Control Method, Device and Wearable Device of Wearable Device

Abstract

An embodiment of the present application discloses a control method, device, and wearable device for a wearable device, belonging to the technical field of control methods for wearable devices. Among them, the method includes: obtaining a first parameter and a second parameter, where the first parameter is the motion deviation between the target object and the wearable device, and the second parameter is the interaction force between the target object and the wearable device; determining a first control parameter based on the first parameter and the second parameter; processing the first control parameter using a first preset model to obtain a second control parameter; and controlling the action of the wearable device based on the second control parameter. Therefore, the embodiment of the present application can solve the technical problem of low accuracy in controlling wearable devices in the related art.

Description

Technical Field

[0001] The present application relates to the field of wearable devices, and more specifically, to a control method and device for a wearable device and a wearable device. Background Art

[0002] Wearable devices are a new technology hotspot that has only been gradually valued in recent years. For example, exoskeletons can be used in medical rehabilitation, elderly care, industrial assistance, military assistance and other fields. Exoskeletons must adapt to the physiological characteristics of the human body and meet the wearability requirements, while also meeting the robot characteristics of active energy output and assistance. In the actual movement and operation of the "human-exoskeleton" system, the role of the exoskeleton is to bear weight, assist, and output movements consistent with the human body, and the role of the human body is to drive the exoskeleton to move and keep the exoskeleton balanced.

[0003] When a person is moving, the exoskeleton quickly detects the person's movement and even predicts the person's intention to move. After detecting the person's movement, the exoskeleton needs to be able to keep up with the person's movement and output auxiliary movements to achieve the power-assisting effect. The power-assisting effect of the exoskeleton on human movement depends on tracking and predicting the person's movements. However, the complexity, diversity, and variability of human movement make the exoskeleton's movement control difficult, the main problem being the lack of coordination between human and machine movements.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present application provide a control method and apparatus for a wearable device, and a wearable device, so as to at least solve the technical problem of low accuracy in controlling the wearable device in the related art.

[0006] According to one aspect of an embodiment of the present application, a control method for a wearable device is provided, comprising: obtaining a first parameter and a second parameter, wherein the first parameter is a motion deviation between a target object and the wearable device, and the second parameter is an interaction force between the target object and the wearable device; determining a first control parameter based on the first parameter and the second parameter; processing the first control parameter using a first preset model to obtain a second control parameter; and controlling an action of the wearable device based on the second control parameter.

[0007] According to another aspect of an embodiment of the present application, a control device for a wearable device is provided, characterized in that it includes: a first acquisition module, used to acquire a first parameter and a second parameter, wherein the first parameter is a motion deviation between a target object and the wearable device, and the second parameter is an interaction force between the target object and the wearable device; a first determination module, used to determine a first control parameter based on the first parameter and the second parameter; a processing module, used to process the first control parameter using a first preset model to obtain a second control parameter; and a first control module, used to control the movement of the wearable device based on the second control parameter.

[0008] According to another aspect of an embodiment of the present invention, a computer storage medium is further provided, wherein the computer storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the above-mentioned control method of the wearable device.

[0009] According to another aspect of an embodiment of the present invention, there is further provided a robot, comprising: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the above-mentioned control method of the wearable device.

[0010] Through the above-mentioned embodiments of the present application, a first parameter of the motion deviation between the target object and the wearable device is first obtained, and a second parameter of the interaction force between the target object and the wearable device is obtained. Then, based on the first parameter and the second parameter, a first control parameter is determined, and the first control parameter is processed by using a first preset model to obtain a second control parameter. Based on the second control parameter, the action of the wearable device is controlled, thereby achieving precise control of the wearable device according to the state between the target object and the wearable device. By tracking and predicting the action of the target object, the problem of uncoordinated motion between the wearable device and the target object can be effectively reduced, thereby solving the technical problem of low accuracy in controlling the wearable device in the related technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0012] Figure 1 is a flow chart of a control method of a wearable device according to an embodiment of the present application;

[0013] Figure 2a It is a hardware configuration of an exoskeleton human-computer interaction control method according to an embodiment of the present application;

[0014] Figure 2b is a system block diagram of an exoskeleton human-computer interaction control method according to an embodiment of the present application;

[0015] Figure 3 is a schematic diagram of a control device for a wearable device according to an embodiment of the present application. DETAILED DESCRIPTION

[0016] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0017] When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are only examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims.

[0018] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. In addition, in the description of the present application, unless otherwise specified, "multiple" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are a kind of "or" relationship.

[0019] The hardware part of the wearable device is composed of mechanical components, controllers, sensors and other parts, which are combined together by overall structural parts and are also supported by a dedicated software system. The mechanical components include mechanical legs and mechanical feet. The mechanical legs are used to support the human legs, and the mechanical feet are used to support the human feet. The controller is used to control the mechanical legs and mechanical feet of the wearable device to assist human movement.

[0020] Example 1

[0021] According to an embodiment of the present application, a robot state detection method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is used in the flowchart, in some cases, the steps shown or described can be executed in an order different from this.

[0022] Figure 1 is a flow chart of a control method for a wearable device according to an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0023] Step S102, obtaining a first parameter and a second parameter.

[0024] Among them, the first parameter is the motion deviation between the target object and the wearable device, and the second parameter is the interaction force between the target object and the wearable device.

[0025] The wearable device in the above steps can be an exoskeleton, also known as an exoskeleton robot, and the target object in the above steps can be a human body, also known as an exoskeleton wearer. Among them, the exoskeleton is a wearable robot that combines man and machine, that is, an intelligent mechanical structure worn on the outside of the user's body, a wearable device that couples the human sensory organs, human thinking organs, and human movement organs with the machine perception system, machine intelligent processing center, and machine control system.

[0026] In addition, the human body and the exoskeleton can be an integral coupling system, also known as a human-exoskeleton coupling system. The human body and the exoskeleton are connected at various parts of the human body (e.g., feet, calves, thighs, waist, etc.) through straps, jackets and other structures to anchor the exoskeleton on the human body. The exoskeleton follows the body's limb movements to provide support and assistance.

