely operated control devices via electromagnetic signals. The rf circuit 104 converts an electrical signal into an electromagnetic signal for transmission, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 104 comprises: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and so forth. The radio frequency circuitry 104 may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocols include, but are not limited to: metropolitan area networks, various generation mobile communication networks (2G, 3G, 4G, and 5G), Wireless local area networks, and/or WiFi (Wireless Fidelity) networks. In some embodiments, the rf circuit 104 may further include NFC (Near Field Communication) related circuits, which are not limited in this application.
The display screen 105 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display screen 105 is a touch display screen, the display screen 105 also has the ability to capture touch signals on or over the surface of the display screen 105. The touch signal may be input to the processor 101 as a control signal for processing. At this point, the display screen 105 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, the display screen 105 may be one, the front panel of the remote operation control device; in other embodiments, the display screens 105 may be at least two, each disposed on a different surface of the remote operation control device or in a folded design; in some embodiments, the display screen 105 may be a flexible display screen, disposed on a curved surface or on a folding surface of the remote operation control device. Even further, the display screen 105 may be arranged in a non-rectangular irregular pattern, i.e. a shaped screen. The Display screen 105 may be made of LCD (liquid crystal Display), OLED (Organic Light-Emitting Diode), and the like.
The power supply 106 is used to supply power to various components in the remote operation control apparatus. The power source 106 may be alternating current, direct current, disposable batteries, or rechargeable batteries. When the power source 106 includes a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the teleoperational control device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
Based on the above hardware structure, embodiments of the present invention are proposed.
Referring to fig. 2, fig. 2 is a schematic flow chart of a remote operation control method according to a first embodiment of the present invention, the remote operation control method includes the following steps:
step S10: the control end collects surface electromyography data and inertia measurement data.
It should be noted that, in the embodiment of the present invention, the surface electromyography data refers to a surface electromyography (sEMG), where the surface electromyography is a cumulative electrical effect of electrical activities on a skin surface layer in a process of completing various limb actions by a human body, and electrical activities in a process of conducting muscle and nerve on a limb surface layer are usually found on a skeletal muscle surface related to movement in a process of active movement of the human body, and are generally recorded by pasting an electrode sheet on the muscle surface. On the premise of obtaining good surface electromyographic signals, comprehensive information such as energy change, frequency band range and the like of the surface electromyographic signals can reflect physiological and mechanism states of tested muscles quantitatively to a great extent, the characteristics of deep mechanism principle are extracted according to signal representation by means of a surface electromyographic signal processing method, muscle movement fatigue degree, limb action mode reconstruction, muscle movement function evaluation and coupling relation of the electromyographic signals and nerve centers can be described effectively, the electromyographic signals can be researched more deeply, the inherent mechanism of neuroscience can be searched, and self recognition of a human body is deepened.
It should be noted that, in the embodiment of the present invention, the inertial measurement data is obtained by combining nodes of the inertial sensor to achieve continuous detection of the motion, where along with the continuous development of the sensor technology, the inertial sensor has a smaller volume, better portability, richer inertial measurement data, and lower power consumption, and the commonly used inertial sensor mainly includes an accelerometer, a gyroscope, a geomagnetic sensor, and the like.
In the embodiment of the invention, the control end can acquire surface electromyogram data and inertia measurement data according to a preset sampling frequency; for example, the control end collects surface electromyogram data and inertial measurement data once every 10ms, wherein the preset sampling frequency can be set by related workers in advance, and in practical application, the preset sampling frequency can be flexibly adjusted according to a specific application scene. Therefore, the control end collects the surface electromyogram data and the inertia measurement data according to the preset sampling frequency, and the flexibility of collecting the surface electromyogram data and the inertia measurement data can be improved; and the resource consumption of the control terminal can be reduced to a certain extent, the electric quantity is saved, and the like.
Step S20: and the control end preprocesses the surface electromyogram data to obtain the posture parameter.
It should be clear that, after the control end acquires the surface electromyography data and the inertial measurement data in the embodiment of the present invention, the surface electromyography data and the inertial measurement data need to be further preprocessed, respectively, so as to obtain corresponding parameters.
In the embodiment of the present invention, the step of preprocessing the surface electromyography data by the control end to obtain the posture parameter may include the following steps:
firstly, denoising surface electromyography data by a control end to obtain first surface electromyography data;
then, the control end performs feature extraction on the first surface electromyographic data to obtain second surface electromyographic data;
and thirdly, performing pattern recognition on the second surface electromyography data by the control end to obtain third surface electromyography data, and taking the third surface electromyography data as a posture parameter corresponding to the surface electromyography data.
