CN116276918A - Exoskeleton assisting method, system and computer readable medium based on non-contact knee joint of lower limb - Google Patents
Exoskeleton assisting method, system and computer readable medium based on non-contact knee joint of lower limb 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
- B25J9/0006—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
- B25J9/16—Programme controls
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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
- B25J9/1694—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 provides a non-contact lower limb knee joint exoskeleton-based power assisting method, a non-contact lower limb knee joint exoskeleton-based power assisting system and a computer readable medium, wherein the non-contact lower limb knee joint exoskeleton-based power assisting method comprises the following steps of: the method comprises the steps of utilizing a state recognition algorithm to recognize sensing data of a foot of a lower limb knee joint exoskeleton wearer in real time to obtain a foot motion state; judging the foot motion state of a wearer when the wearer moves up and down stairs based on a motion phase identification algorithm, and obtaining the motion phase of the wearer when the wearer moves up and down stairs; and corresponding control operation is executed according to the motion phase adjusting assistance and follow-up control strategy, the control moment is output and transmitted to a main controller in the lower limb knee joint exoskeleton, so that the exoskeleton knee joint motor is controlled to drive a wearer to finish the movement of going up and down stairs. According to the invention, the non-contact type motion sensor is adopted to extract and analyze the power-assisted phase interval of the upstairs and downstairs, and the motion control strategy of the upstairs and downstairs is formulated, so that the motion process of the upstairs and downstairs is more in accordance with the actual motion characteristics of a human body, and the high-efficiency stability of the power assistance of a wearer is improved.
Description
Technical Field
The invention relates to the technical field of exoskeleton motion control, in particular to a non-contact-based exoskeleton assistance method and system for knee joints of lower limbs and a computer readable medium.
Background
In the mountain climbing material transportation process, mountain pickers and material transportation workers need to go up and down stairs for a long time to transport materials, occupational musculoskeletal disease risks are easily induced under the environment when working for a long time, serious damage is caused to lower limbs of a human body, particularly knee joints, fatigue and stiff and painful knee joints are usually generated when middle-aged and elderly tourists perform mountain climbing exercise or up and down stairs activities (after people go to middle-aged, the tendons and ligaments of the knee joints start to be degenerative changes, synovial fluid secretion of joint cavities is reduced, long-term friction of joint bone faces forms bone abrasion, fibrous adhesion is easily caused by inflammation and other reasons, and at present, leg support of the up and down stairs parts is usually carried out by adopting walking sticks or unpowered exoskeletons so as to relieve damage and stiff pain to the knee joints of lower limbs, but the prior art lacks effective power source auxiliary strategy equipment and means, and the solving effect is not ideal.
In CN 114905490A, an auxiliary supporting exoskeleton scheme with active and passive combination is proposed, and through active and passive matching of a ratchet gear and a motor, the characteristics of passive exoskeleton supporting stability and active exoskeleton walking assistance are combined, but the working scene is limited to walking and squatting supporting parts, and assistance to up-and-down stair link parts is lacking.
CN 111452026A proposes a passive knee joint assisting exoskeleton, where a thigh rod member and a shank rod member are combined by a passive component to assist movement in a passive spring manner, but compression of an actual spring still requires human body to do work, which hinders movement of the human body.
Disclosure of Invention
According to a first aspect of the object of the present invention, there is provided a non-contact knee exoskeleton assistance method for lower limbs, comprising:
step 2, judging the foot motion state of the wearer when the wearer moves up and down stairs based on a motion phase identification algorithm, and obtaining the motion phase of the wearer when the wearer moves up and down stairs;
and 3, executing corresponding control operation according to the motion phase adjusting assistance and follow-up control strategy, outputting control moment, and transmitting the control moment to a main controller in the lower limb knee joint exoskeleton so as to control the exoskeleton knee joint motor to drive a wearer to finish the movement of going up and down stairs.
Further, in the step 1, the step of identifying the sensing data of the foot of the wearer with the knee exoskeleton of the lower limb in real time by using a state identification algorithm to obtain the foot motion state includes:
the wearer wears the knee joint exoskeleton of the lower limb and selects a stair climbing mode;
the synchronous calling state recognition algorithm recognizes the sensing data of the foot of the wearer, and calculates the absolute value of the joint angle of the foot and the angular speed of the sole of the foot;
and judging the absolute value of the angle of the foot joint and the angular speed of the sole to obtain the foot motion state.