[0027] In an optional embodiment, the motion parameters of each joint of the human body can be measured by an inertial measurement unit (IMU) provided on the exoskeleton, and the motion parameters of each joint of the exoskeleton can be measured by a joint encoder provided on the exoskeleton. The motion parameters of each joint of the human body and the motion parameters of each joint of the exoskeleton are used to determine the joint motion deviation between the exoskeleton and the human body, that is, the first parameter mentioned above.

[0028] The motion parameters of each joint of the human body may be the angle and angular velocity of the motion of each joint of the human body; the motion parameters of each joint of the exoskeleton may be the angle and angular velocity of the motion of each joint of the exoskeleton.

[0029] In another optional embodiment, due to the inconsistent movement between the exoskeleton and the human body, a mutual pulling and squeezing effect is formed. Therefore, the tensile and compressive interaction force between the exoskeleton and the human body, i.e., the second parameter mentioned above, can be detected in real time by a tensile and compressive sensor installed on the exoskeleton.

[0030] Step S104: determining a first control parameter based on the first parameter and the second parameter.

[0031] In an optional embodiment, the first parameter and the second parameter may be fused to obtain a fusion function, wherein the fusion function may be a linear function or a nonlinear function; when the fusion function is a linear function, it may be implemented through a weight coefficient matrix.

[0032] In another optional embodiment, the first parameter can be input into a PID controller (proportional-integral-differential controller), and then the parameter output by the PID controller and the second parameter are fused based on a weight coefficient matrix to obtain a first control parameter. The first control parameter can be used to directly control the exoskeleton so that the exoskeleton can assist the human body.

[0033] Step S106: Process the first control parameter using the first preset model to obtain a second control parameter.

[0034] The first preset model in the above steps can be a deviation gain model, which is used to obtain the compensation torque of the motion deviation between the exoskeleton and the human body. The first control parameter is compensated by using the compensation torque to obtain the second control parameter, which can make the exoskeleton's assistance to the human body more precise, thereby improving the assistance effect of the exoskeleton.

[0035] Step S108: controlling the action of the wearable device based on the second control parameter.

[0036] In an optional embodiment, each driving joint of the exoskeleton can be controlled to move based on the second control parameter, wherein the each driving joint of the exoskeleton can be a left hip driving joint, a left knee driving joint, a left ankle driving joint, a right hip driving joint, a right knee driving joint, a right ankle driving joint, etc.

[0037] For example, if it is necessary to assist the left knee of the human body, the left knee driving joint corresponding to the human thigh can be controlled to move based on the second control parameter, thereby achieving the effect of assisting the left knee of the human body.

[0038] Through the above-mentioned embodiments of the present application, a first parameter of the motion deviation between the target object and the wearable device is first obtained, and a second parameter of the interaction force between the target object and the wearable device is obtained. Then, based on the first parameter and the second parameter, a first control parameter is determined, and the first control parameter is processed by using a first preset model to obtain a second control parameter. Based on the second control parameter, the action of the wearable device is controlled, thereby achieving precise control of the wearable device according to the state between the target object and the wearable device. By tracking and predicting the action of the target object, the problem of uncoordinated motion between the wearable device and the target object can be effectively reduced, thereby solving the technical problem of low accuracy in controlling the wearable device in the related technology.

[0039] Optionally, the first control parameter is processed using the first preset model to obtain the second control parameter, including: obtaining the product of the first control parameter and the first preset parameter to obtain the second control parameter, wherein the first preset parameter is a parameter pre-stored in the first preset model.

[0040] The first control parameter in the above steps can be represented by F, and the first preset parameter can be represented by d K represents that the second control parameter can be called the compensation torque control amount of the movement deviation between the exoskeleton and the human body, which can be expressed as d τ represents.

[0041] In an optional embodiment, the second control parameter can be obtained by multiplying the first control parameter by the first preset parameter. d τ= d K.F. indicates.

[0042] Optionally, the method also includes: determining an adjustment parameter based on a second preset model and a third parameter, wherein the third parameter is a motion parameter of the target object and the adjustment parameter is a torque parameter required by the target object; obtaining the product of the adjustment parameter and the second preset parameter to obtain a third control parameter, wherein the second preset parameter is used to characterize the preference of the target object.

[0043] The second preset model in the above steps is a human inverse dynamics model, the third parameter in the above steps is a motion parameter of each joint of the human body, and the torque parameter in the above steps may be a joint torque parameter.

[0044] In an optional embodiment, the motion parameters of each joint of the human body may be input into the human body inverse dynamics model, and the joint torque parameters required when the human body moves alone, ie, the above-mentioned adjustment parameters, may be obtained.

[0045] The second preset parameter in the above steps can be set by the user according to his or her own preferences. For example, if the user needs a stronger assisting effect, the second preset parameter can be set to a larger value; if the user needs a weaker assisting effect, the second preset parameter can be set to a smaller value.

[0046] In another optional embodiment, the adjustment parameters can be used b τ represents that the second preset parameter can be used b K represents the third control parameter which can be used It means that according to the product of the adjustment parameter and the second preset parameter, the third control parameter can be obtained by To express.

[0047] Optionally, based on the second control parameter, the step of controlling the action of the wearable device includes: obtaining a sum of the second control parameter and the third control parameter, and controlling the operation of the wearable device based on the sum.

[0048] In an optional embodiment, the exoskeleton is controlled to work by the sum of the second control parameter and the third control parameter, so that the exoskeleton can assist the human body more accurately, meet the human body's assistance needs, and thus reduce the human body's exercise burden.

[0049] Optionally, the method also includes: determining a fourth control parameter based on the third parameter and a preset equation; and controlling the operation of the wearable device based on the sum of the second control parameter, the third control parameter and the fourth control parameter.

[0050] The third parameter in the above steps is the motion parameter of each joint of the human body, and the preset equation in the above steps is the exoskeleton inverse dynamics equation.

