WO2018000854A1

WO2018000854A1 - Human upper limb motion intention recognition and assistance method and device

Info

Publication number: WO2018000854A1
Application number: PCT/CN2017/076273
Authority: WO
Inventors: 刘若鹏; 舒良轩; 王宇驰
Original assignee: 深圳光启合众科技有限公司
Priority date: 2016-06-29
Filing date: 2017-03-10
Publication date: 2018-01-04
Also published as: CN107538469A

Abstract

A method and device for motion intention recognition and assistance of a human upper limb based on a three-dimensional force sensor. The upper limbs of the human body are equipped with an exoskeleton manipulator. The method comprises the following steps: collecting three-dimensional force data between the exoskeleton manipulator and the upper limb of the human body in real time; acquiring position data of each exoskeleton manipulator joint at the current time point; obtaining desired position data at the next time point of each exoskeleton manipulator joint by calculating the three-dimensional force data and the position data at the current time point; generating a control signal for driving the exoskeleton manipulator according to the position data at the current time point and the desired position data at the next time point of the exoskeleton manipulator; and controlling the exoskeleton manipulator to perform the corresponding motion according to the control signal to assist the upper limb of the human body.

Description

Method and device for performing motion intent recognition and assistance on human upper limbs

Technical field

The invention relates to the field of limb movement intent recognition and assistance.

Background technique

Currently, motion recognition of limbs is mainly performed by myoelectric sensors. Since the neuromuscular system produces bioelectrical changes during random and involuntary activities, a one-dimensional voltage time series signal can be obtained by attaching the myoelectric sensor to the surface of the limb and guiding and amplifying the surface electrode. The system using the myoelectric sensor acquires the motion intention of the limb by pattern recognition of the acquired signal.

However, the acquisition process using the myoelectric sensor is inconvenient, the acquired signal is difficult to recognize, and the modeling is complicated.

The present disclosure has been made with respect to, but not limited to, the many factors described above.

Summary of the invention

A brief overview of one or more aspects is provided below to provide a basic understanding of these aspects. This summary is not an extensive overview of all aspects that are conceived, and is not intended to identify key or critical elements in all aspects. Its sole purpose is to present some concepts of one or more aspects

According to an aspect of the present disclosure, a method for performing motion intent recognition and assisting on a human upper limb is provided, the exoskeleton robot arm being mounted on the upper limb of the human body, the method comprising the steps of: acquiring the exoskeleton robot arm in real time And three-dimensional force data generated between the upper limbs of the human body; acquiring position data of current joint points of the joints of the exoskeleton mechanical arm; calculating the three-dimensional force data and the position data of the current time point to obtain the exoskeleton mechanical arms The desired position data of the joint at the next time point; generating a control signal for driving the exoskeleton robot arm according to the position data of the current time point of each joint of the exoskeleton manipulator and the position data desired at the next time point; And controlling the exoskeleton arm according to the control signal to perform corresponding actions to assist the upper limb of the human body.

According to an embodiment of the present disclosure, the calculating includes: performing coordinate transformation on the three-dimensional force data; substituting the coordinate-transformed three-dimensional force data into a force impedance control model to obtain a next time point of each joint of the exoskeleton mechanical arm The desired acceleration, velocity, and position vector; and converting the resulting desired acceleration, velocity, and position vector into desired position data, wherein the control signal includes the obtained desired position data.

According to an embodiment of the present disclosure, performing coordinate transformation on the three-dimensional force data includes transforming the three-dimensional force data from a sensor coordinate system to a coordinate system fixed with respect to a back of a human body by a homogeneous transformation matrix, and obtaining the desired Converting the acceleration, velocity, and position vectors into desired position data includes substituting the resulting desired position vector into the corner of the joint of the exoskeleton manipulator and the length of each link, the origin of the sensor coordinate system The position of the position in the coordinate system fixed with respect to the back of the human body corresponds to the formula to obtain the desired position data.