Further, the foot motion state includes a foot supporting action, a foot lifting action, and a foot falling action.
Further, the absolute value of the foot joint angle and the plantar angular velocity are calculated to judge the foot motion state, and the mathematical expression formula is as follows:
where θ is the measurement of the foot IMU sensor,
is the absolute value of the angle of the foot joint, +.>
Is the angle mean>
For time mean>
To fit the angular velocity of the sole of the foot.
Further, according to the absolute value of the calculated foot joint angle and the plantar angular velocity, judging the absolute value and the plantar angular velocity to obtain a foot motion state, including:
if the absolute value of the angle of the foot joint is smaller than 10 degrees, the foot is supported;
if the absolute value of the angle of the foot joint is larger than 10 degrees and the plantar angular velocity is larger than 5 degrees/s, the foot lifting action is performed;
if the absolute value of the foot joint angle is larger than 10 degrees, the plantar angular velocity is smaller than 5 degrees/s, and the foot motion state at the last moment is not a supporting motion or a foot lifting motion, the foot falling motion is performed.
Further, in the step 2, the motion state of the foot when the wearer moves up and down stairs is determined based on the motion phase recognition algorithm, so as to obtain the motion phase when the wearer moves up and down stairs, wherein the motion phase comprises a power-assisted phase and a follow-up phase.
Further, when a wearer walks up stairs, if the foot lifting action occurs on the rear side foot of the wearer, the foot lifting action is the power-assisted phase;
if the foot of the rear side of the wearer does not have foot lifting action, the foot lifting action is the follow-up phase;
when a wearer goes down stairs, if the foot on the rear side of the wearer takes up the foot, the foot is the follow-up phase;
and if the foot of the rear side of the wearer does not have the foot lifting action and the foot of the front side of the wearer has the supporting action, the power assisting phase is the power assisting phase.
Further, in the step 3, corresponding control operation is executed according to the motion phase adjustment assisting force and the follow-up control strategy, and a control moment is output, including:
if the follow-up phase is the follow-up phase, a follow-up control strategy is called, low-pass filtering processing is carried out based on man-machine interaction force in a real-time movement process, a real-time interaction force error is obtained by making a difference with a target man-machine interaction force, and then moment summation is carried out by a PD controller and feedforward input to act on an exoskeleton knee joint motor so as to drive a wearer to finish up-down stairs movement;
and if the power-assisted phase is the power-assisted phase, a power-assisted auxiliary control strategy is called, an output moment is obtained based on the difference between the foot joint angle and the target joint position in the real-time motion process, and the output moment is summed with a feedforward input through a PD controller and acts on an exoskeleton knee joint motor to drive a wearer to finish the stair climbing motion.
According to a second aspect of the object of the present invention, there is provided a non-contact knee exoskeleton assistance system for lower limbs, comprising:
one or more processors;
a memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising a flow of the non-contact lower limb knee exoskeleton assistance based method as described.
According to a third aspect of the object of the present invention, there is provided a computer readable medium storing software, characterized in that: the software includes instructions executable by one or more computers, the instructions, by such execution, causing the one or more computers to perform operations comprising a flow of the non-contact lower limb knee exoskeleton assistance based method as described.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the non-contact type motion sensor is adopted to extract and analyze the power-assisted phase interval of the upstairs and downstairs, and the motion control strategy of the upstairs and downstairs is formulated, so that the actual motion characteristics of a human body are more met in the motion process of the upstairs and downstairs, and the high-efficiency stability of the power assistance of a wearer is improved; meanwhile, different motion control targets are set for the motions of going up and down stairs, zero interaction force is used as a control strategy in the rapid swing stage of lifting legs, the rapid swing of the knee joint of the human body is realized, zero position is used as a target in the support stage, the knee joint of the human body is controlled to quickly recover to a support state, and the support assistance of going up and down stairs is realized.
