Method for controlling self-balancing walking of exoskeleton under unknown terrain

Abstract

The invention provides a control method for self-balancing walking of an exoskeleton under an unknown terrain. The control method comprises the steps that the tail end of a foot of an exoskeleton robot is simplified into a virtual impedance compliance control model; carrying out stress analysis on the exoskeleton robot according to the impedance compliance control model to obtain expected force and actual force of the exoskeleton robot in the movement process; carrying out calculation processing according to the expected force and the actual force, and converting a walking problem into an optimization problem; solving the optimization problem to obtain new expected values of the left and right feet; and the exoskeleton robot executes walking and standing tasks based on the new expected value. According to the method, the expected force is optimized, and the walking stability of the exoskeleton robot under the unknown terrain is improved.

Description

Technical Field

[0001] The present invention relates to the field of robotics technology, and in particular to a method for controlling an exoskeleton to walk in self-balanced manner in unknown terrain. Background Art

[0002] In recent years, with the aging of the population and the aggravation of related diseases, the number of patients with lower limb dysfunction or loss, such as hemiplegia and quadriplegia, caused by factors such as stroke, accidents, and spinal cord injury has increased rapidly. There are more than 13.7 million new cases of stroke each year worldwide, making it the third leading cause of disability in the world. Previous studies have shown that the functional prognosis of patients with lower limb weakness or loss of function can be improved through early intervention and goal-oriented training that gradually adapts to the patient's degree of injury and recovery stage. Therefore, people with motor function loss are increasingly dependent on various medical devices in their daily lives. As an auxiliary device, the lower limb exoskeleton robot can provide support and balance for patients with motor dysfunction, allowing them to restore normal walking ability.

[0003] Usually, the gait generation of lower limb exoskeleton robots is based on the assumption of a horizontal, flat, rigid ground. However, the actual application scenarios are often unstructured environments and uneven roads. The walking control algorithm of the exoskeleton robot is very sensitive to the different heights of the ground. A small height difference may cause the exoskeleton to topple over, thus causing harm to the wearer. Therefore, solving the problem of exoskeleton robots walking on uneven roads is of great significance for the practical application of exoskeleton robots. Summary of the invention

[0004] In view of this, the present invention provides a control method for an exoskeleton to self-balance walking in unknown terrain to solve the above problems.

[0005] The present invention provides a control method for self-balancing walking of an exoskeleton in unknown terrain, comprising: simplifying the foot end of an exoskeleton robot into a virtual impedance compliance control model; performing force analysis on the exoskeleton robot according to the impedance compliance control model to obtain expected force and actual force of the exoskeleton robot during movement; performing calculation processing according to the expected force and the actual force to convert the walking problem into an optimization problem; solving the optimization problem to obtain new expected values ​​of the left and right feet; and the exoskeleton robot performs walking and standing tasks based on the new expected values.

[0006] In another implementation of the present invention, the state space equation of the desired force is expressed as:

[0007]

[0008] in, y z =F m, z represents the position of the end of the foot, F m It indicates the feedback force measured by the sensor;

[0009]

[0010] Among them, F represents the force received by the end of the foot, M represents the mass coefficient, V represents the damping coefficient, K represents the spring coefficient, and T represents the detection period.

[0011] In another implementation of the present invention, the state space equation of the actual force is expressed as:

[0012]

[0013] in, y z =F m , z represents the position of the end of the foot, F m It indicates the feedback force measured by the sensor;

[0014]

[0015] Among them, F represents the force received by the end of the foot, M represents the mass coefficient, V represents the damping coefficient, and K represents the spring coefficient.

[0016] In another implementation of the present invention, the optimization problem is expressed as:

[0017]

[0018] Among them, Q and R are real symmetric positive definite matrices, Δu z Represents a state feedback device.

[0019] In another implementation of the present invention, the following state feedback device is designed to stabilize the system:

[0020]

[0021] Where, ΔF = F d -F r , F d is the expected force, F r For actual force.

[0022] In another implementation of the present invention, the new expected values ​​of the left and right feet are expressed as:

[0023]

[0024] in, The new desired positions for the left and right feet after adjustment. is the desired position of the left and right feet, ΔPL / R It is the adjustment amount of the left and right feet in the current cycle.

[0025] In another implementation of the present invention, it also includes: according to the law of movement of the self-balancing exoskeleton robot, the walking process of the self-balancing exoskeleton robot can be simplified into a center of mass dynamics model; based on the center of mass dynamics model, the expected force is calculated and optimized.