According to an embodiment of the present disclosure, the coordinate transformation is

among them

Is the representation of the three-dimensional force data in the sensor coordinate system O _s ,

Is a representation of the three-dimensional force data in a coordinate system O ₀ fixed relative to the back of the human body, and T _0s is a homogeneous transformation matrix of the O _s coordinate system to the O ₀ coordinate system and

Wherein l ₁ , l ₂ , and l ₃ are the first link above the shoulder joint of the exoskeleton manipulator, the second link between the shoulder joint and the elbow joint, and the length of the third link below the elbow joint, respectively , θ ₁ , θ ₂ , θ ₃ are the internal and external rotation angles of the shoulder, the shoulder flexion angle, and the elbow flexion angle, respectively, and the obtained desired position vector is expressed as

The position correspondence formula is

According to an embodiment of the present disclosure, the time interval between the current time point and the next time point depends on the time required for the calculation, the three-dimensional force data, and the transmission time of the position data, wherein the time interval is greater than or equal to the calculation The sum of the required time and the transmission time.

According to an embodiment of the present disclosure, the force impedance control model is

among them

Is the representation of the three-dimensional force data in a coordinate system O ₀ fixed relative to the back of the human body,

a desired acceleration, velocity, and position vector representing the origin of the coordinate system O ₀ ,

An acceleration, velocity, and position vector representing the current time point of the origin of the coordinate system O ₀ measured by the exoskeleton manipulator, and wherein the parameter M represents the ideal inertia of the exoskeleton manipulator and the parameter C represents the ideal damping of the exoskeleton manipulator, The parameter K represents the ideal stiffness of the exoskeleton manipulator, and wherein the parameters are dynamically determined using an adaptive control algorithm.

According to an embodiment of the present disclosure, the parameters of the force impedance control model can be dynamically adjusted via feedback.

According to another aspect of the present disclosure, there is provided an apparatus for performing motion intent recognition and assistance on a human upper limb, the apparatus comprising: an exoskeleton robot arm mounted on an upper limb of a human body, the exoskeleton The mechanical arm can sense position data of a current time point of each joint of the exoskeleton mechanical arm; the three-dimensional force sensor collects three-dimensional force data generated between the exoskeleton mechanical arm and the upper limb of the human body in real time; the receiving unit The receiving unit is configured to receive data sensed by the three-dimensional force sensor and the robotic arm; and a processing unit configured to: position the three-dimensional force data and a current time point Calculating the data to obtain the desired position data of the joint at the next time point of each joint of the exoskeleton manipulator; generating the position according to the position data of the current time point of each joint of the exoskeleton manipulator and the desired position data of the next time point a control signal for driving the exoskeleton robot arm; and controlling the exoskeleton arm to perform phase according to the control signal Action to help the human upper limb.

According to an embodiment of the present disclosure, the calculating includes: performing coordinate transformation on the three-dimensional force data; substituting the coordinate-transformed three-dimensional force data into a force impedance control model to obtain a next time point of each joint of the exoskeleton mechanical arm The desired acceleration, velocity, and position vector; and converting the resulting desired acceleration, velocity, and position vector into desired position data, wherein the control signal includes The desired location data obtained.

among them

Wherein l ₁ , l ₂ , and l ₃ are the first link above the shoulder joint of the exoskeleton manipulator, the second link between the shoulder joint and the elbow joint, and the length of the third link below the elbow joint, respectively , θ ₁ , θ ₂ , θ ₃ are the inner (outer) rotation angle of the shoulder, the shoulder flexion angle, and the elbow flexion angle, respectively, and

Representing the obtained desired position vector, the position corresponding formula is

According to an embodiment of the present disclosure, the exoskeleton robot arm includes an angle sensor, wherein position data of a current time point of each joint of the exoskeleton robot arm is sensed by the angle sensor.

According to an embodiment of the present disclosure, the mechanical arm includes two left and right mechanical arms, and wherein the two mechanical arms are coupled together by a back bracket.

among them

As described above, by using a three-dimensional force sensor instead of an electromyography sensor to perform motion intent recognition on the upper limb of the human body, the disadvantages of signal acquisition in the prior art, difficulty in recognition of signals, and the like are overcome, and the modeling of the acquired signal is relatively simple. This makes it easier and faster to perform human body upper limb motion intent recognition, thereby improving the accuracy and efficiency of recognition.

DRAWINGS

The above features and advantages of the present invention will be better understood from the following description of the appended claims. In the figures, components are not necessarily drawn to scale, and components having similar related features or features may have the same or similar reference numerals.

1 is a block diagram of an apparatus for performing motion intent recognition and assistance on a human upper limb based on a three-dimensional force sensor in accordance with the present disclosure.