It should be understood that all combinations of the foregoing concepts, as well as additional concepts described in more detail below, may be considered a part of the inventive subject matter of the present disclosure as long as such concepts are not mutually inconsistent. In addition, all combinations of claimed subject matter are considered part of the disclosed inventive subject matter.
The foregoing and other aspects, embodiments, and features of the present teachings will be more fully understood from the following description, taken together with the accompanying drawings. Other additional aspects of the invention, such as features and/or advantages of the exemplary embodiments, will be apparent from the description which follows, or may be learned by practice of the embodiments according to the teachings of the invention.
Drawings
The drawings are not intended to be drawn to scale. In the drawings, each identical or nearly identical component that is illustrated in various figures may be represented by a like numeral. For purposes of clarity, not every component may be labeled in every drawing. Embodiments of various aspects of the invention will now be described, by way of example, with reference to the accompanying drawings.
FIG. 1 is a schematic flow chart of the non-contact lower limb knee joint exoskeleton-based assistance method shown in the present invention;
FIG. 2 is a schematic diagram of an exoskeleton network sensing layout shown in the present invention;
FIG. 3 is a schematic view of a foot motion and motion profile according to the present invention;
FIG. 4 is a flow chart of foot motion status determination according to the present invention;
FIG. 5 is a schematic view of the wearer's movement of the present invention as they go up stairs;
FIG. 6 is a flow chart of motion phase identification of a wearer as they go up stairs, as shown in the present invention;
FIG. 7 is a schematic view showing the movement of the wearer as he or she walks down stairs;
FIG. 8 is a flow chart of motion phase identification of a wearer as they walk down stairs in accordance with the present invention;
FIG. 9 is a schematic diagram of the operational principles of the servo control strategy of the present invention;
fig. 10 is a schematic diagram of the working principle of the assist control strategy according to the present invention.
Detailed Description
For a better understanding of the technical content of the present invention, specific examples are set forth below, along with the accompanying drawings.
Aspects of the invention are described in this disclosure with reference to the drawings, in which are shown a number of illustrative embodiments. The embodiments of the present disclosure are not necessarily intended to include all aspects of the invention. It should be understood that the various concepts and embodiments described above, as well as those described in more detail below, may be implemented in any of a number of ways, as the disclosed concepts and embodiments are not limited to any implementation. Additionally, some aspects of the disclosure may be used alone or in any suitable combination with other aspects of the disclosure.
At present, the rehabilitation exoskeleton in the prior art detects the movement state through plantar pressure or keys, but is easy to damage in the long-term use process; the motion state of the power-assisted exoskeleton is single in detection, gait phase periods are divided only for walking on level ground, and a step of going up and down stairs is omitted; part of exoskeleton collects multidimensional sensing data in the movement process, online network training is needed, and a wearer cannot use the exoskeleton quickly; the passive exoskeleton does not consider the power-assisted requirements of a human body among different phases, and the passive exoskeleton is singly dependent on a passive elastic unit, so that the passive exoskeleton has an obstacle to the movement of the human body and is difficult to adapt to.
Aiming at the problems in the prior art, the embodiment provides a non-contact lower limb knee joint exoskeleton-based power assisting method, which is applied to a main controller carried by the non-contact lower limb knee joint exoskeleton in the form of an algorithm program, so that the exoskeleton can adaptively extract and analyze a power assisting phase interval of the upstairs and downstairs in the moving process of the upstairs and downstairs, and execute a corresponding upstairs and downstairs movement control strategy so as to meet the actual movement characteristics of a human body, improve the high-efficiency stability of the assistance of a wearer, and realize the assistance of the upstairs and downstairs movement for people with requirements for the movement of the upstairs and downstairs.
Referring to the illustration of fig. 2, an AHRS sensor, a strain type interaction force sensor and a main controller for controlling movement of a single-side lower limb are respectively tied up at the foot, the knee joint and the thigh of a wearer, the ankle joint is a passive bearing, after the knee joint exoskeleton is worn, the wearer CAN freely rotate the ankle joint to drive the foot, the sensing data of the foot of the wearer is acquired through a CAN communication network, the sensing data is transmitted to the main controller by utilizing a communication protocol stack to carry out algorithm identification, and the movement phase of the wearer for going up and down stairs is judged, so that the corresponding moment is output to carry out assistance for the wearer for going up and down stairs.