[0051] In an optional embodiment, the motion parameters of each joint of the human body can be input into the inverse dynamics equation of the exoskeleton, and the exoskeleton joint control torque required when the exoskeleton independently performs the human joint motion can be obtained, wherein the exoskeleton independently performs the human joint motion means that the exoskeleton is not worn on the human body but performs the same motion and tasks as the human joint motion (such as weight bearing, walking). If the human body performs weight bearing motion after wearing the exoskeleton, the weight bearing mass also needs to be reflected in the inverse dynamics equation of the exoskeleton. The calculated exoskeleton joint control torque is called the feedforward compensation torque required for the independent motion of the exoskeleton, that is, the fourth control parameter mentioned above.

[0052] In an optional embodiment, the wearable device is controlled based on the sum of the second control parameter, the third control parameter and the fourth control parameter, which can not only provide exoskeleton assistance according to user needs, but also avoid the influence of the exoskeleton itself on the assistance.

[0053] Optionally, the method also includes: obtaining a fifth control parameter, wherein the fifth control parameter is a torque parameter of the wearable device; and controlling the operation of the wearable device based on the sum of the second control parameter, the third control parameter, the fourth control parameter and the difference of the fifth control parameter.

[0054] The fifth control parameter in the above step is the driving joint torque output detected in real time by the joint torque sensors installed in each driving joint of the exoskeleton.

[0055] In an optional embodiment, based on the sum of the second control parameter, the third control parameter, the fourth control parameter and the difference of the fifth parameter, the effects of weight reduction and assistance can be further achieved.

[0056] Specifically, the feedforward compensation torque required for independent movement of the exoskeleton Expected assist torque of the exoskeleton on the human body Compensation torque for exoskeleton and human motion deviation d τ, actual output torque feedback of the exoskeleton system e τ, the torque deviation can be obtained by calculation The torque deviation Δτ is input into the "joint torque controller" to control the exoskeleton system, achieving the effects of exoskeleton assistance and weight reduction. In the process of direct torque control of the exoskeleton, the complex human-exoskeleton control system is decoupled into multiple torque compensation channels (feedforward compensation torque required for independent movement of the exoskeleton, expected exoskeleton assistance torque for the human body, compensation torque for deviation of movement between the exoskeleton and the human body, etc.). This makes it easy to control the specific and specific effects of the exoskeleton on the human body separately, so as to achieve comprehensive weight reduction and assistance effects.

[0057] Optionally, obtaining the first parameter includes: obtaining a third parameter and a fourth parameter, wherein the third parameter is a motion parameter of the target object and the fourth parameter is a motion parameter of the wearable device; and determining the first parameter based on a difference between the third parameter and the fourth parameter.

[0058] The fourth parameter in the above step can be obtained from the joint encoder of the exoskeleton.

[0059] In an optional embodiment, the angle and angular velocity of the driving joint movement can be detected in real time by each joint encoder, and the difference between the angle and angular velocity of the flexion and extension movement of each joint of the human body calculated based on the IMU worn by the human body can be used to obtain the joint movement deviation between the human body and the exoskeleton, that is, the above-mentioned first parameter.

[0060] Combine the following Figure 2a A preferred embodiment of the present application is described in detail with reference to the drawings.

[0061] like Figure 2aThe figure shows the hardware configuration of the exoskeleton human-computer interaction control method, which is a multi-sensor active full lower limb exoskeleton system, and is the electromechanical system body implementation of the exoskeleton human-computer interaction control method based on multiple sensors of the present application. Among them, 1 represents the right lower limb of the exoskeleton, 2 represents the right hip joint, 3 represents the right thigh pressure sensor, 4 represents the right thigh IMU, 5 represents the right knee joint, 6 represents the right thigh IMU, 7 represents the right thigh pressure sensor, 8 represents the right ankle joint, 9 represents the right foot IMU, 10 represents the exoskeleton waist, 11 represents the left hip joint (the joint contains a motor, an encoder, and a torque sensor), 12 represents the left thigh pressure sensor, 13 represents the left thigh IMU, 14 represents the left lower limb of the exoskeleton, 15 represents the left knee joint, 16 represents the left calf IMU, 17 represents the left calf pressure sensor, 18 represents the left ankle joint, 19 represents the left foot IMU, 20 represents the human body, 21 represents the waist and back IMU, 22 represents the left thigh structure, 23 represents the right calf structure, 24 represents the right foot structure, 25 represents the left calf structure, and 26 represents the left foot structure.

[0062] Figure 2a The hardware configuration includes the exoskeleton waist tied to the human body, the exoskeleton left lower limb tied to the human body's left leg, and the exoskeleton right lower limb tied to the human body's right leg. The diagram does not show the straps used to tie the relevant parts of the exoskeleton to the body. The straps can be made of textiles and non-woven fabrics, leather and artificial leather, plastic products, rubber products, etc., or a mixture of them. The binding part strives to be firm and not loose, but the comfort of the human body also needs to be considered. The waist strap firmly ties the exoskeleton waist to the human waist, and the waist and back IMU (inertial measurement unit) can also be tied to the human waist through the strap, or the waist and back IMU is installed in the strap tied to the human waist. The IMU can output the angle, angular velocity, and acceleration of its own posture in three-dimensional space, so the waist and back IMU can detect the posture and movement of the human torso in real time. The posture matrix of the human torso described in the world coordinate system obtained by the waist and back IMU in real time is recorded as The exoskeleton waist is the installation base for the exoskeleton left lower limb and the exoskeleton right lower limb. The exoskeleton left lower limb and the exoskeleton right lower limb are connected to the exoskeleton waist through joints. At the same time, the exoskeleton waist is also the installation and expansion base for other exoskeleton parts, such as the weight-bearing bracket on the waist and back. Like the human body structure, the exoskeleton left lower limb and the exoskeleton right lower limb are in a mirror-symmetrical state.

