CN111956449A - Exoskeleton rehabilitation treatment device for shoulder-elbow joint injury and control system thereof - Google Patents
Exoskeleton rehabilitation treatment device for shoulder-elbow joint injury and control system thereof Download PDFInfo
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- 206010060820 Joint injury Diseases 0.000 title claims abstract description 24
- 210000000323 shoulder joint Anatomy 0.000 claims abstract description 16
- 238000001914 filtration Methods 0.000 claims abstract description 13
- 230000033001 locomotion Effects 0.000 claims abstract description 7
- 238000006243 chemical reaction Methods 0.000 claims abstract description 5
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- 230000005540 biological transmission Effects 0.000 claims description 11
- 230000009467 reduction Effects 0.000 claims description 9
- 210000002310 elbow joint Anatomy 0.000 claims description 8
- 238000000034 method Methods 0.000 claims description 8
- 238000011176 pooling Methods 0.000 claims description 6
- 238000002560 therapeutic procedure Methods 0.000 claims description 5
- 238000013527 convolutional neural network Methods 0.000 claims description 4
- 210000000245 forearm Anatomy 0.000 claims description 4
- 230000001133 acceleration Effects 0.000 claims description 3
- 230000036544 posture Effects 0.000 claims description 3
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- 206010058031 Joint adhesion Diseases 0.000 description 1
- 208000020550 Joint related disease Diseases 0.000 description 1
- 206010023230 Joint stiffness Diseases 0.000 description 1
- 206010034464 Periarthritis Diseases 0.000 description 1
- 208000024288 Rotator Cuff injury Diseases 0.000 description 1
- 208000018286 Shoulder injury Diseases 0.000 description 1
- 208000006011 Stroke Diseases 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 210000003484 anatomy Anatomy 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
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- 201000010603 frozen shoulder Diseases 0.000 description 1
- 230000036541 health Effects 0.000 description 1
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- 210000003205 muscle Anatomy 0.000 description 1
- 231100000878 neurological injury Toxicity 0.000 description 1
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- 210000001364 upper extremity Anatomy 0.000 description 1
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- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H1/00—Apparatus for passive exercising; Vibrating apparatus; Chiropractic devices, e.g. body impacting devices, external devices for briefly extending or aligning unbroken bones
- A61H1/02—Stretching or bending or torsioning apparatus for exercising
- A61H1/0274—Stretching or bending or torsioning apparatus for exercising for the upper limbs
- A61H1/0281—Shoulder
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- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1124—Determining motor skills
- A61B5/1125—Grasping motions of hands
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- A63B23/00—Exercising apparatus specially adapted for particular parts of the body
- A63B23/035—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously
- A63B23/12—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for upper limbs or related muscles, e.g. chest, upper back or shoulder muscles
- A63B23/1245—Primarily by articulating the shoulder joint
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
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- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
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- A61H2201/5023—Interfaces to the user
- A61H2201/5035—Several programs selectable
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H2230/00—Measuring physical parameters of the user
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- A61H2230/625—Posture used as a control parameter for the apparatus
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Abstract
The invention discloses an exoskeleton rehabilitation treatment device for shoulder-elbow joint injury and a control system thereof, wherein the exoskeleton rehabilitation treatment device mainly comprises a wearable exoskeleton, a three-axis moving platform and an equipment base platform; the control system mainly comprises a single chip microcomputer, a driver, a motor, a serial port conversion module and an industrial personal computer, and the operation principle of the control system comprises the acquisition and filtering of signals such as force and attitude and the like, the construction of a one-dimensional convolution neural network and the impedance continuous control based on movement intention identification. The invention provides a novel efficient, stable, individual and convenient rehabilitation mode for shoulder joint diseases, is more expected to change the existing orthopedic rehabilitation mode and resource layout, and creates greater social and economic values.
Description
Technical Field
The invention relates to an exoskeleton rehabilitation treatment device for shoulder, elbow and joint injury and a control system thereof, belonging to the field of medical rehabilitation.