Preferably, the AHRS sensor is configured to collect foot sensing data of a wearer, to transmit the foot sensing data to the main controller in real time for identifying a foot motion state, for example, a kalman filter is used to fuse multiple sensors to collect data, and the data is filtered, so that noise is reduced, and accuracy of data collection is improved.
Preferably, the strain type interaction force sensor obtains man-machine interaction force through knee joint driving, and the man-machine interaction force is transmitted to the main controller in real time to perform zero interaction force control operation, and control moment is output.
Preferably, in combination with the flowchart shown in fig. 1, the present embodiment provides a non-contact type lower limb knee exoskeleton-based assistance method, and the method is applied to a main controller carried by the non-contact type lower limb knee exoskeleton in the form of an algorithm program, so that an assisting wearer can complete up-and-down stair movement, and the method includes the following steps:
step 2, judging the foot motion state of the wearer when the wearer moves up and down stairs based on a motion phase identification algorithm, and obtaining the motion phase of the wearer when the wearer moves up and down stairs;
and 3, executing corresponding control operation according to the motion phase adjusting assistance and follow-up control strategy, outputting control moment, and transmitting the control moment to a main controller in the exoskeleton of the knee joint of the lower limb so as to control the motor of the knee joint of the exoskeleton to drive the wearer to finish the movement of going up and down stairs.
The implementation and/or effects of certain examples of the present invention are described in more detail below in conjunction with the flowcharts shown in fig. 3-10 and some preferred or alternative examples of the present invention.
[ identifying foot movement State ]
In the step 1, the sensing data of the foot of the wearer with the knee joint exoskeleton of the lower limb is identified in real time by using a state identification algorithm, so as to obtain the foot motion state, which comprises the following steps:
the wearer wears the knee exoskeleton of the lower limb, selects a stair climbing mode, and drives the foot to move through the ankle joint;
the foot-bound AHRS sensor collects sensing data of the foot in real time and transmits the sensing data to the main controller through a communication protocol stack;
the main controller invokes a state recognition algorithm to recognize the received foot sensing data, calculates the absolute value of the angle of the foot joint and the angular speed of the sole, and the mathematical expression formula is as follows:
where θ is the measurement of the foot IMU sensor,
is the absolute value of the angle of the foot joint, +.>
Is the angle mean>
For time mean>
Fitting the plantar angular velocity;
the absolute value of the foot joint angle and the angular velocity of the sole are identified according to the judgment conditions, so as to obtain the foot movement state, and referring to fig. 4, the judgment conditions are as follows:
if the absolute value of the angle of the foot joint is smaller than 10 degrees, the foot support action is performed;
if the absolute value of the angle of the foot joint is larger than 10 degrees and the angular speed of the sole is larger than 5 degrees/s, the foot lifting action is performed;
if the absolute value of the angle of the foot joint is larger than 10 degrees, the angular speed of the sole is smaller than 5 degrees/s, and the foot motion state at the last moment is not a supporting motion or a foot lifting motion, the foot is a foot falling motion;
the foot motion state comprises a foot supporting action, a foot lifting action and a foot falling action, the judging condition is an optimal value obtained through a large number of experimental tests, and the judging condition is set in the main controller in advance through a program coding mode;
and storing the real-time foot motion state of the wearer obtained by recognition into a memory of the main controller for real-time calling application of the motion phase recognition algorithm.
Referring to fig. 3, in this embodiment, taking an example of the determination of the movement state of the right foot of the wearer on the stairs, when the wearer goes on the stairs, four links of lifting foot, falling foot, pre-supporting and supporting are respectively experienced, according to the schematic diagram of fig. 3, (1) represents lifting foot, (2) represents falling foot, and (3) represents pre-supporting and supporting, wherein the pre-supporting link is shorter, the pre-supporting angle conversion range is smaller, and when the wearer goes on the stairs or walks on the flat bottom, the pre-supporting link is determined as the supporting state when the wearer is determined.