[0063] The left lower limb of the exoskeleton is respectively tied to the left thigh, left calf and left foot of the human body by straps. The left hip joint of the left lower limb of the exoskeleton is arranged in the coaxial direction with the flexion and extension movement of the human hip joint, and the motor on the joint can realize the flexion and extension movement control of the left hip joint of the left lower limb of the exoskeleton. The left knee joint of the left lower limb of the exoskeleton is arranged in the coaxial direction with the flexion and extension movement of the human knee joint, and the motor on the joint can realize the flexion and extension movement control of the left knee joint of the left lower limb of the exoskeleton. The left ankle joint of the left lower limb of the exoskeleton is arranged in the coaxial direction with the flexion and extension movement of the human ankle joint, and the motor on the joint can realize the flexion and extension movement (dorsiflexion and plantar flexion) control of the left ankle joint of the left lower limb of the exoskeleton. The left hip joint, left knee joint and left ankle joint of the exoskeleton are all equipped with drive unit modules, each of which contains components such as motors, encoders, torque sensors, etc., so that the drive unit module can drive and control the corresponding joint degrees of freedom, and can also detect the joint output torque, angular velocity and angle of joint movement in real time.

[0064] The structure between the left hip joint and the left knee joint of the exoskeleton is called the left thigh structure of the exoskeleton, which is used for bearing force, binding, installing the left thigh pulling pressure sensor, and adjusting the size between the left hip joint and the left knee joint of the exoskeleton according to the actual body size of the exoskeleton wearer. The structure between the left knee joint and the left ankle joint of the exoskeleton is called the left calf structure of the exoskeleton, which is used for bearing force, binding, installing the left calf pulling pressure sensor, and adjusting the size between the left knee joint and the left ankle joint of the exoskeleton according to the actual body size of the exoskeleton wearer. The structure below the left ankle joint of the exoskeleton is the left foot structure of the exoskeleton, which is used for bearing force, binding, and adjusting the size between the left ankle joint of the exoskeleton and the ground according to the actual body size of the exoskeleton wearer.

[0065] The base of the exoskeleton left thigh tension and pressure sensor is fixedly connected to the left thigh structure, and the other end is firmly connected to the strap of the exoskeleton on the left thigh of the human body. Thus, the left thigh tension and pressure sensor connects the left thigh structure of the exoskeleton and the left thigh of the human body, and can detect the tension and compression interaction force f between the left thigh structure of the exoskeleton and the left thigh of the human body in real time. lt The left thigh IMU can also be tied to the left thigh of the human body by a strap, or the left thigh IMU can be installed in the strap tied to the left thigh of the human body. In this way, the left thigh IMU can detect the posture and movement of the left thigh of the human body in real time. The posture matrix of the left thigh of the human body described in the world coordinate system obtained by the left thigh IMU in real time is recorded as Combined with the real-time posture of waist and back IMU Real-time posture with left thigh IMU The flexion and extension angle of the left hip joint can be calculated Its angular velocity In addition, the left hip joint of the exoskeleton is equipped with an encoder that can detect the angle of the left hip joint of the exoskeleton in real time. e θ lh and angular velocity The left hip joint of the exoskeleton is equipped with a torque sensor, which can detect the output torque value of the left hip joint of the exoskeleton in real time. e τ th .

[0066] The base part of the exoskeleton left calf tension pressure sensor is fixedly connected to the left calf structure, and the other end is firmly connected to the strap of the exoskeleton on the left calf of the human body. Thus, the left calf tension pressure sensor connects the left calf structure of the exoskeleton and the left calf of the human body, and can detect the tension and compression interaction force f between the left calf structure of the exoskeleton and the left calf of the human body in real time. ls The left calf IMU can also be tied to the left calf of the human body by a strap, or the left calf IMU can be installed in the strap tied to the left calf of the human body. In this way, the left calf IMU can detect the posture and movement of the left calf of the human body in real time. The posture matrix of the left calf of the human body described in the world coordinate system obtained by the left calf IMU in real time is recorded as Combined with the real-time posture of the left thigh IMU Real-time posture of the left calf IMU The flexion and extension angle of the left knee joint can be calculated Its angular velocity In addition, the left knee joint of the exoskeleton is equipped with an encoder that can detect the angle of the left knee joint of the exoskeleton in real time. e θ lk and angular velocity The left knee joint of the exoskeleton is equipped with a torque sensor, which can detect the output torque value of the left knee joint of the exoskeleton in real time. e τ lk .

[0067] The left foot IMU can also be tied to the left foot of the human body through the straps on the left foot structure of the exoskeleton, or the left foot IMU can be installed in the straps tied to the left foot of the human body. In this way, the left foot IMU can detect the posture and movement of the left foot of the human body in real time. The posture matrix of the left foot of the human body described in the world coordinate system obtained by the left foot IMU in real time is recorded as Combined with the real-time posture of the left calf IMU Real-time posture of the left foot IMU The flexion and extension angle of the left ankle joint can be calculated Its angular velocity In addition, the left ankle joint of the exoskeleton is equipped with an encoder that can detect the angle of the left ankle joint of the exoskeleton in real time. e θ la and angular velocity The exoskeleton left ankle joint is equipped with a torque sensor that can detect the output torque value of the exoskeleton left ankle joint in real time. e τ la .