Background
Common shoulder joint diseases, such as frozen shoulder and rotator cuff injuries, usually require continuous medical and rehabilitation exercises at specific stages to treat or prevent shoulder joint adhesion, joint stiffness, muscle strength decline, etc. to improve prognosis. Traditional rehabilitation therapy models require one-to-one manual interaction of the patient with the rehabilitation practitioner. However, the rehabilitation mode is easily affected by subjective factors of rehabilitation doctors, and the high-platform centralized doctor distribution also makes the rehabilitation of orthopedic and sports medicine related diseases difficult to popularize, and finally leads to the increase of the incidence rate of adverse sequelae of the diseases.
Compared with manual treatment, the robot device is not easy to fatigue, so that the treatment time can be remarkably prolonged. Therefore, if the rehabilitation robot is integrated into rehabilitation therapy, the rehabilitation efficiency is expected to be improved. In addition, the exoskeleton rehabilitation robot is provided with a digital diagnosis and evaluation system, so that a clinician can be helped to more accurately and objectively monitor the condition of the patient in real time, and accordingly, the rehabilitation stage of the patient is judged. More importantly, the rehabilitation robot can be widely placed in various primary hospitals, and patients can perform rehabilitation exercises from upper-level hospitals to nearby community health hospitals by means of the robot after visiting a doctor, so that the rehabilitation resource layout is optimized under the condition of not changing the distribution of existing rehabilitation doctors, and the popularization of rehabilitation treatment is improved.
However, most of the current exoskeleton designs are applied to rehabilitation of stroke patients with neurological injuries, and exoskeleton application in the fields of orthopedics and sports medicine is rarely researched. Therefore, the invention proposes to design and construct a novel exoskeleton rehabilitation robot, aiming at different shoulder joint diseases and different rehabilitation stages, and simultaneously providing a large amount of strengthened training in a continuous mode in an individualized way precisely according to the requirements of patients. If the project can be successfully implemented, a novel efficient, stable, individual and convenient rehabilitation mode is hopeful to be provided for shoulder joint diseases, and the existing orthopedic rehabilitation mode and resource layout are hopeful to be changed, so that the overall prognosis of the diseases is further improved, and a great social and economic value is created.
Disclosure of Invention
In order to achieve the effect, the technical scheme adopted by the invention is as follows:
an exoskeleton rehabilitation treatment device for shoulder-elbow joint injury comprises a wearable exoskeleton, a three-axis moving platform and an equipment base platform, wherein the wearable exoskeleton is installed on the three-axis moving platform;
the wearable exoskeleton comprises a back structure, a shoulder structure, a large arm structure, an elbow structure, a small arm structure and a hand structure; the back structure comprises a mobile platform mounting plate, a linear bearing, a motor reducer mounting part, a limiting spring and a limiting ring; the shoulder structure comprises a motor reducer long connecting piece and a motor reducer short connecting piece; the large arm structure comprises a large arm upper component and a large arm lower part; the small arm structure comprises a small arm upper component, a small arm lower component, a steering engine, a two-connecting-rod transmission mechanism at the output end of the steering engine, a double-rocker four-connecting-rod mechanism, a two-connecting-rod mechanism, a steering engine mounting component and a hand connecting piece; the back structure, the shoulder structure, the large arm structure, the elbow structure and the small arm structure are connected with the M4 screw through the motor reducer mounting part in sequence;
the motor reducer mounting component is fixed on the back structure through an M4 screw, the limiting spring is sleeved on a shaft extending out of the limiting ring, and a contact end of the limiting spring is welded and fixed with the limiting ring; the motor reducer long connecting piece and the motor reducer short connecting piece are connected with an M4 screw through a motor reducer mounting part; the upper large arm component and the lower large arm component are fixed in place through an M4 bolt after being adjusted; the upper small arm component and the lower small arm component are fixed through an M4 bolt after being adjusted in place; the steering engine is connected with the small arm component through an M3 bolt, the two-link transmission mechanism at the output end of the steering engine is connected with the steering engine through an M3 bolt, the two-rocker four-link mechanism is connected with the two-link transmission mechanism at the output end of the steering engine through a pin shaft with flat keys at two ends, the two-link mechanism is connected with the two-rocker four-link mechanism through a pin shaft and a small bearing, the steering engine mounting component is connected with the two-link mechanism through an M6 bolt, the steering engine mounting component is connected with the steering engine through an M3 bolt, and the hand connecting piece is connected with the output end of the steering engine through an M3 bolt.
