A self-balancing lower limb exoskeleton robot compliant walking control method

Abstract

This invention provides a compliant walking control technology for a self-balancing lower limb exoskeleton robot. The technology includes simplifying the lower limb exoskeleton robot into an inverted pendulum model and obtaining the expected center-of-mass trajectory and expected landing point trajectory from the pre-planned control program. Based on the inverted pendulum model, the expected center-of-mass trajectory, and the expected landing point trajectory, dynamic calculations are performed to obtain the expected ankle joint torque. The actual ankle joint torque of the lower limb exoskeleton is measured, and the difference between the actual and expected ankle joint torques is calculated. Based on the difference between the actual and expected ankle joint torques and the exoskeleton walking control strategy using a fractional-order viscoelastic model, a center-of-mass compensation amount is calculated. The sum of the expected center-of-mass position and the compensation amount, along with the expected landing point position, are input into an inverse kinematics solver to obtain the joint angles during lower limb exoskeleton walking. This invention improves the flexibility and compliance of the robot's control strategy.

Description

Technical Field

[0001] This invention relates to the field of robotics, and in particular to a method for controlling the compliant walking of a self-balancing lower limb exoskeleton robot. Background Technology

[0002] A self-balancing lower limb exoskeleton robot is a highly free, fully driven robot capable of dynamic, balanced walking. For individuals unable to maintain balance and walk independently, such as hemiplegic, quadriplegic, or elderly people with mobility issues, a self-balancing exoskeleton can be worn for support and protection while walking. Traditional exoskeleton robots often lack self-balancing capabilities due to structural or control algorithm limitations, requiring wearers to use assistive devices like canes or carts, which is unsuitable for those with insufficient upper limb strength. Through the design of mechanical structures and control algorithms, the self-balancing exoskeleton adds balance maintenance functionality to traditional lower limb exoskeletons. However, developing a walking control algorithm for a self-balancing exoskeleton is a challenging task. The algorithm must ensure sufficient smoothness during exoskeleton movement to avoid impacts with the ground and other external environments that could affect balance, while also guaranteeing sufficient stability and flexibility to adapt to different wearers.

[0003] The lower limb exoskeleton system is a highly nonlinear system, and modeling and controlling the exoskeleton system is a major challenge. On the one hand, because the lower limb exoskeleton needs to interact frequently with the user and the environment, its movement compliance is highly required. On the other hand, in order to ensure that different patients can use the exoskeleton for rehabilitation training, the exoskeleton control algorithm needs to have sufficient stability and flexibility. Summary of the Invention

[0004] In view of this, the present invention provides a method for controlling the compliant walking of a self-balancing lower limb exoskeleton robot to solve the above problems.

[0005] This invention provides a method for compliant walking control of a self-balancing lower limb exoskeleton robot, comprising: simplifying the lower limb exoskeleton robot into a centroid inverted pendulum model, and obtaining the expected centroid trajectory and expected foot landing trajectory of the pre-observed control plan; performing dynamic calculations based on the centroid inverted pendulum model, the expected centroid trajectory of the pre-observed control plan, and the expected foot landing trajectory to obtain the expected ankle joint torque; measuring the actual ankle joint torque of the lower limb exoskeleton and calculating the difference between the actual ankle joint torque and the expected ankle joint torque; calculating the centroid compensation amount based on the difference between the actual ankle joint torque and the expected ankle joint torque and the exoskeleton walking control strategy of the fractional viscoelastic model; inputting the expected centroid position and the sum of the centroid compensation amount, as well as the expected foot landing position, into an inverse kinematics solver to obtain the joint angles of the lower limb exoskeleton during walking.

[0006] In another implementation of the present invention, the difference between the actual torque and the desired ankle joint torque of the lower limb exoskeleton is expressed as:

[0007]

[0008] in, The actual center of mass position and reference centroid position Virtual forces between them τ is the desired torque, and τ is the actual torque; desired torque Represented as:

[0009]

[0010] in, The location of the center of mass. This is the acceleration of the center of mass.