2 is a schematic skeletal model diagram of an apparatus for performing motion intent recognition and assistance on a human upper limb based on a three-dimensional force sensor in accordance with the present disclosure.

3 is a flow chart of a method for motion intent recognition and assistance of a human upper limb based on a three-dimensional force sensor in accordance with the present disclosure.

detailed description

The invention is described in detail below with reference to the drawings and specific embodiments. It is to be noted that the aspects described below in conjunction with the drawings and the specific embodiments are merely exemplary and are not to be construed as limiting the scope of the invention.

It will be understood that although various embodiments are illustrated herein with human upper limbs as an example, embodiments of the present disclosure may be applied to upper limbs, lower limbs, and the like of other animals or robots. Moreover, it will also be appreciated that embodiments of the present disclosure may be applied to a whole body exoskeleton, rather than just a limb. However, for the sake of brevity, the various embodiments of the present disclosure are described below only for human upper limbs.

1 shows a block diagram of an apparatus 100 for motion intent recognition and assistance of a human upper limb based on a three-dimensional force sensor in accordance with the present disclosure.

As shown in FIG. 1, the device 100 includes a three-dimensional force sensor 102, an exoskeleton robot arm 103, a receiving unit 104, and a processing unit 101. In the example shown in Figure 1,

Is the contact force between the exoskeleton robot 103 and the human; the three-dimensional force sensor 102 can collect the three-dimensional force data generated between the exoskeleton robot 103 and the upper limb of the human body in real time.

And represent it as

which is

It is represented in the sensor coordinate system of the three-dimensional force sensor 102. Subsequently, as shown in FIG. 1, the data sensed by the three-dimensional force sensor 102 in real time is transmitted to the receiving unit 104. In an example, the three-dimensional force sensor 102 can communicate with the receiving unit 104 in any suitable manner to communicate data representative of the sensed force. For example, the three-dimensional force sensor 102 can communicate with the receiving unit 104 via various wired or wireless communication technologies.

In the example shown in FIG. 1, the exoskeleton robot 103 also senses the position of the exoskeleton arm by an angle sensor (not shown) on the exoskeleton arm. For example, the exoskeleton robot arm 103 is mounted on the upper limb of the human body, and can sense position data of the current time point of each joint of the exoskeleton robot arm 103. For example, as shown in FIG. 1, the exoskeleton robot arm 103 includes three arm joints, namely, a robot arm joint 1, a robot arm joint 2, and a robot arm joint 3. According to an embodiment of the present disclosure, the exoskeleton robot arm 103 includes an angle sensor, wherein the position data of the current time point of each joint of the exoskeleton robot arm 103 is sensed by the angle sensor. In an example, an angle sensor can be placed at the joints of the robot arms to obtain the position of the joints of the various arm arms. In addition, the position measured according to the angle sensor

However, in an example, the exoskeleton robot 103 may only transmit position data, and the corresponding speed and acceleration data may be calculated by the processing unit 101 based on the received position data. In yet another embodiment of the present disclosure, the exoskeleton robotic arm 103 can also include a speed sensor and/or an acceleration sensor such that corresponding speed and/or acceleration data can be directly measured and transmitted. In an example, the exoskeleton robotic arm 103 can communicate with the receiving unit 104 to communicate the sensed data in any suitable manner. For example, the exoskeleton robotic arm 103 can communicate with the receiving unit 104 via various wired or wireless communication technologies.

In accordance with yet another embodiment of the present disclosure, although the three-dimensional force sensor 102 and the exoskeleton robot 103 are shown separately in FIG. 1, those skilled in the art will appreciate that this is for illustrative purposes only. The three-dimensional force sensor 102 and the exoskeleton robot arm 103 can be integrated together or separated from one another without departing from the scope of the present disclosure. For example, the three-dimensional force sensor 102 can be integrated onto a handle that is coupled to the exoskeleton robotic arm 103, or the three-dimensional force sensor 102 can be separated from the exoskeleton robotic arm 103.

In the example shown in FIG. 1, the receiving unit 104 forwards the data sensed by the three-dimensional force sensor 102 and the exoskeleton robot 103 to the processing unit 101.