It should be clear that, after the control end acquires the surface electromyography data, the control end in the embodiment of the present invention may first perform noise reduction on the surface electromyography data to obtain first surface electromyography data, then perform feature extraction on the first surface electromyography data to obtain second surface electromyography data, and perform pattern recognition on the second surface electromyography data again to obtain third surface electromyography data; and obtaining third surface electromyography data, wherein the obtained third surface electromyography data is a posture parameter corresponding to the surface electromyography data.
In some examples, the step of denoising the surface electromyography data by the control end to obtain first surface electromyography data may include: and the control end utilizes wavelet transformation to perform noise reduction on the surface electromyography data to obtain first surface electromyography data.
It should be clear that Wavelet Transform (WT) is a transform analysis method, which inherits and develops the idea of short-time fourier transform localization, and overcomes the disadvantage that the window size does not change with frequency, etc., and can provide a "time-frequency" window that changes with frequency, and is an ideal tool for signal time-frequency analysis and processing. The method is mainly characterized in that the characteristics of certain aspects of the problem can be fully highlighted through transformation, the time (space) frequency can be locally analyzed, signals (functions) are gradually subjected to multi-scale refinement through telescopic translation operation, finally, high-frequency time subdivision and low-frequency subdivision are achieved, the method can automatically adapt to the requirement of time-frequency signal analysis, accordingly, any details of the signals can be focused, the problem of difficulty of Fourier transformation is solved, and the method becomes a major breakthrough in a scientific method following the Fourier transformation.
Therefore, the control end utilizes wavelet transformation to reduce noise of the collected surface electromyography data, so that first surface electromyography data are obtained, the noise reduction effect can be improved to the greatest extent, and the obtained first surface electromyography data are more accurate.
In some examples, the step of performing feature extraction on the first surface electromyography data by the control terminal to obtain second surface electromyography data may include: and the control terminal extracts amplitude and/or frequency and/or wavelet energy coefficients from the first surface electromyographic data according to a time domain and/or a frequency domain to obtain second surface electromyographic data.
It should be clear that, the control end may extract amplitude and/or frequency and/or wavelet energy coefficient from the first surface electromyography data according to the time domain to obtain second surface electromyography data; or the control end can extract amplitude and/or frequency and/or wavelet energy coefficient from the first surface electromyography data according to the frequency domain to obtain second surface electromyography data; or the control end can extract amplitude and/or frequency and/or wavelet energy coefficients from the first surface electromyography data according to the time domain and the frequency domain to obtain second surface electromyography data.
Therefore, the control end extracts the amplitude and/or frequency and/or wavelet energy coefficient from the first surface electromyography data according to the time domain and/or the frequency domain, so that the second surface electromyography data is obtained, the accuracy of feature extraction can be improved, and the obtained second surface electromyography data is more accurate.
In some examples, the step of performing pattern recognition on the second surface electromyography data by the control terminal to obtain third surface electromyography data may include: and the control end performs pattern recognition on the second surface electromyographic data by using the artificial neural network to obtain third surface electromyographic data.
It should be clear that an Artificial Neural Network (ANN), also referred to as Neural Network or Neural Network for short, abstracts a human brain neuron Network from an information processing perspective, establishes a simple model, and forms different networks according to different connection modes. The artificial neural network is an operational model, which is formed by a large number of nodes (or neurons) connected with each other, each node represents a specific output function called excitation function, and the connection between every two nodes represents a weighted value for a signal passing through the connection called weight, which is equivalent to the memory of the artificial neural network. The output of the network is different according to the connection mode of the network, the weight value and the excitation function.
The control end carries out pattern recognition on the second surface myoelectric data by utilizing the artificial neural network, so that third surface myoelectric data are obtained, the accuracy of pattern recognition can be improved, and the obtained third surface myoelectric data are more accurate.
Step S30: the control end preprocesses the inertia measurement data to obtain a posture motion parameter, and determines a target posture motion parameter value according to an interval range to which the posture motion parameter value belongs.
In the embodiment of the present invention, the step of preprocessing the inertia measurement data by the control end to obtain the posture motion parameter may include the following steps:
firstly, the control end performs preset element number conversion on inertia measurement data to obtain first inertia measurement data;
and then, the control end compensates the first inertia measurement data according to a filtering algorithm to obtain second inertia measurement data, and the second inertia measurement data is used as the posture motion parameters corresponding to the inertia measurement data.
