A time-sharing adaptive precise assisting method adaptive to target assisting demand switching

Abstract

This disclosure relates to a time-sharing adaptive precision assistance method, device, electronic device, and storage medium that adapts to changing target assistance needs. The method includes: calibrating and initializing sensors in the exoskeleton wearer coupling system; identifying the wearer's gait characteristics; predicting the wearer's current target assistance needs based on gait characteristics, joint interaction force characteristics, and center of mass motion characteristics, and matching joint controller parameters accordingly; establishing an exoskeleton swing phase and support phase enhancement torque controller that adaptively adjusts with joint motion amplitude and frequency; and switching the exoskeleton swing phase and support phase enhancement torque controller based on the target assistance needs, thereby achieving time-sharing adaptive assistance of the exoskeleton to adapt to changing target assistance needs. This disclosure achieves dynamic matching of the target motion position by adjusting joint controller parameters, which helps improve the exoskeleton robot's autonomous perception and efficient assistance to the wearer's target assistance needs.

Description

Technical Field

[0001] This disclosure relates to the field of robotics technology, and more specifically, to a time-sharing adaptive precision assistance method, apparatus, electronic device, and computer-readable storage medium that adapts to the switching of target assistance needs. Background Technology

[0002] With the rapid development of human-machine collaborative control technology, exoskeleton robots have been widely applied in various scenarios. Taking multi-terrain activity scenarios as an example, wearers typically face numerous tasks requiring limb joint assistance, including walking on flat ground, going up / down stairs, and standing / squatting. For exoskeleton robots in different scenarios, especially for different movement characteristics, different terrains, and different assistance needs, the wearer's target assistance requirements are usually different, even within the same movement mode, the assistance requirements for the swinging leg and the supporting leg are different. A full-time driven controller model is difficult to provide precise assistance for different movement scenarios. How to predict the wearer's current target assistance requirements based on the joint interaction force characteristics, gait characteristics, and center of mass movement characteristics reflected by the human-machine system, adjust and switch the exoskeleton robot's target movement position relative to the human-machine system, and use a normalized motion enhancement controller to provide time-sharing precise assistance to each leg under different gait modes, movement amplitudes, and movement speed ranges, directly relates to whether the exoskeleton robot can effectively assist the wearer in completing non-rhythmic movements in relevant task scenarios. Currently, there are few methods in the field of robot collaborative control that can adapt to the switching of target assistance requirements for time-sharing adaptive precise assistance in exoskeletons.

[0003] Therefore, one or more methods are needed to solve the above problems.

[0004] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this disclosure is to provide a time-sharing adaptive precision assistance method, device, electronic device, and computer-readable storage medium that adapts to the switching of target assistance needs, thereby overcoming at least to some extent one or more problems caused by the limitations and defects of related technologies.

[0006] According to one aspect of this disclosure, a time-sharing adaptive precision assistance method is provided that adapts to changes in target assistance needs, comprising:

[0007] Calibration and initialization are performed on the linkage posture sensor, joint interaction force sensor, power assist motor driver, and plantar film contact force sensor of the exoskeleton wearer coupling system.

[0008] The wearer's gait characteristics are identified based on the multimodal sensing features of the exoskeleton and the features of the foot contact array.

[0009] The target assistance needs of the current wearer are predicted by gait characteristics, joint interaction force characteristics, and center of mass motion characteristics, and the joint controller parameters of each leg in the swing phase and the support phase are matched.

[0010] Establish an exoskeleton swing phase enhancement torque controller that adapts to the amplitude and frequency of joint movement, and establish an exoskeleton support phase enhancement torque controller that dynamically pulls with the coupled potential field of the centroid target.

[0011] Based on the target assistance requirements, the exoskeleton swing phase enhancement torque controller and the exoskeleton support phase enhancement torque controller are switched to achieve time-sharing adaptive assistance of the exoskeleton to adapt to the switching of target assistance requirements.

[0012] In one exemplary embodiment of this disclosure, the method further includes:

[0013] Zero-point calibration and initialization are performed on the linkage pose sensor and joint interaction force sensor of the exoskeleton wearer coupling system.