[0026] The control method of the exoskeleton for self-balancing walking in unknown terrain is based on the impedance-controlled bipedal compliant control model, which is converted into an optimization problem, thereby deriving the control law of the human-machine hybrid system during walking. The expected force calculation method is based on the center of mass dynamics, and the expected force is optimized by considering the zero-moment point stability constraint, thereby improving the stability of the exoskeleton robot when walking in unknown terrain. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. By reading the detailed description of the following implementations, the advantages and benefits of the solutions become clear to those skilled in the art. The drawings are only used to illustrate the preferred implementations and are not to be considered as limiting the present invention.

[0028] In the attached picture:

[0029] Figure 1 The figure is a flow chart of a method for controlling the self-balancing walking of an exoskeleton in unknown terrain according to an embodiment of the present invention.

[0030] Figure 2 Schematic diagram of a foot end impedance compliance control model according to an embodiment of the present invention.

[0031] Figure 3 Schematic diagram of a simulation experiment of an embodiment of the present invention.

[0032] Figure 4 Schematic diagram of a prototype experiment of an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order 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 described clearly and in detail below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in the field based on the embodiments in the embodiments of the present invention should fall within the scope of protection of the embodiments of the present invention.

[0034] Figure 1A flow chart of a control method for self-balancing walking of an exoskeleton in an unknown terrain provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, this embodiment mainly includes:

[0035] S101. Simplify the end of the foot of the exoskeleton robot into a virtual impedance compliance control model.

[0036] For example, Figure 2 As shown in the figure, taking the z direction of the left foot as an example, the end of the foot of the self-balancing exoskeleton robot is simplified into a virtual impedance compliance control model, and the force on the end of the foot and the motion equation of the end of the foot are obtained as follows:

[0037]

[0038] Among them, z is the position of the end of the foot, F is the force received by the end of the foot, M is the mass coefficient, V is the damping coefficient, and K is the spring coefficient.

[0039] In actual motion, since the value measured by the six-dimensional force / torque sensor is delayed by one detection period T relative to the theoretical value, it can be expressed as:

[0040]

[0041] Among them, F m It is the force measured by the sensor to provide feedback. In this paper, the detection cycle is the same as the control cycle.

[0042] Rearranging the equation, we can get:

[0043]

[0044] Writing the above equation in state space form:

[0045]

[0046] Through the above equations, the state space equation of the self-balancing exoskeleton robot foot can be written as:

[0047]

[0048] in, y z =F m ,and:

[0049]

[0050] S102. Perform force analysis on the exoskeleton robot according to the impedance compliance control model to obtain expected force and actual force of the exoskeleton robot during movement.

[0051] S103, performing calculations based on the expected force and the actual force, and converting the walking problem into an optimization problem.

[0052] S104, solving the optimization problem and obtaining new expected values ​​of the left and right feet.

[0053] S105. The exoskeleton robot performs walking and standing tasks based on the new expected values.

[0054] The control method of the exoskeleton for self-balancing walking in unknown terrain is based on the impedance-controlled bipedal compliant control model, which is converted into an optimization problem, thereby deriving the control law of the human-machine hybrid system during walking. The expected force calculation method is based on the center of mass dynamics, and the expected force is optimized by considering the zero-moment point stability constraint, thereby improving the stability of the exoskeleton robot when walking in unknown terrain.

[0055] In another implementation of the present invention, the state space equation of the desired force is expressed as:

[0056]

[0057] in, y z =F m , z represents the position of the end of the foot, F m It indicates the feedback force measured by the sensor;

[0058]

[0059] Among them, F represents the force received by the end of the foot, M represents the mass coefficient, V represents the damping coefficient, and K represents the spring coefficient.

[0060] In another implementation of the present invention, the state space equation of the actual force is expressed as:

[0061]

[0062] in, y z =F m , z represents the position of the end of the foot, F m It indicates the feedback force measured by the sensor;

[0063]

[0064] Among them, F represents the force received by the end of the foot, M represents the mass coefficient, V represents the damping coefficient, and K represents the spring coefficient.

[0065] Exemplarily, subtracting the formulas for the desired force from the actual force yields:

[0066]

[0067] In another implementation of the present invention, the optimization problem is expressed as:

[0068]

[0069] Among them, Q and R are real symmetric positive definite matrices, Δu z Represents a state feedback device.

[0070] In another implementation of the present invention, the following state feedback device is designed to stabilize the system:

[0071]

[0072] Where, ΔF = F d -F r , F d is the expected force, F r For actual force.

