Active and passive hybrid driving flexible lower limb exoskeleton system and coordination control method

Abstract

The invention discloses an active and passive hybrid driving flexible lower limb exoskeleton system and a coordination control method.The skeleton system comprises an elastic energy storage element, a rope driving system, a flexible binding device, a sensing system and a control system, and the control system comprises a gait recognition algorithm, a power-assisted trajectory planning algorithm and a force trajectory tracking algorithm; the gait recognition algorithm detects the angle and the angular speed and detects the motion state, the assistance trajectory planning algorithm calculates the rope drive assistance, the force trajectory tracking algorithm converts the expected force into the motor speed, correction is conducted through the feedback information of the force sensor, and accurate expected force trajectory tracking is achieved. An active power assisting stage and a passive power assisting stage in a gait cycle are divided through a finite-state machine, and the power assisting magnitude of the active power assisting stage and active and passive power assisting mode switching are controlled in a coordinated mode according to the passive energy storage principle and the active power assisting principle. According to the invention, the active and passive hybrid driven flexible lower limb exoskeleton can be controlled in a coordinated manner, and high-precision, high-robustness and high-response-speed force control is realized.

Description

Technical Field

[0001] The present invention relates to an exoskeleton robot and a control method, and in particular to an active-passive hybrid drive flexible lower limb exoskeleton system and a coordinated control method. Background Art

[0003] For the elderly, there may be insufficient lower limb muscle strength, which makes it difficult to travel and seriously affects their daily lives. As my country's aging population deepens, this phenomenon will become more and more common.

[0005] Lower limb exoskeletons can assist walking and help the elderly complete daily activities such as outdoor travel. The development of lower limb exoskeletons is one of the effective ways to deal with the deepening of the aging of the population in my country, the increase in the elderly population, and the difficulty of traveling due to insufficient lower limb muscle strength in the elderly. For those with lower limb dysfunction, lower limb exoskeletons can provide rehabilitation training to help restore lower limb motor function. Replacing the work of some rehabilitation therapists can effectively alleviate the problem of the serious shortage of rehabilitation therapists in my country.

[0006] Lower limb exoskeletons can be divided into rigid lower limb exoskeletons and flexible lower limb exoskeletons. Rigid lower limb exoskeletons have some disadvantages, such as when the exoskeleton joints are misaligned with the wearer's biological joints or the exoskeleton's freedom of movement does not meet the wearer's needs, it may interfere with the wearer's free movement. The rigid structure at the distal position has a large inertia, which will significantly increase the wearer's net metabolic rate.

[0007] Flexible lower limb exoskeleton not only makes up for the shortcomings of rigid lower limb exoskeleton, but also has the characteristics of light weight, convenient and comfortable to wear, and can provide auxiliary force, meeting the needs of different groups of people for enhanced lower limb motor function. Active and passive hybrid drive flexible lower limb exoskeleton can not only provide active assistance to the human body, but also provide passive assistance by absorbing the gravitational potential energy of the human body, improving the energy utilization efficiency of the exoskeleton system. The research and development of active and passive hybrid drive flexible lower limb exoskeleton is one of the important solutions to enhance the motor function of the human lower limbs.

[0008] Therefore, technicians in this field are committed to providing a coordinated control method for an active-passive hybrid drive flexible lower limb exoskeleton system to provide hip joint assistance for the wearer, assist lower limb movement, and enhance the stability, safety, and comfort of the wearer's daily lower limb movement. Summary of the invention

[0009] Purpose of the invention: The present invention provides an active-passive hybrid drive flexible lower limb exoskeleton system and a coordinated control method.

[0010] Technical solution: The active-passive hybrid drive flexible lower limb exoskeleton system and coordinated control method of the present invention include the following steps:

[0011] (1) When the inertial sensor detects that the angular velocity of the hip joint reaches a threshold, the active-passive hybrid drive flexible lower limb exoskeleton assistance system is started, and the gait recognition algorithm identifies the current motion state of the human hip joint by obtaining the angle and angular velocity information detected by the inertial sensor;

[0012] (2) Under the condition that the hip joint motion state meets the requirements, the power-assistance trajectory required for the current motion state is planned. The power-assistance trajectory planning algorithm plans the power-assistance trajectory required for the current motion stage and outputs the power-assistance required for the rope drive;

[0013] (3) The force trajectory tracking algorithm tracks the power trajectory output by the power trajectory planning algorithm. The power trajectory planning algorithm outputs the force F d (θ) and the force F measured by the tension sensor c The output force F is calculated by the PID controller. e , output force F e The motor speed V is output through the admittance controller c , the motor rotates the pull rope to provide assistance to the human body;

[0014] (4) The condition for judging whether to stop working is when the angular velocity of the hip joint is less than a certain set threshold value approaching zero.