Preferably, the judging condition (the absolute value of the joint angle is smaller than 10 degrees, the angular speed of the sole is larger than or smaller than 5 degrees/s) is an optimal value obtained through a large number of experimental tests, the judging of the motion state of the foot is greatly influenced, the system misjudgment is caused by an excessively small angular speed threshold value, the system response is delayed due to an excessively large angular speed threshold value, and the occurrence of the problems can be avoided through the optimal value selected through a large number of experimental tests, so that accurate real-time response is provided for the recognition of the motion state of the foot, and the accuracy and the efficiency of the subsequent recognition of the motion phase are improved.
[ identifying motion phases ]
In the step 2, the foot motion state of the wearer during the up-and-down stairs is judged based on the motion phase identification algorithm, so as to obtain the motion phase of the wearer during the up-and-down stairs, wherein the motion phase comprises a power-assisted phase and a follow-up phase;
the motion phase recognition algorithm reads the stored real-time foot motion state of the wearer in real time, judges whether the wearer moves up stairs or down stairs, and performs phase recognition according to the corresponding motion mode, and specifically comprises the following steps:
referring to fig. 5, the wearer performs a stair climbing exercise, and the judgment conditions include: the wearer is on the stairs, both feet are in a supporting state, one side lower limb is stepped on the front stair step, the other side lower limb is stepped on the lower step, at the moment, the wearer needs to exert force on the front side lower limb, lift the rear side lower limb, hang in the air, control the other side lower limb to move forward to reach the same or higher-level step as the current lower limb, thereby completing the step of the first-level step, the both feet enter the supporting state again, and the difference is that compared with the initial posture, the front side and the rear side of the foot position are overturned, the actions are repeated, and the reciprocating stair climbing movement is started;
referring to fig. 6, when the wearer moves up stairs, the assisting phase is the assisting phase if the foot of the rear side of the wearer is lifted, and the following phase is the following phase if the foot of the rear side of the wearer is not lifted;
referring to fig. 7, the wearer performs a downstairs movement, and the judgment conditions include: the wearer is on the stairs, both feet are in a supporting state, one lower limb is stepped on the front stair step, the other lower limb is stepped on the lower step, at the moment, the wearer needs the front lower limb to be actively supported, the rear lower limb is actively bent and suspended, the rear lower limb is controlled to be forwards and to step up to the same level as the current lower limb or a lower level, thus the step of the step is completed, both feet enter the supporting state again, and the difference is that compared with the initial posture, the front side and the rear side of the foot position are overturned, the actions are repeated, and the reciprocating stair descending movement is started;
referring to fig. 8, when the wearer moves down stairs, if the foot of the rear side of the wearer is lifted, the follow-up phase is performed, and if the foot of the rear side of the wearer is not lifted, and the foot of the front side of the wearer is supported, the power-assisted phase is performed;
and transmitting the motion phase result obtained by recognition to a power assisting and follow-up control strategy to execute corresponding control operation and output control moment.
Preferably, the above motion phase recognition provided in this embodiment starts not from detecting a forward force foot but from a rear foot suspension lifting for the moment of assisting in actively stepping up the stairs; the assisting moment for going down stairs is not started from the swing side foot supporting action, but is started from the pre-supporting action, the foot lifting action of the other side foot is ended, and the rest moment is divided into follow-up phases.
Invoking corresponding control algorithm, outputting control moment ]
In the step 3, corresponding control operation is executed according to the motion phase adjusting assistance and the follow-up control strategy, and a control moment is output, including:
referring to fig. 9, if the phase is the follow-up phase, a follow-up control strategy (zero interaction force control strategy) is called, low-pass filtering processing is performed (more than 0 is 1 and less than 0 is-1) based on man-machine interaction force in the real-time motion process, and a difference is made between the low-pass filtering processing and a target man-machine interaction force (zero position) to obtain a real-time interaction force error, and then the real-time interaction force error is subjected to moment summation with a feedforward input through a PD controller to act on an exoskeleton knee joint motor;
the mathematical expression is as follows:
wherein, the liquid crystal display device comprises a liquid crystal display device,
for the derivative of the actual man-machine interaction force, err is the man-machine interaction force error, and V is the joint angular velocitySgn is a sign function of the angular velocity of the joint;
referring to fig. 10, if the phase is the assist phase, a assist control strategy (second-order spring damping control strategy) is called, an output torque is obtained based on the foot joint angle in the real-time motion process and the difference between the foot joint angle and the target joint position, and the output torque is summed with the feedforward input through the PD controller to act on the exoskeleton knee joint motor;
the mathematical expression is as follows:
wherein, the liquid crystal display device comprises a liquid crystal display device,
for the derivative of the actual human-machine interaction force, P _err 2 v is the joint angular velocity, sgn is the sign function of the joint angular velocity, which is the current position error compared with the standing moment;
the exoskeleton knee joint motor receives the electric signal of the control moment and acts on the knee joint motor driver to drive a wearer to move up and down stairs, so that man-machine coupling exoskeleton power assisting is completed.
