CN116265200A - Control method for automatically adjusting gait of tripping condition of exoskeleton - Google Patents
Control method for automatically adjusting gait of tripping condition of exoskeleton Download PDFInfo
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- CN116265200A CN116265200A CN202111549698.9A CN202111549698A CN116265200A CN 116265200 A CN116265200 A CN 116265200A CN 202111549698 A CN202111549698 A CN 202111549698A CN 116265200 A CN116265200 A CN 116265200A
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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
- B25J9/0006—Exoskeletons, i.e. resembling a human figure
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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
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- 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
- B25J9/00—Programme-controlled manipulators
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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
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- B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
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Abstract
The invention belongs to the field of robot control, and particularly relates to a control method for automatically adjusting the tripping condition gait of an exoskeleton. The method comprises the following steps: acquiring the data of the wearers collected by the encoder and the pressure sensor; judging the movement state of the wearer according to the wearer data; selecting a control mode according to the movement state of the wearer; and calculating different control amounts of the driver according to different control modes, and controlling the driving motor to control the exoskeleton robot. The invention adopts the joint encoder, the plantar pressure sensor and the toe pressure sensor to collect motion information, and the designed controller can drive the exoskeleton to lift feet to cross obstacles when a wearer gets over by the obstacles, so as to realize the self-balancing function under the condition of tripping.
Description
Technical Field
The invention belongs to the field of robot control, and particularly relates to a control method for automatically adjusting the tripping condition gait of an exoskeleton.
Background
The problem of aging of the population in China is more and more serious, and the population aged 65 years and older accounts for 13.5% according to the 7 th national population census result, namely, the population is about to enter a deep aging society. Cerebral apoplexy is a cerebrovascular disease, is the first cause of disability of adults in China, and increases more than 200 tens of thousands of patients each year. Aging and cerebral apoplexy diseases severely limit the exercise ability of the human body. The exoskeleton is wearable equipment, can assist human body movement, improves the movement capacity of a wearer, and currently, various exoskeleton control methods exist for driving the exoskeleton to achieve the function of assisting the wearer. However, most of the conventional control methods are only suitable for use in unobstructed terrains, and when the control method is stumbled, the control method cannot autonomously restore the balance and fall down. For example, one exoskeleton control method described in patent application CN201910981434.7 cannot solve the problem that when a wearer gets caught by an obstacle, patent application CN202011497152.9 collects information through an infrared device, a photoelectric sensor and an IMU, and assists the wearer in movement, but no control method is described for when a wearer gets caught.
Disclosure of Invention
The invention aims to provide an exoskeleton control method, wherein a person wears an exoskeleton to move, and when the person is stumbled by an obstacle, the exoskeleton robot can automatically restore balance, so that the whole man-machine is prevented from falling down.
The technical scheme adopted by the invention for achieving the purpose is as follows:
the utility model provides a control device for tripping condition gait automatic adjustment of ectoskeleton, installs the encoder in the left and right both sides hip joint of ectoskeleton robot and left and right both sides knee joint department respectively for gather the left and right both sides hip joint angle value and the angular velocity value and the left and right both sides knee joint angle value and the angular velocity value of ectoskeleton robot wearer, install pressure sensor at the plantar and the toe of ectoskeleton robot respectively, be used for gathering the plantar pressure value and the toe pressure value of ectoskeleton robot, encoder and pressure sensor all link to each other with the controller.
A control method for automatic adjustment of a tripping condition gait of an exoskeleton, comprising the steps of:
acquiring the data of the wearers collected by the encoder and the pressure sensor;
judging the movement state of the wearer according to the wearer data;
selecting a control mode according to the movement state of the wearer;
and calculating different control amounts of the driver according to different control modes, and controlling the driving motor to control the exoskeleton robot.
The wearer data includes: the left hip joint angle value, the right hip joint angle value, the left angular velocity value, the right knee joint angle value, the angular velocity value and the plantar pressure value and the toe pressure value of the exoskeleton robot are acquired by the encoder.
The wearer's state of motion includes: a stationary standing state, a walking state, and a stumbling back state.
The method for judging the motion state of the wearer according to the wearer data comprises the following steps:
setting the initial state of the exoskeleton robot to be a static standing state;
when the angular velocity value of any one joint is greater than or equal to a first threshold value, switching the exoskeleton robot to a walking state;
when the exoskeleton robot is in a walking state, and when the angular velocity value of any one joint is greater than or equal to a first threshold value and the toe pressure value is smaller than a second threshold value, the exoskeleton robot keeps in the walking state; when the angular velocity values of the four joints are smaller than a first threshold value, switching the exoskeleton robot to a static standing state; when the angular velocity value of any one joint is greater than or equal to a first threshold value and the toe pressure value is greater than or equal to a second threshold value, switching the exoskeleton robot to a tripping return state;
when the exoskeleton robot is in a tripping return state, the exoskeleton robot keeps the tripping return state when the plantar pressure value is smaller than a third threshold value; and when the plantar pressure value is greater than or equal to a third threshold value, switching the exoskeleton robot to a static standing state.