It should be clear that, after the control end acquires the inertia measurement data, the control end in the embodiment of the present invention may first perform preset element number conversion on the inertia measurement data to obtain first inertia measurement data, and then compensate the first inertia measurement data according to a filtering algorithm to obtain second inertia measurement data; wherein the obtained second inertia measurement data is the posture motion parameter corresponding to the inertia measurement data.
In some examples, the control end performs preset element number conversion on the inertia measurement data to obtain a preset element number of the first inertia measurement data, which may be a quaternion, wherein the preset element number may be set in advance by a relevant worker, and in practical applications, the preset element number may be flexibly adjusted according to a specific application scenario.
In some examples, the control terminal compensates the first inertia measurement data according to a filtering algorithm, and the filtering algorithm for obtaining the second inertia measurement data may adopt a kalman filtering algorithm, wherein the filtering algorithm may be set by a relevant worker in advance, and in practical application, the filtering algorithm may be flexibly adjusted according to a specific application scenario.
It should be understood that the wave Kalman filtering algorithm (Kalman filtering) is an algorithm that uses a linear system state equation to optimally estimate the system state by inputting and outputting observation data through the system. Since the observed data includes the influence of noise and interference in the system, the optimal estimation can also be regarded as a filtering process; data filtering is a data processing technique for removing noise and restoring true data, and Kalman filtering can estimate the state of a dynamic system from a series of data with measurement noise under the condition that measurement variance is known.
In the embodiment of the present invention, the step of determining, by the control end, the target posture motion parameter value according to the interval range to which the posture motion parameter value belongs may include the following steps:
firstly, a control end acquires a plurality of interval ranges;
then, searching an interval range to which the posture and motion parameter value belongs in a plurality of interval ranges;
and thirdly, acquiring a target value corresponding to the range of the belonged interval, and determining the target value as a target posture motion parameter value.
It should be clear that, in the embodiment of the present invention, after the control end preprocesses the inertia measurement data to obtain the posture motion parameter, the control end may first obtain a plurality of interval ranges, then search an interval range to which the posture motion parameter value belongs in the plurality of interval ranges, obtain the target value corresponding to the interval range to which the posture motion parameter value belongs again, and determine the target value as the target posture motion parameter value.
It should be noted that, in the embodiment of the present invention, the step of preprocessing the surface electromyogram data by the control end to obtain the posture parameter and the step of preprocessing the inertia measurement data by the control end to obtain the posture motion parameter may be executed in parallel or in any exchange order, which is not specifically limited in this respect.
Step S40: the control end determines an operation instruction according to the posture parameter, the target posture motion parameter value and the mapping relation between the preset parameter and the operation instruction; the preset parameter and operation instruction mapping relation is preset with a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values respectively.
It should be clear that, in the embodiment of the present invention, after the control end respectively preprocesses the surface electromyogram data and the inertial data to obtain corresponding parameters, the control end needs to further determine an operation instruction according to the corresponding parameters and a mapping relationship between preset parameters and the operation instruction.
In the embodiment of the present invention, a mapping relationship between preset parameters and an operation instruction is preset, where the mapping relationship between the preset parameters and the operation instruction is preset with a plurality of posture parameters and posture motion parameter values, and operation instructions corresponding to the posture parameters and the posture motion parameter values, respectively, as shown in table one, which is an exemplary mapping relationship between the preset parameters and the operation instruction.
Watch 1
It is understood that, in the embodiment of the present invention, the gesture parameter includes, but is not limited to, an action type, and accordingly, the corresponding operation instruction is an operation instruction for executing a certain action, the gesture motion parameter includes, but is not limited to, an angle, an acceleration, an amplitude, and the like of a control action, and accordingly, the corresponding operation instruction is an operation instruction for controlling executing a certain action; the action types can be hand lifting, palm clapping, leg kicking and the like, the angles can be 30 degrees, 60 degrees and the like, the acceleration can be 1 m/s & lt 2 & gt and the like, and the action amplitude can be large, moderate, small and the like; in practical application, the gesture parameters, the gesture motion parameters and the operation instructions corresponding to the gesture parameters and the gesture motion parameters can be flexibly adjusted according to specific application scenes.
Step S50: and the control end sends the operation instruction to the execution end.
It should be clear that, in the embodiment of the present invention, after the control end determines the operation instruction according to the posture parameter, the target posture motion parameter value, and the mapping relationship between the preset parameter and the operation instruction, the operation instruction needs to be further sent to the execution end, so that the execution end can control the robot to execute the corresponding action according to the operation instruction.