[0073] Exemplarily, by iterating the equation:

[0074]

[0075] Get the new desired position:

[0076] z * (k+1)=z d (k+1)+Δz(k+1)

[0077] In another implementation of the present invention, the new expected values ​​of the left and right feet are expressed as:

[0078]

[0079] in, The new desired positions for the left and right feet after adjustment. is the desired position of the left and right feet, ΔP L / R It is the adjustment amount of the left and right feet in the current cycle.

[0080] In another implementation of the present invention, it also includes: according to the law of movement of the self-balancing exoskeleton robot, the walking process of the self-balancing exoskeleton robot can be simplified into a center of mass dynamics model; based on the center of mass dynamics model, the expected force is calculated and optimized.

[0081] For example, according to the movement law of the self-balancing exoskeleton robot, the walking process of the self-balancing exoskeleton robot can be simplified into a center of mass dynamics model.

[0082] The forces and torques of the left and right feet are transformed into the world coordinate system through the rotation matrix:

[0083]

[0084] The following equation is obtained through center-of-mass dynamics:

[0085]

[0086] In addition, according to the relationship between the force and position of the two feet, the positions of the zero moment points (ZMP) of the left and right feet are obtained as follows:

[0087]

[0088] Set the cost function:

[0089]

[0090] The optimization objective is expressed as:

[0091] min{J L +J R}

[0092] And the equality constraints are satisfied:

[0093]

[0094] The inequality constraints are satisfied as follows:

[0095]

[0096] Through the above formula, the expected force F of the two feet of the self-balancing exoskeleton robot during walking is calculated. d .

[0097] In another implementation of the present invention, simulation experiments and prototype experiments were performed. Figure 3 As shown in the figure, in the simulation environment, the lower limb self-balancing exoskeleton robot can carry people and walk stably on uneven roads with different height differences; Figure 4 As shown in the figure, in the prototype experiment, the lower limb self-balancing exoskeleton robot was able to carry a person and walk stably on an uneven road with a height difference of 4 cm.

[0098] Thus far, specific embodiments of the present invention have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims may be performed in a different order and still achieve the desired results. Additionally, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing may be advantageous.

[0099] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0100] In the description of the present invention, the terms "first" and "second" are only used to facilitate the description of different components or names, and cannot be understood as indicating or implying a sequential relationship, relative importance, or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features.

[0101] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0102] It should be noted that although the specific embodiments of the present invention are described in detail in conjunction with the accompanying drawings, it should not be understood as limiting the scope of protection of the present invention. Within the scope described in the claims, various modifications and variations that can be made by those skilled in the art without creative work still belong to the scope of protection of the present invention.

[0103] 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 improper limitations of the embodiments of the present invention.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling an exoskeleton to self-balance walking in unknown terrain, characterized in that: include: The end of the exoskeleton robot's foot is simplified into a virtual impedance compliance control model; Performing force analysis on the exoskeleton robot according to the impedance compliance control model to obtain expected force and actual force of the exoskeleton robot during movement; Performing calculations based on the expected force and the actual force to transform the walking problem into an optimization problem; Solve the optimization problem to obtain new expected values ​​of the left and right feet; The exoskeleton robot performs walking and standing tasks based on the new expected values.

2. The method according to claim 1, characterized in that The state space equation of the desired force is expressed as: in, y z =F m , z represents the position of the end of the foot, F m It indicates the feedback force measured by the sensor; Among them, F represents the force received by the end of the foot, M represents the mass coefficient, V represents the damping coefficient, and K represents the spring coefficient.

3. The method according to claim 2, characterized in that The state space equation of the actual force is expressed as: in, y z =F m , z represents the position of the end of the foot, F m It indicates the feedback force measured by the sensor; Among them, F represents the force received by the end of the foot, M represents the mass coefficient, V represents the damping coefficient, K represents the spring coefficient, and T represents the detection period.

4. The method according to claim 1, characterized in that: The optimization problem is expressed as: Among them, Q and R are real symmetric positive definite matrices, Δu z Represents a state feedback device.

5. The method according to claim 4, characterized in that Also includes: In order to make the system stable, the following state feedback is designed: Where, ΔF = F d -F r , F d is the expected force, F r For actual force.

6. The method according to claim 5, characterized in that The new expected values ​​of the left and right feet are expressed as: in, The new desired positions for the left and right feet after adjustment. is the desired position of the left and right feet, ΔP L / R It is the adjustment amount of the left and right feet in the current cycle.

7. The method according to claim 1, characterized in that Also includes: According to the movement law of the self-balancing exoskeleton robot, the walking process of the self-balancing exoskeleton robot can be simplified into a center of mass dynamics model; The desired force is calculated and optimized based on the center of mass dynamics model.

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