The control mode includes: a follow-up mode and a power-assisted mode, wherein the follow-up mode is selected when the motion state of the wearer is a static standing state, and the power-assisted mode is selected when the motion state of the wearer is a walking state and a tripping return state.
In the follow-up mode, a wearer actively moves and drives the exoskeleton robot to synchronously move together, and a joint motor of the exoskeleton robot outputs a moment required by the movement of the exoskeleton robot; in the power-assisted mode, the wearer and the exoskeleton robot are driven together, the wearer and the exoskeleton robot form a human-computer whole, and when the driving angle of the human-computer whole joint is inconsistent with the expected angle of the human-computer whole joint, the joint motor of the exoskeleton robot provides required torque.
The follow-up mode adopts a torque PID control method, and specifically comprises the following steps:
carrying out dynamic calculation on the joint angle value and the angular velocity value acquired by the encoder to obtain the actual moment of the joint of the exoskeleton robot, and obtaining the driving moment of the joint of the exoskeleton robot by the controller;
the control quantity of the driver is obtained through calculation of joint moment difference between the actual moment of the joint of the exoskeleton robot and the driving moment of the joint of the exoskeleton robot and the PID control coefficient, and then the driving motor is controlled to control the exoskeleton robot.
The power assisting mode adopts an impedance PID control method, and specifically comprises the following steps:
obtaining a man-machine integral joint driving angle according to the encoder;
obtaining a man-machine integral joint angle difference according to the man-machine integral joint driving angle and the set man-machine integral joint expected angle;
impedance control is carried out on the angle difference of the human-machine integral joint, so that the expected moment of the human-machine integral joint is obtained;
carrying out dynamic calculation on the joint angle value and the angular velocity value acquired by the encoder to obtain a human-machine integral joint driving moment, and calculating to obtain a human-machine integral joint moment difference according to the human-machine integral joint expected moment and the human-machine integral joint driving moment;
and calculating to obtain a driver control quantity according to the man-machine integral joint moment difference and the PID control coefficient, and further controlling the driving motor to control the exoskeleton robot.
When the exoskeleton robot is in a walking state, when the toe collides with an obstacle, the controller detects that the exoskeleton is stumbled by the obstacle when the value of the toe pressure sensor is larger than or equal to a second threshold value, the controller switches the exoskeleton robot to a stumbled return state, the exoskeleton robot starts to lift feet and restore balance, namely, in a set time, the swing side hip joint continues to perform buckling motion, the swing side knee joint continues to perform buckling motion, so that the height of the feet is lifted to be higher than the obstacle, and meanwhile, the angles of the support side hip joint and the knee joint are unchanged;
when the foot is lifted to be higher than the height of the obstacle, the controller controls the foot to move forwards and gradually fall, after the foot on the swinging side is contacted with the ground, the plantar pressure value is gradually increased, when the plantar pressure value is greater than or equal to a third threshold value, the exoskeleton robot is switched to a static standing state, a follow-up control mode is adopted, at the moment, the wearer stops moving, the exoskeleton robot keeps in the static standing state, or the wearer continues to move forwards, and the exoskeleton robot is switched to a walking state.
The invention has the following beneficial effects and advantages:
1. according to the invention, the motion data of a wearer is obtained through the encoder, the plantar pressure sensor and the toe pressure sensor, the wearer is judged to be in a static standing, walking or tripping recovery state according to the motion data of the wearer, and then a corresponding control mode is selected according to the motion state, wherein the control mode comprises the following steps: a follow-up mode and a boost mode.
2. The invention can detect that the exoskeleton is stumbled by the obstacle through the toe pressure sensor, thereby increasing the movement obstacle detection function.
3. The invention provides a control method, which enables an exoskeleton to start to lift feet and cross an obstacle when the exoskeleton is stumbled by the obstacle, and finally achieves a self-balancing function under the stumbled condition.