[0068] The right lower limb of the exoskeleton is in a mirror-symmetric state with the left lower limb of the exoskeleton, including the configuration of each joint, the configuration of each binding, the installation of each tension and pressure sensor 11, the installation of each IMU, etc., which are all in a mirror-symmetric state with the corresponding left part. The expression of each measurement quantity of the right lower limb of the exoskeleton is as follows: rt It represents the tensile and compressive interaction force between the right thigh structure of the exoskeleton and the right thigh of the human body; Represents the posture matrix of the human body's right thigh in the world coordinate system; Indicates the flexion and extension angle of the right hip joint of the human body; It represents the flexion and extension angular velocity of the right hip joint of the human body; e θ rh represents the angle of the right hip joint of the exoskeleton; represents the angular velocity of the right hip joint of the exoskeleton; e τ rh represents the output torque value of the right hip joint of the exoskeleton; f rs It represents the tensile and compressive interaction between the right calf structure of the exoskeleton and the right calf of the human body; Represents the posture matrix of the human body's right calf in the world coordinate system; Indicates the flexion and extension angle of the right knee joint of the human body; It represents the flexion and extension angular velocity of the right knee joint of the human body; e θ rk represents the angle of the right knee joint of the exoskeleton; represents the angular velocity of the right knee joint of the exoskeleton; e τ rk Represents the output torque value of the right knee joint of the exoskeleton; Represents the posture matrix of the human body's right foot in the world coordinate system; Indicates the flexion and extension angle of the right ankle joint of the human body; It represents the flexion and extension angular velocity of the right ankle joint of the human body; e θ ra represents the angle of the right ankle joint of the exoskeleton; represents the angular velocity of the right ankle joint of the exoskeleton; e τ ra Represents the output torque value of the right ankle joint of the exoskeleton.

[0069] like Figure 2b The figure shows a system block diagram of an exoskeleton human-machine interactive control method, which describes the principle and electronic control implementation of the exoskeleton human-machine interactive control based on multiple sensors in the present application.

[0070] The control method of the present application takes the exoskeleton system as the control object, and includes two-way feedforward control and four-loop feedback control. The two-way feedforward control is human inverse dynamics feedforward and exoskeleton inverse dynamics feedforward; the four-loop feedback control is joint torque feedback, joint motion feedback, tension and compression interaction force feedback, and human body assistance feedback. The overall purpose of the two-way feedforward: based on the knowledge of the exoskeleton inverse dynamics model, human inverse dynamics, and user preferences, the direct torque control of the exoskeleton for human motion tracking and motion assistance can be quickly realized. The overall purpose of the four-loop feedback: based on the feedback signals of multiple sensors, the exoskeleton can accurately track human motion and accurately achieve the desired motion assistance effect.

[0071] Exoskeleton system Figure 2a The exoskeleton electromechanical system described, the active full lower limb exoskeleton includes 6 driving joints (left hip joint, left knee joint, left ankle joint, right hip joint, right knee joint, right ankle joint), each driven joint is driven and controlled by an independent joint driving module. Each driving unit module includes components such as motors, encoders, torque sensors, etc., wherein the motor outputs the joint torque for direct control of the exoskeleton, the torque sensor detects the joint output torque value in real time, and the encoder detects the joint motion angle and angular velocity in real time.

[0072] The driving joints are controlled by joint torque controllers. One joint torque controller can drive and control one driving joint or multiple driving joints. Each joint torque controller receives the torque deviation of each joint (the difference between the expected driving torque value of each joint and the torque value detected by each joint torque sensor 9), and outputs control and drive signals to the corresponding driving joint motor. The six joint motors (motors in the joints) installed in the driving joints receive the control and drive signals of their corresponding joint torque controllers respectively, and then output torque to control the six driving joints, so that the exoskeleton moves. The joint torque sensors installed in each driving joint detect the corresponding driving joint torque output in real time as a torque feedback signal, which is used to adjust the output torque of each driving joint so that each driving joint tracks the expected driving joint torque. The torque feedback signal is recorded as e τ=[ e τ lh e τ lk e τ la e τ rh e τ rk e τ ra ] T This constitutes the joint torque feedback loop in this method.

[0073] Among them, each joint encoder 10 on the 6 driving joints detects the angle and angular velocity of the driving joint movement in real time, and the difference between the angle and angular velocity of the flexion and extension movement of each joint of the human body obtained by the IMU solution module 12 based on the human body is used to obtain the joint movement deviation between the human body and the exoskeleton. The 6 joint movement deviations corresponding to the 6 driving joints are: the left hip joint movement deviation of the human body and the exoskeleton b θ lh - e θ lh , left knee joint motion deviation of human and exoskeleton b θ lk - e θ lk , the left ankle joint motion deviation of human and exoskeleton b θ la - e θ la , right hip joint motion deviation of human and exoskeleton b θ rh - e θ rh , right knee joint motion deviation of human and exoskeleton b θ rk - e θ rk , right ankle joint motion deviation of human and exoskeleton b θ ra - e θ ra The joint motion deviation between the human body and the exoskeleton is introduced as input into the motion and force deviation fusion module, thus forming a joint motion feedback loop.

[0074] The inconsistency between human movement and exoskeleton movement results in mutual pulling and squeezing. The four tension and pressure sensors installed on the left and right thigh straps and the left and right calf straps detect the interaction forces between the human body and the exoskeleton at four locations on the left and right thighs and the left and right calves (f lt 、f ls 、f rt 、f rs The tension and compression interaction forces between the human body and the exoskeleton are introduced into the "motion and force deviation fusion" module, thus forming a tension and compression interaction force feedback loop.

[0075] There is a motion-force coupling relationship between the joint motion deviation (i.e., motion interaction) between the human body and the exoskeleton, and the tension-compression interaction force (i.e., force interaction) between the human body and the exoskeleton. In other words, the joint motion feedback loop and the tension-compression interaction force feedback loop cannot be completely decoupled. In this application, the control effects of the two feedback loops are fused through the motion and force deviation fusion module. The fusion function is recorded as:

[0076] F( b θ lh - e θ lh , b θ lk - e θ lk , b θ la - e θ la , b θ rh - e θ rh , b θ rk - e θ rk , b θ ra - e θ ra ,f lt , f ls , f rt , f rs ).