[0014] Initialize the power assist motor driver and the plantar diaphragm contact force sensor.

[0015] In one exemplary embodiment of this disclosure, the method further includes:

[0016] The target's exoskeleton multimodal sensing features are acquired based on the linkage pose sensor;

[0017] The target's foot contact array characteristics are collected based on the foot film contact force sensor.

[0018] The joint interaction force characteristics of the target are collected based on the joint interaction force sensor;

[0019] The target's center of mass motion characteristics are acquired based on the assist motor driver.

[0020] In one exemplary embodiment of this disclosure, the method further includes:

[0021] Collect the exoskeleton multimodal sensing features and foot contact array features at the current moment and the n previous periods to generate a feature sequence;

[0022] The wearer's gait characteristics are identified based on the feature sequence, and the gait characteristics include gait pattern and gait phase.

[0023] In one exemplary embodiment of this disclosure, the method further includes:

[0024] The target assistance needs of the current wearer are predicted by gait characteristics, joint interaction force characteristics, and center of mass motion characteristics. The target assistance needs include the degree of intervention of target assistance needs in the support phase and the degree of intervention of target assistance needs in the swing phase.

[0025] In one exemplary embodiment of this disclosure, the method further includes:

[0026] Based on the Lyapunov stability requirements, an exoskeleton swing phase enhancement torque controller based on adaptive fuzzy system dynamic adjustment is established, which adaptively approximates the joint motion amplitude and motion frequency.

[0027] In one exemplary embodiment of this disclosure, the method further includes:

[0028] Based on an adaptive fuzzy strategy, an exoskeleton support phase enhanced torque controller is established based on the coupling traction of the transient capture point ICP equilibrium potential field and the gravitational potential field.

[0029] In one aspect of this disclosure, a time-sharing adaptive precision assist device that adapts to switching target assist needs is provided, comprising:

[0030] The calibration and initialization module is used to calibrate and initialize the linkage posture sensor, joint interaction force sensor, power assist motor driver, and plantar film contact force sensor of the exoskeleton wearer coupling system.

[0031] The gait feature generation module is used to collect multimodal sensing features of the exoskeleton and foot contact array features to generate feature sequences, and to identify the wearer's gait features based on the feature sequences;

[0032] The target assistance demand generation module is used to predict the current wearer's target assistance demand through gait characteristics, joint interaction force characteristics, and center of mass motion characteristics, and to match the joint controller parameters of each leg in the swing phase and the support phase.

[0033] The controller establishment module is used to establish an exoskeleton swing phase enhancement torque controller that adapts to the amplitude and frequency of joint movement, and to establish an exoskeleton support phase enhancement torque controller that dynamically pulls with the coupled potential field of the centroid target.

[0034] The assist control module is used to switch the exoskeleton swing phase enhancement torque controller and the exoskeleton support phase enhancement torque controller based on the target assist demand, so as to realize the time-sharing adaptive assist of the exoskeleton to adapt to the switching of the target assist demand.

[0035] In one aspect of this disclosure, an electronic device is provided, comprising:

[0036] Processor; and

[0037] A memory storing computer-readable instructions that, when executed by the processor, implement the method according to any one of the preceding claims.

[0038] In one aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method according to any one of the preceding claims.