Drawings
FIG. 1 is a schematic diagram of an exoskeleton robot used in the present invention;
FIG. 2 is a flow chart of an implementation of the exoskeleton control method of the present invention;
FIG. 3 is a schematic diagram of a wearer's movement state switch for the exoskeleton control method of the present invention;
FIG. 4 is a schematic representation of a tripping return state human-machine gesture of the exoskeleton control method of the present invention;
FIG. 5 is a schematic diagram of a system architecture of an exoskeleton control method;
fig. 6 is a control flow diagram of the exoskeleton control method of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
The invention provides an exoskeleton control method, as shown in fig. 2, comprising the following steps:
obtain the wearer data that encoder, plantar pressure sensor and toe pressure sensor gathered, the wearer data include: the left hip joint angle value and the angular velocity value acquired by the encoder, the left knee joint angle value and the angular velocity value acquired by the encoder, the right hip joint angle value and the angular velocity value acquired by the encoder, the right knee joint angle value and the angular velocity value acquired by the encoder, the plantar pressure value acquired by the plantar pressure sensor and the pressure value of the collision part of the exoskeleton toe and the obstacle acquired by the toe pressure sensor;
judging a wearer motion state according to the wearer data, wherein the wearer motion state comprises: a standing still state, a walking state and a tripping return state;
selecting corresponding control modes according to different motion states, wherein the control modes comprise: a follow-up mode and a power-assisted mode, specifically, a follow-up mode is adopted when in a stationary standing state, and a power-assisted mode is adopted when in a walking state and a tripping return state;
transmitting control signals to the driver driving motor according to different control modes to control the exoskeleton;
further, the motion state of the wearer is determined, as shown in fig. 3, specifically:
setting an initial state as a static standing state;
when the left hip joint angular velocity value is greater than or equal to a first threshold value, or the left knee joint angular velocity is greater than or equal to a first threshold value, or the right hip joint angular velocity is greater than or equal to a first threshold value, or the right knee joint angular velocity is greater than or equal to a first threshold value, switching the exoskeleton to a walking state;
when the exoskeleton is in a walking state, the exoskeleton keeps in the walking state when the left hip joint angular velocity value is greater than or equal to a first threshold value, or the left knee joint angular velocity is greater than or equal to the first threshold value, or the right hip joint angular velocity is greater than or equal to the first threshold value, or the right knee joint angular velocity is greater than or equal to the first threshold value, otherwise, the exoskeleton is switched to a static standing state;
when the exoskeleton is in a walking state, the exoskeleton keeps the walking state when the toe pressure value is smaller than a second threshold value, and when the toe pressure value is larger than or equal to the second threshold value, the exoskeleton is switched to a tripping return state,
when the exoskeleton is in a tripping return state, the tripping return state is maintained when the plantar pressure is smaller than a third threshold value, and when the plantar pressure value is larger than or equal to the third threshold value, the exoskeleton is switched to a static standing state.
1) Follow-up mode
In the follow-up mode, the human body actively moves and drives the exoskeleton to synchronously move together, and the motor of the exoskeleton joint outputs the moment required by the movement of the exoskeleton itself.
Further, when the human body drives the exoskeleton to move, the actual moment of the exoskeleton joint is calculated by dynamics. The controller controls the driving moment of the exoskeleton joint to enable the driving moment of the exoskeleton joint to be close to the actual moment of the exoskeleton joint.
Specifically, the follow-up mode adopts a torque PID control method:
and calculating the moment difference of the exoskeleton joints according to the actual moment of the exoskeleton joints and the driving moment of the exoskeleton joints, wherein the actual moment of the exoskeleton joints is obtained by dynamic calculation after data are measured by an encoder.
And calculating to obtain the control quantity of the driver according to the exoskeleton joint moment difference and the PID control coefficient. The PID control coefficient is given by human beings, and the driver control quantity is the driving moment increment of the exoskeleton joint.
And driving the motor to control the exoskeleton according to the driver control quantity.
2) Assistance mode
In the power-assisted mode, the human body and the exoskeleton are driven together, and the human body and the exoskeleton form a human-computer whole. When the driving angle of the human-machine integral joint is inconsistent with the expected angle of the human-machine integral joint, the exoskeleton joint motor provides the required moment.
Further, the expected angle of the human-machine integral joint is given by human and stored in the controller. When the human-machine integral motion is performed, the controller calls the expected angle of the human-machine integral joint, the expected angle is compared with the driving angle of the human-machine integral joint, the angle difference of the human-machine integral joint is obtained, the driving moment increment of the human-machine integral joint is calculated and obtained through an impedance PID control method, and the driving motor is driven to perform motion.
Specifically, the power assisting mode adopts an impedance PID control method:
and calculating the man-machine integral joint angle difference according to the man-machine integral joint expected angle and the man-machine integral joint driving angle, wherein the man-machine integral joint driving angle is measured by an encoder.
And carrying out impedance control according to the angle difference of the human-machine integral joint, and calculating to obtain the expected moment of the human-machine integral joint, wherein the impedance control rigidity coefficient and the impedance control damping coefficient are given by people.