A control system of an exoskeleton rehabilitation treatment device for shoulder-elbow joint injury comprises a single chip microcomputer, a driver, a motor, a serial port conversion module and an industrial personal computer; each single chip microcomputer is connected with 5 drivers and motors, and the single chip microcomputers communicate with the drivers and the motors through a CAN; the single chip microcomputer is communicated with an industrial personal computer through a USB-to-serial port module and stores and processes information.
A control method of a control system of an exoskeleton rehabilitation therapy device for shoulder-elbow joint injury, comprising the following steps:
s1: acquiring real-time force sensor signals and joint angles of postures during motion control, and filtering the signals by adopting a Kalman filtering algorithm;
s2: constructing a one-dimensional convolution neural network according to different joint measuring forces and rotation angles measured by an encoder of the motor to estimate the moment of the non-joint position;
s3: calculating based on the estimated joint moment, converting the moment into hand force through a Jacobian matrix so as to calculate hand speed and acceleration, calculating the hand force through an impedance control algorithm so as to calculate the moment required by the motor, and performing continuous moment control.
Preferably, the kalman filtering algorithm has the formula:
in the formula, the first step is that,
and
respectively the estimated state and the predicted estimated state at time k,
and
respectively the state covariance matrix and the prediction covariance matrix at time K, KkAnd expressing a Kalman filtering gain matrix at the k moment, wherein Q is a covariance matrix of system noise, and R is a covariance matrix of observation noise.
Preferably, the one-dimensional convolutional neural network; the leftmost side is an input sequence, input signals are seven groups of force sensor signals and five groups of attitude angles respectively, the input signals pass through a first convolution layer, pass through two groups of constructed 128 filters with the size of 1 multiplied by 3, and then pass through a pooling layer for dimensionality reduction; the signals after dimensionality reduction enter a second convolution layer, and are subjected to dimensionality reduction through a pooling layer after passing through two groups of 256 filters with the number of 1 multiplied by 3; finally, outputting after full connection to obtain seven groups of corresponding joint moments.
Has the advantages that:
1) the invention starts with human anatomy in terms of mechanical design, and creatively manufactures and designs the multi-freedom-degree upper limb rehabilitation exoskeleton which can adapt to most shoulder joint diseases and is safe, reliable and comfortable to wear.
2) The invention adopts Kalman filtering algorithm in signal processing to realize smooth transmission of force sensor and position data.
3) The invention constructs force sensor signals, attitude angle input and seven groups of joint torque output to train a convolutional neural network, and realizes active movement intention recognition.
4) According to the exoskeleton rehabilitation robot, accurate active following and rehabilitation movement is realized through virtual force conversion and an impedance control algorithm, the exoskeleton rehabilitation robot suitable for shoulder joint related disease rehabilitation is creatively constructed, an efficient, convenient and quick rehabilitation treatment mode is hopefully provided for various shoulder joint diseases, the possibility of applying the exoskeleton rehabilitation robot to orthopedic related diseases is explored, effective theoretical and practical bases are provided, and rich medical science and social values are created.