It should be noted that the man-machine interaction force is obtained by a strain type interaction force sensor tied to the knee joint driving part.
In the supporting stage, the zero position is used as a target, the knee joint of the human body is controlled to quickly recover to a supporting state, supporting assistance of movement of going up and down stairs is realized, feedforward compensation is used for compensating hysteresis friction and viscous friction in the rotating process, and the problem that the hysteresis of the system does not respond is avoided.
Preferably, on one hand, the moment is directly controlled by selecting a follow-up control strategy, so that the friction force is compensated in a feedforward way, the complexity of the system is reduced, and the influence of non-dynamic characteristics is less; on the other hand, the power assisting control strategy is selected to quickly respond to the control moment, proper damping is selected in a self-adaptive mode to carry out load calculation on the power assisting control strategy, vibration energy is weakened, vibration performance of the system is reduced, a wearer is not affected by vibration of knee joint exoskeleton equipment when moving up and down stairs, and stable and comfortable feeling is kept.
The above-mentioned method for identifying the motion state and motion phase of the foot can be performed by means of the methods and means in the prior art, and will not be described in detail in this example.
In accordance with the teachings of the above embodiments, further aspects of the present disclosure provide a non-contact based exoskeleton system for a knee joint of a lower limb, comprising: one or more processors and memory.
The memory is used to store instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including the flow of the non-contact lower limb knee exoskeleton assistance method based method of the previous embodiment, and in particular the flow of the method shown in fig. 1.
Still further aspects of the disclosure of embodiments of the present invention provide a computer-readable medium storing software comprising instructions executable by one or more computers, the instructions, when executed, cause the one or more computers to perform operations comprising the process of the non-contact lower extremity exoskeleton method based on the foregoing embodiment, and in particular, the process of the method shown in fig. 1.
While the invention has been described with reference to preferred embodiments, it is not intended to be limiting. Those skilled in the art will appreciate that various modifications and adaptations can be made without departing from the spirit and scope of the present invention. Accordingly, the scope of the invention is defined by the appended claims.
Claims (10)
1. The non-contact-based exoskeleton assisting method for the knee joints of the lower limbs is characterized by comprising the following steps of:
step 1, real-time identifying the sensing data of the foot of a wearer with the knee joint exoskeleton of the lower limb by using a state identification algorithm to obtain the motion state of the foot;
step 2, judging the foot motion state of the wearer when the wearer moves up and down stairs based on a motion phase identification algorithm, and obtaining the motion phase of the wearer when the wearer moves up and down stairs;
and 3, executing corresponding control operation according to the motion phase adjusting assistance and follow-up control strategy, outputting control moment, and transmitting the control moment to a main controller in the lower limb knee joint exoskeleton so as to control the exoskeleton knee joint motor to drive a wearer to finish the movement of going up and down stairs.
2. The non-contact based knee exoskeleton method of claim 1, wherein in the step 1, the sensing data of the foot of the wearer of the knee exoskeleton of the lower limb is identified in real time by using a state identification algorithm, and the foot motion state is obtained, comprising:
the wearer wears the knee joint exoskeleton of the lower limb and selects a stair climbing mode;
the synchronous calling state recognition algorithm recognizes the sensing data of the foot of the wearer, and calculates the absolute value of the joint angle of the foot and the angular speed of the sole of the foot;
and judging the absolute value of the angle of the foot joint and the angular speed of the sole to obtain the foot motion state.
3. The non-contact lower extremity knee exoskeleton assistance method of claim 2 wherein said foot motion state includes a foot supporting motion, a foot lifting motion and a foot dropping motion.