[0077] The fusion function is a six-dimensional function, corresponding to the six driving joints. The fusion function can be a linear function or a nonlinear function. The simplest linear fusion can be achieved through the weight coefficient matrix:

[0078]

[0079] Among them, F lh Affects the torque control of the left hip joint, F lk Affects the torque control of the left knee joint, F la Affects the torque control of the left ankle joint, F rh Affects the torque control of the right hip joint, F rk Affects the torque control of the right knee joint, F ra The torque control that affects the right ankle joint. The weight coefficient matrix is:

[0080]

[0081] It can be seen from the weight coefficient matrix that: the motion deviation of the corresponding joint only affects the torque control of the corresponding joint; the tension and compression interaction forces at the thigh and calf affect the hip joint control torque and the knee joint control torque; the interaction force of the left lower limb will not affect the joint control torque of the right lower limb, and vice versa; the tension and compression interaction forces at the thigh and calf have no effect on the ankle joint control torque, and the ankle joint control torque is only affected by the motion deviation of the ankle joint.

[0082] Among them, the weight coefficient matrix is ​​adjusted according to the actual usage and actual user strategy:

[0083] For example, if the user's sensitivity to the tensile and compressive interaction force is greater than the motion deviation, then the weights of the tensile and compressive interaction force between the human body and the exoskeleton (respectively ) is greater than the weight of the joint motion deviation between the human body and the exoskeleton ( θ w lh , θ w lk , θ w la , θ w rh , θ w rk , θ w ra )); For example, if the user is more concerned about the exoskeleton's assistance to the human hip joint, then the weight coefficient of the hip joint movement ( θ w lh , θ w rh ) is greater than the motion weight coefficient of the knee and ankle joints ( θ w lk , θ w la , θ w rk , θ w ra ); For example, if the user wants to feel less tension and compression interaction force at the thigh (i.e. less resistance when the thigh moves), the weight coefficient of the tension and compression interaction force at the thigh is Greater than the weight coefficient of the tension-compression interaction force at the calf

[0084] There are many ways to construct a fusion function. Here is another example: for example, the joint motion deviation between the human body and the exoskeleton is first passed through a PID controller, and then fused with the tensile and compressive interaction forces between the human body and the exoskeleton based on a weight coefficient matrix.

[0085] The "motion and force deviation fusion 1" module needs further explanation. Through the construction of the fusion function F, motion interaction and force interaction can be represented simultaneously or independently in the fusion function. That is to say, the motion and force deviation fusion module is compatible with different human-exoskeleton interaction control types such as only motion interaction, only force interaction, and both motion interaction and force interaction.

[0086] The six-dimensional fusion function F obtained by the "motion and force deviation fusion" module passes through the deviation gain module 2 to obtain the compensation torque control value of the exoskeleton and human motion deviation d τ= d K·F. Deviation gain dK is a six-dimensional vector corresponding to the gain value vector on the six driving joints. Thus, the desired control of the joint motion feedback loop and the tension-compression interaction force feedback loop is merged and then enters the joint torque controller 3.

[0087] The joint torque, joint movement, interaction force, etc. output by the exoskeleton main system form a power-assisting effect on the exoskeleton wearer 13 (more precisely, the human musculoskeletal system of the exoskeleton wearer). The exoskeleton wearer can feel that his movement intention is tracked by the exoskeleton and his musculoskeletal output is assisted by the exoskeleton. In this way, when the movement intention represented by the neural signal emitted by the human brain nervous system 14 is achieved, the human musculoskeletal system of the exoskeleton wearer can output a smaller muscle force than when not wearing the exoskeleton. On the contrary, if the exoskeleton wearer puts on the exoskeleton to exercise, he finds that the exoskeleton cannot track his movement, and the exoskeleton does not assist the wearer, or even hinders the wearer's movement and increases the wearer's burden. In this case, in order to achieve the movement intention emitted by the human brain nervous system, the human musculoskeletal system of the exoskeleton wearer needs to output a larger muscle force than when not wearing the exoskeleton. Thus, a feedback loop for human assistance is formed between the wearer and the exoskeleton, which is the outermost feedback loop. The joint torque feedback loop, joint motion feedback loop, tension and compression interaction force feedback loop, and human body assistance feedback loop constitute the four-layer feedback loop of the exoskeleton human-computer interaction control method from the inside to the outside, enabling the exoskeleton to accurately track human motion and accurately achieve the desired motion assistance effect.

[0088] In the entire control system, the motor intention neural signal of the human brain nervous system of the exoskeleton wearer is the control signal source, and the human musculoskeletal system executes the corresponding motor intention to perform limb movements (such as walking, running, sitting down, standing up, climbing stairs, etc.). Seven IMU sensors (waist and back IMU, left thigh IMU, right thigh IMU, left calf IMU, right calf IMU, left foot IMU, right foot IMU) are installed on the human waist and back, left and right thighs, left and right calves, left and right feet, etc., to obtain the real-time data collected by these IMU sensors, and through the human motion module based on the IMU worn by the human body, the following are calculated: the flexion and extension angle of the left hip joint of the human body b θ lh Its angular velocity Human right hip flexion and extension angle b θ rh Its angular velocity Human left knee flexion and extension angle b θ lk Its angular velocity Human right knee flexion and extension angle b θ rk Its angular velocity Human left ankle flexion and extension angle b θla Its angular velocity Human right ankle flexion and extension angle b θ ra Its angular velocity The flexion and extension angles and angular velocities of each of these joints constitute the human joint movement (to be more precise, the human lower limb joint movement under the method of the present application).

[0089] The two-way feedforward is based on the setting of the exoskeleton inverse dynamics model, the human inverse dynamics model 5, and the user preference 6 to achieve predictive control of exoskeleton tracking and assisting human movement, so that the exoskeleton human-computer interaction control system in this application can quickly obtain the desired control effect (i.e., the effect of weight bearing and assistance).