[0015] The active-passive hybrid-driven flexible lower limb exoskeleton includes an elastic energy storage element, a rope drive system, a flexible binding device, a sensor system, and a control system. The control system includes a gait recognition algorithm, an assist trajectory planning algorithm, and a force trajectory tracking algorithm. The gait recognition algorithm detects the angle and angular velocity information of the hip joint in the sagittal plane through an inertial sensor, and detects the movement state of the human hip joint in real time. The assist trajectory planning algorithm calculates the rope drive assist in real time according to the movement state of the hip joint. The force trajectory tracking algorithm converts the desired force into a motor speed through an admittance controller, and performs real-time correction through feedback information from the force sensor to reduce tracking errors and achieve accurate desired force trajectory tracking.

[0016] The sensing system comprises inertial sensors respectively installed on the front sides of two thighs and a tension sensor installed on the rope driving device.

[0017] In the above scheme,

[0018] Each sensor provides stable and effective physical signals for the control system and is used to identify the movement state of the human body.

[0019] The data measured by each sensor is filtered through a low-pass filter to remove abnormal data and obtain smooth data. The low-pass filter formula is as follows:

[0020] Y(n)=αX(n)+(1-α)Y(n-1),

[0021] Where α is the filter coefficient, X(n) is the current sampling value, Y(n-1) is the previous filter output value, and Y(n) is the current filter output value.

[0022] Furthermore, the gait recognition algorithm obtains the hip joint angle θ and angular velocity v information through the data measured by the inertial sensor, and divides the gait cycle through the finite state machine to obtain the current state. The states of the finite state machine are as follows:

[0023] The first state: 0 to 30% of the gait cycle, in this state the rope drives the assistance, and its force includes the hip joint assistance and the spring tension force.

[0024] The second state: 30% to 50% of the gait cycle. In this state, the spring uses the gravitational potential energy of the human body to store energy.

[0025] The third state: 50% to 87% of the gait cycle, in this state the spring releases energy to assist the person.

[0026] The fourth state: 87% to 100% of the gait cycle, in this state the rope drives the assistance, the force is the hip joint assistance, and the spring uses the gravity of the human leg to store energy.

[0027] Furthermore, the power-assistance trajectory planning algorithm designs the power-assistance trajectory of each stage of the rope drive system:

[0028] Phase 1: 0 to 10% of the gait cycle, the rope drive power size in this phase is:

[0029]

[0030] Phase 2: 10% to 30% of the gait cycle, the rope drive power size in this phase is:

[0031]

[0032] Phase 3: 30% to 87% of the gait cycle, during this phase the rope remains in a warning state, and the force on the rope is:

[0033] F e ,

[0034] Phase 4: 87% to 100% of the gait cycle, the rope drive power size in this phase is:

[0035]

[0036] In the formula, is the expected joint force peak, F p is the rope warning force, F s is the spring tension, θ is the angle between the hip joint and the vertical direction, is the maximum angle of the hip joint, is the hip angle at peak force.

[0037] Furthermore, the current corresponding rope drive system power-assisting stage is obtained according to the gait recognition algorithm, and the expected auxiliary force F of the current rope drive system is calculated through the power-assisting trajectory planning algorithm. d (θ).

[0038] Furthermore, the desired auxiliary force F of the rope drive system is d (θ) and the force F measured by the tension sensor c The output force F is calculated by the PID controller. e , the PID algorithm calculation formula is as follows:

[0039]

[0040] In the formula, F e (t) is the output force of the PID controller, K p is the proportional gain, T t is the integration time constant, T D is the differential time constant, and e(t) is the difference between the desired force and the measured force.

[0041] Furthermore, the output force calculated by the PID algorithm is converted into the required motor speed V through the admittance controller. c , the admittance control model is as follows:

[0042]

[0043] Where M d is the inertia coefficient, B d is the damping coefficient, K d is the stiffness coefficient, x r is the reference position, X is the actual position, F e It is the contact force.

[0044] The admittance equation is defined in the Laplace domain as:

[0045]

[0046] Where Y is the virtual admittance, V c is the rope velocity of the feedback term, M v is the virtual inertia, C v It's damping.