After receiving the data from the receiving unit 104, the processing unit 101 calculates a control signal for the exoskeleton robot 103 based on the data. In an embodiment, the processing unit 101 calculates the received three-dimensional force data and the position data of the current time point to obtain the desired position data of the next time point of each joint of the exoskeleton robot 103, and according to the exoskeleton robot 103 The position data of the current time point of each joint and the position data desired at the next time point generate a control signal for driving the exoskeleton robot 103. In an example, the control signal includes the desired joint position data obtained. For example, as shown in Figure 1, the control signal is the desired position, velocity, and acceleration vector.

In an example, the control signal includes three components that are respectively transmitted to the joints of the three robot arms, each component being a combination of position, velocity, and acceleration vectors. Therefore, the processing unit 101 can control the exoskeleton robot arm 103 to perform corresponding actions on the human body upper limb according to the control signal.

According to an embodiment of the present disclosure, the time interval between the current time point and the next time point depends on the time required for the calculation, the three-dimensional force data, and the transmission time of the joint position data. In an example, for example, Assuming that the time required for the processing unit to perform the calculation is L seconds, and the transmission time of the three-dimensional force data and the joint position data is M seconds, the time interval is at least equal to L+M seconds for the processing unit 101 to perform the processing efficiently. .

In an embodiment of the present disclosure, the processing unit 101 may be any device having processing capabilities, such as a stand-alone general purpose personal computer, a mobile phone, a tablet computer, a dedicated processing device, a DSP, an ASIC, or integrated with an exoskeleton robot 103. Any processing device that is together.

According to another embodiment of the present disclosure, the control signal is calculated by the processing unit 101 through a force impedance control model. The force impedance control model and the associated calculation of the control signals will be described in more detail below in connection with FIG. 2.

In an embodiment, based on the received control signal, the drive unit (not shown in FIG. 1) of the exoskeleton robot 103 controls the action of the exoskeleton robot 103 to enable the exoskeleton arm 103 to follow the movement of the limb or Provides assistance to the limbs.

According to an embodiment of the present disclosure, the device 100 includes two exoskeleton robot arms, and wherein the two exoskeleton robot arms are coupled together by a back bracket. The skeleton model diagram of this embodiment will be described in more detail below in connection with FIG.

2 is a schematic skeletal model diagram of an apparatus 200 for performing motion intent recognition and assistance on a human upper limb based on a three-dimensional force sensor, in accordance with an embodiment of the present disclosure.

As shown in FIG. 2, device 200 includes two exoskeleton

robotic arms

201, 202, and wherein the two exoskeleton robotic arms are coupled together by a back bracket 203. However, those skilled in the art will appreciate that the three-dimensional force sensor based limb intent recognition and assisting device of the present disclosure may include only one exoskeleton robotic arm. The operation of device 200 will be described below in connection with exoskeleton robotic arm 201, but those skilled in the art will appreciate that these operations are equally applicable to exoskeleton robotic arm 202.

As shown in FIG. 2, the exoskeleton robot arm 201 includes a first link l ₁ above the shoulder joint, a second link l ₂ between the shoulder joint and the elbow joint, and a third link l ₃ below the elbow joint, and Wherein the first link l ₁ and the second link l ₂ are connected by a joint 205 (shoulder joint), the second link l ₂ and the third link l ₃ are connected by a joint 204 (elbow joint), and the first link The l ₁ and the back support 203 are connected by a joint 206. In an embodiment of the present disclosure, the

joints

204, 205, 206 may be the robot arm joints 1-3 shown in FIG.

An example of use of an embodiment of the present disclosure is described below in conjunction with FIGS. 1-2.

In use, the exoskeleton robotic arm 201 is worn on the user's upper limb (eg, the left or right arm). The device 200 senses the motion intent of the wearer's upper limb by a three-dimensional force sensor at the end of the exoskeleton robotic arm 201 (eg, the three-dimensional force sensor 102 in FIG. 1). For example, the three-dimensional force sensor may be located at one end of the third link ₁₃ opposite the joint 204, or it may be separated from the third link ₁₃ . In an embodiment of the present disclosure, a three-dimensional force sensor is placed on the handle attached to the exoskeleton

robotic arms

201, 202. In this embodiment, the user's hand grasps the handle with the three-dimensional force sensor, and when the user's upper limb moves, the force is generated by the handle (such as the force shown in FIG. 1).

), the force can be obtained by three-dimensional force sensor measurement. As shown above in Figure 1, the measured three-dimensional force is represented in the sensor coordinate system O _s , ie

As can be appreciated, O _s is the follower coordinate system.