[0090] The "Feedforward Compensation 4 Based on Exoskeleton Inverse Dynamics Model" module is essentially the inverse dynamics equation of the exoskeleton and the applied weight. The human joint motion is input, and the exoskeleton joint control torque required for the exoskeleton to independently execute the human joint motion is calculated. The so-called independent execution of the human joint motion by the exoskeleton means that the exoskeleton is not worn on the human body but performs the same motion and tasks as the human joint motion (such as weight bearing, walking). If the human body performs weight-bearing exercise after wearing the exoskeleton, the weight-bearing mass also needs to be reflected in the inverse dynamics equation of the exoskeleton. The calculated exoskeleton joint control torque is called the feedforward compensation torque required for independent movement of the exoskeleton, denoted as The compensation torque corresponding to each drive switch is also six-dimensional. The exoskeleton inverse dynamics model can be obtained by referring to the dynamics modeling method of the bipedal walking robot, which is not expanded in this application. We call this feedforward the exoskeleton inverse dynamics feedforward. The purpose of this feedforward is (1) the static and dynamic loads generated by the external weight are borne by the exoskeleton so that the human body does not feel the burden of the heavy object, and (2) to eliminate the influence of the exoskeleton's main body dynamics on the wearer (or to eliminate the exoskeleton's own hindrance to the wearer's movement).

[0091] In addition to compensating for the dynamic burden of external loads and the dynamic burden of the exoskeleton itself, the muscle force during the free movement of the human body also needs to be compensated and assisted by the exoskeleton, which can further reduce the human body's movement consumption and reduce movement fatigue. In this application, the interaction of controlling the exoskeleton can only be generated after the human body moves. Any human body movement requires muscle output and energy consumption, so the power-assisting effect cannot achieve full power-assistance (that is, the human body can achieve any movement intention without any effort); at the same time, excessive power-assisting effect means the expansion of system gain, making the exoskeleton output force too large to affect the wearer's safety, and even excessive system gain makes the system unstable and causes accidents; finally, partial compensation power-assistance while retaining the interaction between the human body and the exoskeleton can satisfy the wearer's sense of control over the exoskeleton.

[0092] The "Human Inverse Dynamics Model" module is an inverse dynamics model of the human musculoskeletal system. By inputting the human joint motion, the human joint torque corresponding to each human joint is obtained, which is synthesized by the muscle force. In this application, the "Human Inverse Dynamics Model" module outputs the flexion and extension torque of the left hip joint, the right hip joint, the left knee joint, the right knee joint, the left ankle joint, and the right ankle joint. The vector composed of the flexion and extension torque of the six joints is denoted as b τ. The exoskeleton wearer sets the parameters of the "Assistance Gain 7" module through the exoskeleton's "Usage Preference Center" module based on his or her expectations of the exoskeleton's assistance to his or her movements (the effect of reducing burden) and his or her preference for the exoskeleton's controllability (the feeling of human-machine interaction). b K, so that the exoskeleton is set according to the wearer, partially compensating for the joint torque required by the human body itself b τ. Parameters of the "boost gain" module b K is a six-dimensional parameter vector, taking into account the partial boost effect, b The values ​​of each component of K are between 0 and 1, and the specific values ​​are set according to the wearer's preference. Through the "human inverse dynamics model" feedforward, the desired exoskeleton assist torque on the human body is obtained. Realize the auxiliary driving effect of the exoskeleton on human movement (that is, the power-assisting effect), calculate

[0093] Based on two-way feedforward and four-loop feedback, the feedforward compensation torque required for independent movement of the exoskeleton Expected assist torque of the exoskeleton on the human body Compensation torque for exoskeleton and human motion deviation d τ, actual output torque feedback of the exoskeleton system 8 e τ, the torque deviation can be obtained by calculation The torque deviation Δτ is input into the "joint torque controller" to control the exoskeleton system, achieving the effects of exoskeleton assistance and weight reduction. In the process of direct torque control of the exoskeleton, the complex human-exoskeleton control system is decoupled into multiple torque compensation channels (feedforward compensation torque required for independent movement of the exoskeleton, expected exoskeleton assistance torque for the human body, compensation torque for deviation of movement between the exoskeleton and the human body, etc.). This makes it easy to control the specific and specific effects of the exoskeleton on the human body separately, so as to achieve comprehensive weight reduction and assistance effects.

[0094] Example 2

[0095] According to an embodiment of the present application, a control device for a wearable device is also provided, which can execute the control method for the wearable device in the above embodiment. The specific implementation method and preferred application scenario are the same as those in the above embodiment and will not be repeated here.

[0096] Figure 3 is a schematic diagram of a control device for a wearable device according to an embodiment of the present application, such as Figure 3 As shown, the device comprises:

[0097] A first acquisition module 40, configured to acquire a first parameter and a second parameter, wherein the first parameter is a motion deviation between the target object and the wearable device, and the second parameter is an interaction force between the target object and the wearable device;

[0098] A first determination module 42, configured to determine a first control parameter based on the first parameter and the second parameter;

[0099] A processing module 44, configured to process the first control parameter using the first preset model to obtain a second control parameter;

[0100] The first control module 46 is used to control the movement of the wearable device based on the second control parameter.

[0101] Optionally, the device also includes: a second determination module, used to determine the adjustment parameter based on the second preset model and the third parameter, wherein the third parameter is the motion parameter of the target object, and the adjustment parameter is the torque parameter required by the target object; a second acquisition module, used to obtain the product of the adjustment parameter and the second preset parameter to determine the third control parameter; and a second control module, used to control the operation of the wearable device based on the sum of the second control parameter and the third control parameter.

[0102] Optionally, the processing module includes: a first acquisition unit, used to acquire the product of the first control parameter and the first preset parameter to obtain the second control parameter, wherein the first preset parameter is a parameter pre-stored in the first preset model.

[0103] Optionally, the device also includes: a third determination module, used to determine the adjustment parameter according to the second preset model and the third parameter, wherein the third parameter is the motion parameter of the target object, and the adjustment parameter is the torque parameter required by the target object; a third acquisition module, used to obtain the product of the adjustment parameter and the second preset parameter to obtain a third control parameter, wherein the second preset parameter is used to characterize the preference of the target object; a third control module, used to control the action of the wearable device based on the second control parameter, including the steps that the third acquisition module is also used to obtain the sum of the second control parameter and the third control parameter, and control the operation of the wearable device based on the sum.