[0047] Furthermore, the working process of the control system includes the following steps:

[0048] At the maximum flexion point of the hip joint, the rope drive system starts to assist, and stops assisting at 30% of the gait cycle. At the maximum flexion point of the hip joint, the elastic energy storage element starts to store energy, stops storing energy at the maximum extension point of the hip joint, and starts to release elastic potential energy, and stops releasing elastic potential energy at the next maximum flexion point of the hip joint, and starts to store energy.

[0049] The gait recognition algorithm detects the current hip joint angle θ, and the assist trajectory planning algorithm calculates the rope-driven assist force F corresponding to the current hip joint angle θ. d , the expected auxiliary force F d The rope force F detected by the tension sensor c After the difference is made, the output force F is obtained through the PID controller. e (t), the force trajectory tracking algorithm converts the PID controller output force F through the admittance controller e (t) is converted into the required motor speed V c , the motor pulls the rope to output auxiliary force to do work on the human body.

[0050] Furthermore, when the hip joint angle or angular velocity exceeds a set threshold, the active-passive hybrid drive flexible lower limb exoskeleton stops working.

[0051] Furthermore, when the rope drive system does not provide assistance, a low preload is maintained on the rope, so that the rope is always kept in a tensioned state, the rope can remain close to the slideway, and can respond quickly when providing assistance in the next cycle.

[0052] Furthermore, the active-passive hybrid drive flexible lower limb exoskeleton system includes a battery, a soft exosuit, a rope drive system, a sensor system, an elastic energy storage element, a flexible binding device, a Bowden cable drive device and a control system.

[0053] The battery is installed on the chest to provide energy for the control system

[0054] The soft exosuit is worn on the human body, and the battery, rope drive system, and elastic energy storage element are installed on the soft exosuit. The rope drive system is installed on the back of the human body to provide power for the control system.

[0055] The sensing system includes inertial sensors installed on the front sides of the two thighs and a tension sensor installed on the rope drive device.

[0056] The elastic energy storage element is installed on the front of the thigh, which stores energy when it stretches and releases energy when it contracts.

[0057] The flexible binding device is installed on the upper and lower sides of the knee joint. Its main function is to fix the connection points between the elastic energy storage element and the Bowden cable drive device and the human body, while making the human body evenly stressed.

[0058] The Bowden cable drive is installed on the back of the thigh to provide auxiliary force for the hip joint

[0059] The control system collects human motion information through the sensor system, and the control rope drive system drives the Bowden cable drive device to provide power for the lower limbs of the human body.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] 1. The active-passive hybrid drive flexible lower limb exoskeleton system coordinated control method provided by the present invention includes a gait recognition algorithm, an assist trajectory planning algorithm and a force trajectory tracking algorithm. The gait recognition algorithm detects the angle and angular velocity information of the hip joint in the sagittal plane through an inertial sensor, and detects the movement state of the human hip joint in real time. The assist trajectory planning algorithm calculates the rope drive assist in real time according to the movement state of the hip joint. The force trajectory tracking algorithm converts the desired force into motor speed through an admittance controller. The motor pulls the rope to output force to the human leg, and the force sensor feedback information is used for real-time correction to reduce tracking errors and achieve accurate desired force trajectory tracking.

[0062] 2. The active-passive hybrid drive flexible lower limb exoskeleton system coordination control method provided by the present invention adopts a single inertial sensor installed on the front of the thigh to collect hip joint angle and angular velocity information, and identifies the hip joint movement state through a finite state machine. The gait recognition algorithm has the characteristics of high precision and high real-time performance. At the same time, single sensor acquisition is more friendly to wearable exoskeletons and has good generalization ability and adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 2 is a side view schematic diagram of the wearing effect of the active-passive hybrid drive flexible lower limb exoskeleton according to an embodiment of the present invention;

[0064] Figure 2 It is an overall schematic diagram of the coordinated control method of the active-passive hybrid drive flexible lower limb exoskeleton system provided by an embodiment of the present invention;

[0065] Figure 3 This is a workflow diagram of a coordinated control method for an active-passive hybrid drive flexible lower limb exoskeleton system provided by an embodiment of the present invention;

[0066] Figure 4 is a schematic diagram of a finite state machine used in a gait recognition algorithm provided in an embodiment of the present invention;

[0067] Figure 5 It is a schematic diagram of the energy storage and release stages of the elastic energy storage element provided by an embodiment of the present invention;

[0068] Figure 6 It is a schematic diagram of the rope-driven working stage provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be further described below.