And calculating the moment difference of the human-machine integral joint according to the expected moment of the human-machine integral joint and the driving moment of the human-machine integral joint. The man-machine integral joint driving moment is obtained by dynamic calculation after data are measured by an encoder.
And calculating to obtain the control quantity of the driver according to the moment difference of the human-machine integral joint and the PID control coefficient, wherein the PID control coefficient is given by human. The driver control quantity is the increment of the driving moment of the human-machine integral joint.
And driving the motor to control the exoskeleton by using the control amount of the driver.
Further, the static standing state, the exoskeleton is in a follow-up mode.
Further, in the walking state of the land, the exoskeleton is in a power-assisted mode, the expected angle of the exoskeleton is given by human beings and is stored in the controller, and the exoskeleton is called by the controller when in movement.
Further, in the tripping return state, the exoskeleton is in a power-assisted mode, the expected angle of the exoskeleton is given by human beings and is stored in the controller, the exoskeleton is called by the controller when in motion, and the operation posture is shown in fig. 4. When the exoskeleton is in a walking state, and when the toe collides with an obstacle, and the value of the toe pressure sensor is larger than or equal to a second threshold value, the controller detects that the exoskeleton is stumbled by the obstacle, and switches the exoskeleton to a stumbled recovery state, the exoskeleton starts to lift feet, and balance is restored: at t 1 And in the second time, the swing side hip joint continues to perform buckling movement, the swing side knee joint continues to perform buckling movement, so that the foot height is lifted to be higher than the obstacle, and meanwhile, the angles of the support side hip joint and the knee joint are unchanged.
Specifically, the swing-side hip joint and knee joint continue to flex for a movement time t 1 The second is given by the person, the bending movement angle of the swing side hip joint and the bending movement angle of the swing side knee joint are given by the person, the two are stored in the controller, and the controller calls the two when in movement.
Further, when the foot is lifted to a sufficient height, the controller invokes gait planning manually specified to control the foot to move forward and gradually drop, after the foot on the swing side is contacted with the ground, the plantar pressure value gradually increases, when the plantar pressure value is greater than or equal to a third threshold value, the exoskeleton is switched to a static standing state, a follow-up control mode is adopted, at the moment, the wearer can stop moving, the exoskeleton is kept in the static standing state, the wearer can continue to move forward, and the exoskeleton is switched to a walking state.
Embodiment one:
an embodiment of the invention provides an exoskeleton control method.
Fig. 1 shows an exoskeleton robot used in the present invention, which is designed with straps at the thigh and the shank, and can fix the lower limbs of the human body to the legs of the exoskeleton robot. The two sides of the exoskeleton robot are provided with the hip joints and the knee joints which are provided with the direct current motors, and the motors are provided with the encoders which are used for detecting the motion state. The robot toe is provided with a pressure sensor for detecting collision between the toe and an obstacle and triggering a tripping return state. The sole is provided with a pressure sensor for detecting contact between the swing side and the ground in the tripping return state and triggering termination of the tripping return state. The motor can be driven by the control method provided by the invention, and when a wearer is tripped, the self-balancing function in the tripping condition is provided. An exoskeleton, which can be controlled by the exoskeleton control method according to any one of the embodiments, falls within the scope of the present embodiment.