According to an embodiment of the present disclosure,

Need to be established with respect to the transformed coordinate system fixed to the back at the joints O ₀ 206. As such, the calculations performed by the processing unit 101 of FIG. 1 include coordinate transformation of the three-dimensional force data. According to an embodiment of the present disclosure, performing coordinate transformation on the three-dimensional force data includes transforming the three-dimensional force data from the sensor coordinate system to a coordinate system fixed relative to the back of the human body by the homogeneous transformation matrix. For example, the coordinate transformation is

Where T _0s is a homogeneous transformation matrix of the O _s coordinate system to the O ₀ coordinate system and

Wherein l ₁ , l ₂ , and l ₃ are the first link above the shoulder joint of the exoskeleton manipulator, the second link between the shoulder joint and the elbow joint, and the length of the third link below the elbow joint, respectively , θ ₁ , θ ₂ , and θ ₃ are the inner (outer) rotation angle of the shoulder, the shoulder flexion angle, and the elbow flexion and extension angle, respectively.

Subsequently, processing unit 101 substitutes the coordinate transformed force data into the force impedance control model to obtain the desired acceleration, velocity, and position vector, and then converts the resulting desired acceleration, velocity, and position vector into the desired joint position data. In an embodiment, the processing unit 101 will transform the resulting

Substituting the force impedance control model (for example, according to N. Hogan's force impedance control model) in the following formula:

among them

The acceleration, velocity, and position vector representing the current time point of the origin of the coordinate system O ₀ measured by the exoskeleton robot 201; and wherein the parameter M represents the ideal inertia of the robot, the parameter C represents the ideal damping of the robot, and the parameter K represents the robot's Ideal stiffness, these parameters are determined by the model of the device. Thus, solving the formula (1) can obtain the desired acceleration, velocity and position vector.

Subsequently, the processing unit 101 substitutes the obtained desired position vector into the position of the joint of the joint of the exoskeleton robot 103 and the length of each link, the origin of the sensor coordinate system in a coordinate system fixed with respect to the back of the human body. In the formula, to obtain the desired joint position data. For example, according to an embodiment of the present disclosure, the origin of the joints 204, 205, 206 of the exoskeleton robotic arm 201 and the length of each link of the exoskeleton robot 201 may represent the origin of the O _s coordinate system in the O ₀ coordinate system. Position (x ₄₀ , y ₄₀ , z ₄₀ ):

Where l ₁ , l ₂ , and l ₃ are the lengths of the first link, the second link, and the third link, respectively; θ ₁ , θ ₂ , and θ ₃ are the inner (outer) rotation angle and the shoulder flexion angle of the shoulder, respectively. And the elbow flexion angle. In this example, the desired position vector

It can be substituted into the above formula (2), and the kinematic inverse solution can be used to obtain the desired positions θ ₁ , θ ₂ , and θ _{3 of the} three joints. The desired position of the joint can be used as an input to control the movement of the drive unit (not shown in FIG. 2) of the exoskeleton robot 201, thereby enabling the exoskeleton arm to follow the intended movement of the human body or to assist the arm.

According to an embodiment of the present disclosure, the parameters M, K, and C of the force impedance control model in equation (1) are not fixed, but are dynamically determined using an adaptive control algorithm. For example, in an example The values of the parameters M, K, C can be first calculated by the adaptive control algorithm based on the received force and the position vector, and then the calculated position values are used to calculate the desired position vector. In another example, a lookup table of parameters M, K, C and corresponding forces and position vectors can be maintained; upon receiving the force and position vector, device 200 can look up the table to obtain the corresponding M, K, C values. And use these parameter values to calculate the desired position vector.

According to still another embodiment of the present disclosure, the parameters M, K, C of the force impedance control model in equation (1) can be adjusted via feedback. For example, a user wearing the exoskeleton robotic arm 201 can indicate that the calculated desired position vector always lags behind the user's intent. Based on this feedback, device 200 can recalculate and adjust the values of parameters M, K, C. Alternatively, in yet another example, the exoskeleton robotic arm 201 can also include a pressure sensor for providing pressure between the arm and the exoskeleton robotic arm. In this example, the device 200 can determine whether there is a match between the exoskeleton robot arm 201 and the user's intention by the pressure change sensed by the pressure sensor, and adjust the parameters M, K of the force impedance control model depending on the determined result. , C.