[0070] In the drawings, components with the same structure are indicated by the same numerical reference numerals, and components with similar structures or functions are indicated by similar numerical reference numerals. The size and thickness of each component shown in the drawings are arbitrarily shown, and the present invention does not limit the size and thickness of each component. In order to make the illustration clearer, the thickness of the components is appropriately exaggerated in some places in the drawings.

[0071] This embodiment provides a coordinated control method for an active-passive hybrid drive flexible lower limb exoskeleton system, which is used for controlling an active-passive hybrid drive flexible lower limb exoskeleton.

[0072] like Figure 1 As shown, the active-passive hybrid drive flexible lower limb exoskeleton of the present invention includes a battery 1, a soft exosuit 2, a drive system 3, a sensor system 4, an elastic energy storage element 5, a binding device 6 and a Bowden cable drive device 7. The drive system 3 is driven by a motor and provides a power source for the exoskeleton. The sensor system 4 includes an inertial sensor and a tension sensor. The inertial sensor detects the hip joint angle and angular velocity information, and the tension sensor detects the tension on the Bowden cable.

[0073] The active-passive hybrid drive flexible lower limb exoskeleton system coordinated control method of this embodiment includes a gait recognition algorithm, an assist trajectory planning algorithm and a force trajectory tracking algorithm. The gait recognition algorithm detects the angle and angular velocity information of the hip joint in the sagittal plane through an inertial sensor, and detects the movement state of the human hip joint in real time. The assist trajectory planning algorithm calculates the rope-driven assist in real time according to the movement state of the hip joint. The force trajectory tracking algorithm converts the desired force into motor speed through an admittance controller. The motor pulls the rope to output force to the human leg, and the force sensor feedback information is used to perform real-time correction to reduce tracking errors and achieve accurate desired force trajectory tracking.

[0074] The specific implementation method is as follows:

[0075] The inertial sensor collects the angle and angular velocity information of the hip joint movement on the sagittal plane, and filters the collected data through low-pass filtering. The low-pass filtering formula is as follows:

[0076] Y(n)=aX(n)+(1-α)Y(n-1),

[0077] Where α is the filter coefficient, X(n) is the current sampling value, Y(n-1) is the previous filter output value, and Y(n) is the current filter output value.

[0078] The gait recognition algorithm determines the current motion state through the filtered angle and angular velocity information. The motion state is classified as follows:

[0079] The first state: 0 to 30% of the gait cycle, in this state the rope drives the assistance, and its force includes the hip joint assistance and the spring tension force.

[0080] The second state: 30% to 50% of the gait cycle. In this state, the spring uses the gravitational potential energy of the human body to store energy.

[0081] The third state: 50% to 87% of the gait cycle, in this state the spring releases energy to assist the person.

[0082] The fourth state: 87% to 100% of the gait cycle, in this state the rope drives the assistance, the force is the hip joint assistance, and the spring uses the gravity of the human leg to store energy.

[0083] The rope-driven power-assisted trajectory planning algorithm plans the rope-driven power-assisted trajectory according to the human motion information detected by the gait recognition algorithm. The power-assisted trajectory of each stage is as follows:

[0084] Phase 1: 0 to 10% of the gait cycle, the rope drive power size in this phase is:

[0085]

[0086] Phase 2: 10% to 30% of the gait cycle, the rope drive power size in this phase is:

[0087]

[0088] Phase 3: 30% to 87% of the gait cycle, during this phase the rope remains in a warning state, and the force on the rope is:

[0089] F p ,

[0090] Phase 4: 87% to 100% of the gait cycle, the rope drive power size in this phase is:

[0091]

[0092] In the formula, is the expected joint force peak, F p is the rope warning force, F s is the spring tension, θ is the angle between the hip joint and the vertical direction, is the maximum angle of the hip joint, is the hip angle at peak force.

[0093] The force trajectory tracking algorithm tracks the force trajectory output by the assist trajectory planning algorithm, and detects the tension F on the Bowden wire through the tension sensor. c , expected auxiliary force F of the rope drive system d (θ) and the force F measured by the tension sensor cThe output force F is calculated by the PID controller. e , the PID algorithm calculation formula is as follows:

[0094]

[0095] In the formula, F e (t) is the output force of the PID controller, K p is the proportional gain, T t is the integration time constant, T D is the differential time constant, and e(t) is the difference between the desired force and the measured force.