4. A non-contact lower limb knee joint exoskeleton assistance method as claimed in claim 2 or 3, wherein the absolute value of the foot joint angle and the plantar angular velocity are calculated to determine the foot movement state, and the mathematical expression formula is as follows:
where θ is the measurement of the foot IMU sensor,
is the absolute value of the angle of the foot joint, +.>
Is the angle mean>
For time mean>
To fit the angular velocity of the sole of the foot.
5. The non-contact knee joint exoskeleton helping hand method of claim 4, wherein determining the absolute value and the angular velocity of the sole according to the absolute value and the angular velocity of the sole of the foot obtained by calculation, to obtain the foot motion state, comprises:
if the absolute value of the angle of the foot joint is smaller than 10 degrees, the foot is supported;
if the absolute value of the angle of the foot joint is larger than 10 degrees and the plantar angular velocity is larger than 5 degrees/s, the foot lifting action is performed;
if the absolute value of the foot joint angle is larger than 10 degrees, the plantar angular velocity is smaller than 5 degrees/s, and the foot motion state at the last moment is not a supporting motion or a foot lifting motion, the foot falling motion is performed.
6. The non-contact knee exoskeleton assisting method of claim 5, wherein in the step 2, the foot motion state of the wearer during the up-and-down stairs is determined based on a motion phase recognition algorithm, so as to obtain a motion phase of the wearer during the up-and-down stairs, wherein the motion phase includes an assisting phase and a following phase.
7. The non-contact knee exoskeleton-based power assisting method of claim 6, wherein the power assisting phase is the power assisting phase if the foot of the rear side of the wearer takes a foot lifting action when the wearer goes up stairs;
if the foot of the rear side of the wearer does not have foot lifting action, the foot lifting action is the follow-up phase;
when a wearer goes down stairs, if the foot on the rear side of the wearer takes up the foot, the foot is the follow-up phase;
and if the foot of the rear side of the wearer does not have the foot lifting action and the foot of the front side of the wearer has the supporting action, the power assisting phase is the power assisting phase.
8. The non-contact knee exoskeleton assistance method of claim 7, wherein in the step 3, corresponding control operation is performed according to the motion phase adjustment assistance and follow-up control strategy, and a control moment is output, including:
if the follow-up phase is the follow-up phase, a follow-up control strategy is called, low-pass filtering processing is carried out based on man-machine interaction force in a real-time movement process, a real-time interaction force error is obtained by making a difference with a target man-machine interaction force, and then moment summation is carried out by a PD controller and feedforward input to act on an exoskeleton knee joint motor so as to drive a wearer to finish up-down stairs movement;
and if the power-assisted phase is the power-assisted phase, a power-assisted auxiliary control strategy is called, an output moment is obtained based on the difference between the foot joint angle and the target joint position in the real-time motion process, and the output moment is summed with a feedforward input through a PD controller and acts on an exoskeleton knee joint motor to drive a wearer to finish the stair climbing motion.
9. A non-contact lower limb knee joint exoskeleton-based power assisting system, comprising:
one or more processors;
a memory storing instructions operable, when executed by the one or more processors, to cause the one or more processors to perform operations comprising the flow of a non-contact lower limb knee exoskeleton assistance method based on any one of claims 1 to 8.
10. A computer readable medium storing software, characterized by: the software includes instructions executable by one or more computers which, by such execution, cause the one or more computers to perform operations comprising the flow of a non-contact lower limb knee exoskeleton assistance based method as claimed in any one of claims 1 to 8.
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|---|---|---|---|
| CN202310436294.1A CN116276918A (en) | 2023-04-21 | 2023-04-21 | Exoskeleton assisting method, system and computer readable medium based on non-contact knee joint of lower limb |
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| CN202310436294.1A CN116276918A (en) | 2023-04-21 | 2023-04-21 | Exoskeleton assisting method, system and computer readable medium based on non-contact knee joint of lower limb |
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| CN202310436294.1A Pending CN116276918A (en) | 2023-04-21 | 2023-04-21 | Exoskeleton assisting method, system and computer readable medium based on non-contact knee joint of lower limb |
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| Country | Link |
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| CN (1) | CN116276918A (en) |
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