[0039] An exemplary embodiment of this disclosure discloses a time-sharing adaptive precision assist method for switching target assist requirements. The method includes: calibrating and initializing the linkage posture sensor, joint interaction force sensor, assist motor driver, and plantar film contact force sensor of the exoskeleton wearer coupling system; collecting exoskeleton multimodal sensing features and plantar contact array features to generate a feature sequence, and identifying the wearer's gait features based on the feature sequence; predicting the wearer's current target assist requirement through gait features, joint interaction force features, and center of mass motion features, and matching the joint controller parameters of each leg in the swing phase and support phase; establishing an exoskeleton swing phase enhancement torque controller that adaptively adjusts with joint motion amplitude and frequency, and establishing an exoskeleton support phase enhancement torque controller that dynamically tractions with the target coupling potential field of the center of mass; and switching the exoskeleton swing phase enhancement torque controller and the exoskeleton support phase enhancement torque controller based on the target assist requirement to achieve time-sharing adaptive assist for the exoskeleton that adapts to the switching of target assist requirements. This disclosure predicts the wearer's target assistance needs by detecting joint interaction force characteristics, gait characteristics, and center of mass movement characteristics during the human-machine system's movement process. It adaptively adjusts the joint controller parameters of each leg and dynamically matches the wearer's target movement position. This compensates for the shortcomings of exoskeleton robots in adapting to enhanced assistance across different movement modes and speed ranges. It also fills the gap in exoskeleton robots using normalized assist controllers for time-sharing motion enhancement to meet different target assistance needs, thus helping to improve the autonomous perception and efficient assistance of exoskeleton robots to the wearer's target assistance needs.

[0040] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0041] The above and other features and advantages of this disclosure will become more apparent from the detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0042] Figure 1 A flowchart is shown below for a time-sharing adaptive precision assist method that adapts to target assist demand switching, according to an exemplary embodiment of the present disclosure.

[0043] Figure 2 A schematic diagram of a human-machine system assist demand prediction and motion enhancement method according to an exemplary embodiment of the present disclosure is shown.

[0044] Figure 3 A flowchart of a time-sharing motion enhancement control algorithm for a time-sharing adaptive precision assist method that adapts to target assist demand switching, according to an exemplary embodiment of the present disclosure, is shown.

[0045] Figures 4A-4E This illustration shows a schematic diagram of joint motion characteristics during the support phase assistance process of a time-sharing adaptive precision assistance method that adapts to the switching of target assistance needs, according to an exemplary embodiment of the present disclosure.

[0046] Figure 5 A block diagram of the swing / support leg time-sharing adaptive precision assist control structure for a time-sharing adaptive precision assist method that adapts to target assist demand switching according to an exemplary embodiment of the present disclosure is shown.

[0047] Figure 6 A structural block diagram of a time-sharing adaptive precision assist device that adapts to target assist demand switching according to an exemplary embodiment of the present disclosure is shown;

[0048] Figure 7 A block diagram of an electronic device according to an exemplary embodiment of the present disclosure is shown schematically;

[0049] Figure 8 The illustration shows a schematic diagram of a computer-readable storage medium according to an exemplary embodiment of the present disclosure. Detailed Implementation

[0050] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted.

[0051] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details described, or other methods, components, materials, apparatuses, steps, etc., can be employed. In other instances, well-known structures, methods, apparatuses, implementations, materials, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0052] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, or in one or more software-hardened modules, or in different network and / or processor devices and / or microcontroller devices.

[0053] In this example embodiment, a time-sharing adaptive precision assistance method that adapts to the switching of target assistance needs is first provided; refer to Figure 1 As shown, the time-sharing adaptive precision assistance method that adapts to the switching of target assistance needs may include the following steps:

[0054] Step S110: Calibrate and initialize the linkage posture sensor, joint interaction force sensor, power assist motor driver, and plantar film contact force sensor of the exoskeleton wearer coupling system.

[0055] Step S120: Collect the multimodal sensing features of the exoskeleton and the features of the foot contact array to generate a feature sequence, and identify the wearer's gait features based on the feature sequence.

[0056] Step S130: Predict the current wearer's target assistance needs through gait characteristics, joint interaction force characteristics, and center of mass motion characteristics, and match the joint controller parameters of each leg in the swing phase and support phase.

[0057] Step S140: Establish an exoskeleton swing phase enhancement torque controller that adapts to the joint movement amplitude and frequency, and establish an exoskeleton support phase enhancement torque controller that dynamically pulls the target potential field coupled with the center of mass.

[0058] Step S150: Based on the target assistance requirements, the exoskeleton swing phase enhancement torque controller and the exoskeleton support phase enhancement torque controller are switched to realize time-sharing adaptive assistance of the exoskeleton to adapt to the switching of target assistance requirements.