Drawings
Fig. 1 is a schematic structural diagram of an overall exoskeleton rehabilitation device for treating shoulder and elbow joint injuries, which is disclosed by the invention;
fig. 2 is a partial structure schematic diagram of an exoskeleton rehabilitation device for treating shoulder and elbow joint injuries, which is disclosed by the invention;
fig. 3 is a partial structural schematic view of an exoskeleton rehabilitation device for treating shoulder and elbow joint injuries, which is disclosed by the invention;
fig. 4 is a partial structural schematic view of an exoskeleton rehabilitation device for treating shoulder and elbow joint injuries, disclosed by the invention;
fig. 5 is a partial structural schematic view of an exoskeleton rehabilitation device for treating shoulder and elbow joint injury, in accordance with the present invention;
fig. 6 is a block diagram of a control system of an exoskeleton rehabilitation device for treating shoulder-elbow joint injury according to the invention;
fig. 7 is a functional diagram of a control system of the exoskeleton rehabilitation device for shoulder-elbow joint injury according to the invention;
fig. 8 is a functional diagram of a control system of the exoskeleton rehabilitation device for shoulder-elbow joint injury according to the present invention;
fig. 9 is a functional diagram of a control system of the exoskeleton rehabilitation device for shoulder-elbow joint injury according to the present invention;
FIG. 10 is a functional block diagram of the control system of the exoskeleton rehabilitation device for shoulder and elbow joint injury according to the present invention;
in the figure: the device comprises a back structure 1, a shoulder structure 2, a large arm structure 3, an elbow structure 4, a small arm structure 5, a platform mounting plate 1.1, a linear bearing 1.2, a motor reducer mounting part 1.3, a limiting spring 1.4, a limiting ring 1.5, a motor reducer long connecting piece 2.1, a motor reducer short connecting piece 2.2, a small arm upper component 5.1, a small arm lower component 5.2, a steering engine 5.3, a steering engine output end two-link transmission mechanism 5.4, a double-rocker four-link mechanism 5.5, a two-link mechanism 5.6, a steering engine mounting component 5.7, a hand connecting piece 5.8 and a hand component 5.9.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in fig. 1-5, an exoskeleton rehabilitation device for treating shoulder-elbow joint injury comprises a wearable exoskeleton, a three-axis moving platform and a device base platform, wherein the wearable exoskeleton is mounted on the three-axis moving platform, and the three-axis moving platform is mounted on the device base platform;
the wearable exoskeleton comprises a back structure 1, a shoulder structure 2, a large arm structure 3, an elbow structure 4, a small arm structure 5 and a hand structure; the back structure comprises a mobile platform mounting plate 1.1, a linear bearing 1.2, a motor reducer mounting part 1.3, a limiting spring 1.4 and a limiting ring 1.5; the shoulder structure comprises a motor reducer long connecting piece 2.1 and a motor reducer short connecting piece 2.2; the large arm structure comprises a large arm upper component and a large arm lower part; the small arm structure comprises a small arm upper component 5.1, a small arm lower component 5.2, a steering engine 5.3, a two-link transmission mechanism 5.4 at the output end of the steering engine, a double-rocker four-link mechanism 5.5, a two-link mechanism 5.6, a steering engine mounting component 5.7 and a hand connecting piece 5.8; the back structure, the shoulder structure, the large arm structure, the elbow structure and the small arm structure are connected with the M4 screw through the motor reducer mounting part in sequence;
the platform mounting plate 1.1 is fixed on a sliding block of an equipment base platform through an M8 screw, the linear bearing 1.2 is fixed on the platform mounting plate 1.1 through an M8 bolt, the motor reducer mounting part 1.3 is fixed on the back structure 1 through an M4 screw, the limiting spring 1.4 is sleeved on a shaft extending out of the limiting ring 1.5, and a contact end of the limiting spring is welded and fixed with the limiting ring 1.5; the motor reducer long connecting piece 2.1 and the motor reducer short connecting piece 2.2 are connected through a motor reducer mounting part 1.3 and an M4 screw; the upper large arm component and the lower large arm component are fixed in place through an M4 bolt after being adjusted; the upper forearm component 5.1 and the lower forearm component 5.2 are fixed by an M4 bolt after being adjusted in place; the steering engine 5.3 is connected with the small arm component through an M3 bolt, the two-link transmission mechanism 5.4 at the output end of the steering engine is connected with the steering engine 5.3 through an M3 bolt, the two-rocker four-link mechanism 5.5 is connected with the two-link transmission mechanism at the output end of the steering engine through a pin shaft with flat keys at two ends 5.4, the two-link mechanism 5.6 is connected with the two-rocker four-link mechanism 5.5 through a pin shaft and a small bearing, the steering engine mounting component 5.7 is connected with the two-link mechanism 5.6 through an M6 bolt, the steering engine mounting component 5.7 is connected with the steering engine 5.3 through an M3 bolt, and the hand connecting component 5.8 is connected with the output end of the steering engine 5.3 through an M3 bolt.