[0011] In another implementation of the present invention, the relationship between the deviation of the positions between the centers of mass and the virtual force is expressed as:

[0012]

[0013] in, The actual location of the center of mass. For reference centroid position, and These are the actual centroid position and the expected centroid position, respectively. Derivative.

[0014] In another implementation of the present invention, the centroid compensation amount is expressed as:

[0015]

[0016] Where T is the control cycle of the controller. , .

[0017] In the compliant walking control method for a self-balancing lower limb exoskeleton robot of the present invention, the control strategy estimates the deviation between the actual center of mass and the desired center of mass based on the deviation between the actual torque and the desired torque at the ankle joint of the lower limb exoskeleton robot, and performs center of mass compensation to maintain the balance of the exoskeleton walking; the relationship between the actual center of mass and the desired center of mass is described by a fractional-order viscoelastic model to increase the compliance of the control strategy; the calculated center of mass compensation amount is combined with the offline planned trajectory, and the target joint angle of each joint at the next moment is calculated by inverse kinematics; the compliant controller based on the fractional-order viscoelastic model introduces multiple adjustable parameters to increase the flexibility and compliance of the control algorithm, eliminates the impact between the exoskeleton and the ground, avoids the exoskeleton falling, and increases the stability of the exoskeleton walking. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. By reading the detailed description of the embodiments below, the advantages and benefits of the solutions will become clear to those skilled in the art. The accompanying drawings are only for illustrating preferred embodiments and are not intended to limit the present invention. In the accompanying drawings:

[0019] Figure 1 This is a flowchart illustrating the steps of a compliant walking control method for a self-balancing lower limb exoskeleton robot according to an embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram of a simplified inverted pendulum model of an exoskeleton based on a fractional-order viscoelastic model, according to another embodiment of the present invention.

[0021] Figure 3 This is a schematic diagram of different stages of exoskeleton walking in a simulated environment, according to another embodiment of the present invention.

[0022] Figure 4 This is a schematic diagram showing the reference center position and the actual center of mass position of the exoskeleton when it walks in a simulated environment, according to another embodiment of the present invention.

[0023] Figure 5 This is a schematic diagram showing the magnitude of the centroid compensation in different directions when the exoskeleton walks in a simulated environment, according to another embodiment of the present invention.

[0024] Figure 6 This is a schematic diagram showing the actual and reference positions of the plantar pressure center when the exoskeleton of another embodiment of the present invention walks in a simulated environment. Detailed Implementation

[0025] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and thoroughly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art should fall within the protection scope of the present invention.

[0026] Figure 1 A flowchart illustrating the steps of a compliant walking control method for a self-balancing lower limb exoskeleton robot provided in an embodiment of the present invention is shown below. Figure 1 As shown, this embodiment mainly includes the following steps:

[0027] S101. Simplify the lower limb exoskeleton robot into a centroid inverted pendulum model, and obtain the expected centroid trajectory and expected landing point trajectory for the predictive control planning.

[0028] For example, such as Figure 2 As shown, the lower limb exoskeleton robot is simplified into a centroid inverted pendulum model. A linear inverted pendulum model is used as a simplified model of the exoskeleton to reduce the computational cost of the control algorithm.

[0029] S102. Based on the inverted pendulum model, the expected trajectory of the center of mass and the expected landing point trajectory of the predictive control plan, perform dynamic calculations to obtain the expected ankle joint torque.

[0030] For example, firstly, based on the linear inverted pendulum model, the exoskeleton has a principal torque in the walking direction during the walking process to maintain the balance of the exoskeleton. Desired torque It can be determined by the position of the center of mass. and center of mass acceleration get:

[0031]

[0032] S103. Measure the actual torque of the ankle joint of the lower limb exoskeleton and calculate the difference between the actual torque of the ankle joint and the expected ankle joint torque.

[0033] For example, during the actual walking process of the exoskeleton, the actual torque τ and the desired torque There is an error between them, which can be expressed as:

[0034]

[0035] in, The actual center of mass position and reference centroid position Virtual forces between them.

[0036] S104. The centroid compensation amount is obtained by calculating the difference between the actual and expected ankle joint torques of the lower limb exoskeleton and the exoskeleton walking control strategy based on the fractional viscoelastic model.