[0059] An exemplary embodiment of this disclosure discloses a time-sharing adaptive precision assist method for switching target assist requirements. The method includes: calibrating and initializing the linkage posture sensor, joint interaction force sensor, assist motor driver, and plantar film contact force sensor of the exoskeleton wearer coupling system; collecting exoskeleton multimodal sensing features and plantar contact array features to generate a feature sequence, and identifying the wearer's gait features based on the feature sequence; predicting the wearer's current target assist requirement through gait features, joint interaction force features, and center of mass motion features, and matching the joint controller parameters of each leg in the swing phase and support phase; establishing an exoskeleton swing phase enhancement torque controller that adaptively adjusts with joint motion amplitude and frequency, and establishing an exoskeleton support phase enhancement torque controller that dynamically tractions with the target coupling potential field of the center of mass; and switching the exoskeleton swing phase enhancement torque controller and the exoskeleton support phase enhancement torque controller based on the target assist requirement to achieve time-sharing adaptive assist for the exoskeleton that adapts to the switching of target assist requirements. This disclosure predicts the wearer's target assistance needs by detecting joint interaction force characteristics, gait characteristics, and center of mass movement characteristics during the human-machine system's movement process. It adaptively adjusts the joint controller parameters of each leg and dynamically matches the wearer's target movement position. This compensates for the shortcomings of exoskeleton robots in adapting to enhanced assistance across different movement modes and speed ranges. It also fills the gap in exoskeleton robots using normalized assist controllers for time-sharing motion enhancement to meet different target assistance needs, thus helping to improve the autonomous perception and efficient assistance of exoskeleton robots to the wearer's target assistance needs.

[0060] The following will further explain a time-sharing adaptive precision assistance method that adapts to the switching of target assistance needs in this example embodiment.

[0061] Example 1:

[0062] In step S110, the linkage posture sensor, joint interaction force sensor, power assist motor driver, and foot film contact force sensor of the exoskeleton wearer coupling system can be calibrated and initialized.

[0063] In this example embodiment, the method further includes:

[0064] Zero-point calibration and initialization are performed on the linkage pose sensor and joint interaction force sensor of the exoskeleton wearer coupling system.

[0065] Initialize the power assist motor driver and the plantar diaphragm contact force sensor.

[0066] In step S120, multimodal sensing features of the exoskeleton and features of the foot contact array can be collected to generate a feature sequence, and the wearer's gait features can be identified based on the feature sequence.

[0067] In this example embodiment, the method further includes:

[0068] The target's exoskeleton multimodal sensing features are acquired based on the linkage pose sensor;

[0069] The target's foot contact array characteristics are collected based on the foot film contact force sensor.

[0070] The joint interaction force characteristics of the target are collected based on the joint interaction force sensor;

[0071] The target's center of mass motion characteristics are acquired based on the assist motor driver.

[0072] In this example embodiment, the method further includes:

[0073] Collect the exoskeleton multimodal sensing features and foot contact array features at the current moment and the n previous periods to generate a feature sequence;

[0074] The wearer's gait characteristics are identified based on the feature sequence, and the gait characteristics include gait pattern and gait phase.

[0075] In step S130, the target assistance needs of the current wearer can be predicted by gait characteristics, joint interaction force characteristics, and center of mass motion characteristics, and the joint controller parameters of each leg in the swing phase and the support phase can be matched.

[0076] In this example embodiment, the method further includes:

[0077] The target assistance needs of the current wearer are predicted by gait characteristics, joint interaction force characteristics, and center of mass motion characteristics. The target assistance needs include the degree of intervention of target assistance needs in the support phase and the degree of intervention of target assistance needs in the swing phase.

[0078] In step S140, an exoskeleton swing phase enhancement torque controller that adaptively adjusts with the joint movement amplitude and movement frequency can be established, as well as an exoskeleton support phase enhancement torque controller that dynamically pulls with the coupled potential field of the centroid target.