Fig. 2 is a flowchart of an implementation of an exoskeleton control method, the flowchart including the following steps:
s1: obtain the data of the wearers collected by the encoder, the plantar pressure sensor and the toe pressure sensor,
in this embodiment, the wearer data includes: the left hip joint angle value and the angular velocity value acquired by the encoder, the left knee joint angle value and the angular velocity value acquired by the encoder, the right hip joint angle value and the angular velocity value acquired by the encoder, the right knee joint angle value and the angular velocity value acquired by the encoder, the plantar pressure value acquired by the plantar pressure sensor, and the pressure value at the collision position of the exoskeleton toe acquired by the toe pressure sensor and the obstacle;
s2: judging a wearer motion state according to the wearer data, specifically, the wearer motion state includes: a standing still state, a walking state and a tripping return state;
s3: selecting corresponding control modes according to different motion states, wherein the control modes comprise: a follow-up mode and a power-assisted mode, specifically, a follow-up mode is adopted when in a stationary standing state, and a power-assisted mode is adopted when in a walking state and a tripping return state;
s4: transmitting control signals to the driver driving motor according to different control modes to control the exoskeleton;
fig. 3 is a schematic diagram of switching the movement state of the wearer in the present embodiment, that is, the movement state of the wearer is obtained according to the movement data of the wearer, and as can be seen from the figure, the initial state is set to be a standing state;
when the left hip joint angular velocity value is greater than or equal to the first threshold value f 1 Or the left knee joint angular velocity is greater than or equal to a first threshold f 1 Or the right hip joint angular velocity is greater than or equal to the first threshold f 1 Or the angular velocity of the right knee joint is greater than or equal to a first threshold f 1 When the exoskeleton is in a walking state, the exoskeleton is switched; when the exoskeleton is in a walking state, the left hip joint angular velocity value is greater than or equal to a first threshold value f 1 Or the left knee joint angular velocity is greater than or equal to a first threshold f 1 Or the right hip joint angular velocity is greater than or equal to the first threshold f 1 Or the angular velocity of the right knee joint is greater than or equal to a first threshold f 1 When the exoskeleton is in a walking state, or else, the exoskeleton is switched to a static standing state; when the exoskeleton is in walking state, the toe pressure value is smaller than the second threshold value f 2 While the exoskeleton is kept walking, when the toe pressure value is greater than or equal to the second threshold value f 2 When the exoskeleton is in a tripping return state, the exoskeleton is switched; when the exoskeleton is in a tripping return state, the plantar pressure is smaller than a third threshold f 3 When the plantar pressure value is greater than or equal to the third threshold value f, the tripping return state is maintained 3 And when the exoskeleton is switched to a static standing state.
In the present embodiment, the first threshold f 1 -a third threshold f 3 The values acquired according to the actual actions can reflect that when the wearer is in different motion states, the encoder, the toe pressure sensor and the plantar pressure sensor acquire different values, and the motion state of the wearer, such as a first threshold f, is judged according to the acquired values 1 Alternatively, values between 1 °/s and 5 °/s are used, i.e. when acquisition takes placeIs greater than or equal to a first threshold f 1 When the wearer is in a walking state, the wearer is switched. Second threshold f 2 Optionally a value between 1N and 10N, i.e. when the collected toe pressure of the wearer is greater than or equal to the second threshold f 2 When the user is in a tripping state, the current movement state of the wearer is switched to a tripping return state. Third threshold f 3 Optionally, the total weight of the man-machine is 1-30%, namely, when the man-machine is in a tripping return state, the collected sole pressure of the swing side of the wearer is greater than or equal to a third threshold f 3 And when the wearer is in a standing state, the motion state of the wearer is switched to a static standing state, and the follow-up control mode is entered. The above values are only illustrative, but not limiting, and any judgment value that can judge the movement state of the wearer through the above judgment process can be used as the threshold value in this embodiment.
In step S3, the control mode includes: the follow-up mode and the assist mode, and two specific control modes are as follows.
1) Follow-up mode
In the follow-up mode, the human body actively moves and drives the exoskeleton to synchronously move together, and the motor of the exoskeleton joint outputs the moment required by the movement of the exoskeleton itself.
Further, when the human body drives the exoskeleton to move, the actual moment of the exoskeleton joint is calculated by dynamics, and the driving moment of the exoskeleton joint is controlled, so that the driving moment of the exoskeleton joint is close to the actual moment of the exoskeleton joint.
Specifically, the follow-up mode adopts a torque PID control method:
calculating an exoskeleton joint moment difference according to the actual moment of the exoskeleton joint and the driving moment of the exoskeleton joint, wherein the exoskeleton joint moment difference is expressed as:
e ET ＝T Ea -T Ed (1)
wherein e ET Representing the moment difference of exoskeleton joints, T Ea Representing the actual moment of the exoskeleton joint, measuring data by an encoder, and then performing kinetic calculation to obtain T Ed Representing the exoskeleton joint drive moment.
Combined with exoskeleton joint moment difference e ET And PID control coefficient calculation to obtain drive control quantity, expressed as:
wherein ≡e ET Dt represents the integral of the exoskeleton joint moment difference,
differential, k, representing exoskeleton joint moment differences p 、k i 、k d Represents PID control coefficients, respectively proportional, integral and differential coefficients of PID control, which can be obtained through experimental data fitting, and u represents the control quantity of the driver, namely the driving moment increment delta T of the exoskeleton joint Ed 。
And driving the motor to control the exoskeleton by using the control quantity of the driver.
2) Assistance mode
In the power-assisted mode, the human body and the exoskeleton are driven together, and the human body and the exoskeleton form a human-computer whole. When the driving angle of the human-machine integral joint is inconsistent with the expected angle of the human-machine integral joint, the exoskeleton joint motor provides the required moment.