[0104] Optionally, the apparatus further includes: a fourth determination module, used to determine a fourth control parameter based on the third parameter and a preset equation; and a fourth control module, used to control the operation of the wearable device based on the sum of the second control parameter, the third control parameter and the fourth control parameter.

[0105] Optionally, the device also includes: a fourth acquisition module, used to obtain a fifth control parameter, wherein the fifth control parameter is a torque parameter of the wearable device; a fifth control module, used to control the operation of the wearable device based on the sum of the second control parameter, the third control parameter, the fourth control parameter and the difference of the fifth control parameter.

[0106] Optionally, the first acquisition module includes: a second acquisition unit, used to acquire a third parameter and a fourth parameter, wherein the third parameter is a motion parameter of the target object and the fourth parameter is a motion parameter of the wearable device; and a determination unit, used to determine the first parameter based on the difference between the third parameter and the fourth parameter.

[0107] Example 3

[0108] According to an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned control method of the wearable device.

[0109] Example 4

[0110] According to an embodiment of the present invention, a wearable device is also provided, including: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the control method of the wearable device in the above-mentioned embodiment 1.

[0111] Through the above-mentioned embodiments of the present application, a first parameter of the motion deviation between the target object and the wearable device is first obtained, and a second parameter of the interaction force between the target object and the wearable device is obtained. Then, based on the first parameter and the second parameter, a first control parameter is determined, and the first control parameter is processed by using a first preset model to obtain a second control parameter. Based on the second control parameter, the action of the wearable device is controlled, thereby achieving precise control of the wearable device according to the state between the target object and the wearable device. By tracking and predicting the action of the target object, the problem of uncoordinated motion between the wearable device and the target object can be effectively reduced, thereby solving the technical problem of low accuracy in controlling the wearable device in the related technology.

[0112] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0113] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0114] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0115] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0116] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0117] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0118] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0119] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0120] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A control method for a wearable device, It is characterized in that include: Acquire a first parameter and a second parameter, wherein the first parameter is a motion deviation between a target object and a wearable device, and the second parameter is an interaction force between the target object and the wearable device; Determine a first control parameter based on the first parameter and the second parameter, wherein the first control parameter is obtained by fusing the first parameter and the second parameter, or a parameter adjusted according to the first parameter and the second parameter; Processing the first control parameter by using a first preset model to obtain a second control parameter, wherein the second control parameter is obtained by compensating the first control parameter by a compensation torque, and the compensation torque is determined by the first preset model; Based on the second control parameter, controlling the action of the wearable device; The method also includes: determining an adjustment parameter according to a second preset model and a third parameter, wherein the third parameter is a motion parameter of the target object, and the adjustment parameter is a torque parameter required by the target object; obtaining the product of the adjustment parameter and the second preset parameter to obtain a third control parameter, wherein the second preset parameter is used to characterize the preference of the target object; based on the second control parameter, the step of controlling the action of the wearable device includes: obtaining a sum of the second control parameter and the third control parameter, and controlling the operation of the wearable device based on the sum.

2. The method according to claim 1, It is characterized in that Processing the first control parameter using a first preset model to obtain a second control parameter includes: The product of the first control parameter and a first preset parameter is obtained to obtain the second control parameter, wherein the first preset parameter is a parameter pre-stored in the first preset model.

3. The method according to claim 1, It is characterized in that The method further comprises: Determining a fourth control parameter based on the third parameter and a preset equation; Based on the sum of the second control parameter, the third control parameter and the fourth control parameter, the wearable device is controlled to operate.

4. The method according to claim 3, It is characterized in that The method further comprises: Acquire a fifth control parameter, wherein the fifth control parameter is a torque parameter of the wearable device; Based on the sum of the second control parameter, the third control parameter, the fourth control parameter and the difference of the fifth control parameter, the wearable device is controlled to operate.

5. The method according to claim 1, It is characterized in that Get the first parameter, including: Acquire a third parameter and a fourth parameter, wherein the third parameter is a motion parameter of the target object, and the fourth parameter is a motion parameter of the wearable device; The first parameter is determined based on a difference between the third parameter and the fourth parameter.

6. A control device for a wearable device, It is characterized in that include: A first acquisition module, configured to acquire a first parameter and a second parameter, wherein the first parameter is a motion deviation between a target object and a wearable device, and the second parameter is an interaction force between the target object and the wearable device; A first determining module, configured to determine a first control parameter based on the first parameter and the second parameter, wherein the first control parameter is obtained by fusing the first parameter and the second parameter, or a parameter adjusted according to the first parameter and the second parameter; a processing module, configured to process the first control parameter using a first preset model to obtain a second control parameter, wherein the second control parameter is obtained by compensating the first control parameter by a compensation torque, and the compensation torque is determined by the first preset model; A first control module, configured to control the movement of the wearable device based on the second control parameter; The device is also used to: determine an adjustment parameter based on a second preset model and a third parameter, wherein the third parameter is a motion parameter of the target object, and the adjustment parameter is a torque parameter required by the target object; obtain the product of the adjustment parameter and the second preset parameter to obtain a third control parameter, wherein the second preset parameter is used to characterize the preference of the target object; based on the second control parameter, the step of controlling the action of the wearable device includes: obtaining the sum of the second control parameter and the third control parameter, and controlling the operation of the wearable device based on the sum.

7. The device according to claim 6, It is characterized in that The device also includes: A second determination module is used to determine an adjustment parameter according to a second preset model and a third parameter, wherein the third parameter is a motion parameter of the target object, and the adjustment parameter is a torque parameter required by the target object; A second acquisition module is used to obtain the product of the adjustment parameter and the second preset parameter to determine a third control parameter; The second control module is used to control the operation of the wearable device based on the sum of the second control parameter and the third control parameter.

8. A computer storage medium, It is characterized in that The computer storage medium stores a plurality of instructions, which are suitable for being loaded by a processor and executing the method steps according to any one of claims 1 to 5.

9. A wearable device, It is characterized in that include: A processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the method steps as claimed in any one of claims 1 to 5.

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