A control system of an exoskeleton rehabilitation treatment device for shoulder-elbow joint injury comprises a single chip microcomputer, a driver, a motor, a serial port conversion module and an industrial personal computer; each single chip microcomputer is connected with 5 drivers and motors, and the single chip microcomputers communicate with the drivers and the motors through a CAN; the single chip microcomputer is communicated with an industrial personal computer through a USB-to-serial port module and stores and processes information.
As shown in fig. 8 to 10, a control method of a control system of an exoskeleton rehabilitation therapy device for shoulder and elbow joint injury comprises the following steps:
s1: acquiring real-time force sensor signals and joint angles of postures during motion control, and filtering the signals by adopting a Kalman filtering algorithm;
s2: constructing a one-dimensional convolution neural network according to different joint measuring forces and rotation angles measured by an encoder of the motor to estimate the moment of the non-joint position;
s3: calculating based on the estimated joint moment, converting the moment into hand force through a Jacobian matrix so as to calculate hand speed and acceleration, calculating the hand force through an impedance control algorithm so as to calculate the moment required by the motor, and performing continuous moment control.
Preferably, the kalman filtering algorithm has the formula:
in the formula, the first step is that,
and
respectively the estimated state and the predicted estimated state at time k,
and
respectively the state covariance matrix and the prediction covariance matrix at time K, KkAnd expressing a Kalman filtering gain matrix at the k moment, wherein Q is a covariance matrix of system noise, and R is a covariance matrix of observation noise.
Preferably, the one-dimensional convolutional neural network; the leftmost side is an input sequence, input signals are seven groups of force sensor signals and five groups of attitude angles respectively, the input signals pass through a first convolution layer, pass through two groups of constructed 128 filters with the size of 1 multiplied by 3, and then pass through a pooling layer for dimensionality reduction; the signals after dimensionality reduction enter a second convolution layer, and are subjected to dimensionality reduction through a pooling layer after passing through two groups of 256 filters with the number of 1 multiplied by 3; finally, outputting after full connection to obtain corresponding seven groups of joint moments
As shown in figure 7, the invention has two independent control modes, namely a remote control assisted rehabilitation mode and an active rehabilitation mode which can identify the condition and the movement intention of a patient, wherein in the assisted rehabilitation mode, a person can set the rotation speed of each motor through a touch screen to realize the forward and reverse rotation of the motor, in the mode, the person can visually see the temperature and the current change of each motor, and the STOP emergency STOP buttons are matched with the exoskeleton arms on the left side and the right side to prevent the patient from being accidentally injured by machinery.
The power supply connected with the control system is 220V alternating current, 12V direct current and 36V direct current are output through the voltage transformation module and the voltage stabilization module, the 12V direct current is used for supplying power to the single chip microcomputer and the industrial personal computer, and the 36V direct current is used for supplying power to the driver and the motor.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and decorations can be made without departing from the invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (5)
1. An exoskeleton rehabilitation treatment device for shoulder-elbow joint injury is characterized by comprising a wearable exoskeleton, a three-axis moving platform and an equipment base platform, wherein the wearable exoskeleton is installed on the three-axis moving platform;
the wearable exoskeleton comprises a back structure (1), a shoulder structure (2), a large arm structure (3), an elbow structure (4), a small arm structure (5) and a hand structure; the back structure comprises a mobile platform mounting plate (1.1), a linear bearing (1.2), a motor reducer mounting part (1.3), a limiting spring (1.4) and a limiting ring (1.5); the shoulder structure comprises a motor reducer long connecting piece (2.1) and a motor reducer short connecting piece (2.2); the large arm structure comprises a large arm upper component and a large arm lower part; the small arm structure comprises a small arm upper component (5.1), a small arm lower component (5.2), a steering engine (5.3), a two-link transmission mechanism (5.4) at the output end of the steering engine, a double-rocker four-link mechanism (5.5), a two-link mechanism (5.6), a steering engine mounting component (5.7) and a hand connecting piece (5.8); the back structure, the shoulder structure, the large arm structure, the elbow structure and the small arm structure are connected with the M4 screw through the motor reducer mounting part in sequence;