Further, the expected angle of the human-machine integral joint is given by human and stored in the controller. When the human-machine integral motion is performed, the controller calls the expected angle of the human-machine integral joint, the expected angle is compared with the driving angle of the human-machine integral joint, the angle difference of the human-machine integral joint is obtained, the driving moment increment of the human-machine integral joint is calculated and obtained through an impedance PID control method, and the driving motor is driven to perform motion.
Specifically, the power assisting mode adopts an impedance PID control method:
calculating a man-machine overall joint angle difference according to the man-machine overall joint expected angle and the man-machine overall joint driving angle, wherein the man-machine overall joint angle difference is expressed as:
e Mq ＝q Ms -q Md (3)
wherein e Mq Represents the angle difference of the human-machine integral joint, q Ms The expected angle of the human-machine integral joint is expressed and is manually specified and stored in a controller, q Md The driving angle of the human-machine integral joint is represented and measured by an encoder.
According to the angle difference e of the human-machine integral joint Mq Impedance control is performed, and the expected moment of the whole joint of the human machine is calculated and expressed as:
wherein T is Ms The expected moment of the human-machine integral joint is represented,
differential representing angle difference of human-machine integral joint, a i Representing the impedance control stiffness coefficient, b i The impedance control damping coefficient is represented, and the impedance control stiffness coefficient and the impedance control damping coefficient can be obtained through fitting experimental data.
According to the expected moment T of the human-machine integral joint Ms And the man-machine integral joint driving moment calculates man-machine integral joint moment difference, expressed as:
e MT ＝T Ms -T Md (5)
wherein e MT Representing the moment difference of the human-machine integral joint, T Md The driving moment of the human-machine integral joint is represented, and the driving moment is obtained by dynamic calculation after the data is measured by an encoder.
According to the moment difference e of the human-machine integral joint MT And PID control coefficients, calculating a drive control amount expressed as:
wherein ≡e MT Dt represents the integral of the man-machine total joint moment difference,
the differential of the moment difference of the human-machine integral joint is represented,k p 、k i 、k d the PID control coefficients are respectively proportional, integral and differential coefficients of PID control, and can be obtained through fitting experimental data, and u represents the control quantity of the driver, and is here the driving moment increment delta T of the human-machine integral joint Md 。
And driving the motor to control the exoskeleton by using the control quantity of the driver.
FIG. 4 is a schematic representation of a tripping return state human-machine gesture of an exoskeleton control method.
When the exoskeleton is in a walking state, the exoskeleton is in a power-assisted mode, the expected angle of the human-machine integral joint is given by human, the human-machine integral joint is stored in the controller, and the human-machine integral joint is called by the controller during movement. When the toe collides with the obstacle, the value of the toe pressure sensor is greater than or equal to a second threshold f 2 When the controller detects that the exoskeleton is stumbled by an obstacle, the controller switches the exoskeleton to a stumbled return state, and the exoskeleton starts to lift feet to restore balance:
setting the moment of the tripping return state at the beginning to be t 0 At this time, the swing side hip joint flexion angle is θ h0 The knee joint on the swing side has a bending angle theta k0 At t 1 In the second time, the swing side hip joint continues to perform buckling movement, and the movement angle is theta h1 The knee joint at the swing side continues to perform buckling movement, and the movement angle is theta k1 The foot is lifted to be higher than the obstacle, the angles of the hip joint and the knee joint at the supporting side are unchanged, and the moment is t 2 ：
t 2 ＝t 0 +t 1
t 2 At the moment, the swing side hip joint flexion angle is θ h2 ：
θ h2 ＝θ h0 +θ h1
t 2 At the moment, the knee joint on the swing side has a bending angle θ k2 ：
θ k2 ＝θ k0 +θ k1
Trip return state start time t 0 Calibrated by a controller, can be set to 0s, and the flexion angle theta of the swing side hip joint h0 Sum pendulumFlexion angle theta of knee joint on dynamic side k0 The time t of the continued buckling movement of the swing side hip joint and the knee joint is acquired by an encoder 1 The second is given by human, and the swing side hip joint continues to perform the buckling movement angle theta h1 And the knee joint at the swinging side continues to perform buckling movement angle theta k1 Is given by man.
After the flexion movement of the swing side hip joint and the knee joint is finished, the time reaches t 2 At that point, the foot has been raised to a sufficient height and the controller invokes the human prescribed gait program to move the foot forward and gradually drop.
t 3 At that moment, the swing leg passes over the obstacle.
When the swing side foot is contacted with the ground, the plantar pressure value is gradually increased, and when the plantar pressure value is larger than or equal to the third threshold value f 3 At this time, let t be 4 The exoskeleton is switched to a static standing state, and a follow-up control mode is adopted. At this time, the wearer stops moving, and the exoskeleton remains in a static standing state; or the wearer continues to move forward and the exoskeleton switches to the walking state.