[0079] In this example embodiment, the method further includes:

[0080] Based on the Lyapunov stability requirements, an exoskeleton swing phase enhancement torque controller based on adaptive fuzzy system dynamic adjustment is established, which adaptively approximates the joint motion amplitude and motion frequency.

[0081] In step S150, the exoskeleton swing phase enhancement torque controller and the exoskeleton support phase enhancement torque controller can be switched based on the target assistance requirements to realize time-sharing adaptive assistance of the exoskeleton that adapts to the switching of target assistance requirements.

[0082] In this example embodiment, the method further includes:

[0083] Based on an adaptive fuzzy strategy, an exoskeleton support phase enhanced torque controller is established based on the coupling traction of the transient capture point ICP equilibrium potential field and the gravitational potential field.

[0084] Example 2:

[0085] In this example embodiment, the time-sharing adaptive precision assistance method is suitable for switching assistance between different target assistance needs of exoskeleton robots, especially for non-rhythmic adaptive motion enhancement of human-machine coupling systems under different gait modes, motion amplitudes, and motion speed ranges. (See attached...) Figure 2 As shown, the system involved in the human-machine system assistance demand prediction and motion enhancement method includes hip joint interactive force / torque sensor I, hip joint interactive force / torque sensor II, center of mass of each link of the human-machine system III, center of mass of the human-machine system as a whole equivalent center of mass IV, equivalent transient capture point V of the human-machine system as a whole, and equivalent target motion position point VI of the human-machine system as a whole.

[0086] The human-machine system is a multi-rigid-body linkage system with multiple rotational joints II. The interaction between the system and the wearer can be detected by interaction force / torque sensor I, which is equivalent to a spring-damped model. The overall equivalent center of mass IV of the human-machine system can be calculated by the center of mass III of each link in the human-machine system. The current equivalent transient capture point V of the human-machine system is obtained by extracting the motion velocity of the center of mass. Based on the joint interaction force characteristics, gait characteristics, and center of mass motion characteristics of the two legs, the target assistance needs of the wearer are predicted, and the overall equivalent target motion position point VI of the human-machine system is solved.

[0087] This embodiment provides a time-sharing motion enhancement method for exoskeletons that adapts to changing target assistance needs, such as... Figure 3 As shown, the method includes:

[0088] Step S110: Complete the zero-point calibration and initialization of the linkage posture sensor and joint interaction force sensor of the exoskeleton-wearer coupling system, and complete the initialization settings of the hip and knee joint active drive motor driver and the foot film contact force sensor.

[0089] Step S120: Collect the multimodal sensing features of the exoskeleton at the current moment. Features of the Foot Contact Array The features of the first n periods constitute the feature sequence. and Identify the wearer's current gait characteristics, including gait patterns (walking, going up / down stairs, standing up / squatting) and gait phases (support phase). Oscillating phase );

[0090] Step S130: Through joint interaction force characteristics T HRI Gait characteristics and center of mass movement characteristics Predict the current wearer's target assistance needs and match the joint controller parameters of each leg in the swing and support phases, including the intervention level α of the target assistance needs in the support phase and the intervention level β of the target assistance needs in the swing phase;

[0091] Step S140: Based on the Lyapunov stability requirements, design an exoskeleton swing phase enhancement torque controller that dynamically adjusts based on the joint motion amplitude and motion frequency, and an exoskeleton support phase enhancement torque controller that is based on the ICP transient capture point equilibrium potential field and the gravitational potential field coupled traction.

[0092] Step S150: Match the controller model and controller parameters of each leg according to the target assistance requirements obtained in the third step, realize the exoskeleton time-sharing motion enhancement method that adapts to the switching of target assistance requirements, complete the calculation of the current exoskeleton joint torque and signal transmission, further perform information collection, and calculate the new target value at the next moment;

[0093] In step S140, when designing the assist controller for the support phase, the wearer's target assist requirement in the support phase depends on the wearer's current gait pattern and target movement position. When the wearer is walking, the center of mass mainly moves forward rapidly along the horizontal direction using inertial oscillation. At this time, the center of mass only undergoes a small range of sinusoidal rhythmic oscillations in the vertical direction. The swing leg has a larger speed and range of motion, exhibiting non-rhythmic oscillation. In this case, the wearer's target assist requirement can be followed in the support phase using the sensitivity amplification principle, while in the swing phase, it needs to quickly follow the wearer's movement. When the wearer is going up / down stairs or standing / squatting in place, the center of mass needs to move from a position S behind the supporting foot... GOM =[z ICP ,y CoM Simultaneously moving longitudinally and laterally, it reaches the wearer's target movement position.