the platform mounting plate (1.1) is fixed on a sliding block of an equipment base platform through an M8 screw, the linear bearing (1.2) is fixed on the platform mounting plate (1.1) through an M8 bolt, the motor reducer mounting part (1.3) is fixed on the back structure (1) through an M4 screw, the limiting spring (1.4) is sleeved on a shaft extending out of the limiting ring (1.5) and a contact end of the limiting spring is welded and fixed with the limiting ring (1.5); the motor reducer long connecting piece (2.1) and the motor reducer short connecting piece (2.2) are connected with an M4 screw through a motor reducer mounting part (1.3); the upper large arm component and the lower large arm component are fixed in place through an M4 bolt after being adjusted; the upper forearm component (5.1) and the lower forearm component (5.2) are fixed by M4 bolts after being adjusted in place; the steering engine is characterized in that the steering engine (5.3) is connected with a small arm component through an M3 bolt, a two-link transmission mechanism (5.4) at the output end of the steering engine is connected with the steering engine (5.3) through an M3 bolt, a two-rocker four-link mechanism (5.5) is connected with the two-link transmission mechanism at the output end of the steering engine through a pin shaft (5.4) with flat keys at two ends, the two-link mechanism (5.6) is connected with a small bearing through a pin shaft and the two-rocker four-link mechanism (5.5), a steering engine mounting component (5.7) is connected with the two-link mechanism (5.6) through an M6 bolt, the steering engine mounting component (5.7) is connected with the steering engine (5.3) through an M3 bolt, and a hand connecting piece (5.8) is connected with the output end of the steering engine (5.3) through an M539.
2. A control system of an exoskeleton rehabilitation treatment device for shoulder-elbow joint injury is suitable for claim 1 and is characterized by comprising a single chip microcomputer, a driver, a motor, a serial port conversion module and an industrial personal computer; each single chip microcomputer is connected with 5 drivers and motors, and the single chip microcomputers communicate with the drivers and the motors through a CAN; the single chip microcomputer is communicated with an industrial personal computer through a USB-to-serial port module and stores and processes information.
3. A control method using a control system of an exoskeleton rehabilitation therapy device for shoulder and elbow joint injury as claimed in claim 2, characterized by comprising the steps of:
s1: acquiring real-time force sensor signals and joint angles of postures during motion control, and filtering the signals by adopting a Kalman filtering algorithm;
s2: constructing a one-dimensional convolution neural network according to different joint measuring forces and rotation angles measured by an encoder of the motor to estimate the moment of the non-joint position;
and S3, calculating based on the estimated joint moment, converting the moment into hand force through a Jacobian matrix so as to calculate hand speed and acceleration, calculating the hand force through an impedance control algorithm so as to calculate the moment required by the motor, and performing continuous moment control.
4. A control method according to claim 3, characterized in that said kalman filter algorithm is of the formula:
in the formula, the first step is that,
and
respectively the estimated state and the predicted estimated state at time k,
and
respectively the state covariance matrix and the prediction covariance matrix at time K, KkAnd expressing a Kalman filtering gain matrix at the k moment, wherein Q is a covariance matrix of system noise, and R is a covariance matrix of observation noise.
5. A control method according to claim 3, wherein said one-dimensional convolutional neural network; the leftmost side is an input sequence, input signals are seven groups of force sensor signals and five groups of attitude angles respectively, the input signals pass through a first convolution layer, pass through two groups of constructed 128 filters with the size of 1 multiplied by 3, and then pass through a pooling layer for dimensionality reduction; the signals after dimensionality reduction enter a second convolution layer, and are subjected to dimensionality reduction through a pooling layer after passing through two groups of 256 filters with the number of 1 multiplied by 3; finally, outputting after full connection to obtain seven groups of corresponding joint moments.
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