In the embodiment of the invention, the control end can send the operation instruction to the execution end according to the preset sending rate; for example, the control end sends an operation instruction every 1s, wherein the preset sending rate can be set by related staff in advance, and in practical application, the preset sending rate can be flexibly adjusted according to a specific application scene. Therefore, the control end sends the operation instruction according to the preset sending rate, and the flexibility of sending the operation instruction can be improved.
In some examples, the step of sending the operation instruction to the execution end by the control end may include the following steps:
judging whether a Bluetooth communication link is established with an execution end;
and if a Bluetooth communication link is established with the execution end, the operation instruction is sent to the execution end through the Bluetooth communication link.
That is, the control end can establish a bluetooth communication link with the execution end first, and then send the operation instruction to the execution end through the established bluetooth communication link, so that the transmission of the operation instruction can be realized without the aid of a network, and the transmission is more flexible and simple. The Bluetooth communication link established between the control end and the execution end can be kept for a preset time, so that the system consumption of the Bluetooth communication link established between the control end and the execution end is saved under the condition of frequent operation instruction sending.
Step S60: and the execution end receives the operation instruction sent by the control end.
It should be clear that, in the embodiment of the present invention, the execution end receives the operation instruction sent by the control end.
Step S70: and the execution end controls the robot to execute corresponding actions according to the operation instruction.
It should be clear that, after the execution end receives the operation instruction sent by the control end in the embodiment of the present invention, the robot needs to be further controlled to execute a corresponding action according to the operation instruction; for example, if the received operation command is a hand-up of 30 degrees, the robot performs the hand-up of 30 degrees.
In some examples, after the step of controlling the robot to perform the corresponding action according to the operation instruction, the execution end may further include the following steps:
monitoring whether the robot executes the corresponding action;
if the robot finishes executing the corresponding action, generating execution finishing information;
and sending execution completion information to the control end.
That is, the execution end can monitor whether the robot executes the corresponding action in real time, if the robot executes the corresponding action, the execution completion information is generated, and then the execution completion information is sent to the control end, so that the control end knows that the execution end executes the corresponding action.
In the embodiment of the invention, the control end combines the surface electromyogram data and the inertial measurement data to jointly determine an operation instruction, and then sends the determined operation instruction to the execution end, and the execution end controls the robot to execute the corresponding action according to the operation instruction; the professional requirement on the operator is not high, the application range is wide, and the method is particularly suitable for special crowds with partial sensory disorder or limb dysfunction; and simultaneously, after the posture motion parameters are obtained, the target posture motion parameter values are determined according to the interval range to which the posture motion parameter values belong, so that the real-time performance of the execution end is higher.
In addition, referring to fig. 3, an embodiment of the present invention further provides a remote operation control device applied to a control end based on the remote operation control method, where the remote operation control device includes:
the acquisition module 201 is used for acquiring surface electromyogram data and inertial measurement data;
the first processing module 202 is configured to perform preprocessing on the surface electromyogram data to obtain a posture parameter;
the second processing module 203 is configured to preprocess the inertia measurement data to obtain a posture motion parameter, and determine a target posture motion parameter value according to an interval range to which the posture motion parameter value belongs;
the determining module 204 is configured to determine an operation instruction according to the posture parameter, the target posture motion parameter value, and a mapping relationship between a preset parameter and the operation instruction; the preset parameter and operation instruction mapping relation is preset with a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values respectively;
the sending module 205 is configured to send the operation instruction to the execution end, so that the execution end controls the robot to execute the corresponding action according to the operation instruction.
In the specific implementation, please refer to fig. 4:
the acquisition module 201 may be divided into a first acquisition module and a second acquisition module, wherein:
the first acquisition module is used for acquiring surface electromyogram data, and an RHS series bioelectricity signal acquisition chip of Intan company, an optional 16 channel, a 32 channel, a 64 channel and the like can be adopted, wherein an amplification circuit, a filter circuit and a 16-bit AD conversion circuit for signal processing are integrated in the chip, and the main control chip inputs a corresponding register configuration instruction through SPI communication and acquires the acquired electromyogram data.
The second acquisition module is used for gathering inertial measurement data, and it can adopt ADI's ADIS16505 chip, integrated three-axis digital gyroscope and three-axis digital accelerometer, realizes the data interaction with main control chip through SPI communication.