[0094] The lateral target equilibrium position of the ICP potential field at the transient capture point. The longitudinal target equilibrium position of the gravitational potential field of the center of mass CoM. To correct the offset of the target movement position relative to the supporting foot during the process of descending a step and squatting in place, the wearer tends to shift their center of mass towards the supporting foot. This ensures that subsequent transitional movements can naturally be propelled by the switching supporting foot, allowing the center of mass to move to its original absolute equilibrium position during work against gravity and to quickly move to the relative equilibrium position of the next transitional gait during work in accordance with gravity. The enabling and disabling of offset correction depends on the tendency of the center of mass to move vertically.

[0095]

[0096] in Let ψ be the rotation matrix about the central axis of the zoy plane, and ψ be the deflection angle formed by the line connecting the two ankles and the ground. This mainly occurs when one ankle is in a deep pit or on a high platform, causing the two ankles to not be on the same horizontal plane. Specifically, when one foot is in the swing phase, Δl is set. ankle <0 at this time This falls under the first category, primarily through sign functions. Switching between squats and stair climbing using a symbolic function. It provides assistance in both the direction of overcoming gravity and the direction of gravity.

[0097] When the wearer is squatting and standing up in place Depends on the stride distance Δl between the feet in the support phase ankle At this point, the wearer's center of mass and the two supporting ankles form a spatial triangle. The target motion position is the most stable equilibrium position. The wearer's target assistance requirement is for the center of mass to reach the absolute equilibrium position of ICP (internal pressure) without overturning moment in the horizontal direction, which is the center of the line connecting the two ankles, and for the center of mass to reach the highest position of gravitational potential energy in the vertical direction. zoy The calculation is determined by the position and distribution characteristics of the centroid of the connecting rods in the sagittal plane of the human-machine coupling system, where n y T The direction vector of the vertical coordinate axis. Let be the mass and direction vector of the center of mass of the link in the exoskeleton-wearer human-machine coupling system.

[0098]

[0099] The transient capture point ICP is a coupled variable concerning the position and velocity of the center of mass. This variable can effectively indicate the current motion trend of the center of mass. Since ICP is the point where the trajectory energy of the linear inverted pendulum model is zero, when the CoP point coincides with the ICP point, the CoM can stop above this point. For the motion of the center of mass during squatting, standing, and climbing stairs, the ideal equilibrium point of the system is the absolute equilibrium position when the inverted pendulum model's swing angle is 0. At this point, the CoM reaches its highest point along the y-axis and its ankle point along the z-axis, and the system's gravitational potential energy reaches its maximum value, meaning the lower limbs and back of the human-machine coupled system are completely upright. Therefore, when planning the potential energy, it is necessary to consider both the gravitational traction potential energy along the vertical direction and the equilibrium traction potential energy along the horizontal direction. The potential field traction energy function can then be expressed as:

[0100]

[0101] In order for the current potential energy point to move rapidly toward the target potential energy point, a negative gradient of energy change is used. The system's center of mass is tractioned and planned as a corrective force. Based on the actual target assistance needs of the wearer during exoskeleton movement, the parameters of the enhanced torque controller involved in the controller are switched and matched, ψ... GoM K is the correction force coefficient corresponding to the traction of the equilibrium potential field and the traction of the gravitational potential field. Δm The intervention coefficient for supporting the target is α, which represents the degree of intervention required to support the target. In addition to balancing the dynamic torque caused by its own inertia, the exoskeleton also needs to provide additional assistance to the dynamic torque caused by the wearer's own inertia. The parameters for the exoskeleton support phase enhancement assist controller are α=0. At this time, the physiological energy consumption of the wearer when wearing the exoskeleton and doing work against gravity, such as metabolic oxygen consumption, heart rate curve, and muscle fatigue, is almost identical to the physiological energy consumption of the wearer when not wearing the exoskeleton. That is, under the action of the exoskeleton support phase enhancement assist controller at α=0, the wearer's motion characteristics are almost unaffected by the exoskeleton's own gravity. The wearer's exercise energy consumption and joint output are only related to the wearer's own weight. Relatedly, the exoskeleton has almost no impact on the wearer's subjective wearing experience or objective characteristic parameters, and the wearer can normally complete dynamic movements that overcome gravity, such as climbing stairs, squatting and standing up.