[0096] The output force calculated by the PID algorithm is converted into the required speed V of the motor through the admittance controller c , the admittance control model is as follows:

[0097]

[0098] Where M d is the inertia coefficient, B d is the damping coefficient, K d is the stiffness coefficient, X r is the reference position, X is the actual position, F e It is the contact force.

[0099] The admittance equation is defined in the Laplace domain as:

[0100]

[0101] Where Y is the virtual admittance, V c is the rope velocity of the feedback term, M v is the virtual inertia, C v It's damping.

[0102] like Figure 3 As shown in FIG. 1 , the specific working process of the coordinated control method of the active-passive hybrid drive flexible lower limb exoskeleton system is as follows:

[0103] The working process of the rope-driven active power-assistance is as follows: when the inertial sensor in the sensing device 4 detects that the angular velocity of the hip joint reaches the threshold value, the active-passive hybrid-driven flexible lower limb exoskeleton power-assistance system is started. The power-assistance trajectory planning algorithm outputs the power-assistance required for the current motion state of the human body according to the angle and angular velocity information detected by the inertial sensor in the sensing device 4. The force trajectory tracking algorithm controls the Bowden cable drive device 7 to assist the lower limbs of the human body from 0 to 30% and 87% to 100% of the gait cycle through the rope drive system 3. First, the auxiliary force is converted into the required speed of the motor in the rope drive system 3 through the admittance controller, and the motor speed is controlled through the speed controller. The motor rotates to drive the actuator, namely the Bowden cable drive device 7, to output power to the human body. The Hall sensor in the motor feeds back the motor speed to the speed controller, and the speed controller corrects the motor speed in real time. The tension sensor in the sensing device 4 feeds back the tension in the Bowden cable drive device 7, and the PID controller corrects the power-assistance required by the Bowden cable drive device 7 in real time. When the hip joint angle or angular velocity exceeds the set threshold, the active-passive hybrid-driven flexible lower limb exoskeleton stops working.

[0104] The passive power-assistance workflow of the elastic energy storage element is as follows: the elastic energy storage element 5 uses the gravitational potential energy during the human body's movement to store energy at 30% to 50% and 87% to 100% of the gait cycle, uses the energy provided by the Bowden cable drive device 7 to store energy at 0% to 30% of the gait cycle, and releases energy at 50% to 87% of the gait cycle to provide passive power assistance for the lower limbs. The elastic energy storage element 5 is a passive drive device, and its state changes with the movement state of the human lower limbs. It is at its original length when the hip joint reaches maximum flexion, is elongated during the extension of the hip joint, and is shortened during the flexion of the hip joint, and does not require control by a control system.

[0105] The coordinated control method of the active-passive hybrid drive flexible lower limb exoskeleton system divides the active and passive power-assisting stages in the gait cycle through a finite state machine. The control rope drive system 3 provides power assistance to the human lower limbs from 0 to 30% and 87% to 100% of the gait cycle, and the elastic energy storage element 5 provides power assistance to the human lower limbs from 50% to 87% of the gait cycle.

[0106] The above is only a preferred embodiment of the present invention and does not limit the present invention in any way. Any technician in the relevant technical field, without departing from the scope of the technical solution of the present invention, makes any form of equivalent replacement or modification to the technical solution and technical content disclosed in the present invention, which does not depart from the content of the technical solution of the present invention and still falls within the protection scope of the present invention.

Claims

1. A coordinated control method for an active-passive hybrid drive flexible lower limb exoskeleton system, characterized in that: The steps include: (1) When the inertial sensor detects that the angular velocity of the hip joint reaches a threshold, the active-passive hybrid drive flexible lower limb exoskeleton assistance system is started, and the gait recognition algorithm identifies the current motion state of the human hip joint by obtaining the angle and angular velocity information detected by the inertial sensor; (2) Under the condition that the hip joint motion state meets the requirements, the power-assistance trajectory required for the current motion state is planned. The power-assistance trajectory planning algorithm plans the power-assistance trajectory required for the current motion stage and outputs the power-assistance required for the rope drive; (3) The force trajectory tracking algorithm tracks the power trajectory output by the power trajectory planning algorithm. The power trajectory planning algorithm outputs the force F d (θ) and the force F measured by the tension sensor c The output force F is calculated by the PID controller. e , output force F e The motor speed V is output through the admittance controller c , the motor rotates the pull rope to provide assistance to the human body; (4) The condition for judging whether to stop working is when the angular velocity of the hip joint is less than a certain set threshold value approaching zero.