3 is a flow diagram of a method 300 of performing motion intent recognition and assistance on a human upper limb based on a three-dimensional force sensor in accordance with the present disclosure.

As shown in FIG. 3, method 300 includes acquiring, in 310, three-dimensional force data generated between the exoskeleton robot and the upper limb of the human body in real time. For example, as described above in connection with FIG. 1, the three-dimensional force sensor 102 senses the force generated by the limb in real time.

At 320, method 300 includes obtaining positional data for a current time point of each joint of the exoskeleton robotic arm. For example, as described above in connection with Figures 1-2, the exoskeleton robotic arm 103 is mounted on the upper extremity of the human body and senses its various joints (mechanical arm joints 1-3 of Figure 1,

joints

204, 205, 206 of Figure 2, The location data of, etc., and transmits this data to the receiving unit 104. According to an embodiment of the present disclosure, the data sensed by the exoskeleton arm is sensed by an angle sensor on the exoskeleton arm. For example, as described above in connection with FIG. 2, an angle sensor is mounted on the

joints

204, 205, 206 for sensing angular position data of the joint.

At 330, the method 300 further includes calculating the positional data of the three-dimensional force data and the current time point to obtain the desired position data for the next time point of each joint of the exoskeleton manipulator. For example, as described above in connection with FIG. 1 or 2, processing unit 101 processes the received data to obtain an exoskeleton robotic arm The desired position data for each joint at the next time point. In an embodiment, the calculating comprises: performing coordinate transformation on the three-dimensional force data; substituting the coordinate-transformed force data into a force impedance control model to obtain a desired acceleration, velocity, and position vector; and obtaining the desired The acceleration, velocity and position vectors are converted to the desired joint position data. In an embodiment, performing coordinate transformation of the three-dimensional force data as described above in connection with FIGS. 1-2 includes transforming the three-dimensional force data from the sensor coordinate system to a coordinate system fixed relative to the back of the human body by a homogeneous transformation matrix; Converting the resulting desired acceleration, velocity, and position vector into desired joint position data includes substituting the resulting desired position vector into the corner of the joint of the exoskeleton manipulator and the length of each link, the sensor coordinate system origin In the formula of the position in the coordinate system fixed with respect to the back of the human body, the desired joint position data is obtained. For example, equation (2) gives the corresponding formula.

At 340, method 300 includes generating a control signal that drives the exoskeleton arm based on position data at a current time point of each joint of the exoskeleton manipulator and position data desired at a next point in time. According to an embodiment of the present disclosure, the control signal is calculated by the force impedance control model, as shown in the above formula (1). According to yet another embodiment of the present disclosure, the parameters of the force impedance control model are dynamically determined using an adaptive control algorithm. According to yet another embodiment of the present disclosure, the parameters of the force impedance control model can be adjusted via feedback. For example, as described above in connection with FIG. 2, various parameters of the force impedance control model can be adjusted by lookup tables, dynamic calculations, user feedback, and the like.

At 350, method 300 further includes controlling the exoskeleton robotic arm to perform a corresponding action to assist the upper limb of the human body based on the control signal. For example, as described above in connection with FIG. 1, processing unit 101 transmits a control signal to exoskeleton robot arm 103 to control the motion of the exoskeleton robotic arm. According to an embodiment of the present disclosure, the control of the exoskeleton manipulator is achieved via a drive unit of the exoskeleton manipulator.

In an embodiment, the time interval between the current time point and the next time point depends on the time required for the calculation performed by the processing unit 101, the three-dimensional force data, and the transmission time of the joint position data. As described above in connection with Figures 1-2, the time interval is greater than or equal to the sum of the time required for the calculation and the transmission time.

Those skilled in the art will appreciate that the order of operations of the various steps described above is presented for purposes of example only, and the various steps may be performed in various suitable sequences.

The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the present disclosure will be obvious to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the public The present invention is not intended to be limited to the examples and designs described herein, but should be accorded the broadest scope of the principles and novel features disclosed herein.