The first processing module 202, the second processing module 203 and the determination module 204 may be integrated together, and may employ ST STM32L4 series control chips, up to 120MHz at maximum frequency, up to 2MB Flash memory and 640KB SRAM, while including advanced low power analog peripherals such as op-amps, comparators, 12-bit DACs and 16-bit ADCs.
The transmitting module 205 may employ a CC2652 radio frequency controller for TI.
The remote operation control device applied to the control end in the embodiment of the present invention adopts all the technical solutions of all the embodiments described above, so that at least all the beneficial effects brought by the technical solutions of the embodiments described above are achieved, and details are not repeated herein.
In addition, referring to fig. 5, an embodiment of the present invention further provides a remote operation control device applied to an execution end based on the remote operation control method, where the remote operation control device includes:
a receiving module 301, configured to receive an operation instruction sent by a control end; the operation instruction is an operation instruction which is determined by acquiring surface electromyographic data and inertial measurement data by a control end, preprocessing the surface electromyographic data to obtain a posture parameter, preprocessing the inertial measurement data to obtain a posture motion parameter, determining a target posture motion parameter value according to an interval range to which the posture motion parameter value belongs, and determining a preset parameter and operation instruction mapping relation according to the posture parameter, the target posture motion parameter value and the preset parameter and operation instruction mapping relation, wherein a plurality of posture parameters and posture motion parameter values are preset in the preset parameter and operation instruction mapping relation, and each posture parameter and posture motion parameter value respectively correspond to the operation instruction;
and a control module 302, configured to control the robot to execute a corresponding action according to the operation instruction.
The remote operation control device applied to the execution end in the embodiment of the present invention adopts all the technical solutions of all the embodiments described above, so that at least all the beneficial effects brought by the technical solutions of the embodiments described above are achieved, and details are not repeated herein.
In addition, referring to fig. 6, an embodiment of the present invention further provides a remote operation control system based on the remote operation control method, where the remote operation control system includes:
the control end 401 is used for acquiring surface electromyography data and inertial measurement data; preprocessing surface electromyogram data to obtain a posture parameter; preprocessing the inertia measurement data to obtain a posture motion parameter, and determining a target posture motion parameter value according to an interval range to which the posture motion parameter value belongs; determining an operation instruction according to the posture parameter, the target posture motion parameter value and the mapping relation between the preset parameter and the operation instruction; the preset parameter and operation instruction mapping relation is preset with a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values respectively; sending the operation instruction to an execution end;
an execution end 402, configured to receive an operation instruction sent by the control end; and controlling the robot to execute corresponding actions according to the operation instructions.
In the embodiment of the present invention, the remote operation control system adopts all technical solutions of all the embodiments, so that at least all the beneficial effects brought by the technical solutions of the embodiments are achieved, and details are not repeated herein.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, where a remote operation control program is stored on the computer-readable storage medium, and when the remote operation control program is executed by a processor, the steps of the remote operation control method at the control end or the execution end are implemented.
The computer-readable storage media include volatile or nonvolatile, removable or non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, computer program modules or other data. Computer-readable storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically erasable Programmable Read-Only Memory), flash Memory or other Memory technology, CD-ROM (Compact disk Read-Only Memory), Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage, or any other medium which can be used to store the desired information and which can be accessed by a computer.
It will be apparent to one skilled in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (11)
1. A remote operation control method is applied to a control end, and comprises the following steps:
collecting surface electromyogram data and inertial measurement data;
preprocessing the surface electromyogram data to obtain a posture parameter;
preprocessing the inertia measurement data to obtain a posture motion parameter, and determining a target posture motion parameter value according to an interval range to which the posture motion parameter value belongs;
determining an operation instruction according to the posture parameter, the target posture motion parameter value and a preset parameter and operation instruction mapping relation; a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values respectively are preset in the preset parameter and operation instruction mapping relation;
and sending the operation instruction to an execution end so that the execution end controls the robot to execute a corresponding action according to the operation instruction.
2. The remote operation control method according to claim 1, wherein the step of preprocessing the surface electromyography data to obtain a posture parameter comprises:
denoising the surface electromyography data to obtain first surface electromyography data; performing feature extraction on the first surface electromyographic data to obtain second surface electromyographic data; performing pattern recognition on the second surface electromyography data to obtain third surface electromyography data, and taking the third surface electromyography data as a posture parameter corresponding to the surface electromyography data;
and/or the presence of a gas in the gas,
the step of preprocessing the inertial measurement data to obtain the posture motion parameters comprises:
performing preset element number conversion on the inertia measurement data to obtain first inertia measurement data; and compensating the first inertia measurement data according to a filtering algorithm to obtain second inertia measurement data, and taking the second inertia measurement data as the posture motion parameters corresponding to the inertia measurement data.