Fig. 5 is a schematic diagram of a system structure of the present embodiment, which includes an encoder 01, a toe pressure sensor 02, a sole pressure sensor 03, a controller 04, a driver 05 and a motor 06, where the encoder 01, the toe pressure sensor 02 and the sole pressure sensor 03 collect data of a wearer in real time, the controller 04 acquires the collected data and determines a movement state of the wearer, switches the movement state of the wearer, and correspondingly matches different control modes at the same time, when the wearer is in a standing still state, the exoskeleton control selects a follow-up mode, when the wearer is in a walking or tripping return state, the power-assisted mode is selected, and the driver control amount in the different control modes is sent to the driver 05 to drive the motor 06 to move so as to realize closed-loop control of the exoskeleton.
As shown in fig. 6, a control flow chart of the present embodiment is shown, firstly, data of the wearer is collected, and the movement state of the wearer is determined.
If the robot is in a static standing state currently, the robot is controlled in a follow-up mode, namely according to the actual moment of the exoskeleton jointT Ea Driving moment T of exoskeleton joint Ed Calculating exoskeleton joint moment difference e ET According to the moment difference e of the exoskeleton joint ET And PID control is carried out on the PID control coefficient, the driver control quantity u is obtained through calculation, the motor is driven according to the driver control quantity u, and the control of the exoskeleton is realized.
If the man-machine integral joint is in a walking or tripping return state, the man-machine integral joint enters a power assisting mode, namely according to the expected angle q of the man-machine integral joint Ms And a man-machine integral joint driving angle q Md Calculating the rotation angle error e of the whole joint of the human-machine Mq Then impedance control is carried out, namely the expected moment T of the human-machine integral joint is calculated Ms According to the expected moment T of the human-machine integral joint Ms And a man-machine integral joint driving moment T Md Calculating the moment difference e of the whole joint of the human machine MT According to the moment difference e of the human-machine integral joint MT And PID control is carried out on the PID control coefficient, the driver control quantity u is obtained through calculation, the motor is driven according to the driver control quantity u, and the control of the exoskeleton is realized.
The invention adopts the joint encoder, the plantar pressure sensor and the toe pressure sensor to collect motion information, and the designed controller can drive the exoskeleton to lift feet and surmount obstacles when a wearer gets over by the obstacles, so as to realize the self-balancing function under the condition of tripping.
Claims (10)
1. The control device for automatically adjusting the gait of the tripping condition of the exoskeleton is characterized in that encoders are respectively arranged at the left hip joint, the right hip joint, the left knee joint and the right knee joint of the exoskeleton robot and used for acquiring the angle value and the angular velocity value of the left hip joint and the right hip joint and the angle value and the angular velocity value of the left knee joint and the right knee joint of a wearer of the exoskeleton robot, pressure sensors are respectively arranged at the sole and the toe of the exoskeleton robot and used for acquiring the sole pressure value and the toe pressure value of the exoskeleton robot, and the encoders and the pressure sensors are connected with a controller.
2. A control method for automatic adjustment of a tripping condition gait of an exoskeleton, comprising the steps of:
acquiring the data of the wearers collected by the encoder and the pressure sensor;
judging the movement state of the wearer according to the wearer data;
selecting a control mode according to the movement state of the wearer;
and calculating different control amounts of the driver according to different control modes, and controlling the driving motor to control the exoskeleton robot.
3. A control method for automatic adjustment of a tripping condition gait of an exoskeleton according to claim 2, wherein said wearer data comprises: the left hip joint angle value, the right hip joint angle value, the left angular velocity value, the right knee joint angle value, the angular velocity value and the plantar pressure value and the toe pressure value of the exoskeleton robot are acquired by the encoder.
4. A control method for automatic adjustment of a tripping condition gait of an exoskeleton according to claim 2, wherein the wearer's movement state comprises: a stationary standing state, a walking state, and a stumbling back state.
5. A control method for automatic adjustment of the tripping situation gait of an exoskeleton according to claim 2 or 3, characterized in that said determining the movement state of the wearer according to the wearer data is specifically:
setting the initial state of the exoskeleton robot to be a static standing state;
when the angular velocity value of any one joint is greater than or equal to a first threshold value, switching the exoskeleton robot to a walking state;
when the exoskeleton robot is in a walking state, and when the angular velocity value of any one joint is greater than or equal to a first threshold value and the toe pressure value is smaller than a second threshold value, the exoskeleton robot keeps in the walking state; when the angular velocity values of the four joints are smaller than a first threshold value, switching the exoskeleton robot to a static standing state; when the angular velocity value of any one joint is greater than or equal to a first threshold value and the toe pressure value is greater than or equal to a second threshold value, switching the exoskeleton robot to a tripping return state;
when the exoskeleton robot is in a tripping return state, the exoskeleton robot keeps the tripping return state when the plantar pressure value is smaller than a third threshold value; and when the plantar pressure value is greater than or equal to a third threshold value, switching the exoskeleton robot to a static standing state.