Claims

A method for recognizing and assisting movement of an upper limb of a human body, wherein an exoskeleton robot arm is mounted on the upper limb of the human body, characterized in that the method comprises the following steps:

Collecting three-dimensional force data generated between the exoskeleton mechanical arm and the upper limb of the human body in real time;

Obtaining position data of a current time point of each joint of the exoskeleton robot arm;

Calculating the position data of the three-dimensional force data and the current time point position data to obtain the desired position data of each joint of the exoskeleton mechanical arm at the next time point;

Generating a control signal for driving the exoskeleton manipulator according to position data of a current time point of each joint of the exoskeleton manipulator and position data desired at a next time point;

The exoskeleton manipulator is controlled according to a control signal to perform a corresponding action to assist the upper limb of the human body.
The method of claim 1 wherein said calculating comprises:

Performing coordinate transformation on the three-dimensional force data;

Substituting the coordinate transformed three-dimensional force data into a force impedance control model to obtain a desired acceleration, velocity, and position vector for the next time point of each joint of the exoskeleton manipulator;

The resulting desired acceleration, velocity, and position vector are converted to desired position data, wherein the control signal includes the obtained desired position data.
The method of claim 2, wherein performing coordinate transformation on the three-dimensional force data comprises transforming the three-dimensional force data from a sensor coordinate system to a coordinate system fixed relative to a back of the human body by a homogeneous transformation matrix, and Converting the resulting desired acceleration, velocity, and position vector to desired position data includes substituting the resulting desired position vector into a corner of the joint of the exoskeleton arm and a length of each link The position of the sensor coordinate system origin in the position relative to the position in the coordinate system fixed to the back of the human body corresponds to the formula to obtain the desired position data.
The method of claim 3 wherein said coordinate transformation is
among them
Is the representation of the three-dimensional force data in the sensor coordinate system O s ,
Is a representation of the three-dimensional force data in a coordinate system O 0 fixed relative to the back of the human body, and T 0s is a homogeneous transformation matrix of the O s coordinate system to the O 0 coordinate system and

Wherein l 1 , l 2 , and l 3 are the first link above the shoulder joint of the exoskeleton manipulator, the second link between the shoulder joint and the elbow joint, and the length of the third link below the elbow joint, respectively , θ 1 , θ 2 , θ 3 are the internal and external rotation angles of the shoulder, the shoulder flexion angle, and the elbow flexion angle, respectively, and the obtained desired position vector is expressed as
The position correspondence formula is
The method of claim 1 wherein the time interval between the current time point and the next time point is dependent on the time required for the calculation, the three-dimensional force data, and the transmission time of the location data, wherein the time interval is greater than Or equal to the sum of the time required for the calculation and the transmission time.
The method of claim 2 wherein said force impedance control model is
among them
Is the representation of the three-dimensional force data in a coordinate system O 0 fixed relative to the back of the human body,
a desired acceleration, velocity, and position vector representing the origin of the coordinate system O 0 ,
An acceleration, velocity, and position vector representing the current time point of the origin of the coordinate system O 0 measured by the exoskeleton manipulator, and wherein the parameter M represents the ideal inertia of the exoskeleton manipulator and the parameter C represents the ideal damping of the exoskeleton manipulator, The parameter K represents the ideal stiffness of the exoskeleton manipulator, and wherein the parameters are dynamically determined using an adaptive control algorithm.
The method of claim 6 wherein the parameters of the force impedance control model are dynamically adjustable via feedback.
A device for recognizing and assisting the movement of an upper limb of a human body, characterized in that Set includes:

An exoskeleton robot arm mounted on an upper limb of the human body, the exoskeleton robot arm capable of sensing position data of a current time point of each joint of the exoskeleton robot arm;

a three-dimensional force sensor that collects three-dimensional force data generated between the exoskeleton mechanical arm and the upper limb of the human body in real time;

a receiving unit configured to receive data sensed by the three-dimensional force sensor and the robotic arm;

a processing unit configured to:

Calculating the position data of the three-dimensional force data and the current time point position data to obtain the desired position data of each joint of the exoskeleton mechanical arm at the next time point;

Generating a control signal for driving the exoskeleton manipulator according to position data of a current time point of each joint of the exoskeleton manipulator and position data desired at a next time point;

The exoskeleton manipulator is controlled according to a control signal to perform a corresponding action to assist the upper limb of the human body.
The device according to claim 8, wherein said exoskeleton robot arm includes an angle sensor, wherein position data of a current time point of each joint of said exoskeleton robot arm is sensed by said angle sensor .
The device of claim 8 wherein said robot arm comprises two left and right robot arms, and wherein the two robot arms are coupled together by a back bracket.