3. The remote operation control method according to claim 1, wherein the step of determining the target posture motion parameter value based on the section range to which the posture motion parameter value belongs includes:
acquiring a plurality of interval ranges;
searching the interval range to which the gesture motion parameter value belongs in the plurality of interval ranges;
and acquiring a target value corresponding to the range of the belonged interval, and determining the target value as a target posture motion parameter value.
4. The remote operation control method according to any one of claims 1 to 3, wherein the step of transmitting the operation instruction to an execution end includes:
judging whether a Bluetooth communication link is established with the execution end;
and if a Bluetooth communication link is established with the execution end, the operation instruction is sent to the execution end through the Bluetooth communication link.
5. A remote operation control method is applied to an execution end, and comprises the following steps:
receiving an operation instruction sent by a control end; the operation instruction is that the control end acquires surface electromyogram data and inertial measurement data, the surface electromyogram data is preprocessed to obtain posture parameters, the inertial measurement data is preprocessed to obtain posture motion parameters, target posture motion parameter values are determined according to the range of the posture motion parameter values, and the target posture motion parameter values are determined according to the posture parameters, the target posture motion parameter values and a preset parameter and operation instruction mapping relation, wherein a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values are preset in the preset parameter and operation instruction mapping relation;
and controlling the robot to execute corresponding actions according to the operation instruction.
6. The remote operation control method according to claim 5, wherein after the step of controlling the robot to perform the corresponding action according to the operation instruction, the remote operation control method further comprises:
monitoring whether the robot executes the corresponding action;
if the robot finishes executing the corresponding action, generating execution completion information;
and sending the execution completion information to the control end.
7. A remote operation control apparatus, applied to a control terminal, comprising:
the acquisition module is used for acquiring surface electromyogram data and inertial measurement data;
the first processing module is used for preprocessing the surface electromyogram data to obtain a posture parameter;
the second processing module is used for preprocessing the inertia measurement data to obtain a posture motion parameter and determining a target posture motion parameter value according to an interval range to which the posture motion parameter value belongs;
the determining module is used for determining an operation instruction according to the posture parameter, the target posture motion parameter value and a preset parameter and operation instruction mapping relation; a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values respectively are preset in the preset parameter and operation instruction mapping relation;
and the sending module is used for sending the operation instruction to an execution end so that the execution end controls the robot to execute the corresponding action according to the operation instruction.
8. A remote operation control apparatus, applied to an execution terminal, comprising:
the receiving module is used for receiving an operation instruction sent by the control end; the operation instruction is that the control end acquires surface electromyogram data and inertial measurement data, the surface electromyogram data is preprocessed to obtain posture parameters, the inertial measurement data is preprocessed to obtain posture motion parameters, target posture motion parameter values are determined according to the range of the posture motion parameter values, and the target posture motion parameter values are determined according to the posture parameters, the target posture motion parameter values and a preset parameter and operation instruction mapping relation, wherein a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values are preset in the preset parameter and operation instruction mapping relation;
and the control module is used for controlling the robot to execute corresponding actions according to the operation instructions.
9. A remote operation control system, characterized in that the remote operation control system comprises:
the control end is used for acquiring surface electromyography data and inertia measurement data; preprocessing the surface electromyogram data to obtain a posture parameter; preprocessing the inertia measurement data to obtain a posture motion parameter, and determining a target posture motion parameter value according to an interval range to which the posture motion parameter value belongs; determining an operation instruction according to the posture parameter, the target posture motion parameter value and a preset parameter and operation instruction mapping relation; a plurality of posture parameters and posture motion parameter values and operation instructions corresponding to the posture parameters and the posture motion parameter values respectively are preset in the preset parameter and operation instruction mapping relation; sending the operation instruction to an execution end;
the execution end is used for receiving the operation instruction sent by the control end; and controlling the robot to execute corresponding actions according to the operation instruction.
10. A remote operation control apparatus characterized by comprising: memory, a processor and a teleoperational control program stored on the memory and running on the processor, the teleoperational control program when executed by the processor implementing the steps of the teleoperational control method of any of claims 1 to 4 or claims 5 to 6.
11. A computer-readable storage medium, characterized in that a remote operation control program is stored thereon, which when executed by a processor implements the steps of the remote operation control program according to any one of claims 1 to 4 or claims 5 to 6.
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Application publication date: 20210625 |