[0037] S105. Input the sum of the desired centroid position and the centroid compensation amount, as well as the desired landing point position, into the inverse kinematics solver to obtain the joint angles of each joint during lower limb exoskeleton walking.

[0038] For example, the exoskeleton centroid position actually used in the inverse kinematics solver is the sum of the desired centroid position and the centroid compensation amount.

[0039] In the compliant walking control method for a self-balancing lower limb exoskeleton robot of the present invention, the control strategy estimates the deviation between the actual center of mass and the desired center of mass based on the deviation between the actual torque and the desired torque at the ankle joint of the lower limb exoskeleton robot, and performs center of mass compensation to maintain the balance of the exoskeleton walking; the relationship between the actual center of mass and the desired center of mass is described by a fractional-order viscoelastic model to increase the compliance of the control strategy; the calculated center of mass compensation amount is combined with the offline planned trajectory, and the target joint angle of each joint at the next moment is calculated by inverse kinematics; the compliant controller based on the fractional-order viscoelastic model introduces multiple adjustable parameters to increase the flexibility and compliance of the control algorithm, eliminates the impact between the exoskeleton and the ground, avoids the exoskeleton falling, and increases the stability of the exoskeleton walking.

[0040] In another implementation of the present invention, the difference between the actual torque and the desired ankle joint torque of the lower limb exoskeleton is expressed as:

[0041]

[0042] in, The actual center of mass position and reference centroid position Virtual forces between them τ is the desired torque, and τ is the actual torque; desired torque Represented as:

[0043]

[0044] in, The location of the center of mass. This is the acceleration of the center of mass.

[0045] In another implementation of the present invention, the relationship between the deviation of the positions between the centers of mass and the virtual force is expressed as:

[0046]

[0047] in, The actual location of the center of mass. For reference centroid position, and These are the actual centroid position and the expected centroid position, respectively. Derivative.

[0048] For example, the relationship between the actual and reference centroid positions is modeled using a fractional-order viscoelastic model, yielding the relationship between the positional deviation between the centroids and the virtual force:

[0049]

[0050] make

[0051]

[0052] We can obtain:

[0053]

[0054] in, and These are the actual centroid position and the expected centroid position, respectively. Derivative.

[0055] In specific control processes, Gr is used. Unwald–Letnikov discrete fractional derivative formula:

[0056]

[0057] Defining time T as the control period of the controller, we can obtain:

[0058]

[0059] The first four terms of this summation formula are selected as the positions of the actual and desired centroids. A reliable approximation of the first derivative is then obtained:

[0060]

[0061] in, , .

[0062] Substituting the virtual force formula obtained from the fractional-order viscoelastic model into the previous relationship between virtual force, actual torque, and expected torque, we obtain the relationship between the deviation of the center of mass position and the deviation of the ankle joint torque as follows:

[0063]

[0064] In another implementation of the present invention, the centroid compensation amount is expressed as:

[0065]

[0066] Where T is the control cycle of the controller. , .

[0067] In another implementation of the present invention, a simulation experiment is performed, such as... Figure 3 As shown, a walking experiment was conducted using an exoskeleton robot in the CoppeliaSim simulation environment to verify the stability of the compliant controller based on a fractional-order viscoelastic model.

[0068] The controller parameters and physical parameters of the exoskeleton used in the simulation experiment are shown in Table 1. The controller parameters can be obtained by adjusting them a few times in the simulation environment according to the walking situation of the exoskeleton.

[0069]

[0070] Table 1

[0071] During the time interval from t=0s to t=24s, the exoskeleton will take six steps forward, each step designed to be 12 cm long. Since the exoskeleton needs a half-step at the end to maintain balance and return to its initial state, the final actual walking distance is 0.785 m. To simplify the inverse kinematics solution and improve computational efficiency, the intersection of the robot's hip joint and longitudinal section is defined as the location of the center of mass in the simulation. A compliant controller based on a fractional-order viscoelastic model uses the torque at the ankle and the required torque to calculate the center of mass compensation, thereby controlling the torque at the exoskeleton's ankle to ensure stability during walking. Figure 4 and Figure 5 As shown, the reference centroid position and the actual centroid position on the x-axis and y-axis are depicted. It can be observed that the actual position of the exoskeleton centroid oscillates around the reference centroid position and eventually converges to the reference centroid position.