2. The coordinated control method of the active-passive hybrid drive flexible lower limb exoskeleton system according to claim 1 is characterized in that: The gait recognition algorithm divides the stages of rope-driven assistance, spring energy storage and spring energy release through a finite state machine. The states of the finite state machine in the gait recognition algorithm are: The first state: 0 to 30% of the gait cycle, in this state, the rope drives the power, and its force includes the hip joint power and the spring tension force; The second state: 30% to 50% of the gait cycle, in this state the spring uses the gravitational potential energy of the human body to store energy; The third state: 50% to 87% of the gait cycle, in this state the spring releases energy to assist the person; The fourth state: 87% to 100% of the gait cycle, in this state the rope drives the assistance, the force is the hip joint assistance, and the spring uses the gravity of the human leg to store energy.

3. The coordinated control method of the active-passive hybrid drive flexible lower limb exoskeleton system according to claim 2 is characterized in that: The power-assisted trajectory planning algorithm adopts piecewise function to design the rope-driven power-assisted size, and the functions of each stage are: Phase 1: 0 to 10% of the gait cycle, the rope drive power size in this phase is: Phase 2: 10% to 30% of the gait cycle, the rope drive power size in this phase is: Phase 3: 30% to 87% of the gait cycle, during this phase the rope remains in a warning state, and the force on the rope is: Fe, Phase 4: 87% to 100% of the gait cycle, the rope drive power size in this phase is: In the formula, is the expected joint force peak, F p is the rope warning force, F s is the spring tension, θ is the angle between the hip joint and the vertical direction, is the maximum angle of the hip joint, is the hip angle at peak force.

4. The coordinated control method of the active-passive hybrid drive flexible lower limb exoskeleton system according to claim 3 is characterized in that: The force trajectory tracking algorithm adopts the admittance control strategy to realize human-machine force interaction control. The admittance model of the joint space of the active-passive hybrid drive flexible lower limb exoskeleton in the gait cycle is: Where M d is the inertia coefficient, B d is the damping coefficient, K d is the stiffness coefficient, X r is the reference position, X is the actual position, F e is the contact force, The admittance equation is defined in the Laplace domain as: Where Y is the virtual admittance, V c is the rope velocity of the feedback term, M v is the virtual inertia, C v It's damping.

5. The coordinated control method of the active-passive hybrid drive flexible lower limb exoskeleton system according to claim 4 is characterized in that: The PID algorithm is used to make the force on the rope quickly and accurately reach the desired force of claim 3. The PID algorithm formula is as follows: In the formula, F e (t) is the output force of the PID controller, K p is the proportional gain, T t is the integration time constant, T D is the differential time constant, and e(t) is the difference between the desired force and the measured force.

6. The active-passive hybrid drive flexible lower limb exoskeleton system coordination control method according to claim 5 is characterized in that: The angle and angular velocity detected by the inertial sensor are filtered through a low-pass filtering algorithm. The calculation formula of the low-pass filtering algorithm is as follows: Y(n)=αX(n)+(1-α)Y(n-1), Where α is the filter coefficient, X(n) is the current sampling value, Y(n-1) is the previous filter output value, and Y(n) is the current filter output value.

7. A system used in the method according to any one of claims 1 to 6, characterized in that: The invention comprises a battery (1), a soft exosuit (2), a rope drive system (3), a sensor system (4), an elastic energy storage element (5), a flexible binding device (6), a Bowden cable drive device (7) and a control system. The battery (1) provides energy for the control system; The soft outer suit (2) is used to install the battery (1), the rope drive system (3), and the elastic energy storage element (5); The rope drive system (3) is installed on the back of the human body to provide power for the control system; The sensing system (4) comprises inertial sensors respectively mounted on the front sides of the two thighs and a tension sensor mounted on the rope drive device; The elastic energy storage element (5) is installed on the front side of the thigh, and stores energy when it is extended and releases energy when it is contracted; The flexible binding device (6) is installed on the upper and lower sides of the knee joint, and its main function is to fix the connection points between the elastic energy storage element (5) and the Bowden cable drive device (7) and the human body, and at the same time make the human body evenly stressed; The Bowden cable drive device (7) is installed on the back of the thigh to provide auxiliary force for the hip joint; The control system collects human body movement information through the sensor system (4), and controls the rope drive system (3) to drive the Bowden cable drive device (7) to provide assistance to the lower limbs of the human body.

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