6. A control method for automatic adjustment of a stumbling gait of an exoskeleton according to claim 2 or 4, wherein said control mode comprises: a follow-up mode and a power-assisted mode, wherein the follow-up mode is selected when the motion state of the wearer is a static standing state, and the power-assisted mode is selected when the motion state of the wearer is a walking state and a tripping return state.
7. The control method for automatic adjustment of the tripping condition gait of the exoskeleton of claim 6, wherein in said follow-up mode, the wearer actively moves and brings the exoskeleton robot together to move synchronously, and the joint motor of the exoskeleton robot outputs the torque required for the exoskeleton robot to move itself; in the power-assisted mode, the wearer and the exoskeleton robot are driven together, the wearer and the exoskeleton robot form a human-computer whole, and when the driving angle of the human-computer whole joint is inconsistent with the expected angle of the human-computer whole joint, the joint motor of the exoskeleton robot provides required torque.
8. The control method for automatic adjustment of the tripping condition gait of the exoskeleton of claim 7, wherein the follow-up mode adopts a torque PID control method, specifically:
carrying out dynamic calculation on the joint angle value and the angular velocity value acquired by the encoder to obtain the actual moment of the joint of the exoskeleton robot, and obtaining the driving moment of the joint of the exoskeleton robot by the controller;
the control quantity of the driver is obtained through calculation of joint moment difference between the actual moment of the joint of the exoskeleton robot and the driving moment of the joint of the exoskeleton robot and the PID control coefficient, and then the driving motor is controlled to control the exoskeleton robot.
9. The control method for automatic adjustment of the tripping condition gait of the exoskeleton of claim 7, wherein the assistance mode adopts an impedance PID control method, specifically:
obtaining a man-machine integral joint driving angle according to the encoder;
obtaining a man-machine integral joint angle difference according to the man-machine integral joint driving angle and the set man-machine integral joint expected angle;
impedance control is carried out on the angle difference of the human-machine integral joint, so that the expected moment of the human-machine integral joint is obtained;
carrying out dynamic calculation on the joint angle value and the angular velocity value acquired by the encoder to obtain a human-machine integral joint driving moment, and calculating to obtain a human-machine integral joint moment difference according to the human-machine integral joint expected moment and the human-machine integral joint driving moment;
and calculating to obtain a driver control quantity according to the man-machine integral joint moment difference and the PID control coefficient, and further controlling the driving motor to control the exoskeleton robot.
10. The control method for automatic adjustment of the tripping condition gait of the exoskeleton of claim 2, wherein when the exoskeleton robot is in a walking state, and when the toe collides with an obstacle, and the value of the toe pressure sensor is greater than or equal to a second threshold value, the controller detects that the exoskeleton is tripped by the obstacle, the controller switches the exoskeleton robot to a tripping recovery state, the exoskeleton robot starts to lift the foot, and the balance is restored, namely, the swing-side hip joint continues to perform buckling motion and the swing-side knee joint continues to perform buckling motion within a set time, so that the foot height is lifted to be higher than the obstacle, and meanwhile, the angles of the support-side hip joint and the knee joint are unchanged;
when the foot is lifted to be higher than the height of the obstacle, the controller controls the foot to move forwards and gradually fall, after the foot on the swinging side is contacted with the ground, the plantar pressure value is gradually increased, when the plantar pressure value is greater than or equal to a third threshold value, the exoskeleton robot is switched to a static standing state, a follow-up control mode is adopted, at the moment, the wearer stops moving, the exoskeleton robot keeps in the static standing state, or the wearer continues to move forwards, and the exoskeleton robot is switched to a walking state.
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| CN117204993A (en) * | 2023-11-09 | 2023-12-12 | 浙江强脑科技有限公司 | Intelligent artificial limb movement pattern recognition method and device, intelligent artificial limb and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117204993A (en) * | 2023-11-09 | 2023-12-12 | 浙江强脑科技有限公司 | Intelligent artificial limb movement pattern recognition method and device, intelligent artificial limb and storage medium |
| CN117204993B (en) * | 2023-11-09 | 2024-02-27 | 浙江强脑科技有限公司 | Intelligent artificial limb movement pattern recognition method and device, intelligent artificial limb and storage medium |
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