[0072] like Figure 6 As shown, to verify whether the exoskeleton can maintain balance during walking, the reference position and actual position of the pressure center of the exoskeleton's foot were recorded. The closer the pressure center of the foot is to the reference position, the better it can stay in the center of the foot's support surface, thus resulting in better balance performance.

[0073] In the compliant walking control method for a self-balancing lower limb exoskeleton robot of this invention, a compliant controller based on a fractional-order viscoelastic model is proposed for stable dynamic walking of the self-balancing lower limb exoskeleton. This compliant controller, based on the fractional-order viscoelastic model, introduces multiple adjustable parameters to increase the flexibility and compliance of the control algorithm, eliminates the impact between the exoskeleton and the ground, prevents the exoskeleton from falling, and increases the stability of the exoskeleton during walking. Using this control strategy in a simulation environment, the centroid compensation is calculated through ankle joint error, and the fractional derivative order, elastic modulus, and impedance modulus are adjusted in the simulation environment to obtain the optimal control effect. Simulation results show that the compliant controller based on the fractional-order viscoelastic model can achieve dynamic and stable walking of the self-balancing exoskeleton.

[0074] Specific embodiments of the invention have now been described. Other embodiments are within the scope of the appended claims. In some cases, the actions described in the claims can be performed in a different order and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing can be advantageous.

[0075] It should be noted that all directional indications (such as up, down, left, right, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0076] In the description of this invention, the terms "first" and "second" are used only for convenience in describing different components or names, and should not be construed as indicating or implying a sequential relationship, relative importance, or implicitly specifying the number of technical features indicated. Thus, a feature defined with "first" and "second" may explicitly or implicitly include at least one of that feature.

[0077] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0078] It should be noted that although specific embodiments of the present invention have been described in detail with reference to the accompanying drawings, this should not be construed as limiting the scope of protection of the present invention. Various modifications and variations that can be made by those skilled in the art without inventive effort within the scope described in the claims still fall within the scope of protection of the present invention.

[0079] The examples of the embodiments of the present invention are intended to concisely illustrate the technical features of the embodiments of the present invention, so that those skilled in the art can intuitively understand the technical features of the embodiments of the present invention, and are not intended to be an improper limitation of the embodiments of the present invention.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling compliant walking in a self-balancing lower limb exoskeleton robot, characterized in that, include: The lower limb exoskeleton robot is simplified into a centroid inverted pendulum model, and the expected centroid trajectory and expected landing point trajectory are obtained for predictive control planning. Based on the inverted pendulum model, the expected trajectory of the center of mass in the predictive control plan, and the expected landing point trajectory, dynamic calculations are performed to obtain the expected ankle joint torque. Measure the actual torque of the ankle joint of the lower limb exoskeleton and calculate the difference between the actual torque of the ankle joint and the expected torque of the ankle joint. The centroid compensation amount is calculated based on the difference between the actual ankle joint torque and the desired ankle joint torque of the lower limb exoskeleton, and the exoskeleton walking control strategy using a fractional-order viscoelastic model. The difference between the actual ankle joint torque and the desired ankle joint torque of the lower limb exoskeleton is expressed as follows: in, The actual center of mass position and reference centroid position Virtual forces between them Let τ be the desired torque and τ be the actual torque. h The height of the exoskeleton's center of mass; The desired torque Represented as: in, The actual location of the center of mass. It is the acceleration of the center of mass; The relationship between the deviation of the positions between the centers of mass and the virtual force is expressed as follows: in, The actual location of the center of mass. For reference centroid position, and These are the actual centroid position and the expected centroid position, respectively. First derivative; The centroid compensation amount is expressed as: Where T is the control cycle of the controller. , ; The sum of the desired centroid position and the centroid compensation amount, along with the desired landing point position, are input into the inverse kinematics solver to obtain the joint angles of each joint during lower limb exoskeleton walking.

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