[0102]

[0103] When walking on flat ground, provide 30% human assistance to the swing phase and no additional assistance to the support phase; when climbing stairs, provide 50% human assistance to the swing phase and α=40% additional human assistance to the support phase; when descending stairs, provide 30% human assistance to the swing phase and α=20% additional human assistance to the support phase; when standing up in place, provide α=60% additional human assistance to the support phase; when squatting in place, provide α=30% additional human assistance to the support phase.

[0104] After determining the corrected force coefficient of the coupled traction potential field, it is necessary to allocate the coefficient γ of each leg according to the torque contribution and motion contribution of each leg during the assist process. i The settings further map the torques of the hip and knee joints. Here, i=0 represents the front supporting leg, and i=1 represents the rear supporting leg. Numerically, the supporting leg closer to the ICP contributes more to the motion planning, and vice versa. Symbolically, the swing leg's contribution to the center of mass motion planning is negligible, and during the lunge stance, the front supporting leg is primarily responsible for active posture adjustment, while the rear supporting leg is in a state of free-swinging, with the toes touching the ground and the foot and ankle joints suspended. This represents the current phase state of the leg. The support phase is 1. The swing phase is 0. The final coupled potential field traction correction force of each leg is defined as follows:

[0105]

[0106] Figures 4A-4E The joint motion characteristics under the action of the support phase motion enhancement controller are such that the motion trend of each joint is consistent with the wearer's natural gait.

[0107] In step S140, when designing the assist controller for the support phase, an adaptive fuzzy strategy is used to approximate the impedance parameters in order to eliminate the human-exoskeleton interaction T. HRI The uncertainty of the time-varying impedance parameters. Considering the general approximation theorem, the system's impedance parameters can be approximated by a multi-input multi-output fuzzy logic system, respectively related to the acceleration deviation. speed deviation The matrix of inertia, damping, stiffness, and impedance parameters corresponding to the position deviation Δq is shown below.

[0108]

[0109] in A column vector of multiple derivatives of the deviation. Designed for adaptive fuzzy control rate. This is a Gaussian membership function. Since impedance compensation for acceleration deviations often causes system oscillations due to misestimation of the inertia matrix parameters, to simplify computational complexity and reduce estimation errors, control systems often use... This is approximately equivalent to the system's own inertia matrix M(q). To enhance the robustness and convergence of the controller, a sliding mode function is used to reconstruct the trajectory following error. And guide convergence.

[0110]

[0111] Where M(q), G(q), The equivalent inertia, Coriolis, gravity, and friction matrix of the human-machine coupled system are calculated as the superposition of the wearer's own mass attribute and the exoskeleton's own mass attribute by a factor of β. At this time τ b This can be viewed as a correction for the inertia term, specifically an online correction and compensation for the error in joint acceleration caused by impedance parameter approximation and simplification. In this case, it is necessary to solve for the adaptive control law of the fuzzy controller in reverse, based on the Lyapunov stability analysis of the system. Therefore, the Lyapunov function is selected as...

[0112]

[0113] Γ 1i , Γ 1i Let be the bias harmonic coefficients. The condition for the Lyapunov first derivative to guarantee stability is: Right now

[0114]

[0115] Ultimately, under the constraint of stability conditions, the adaptive fuzzy control law should be designed as follows:

[0116]

[0117] The final principle block diagram of the time-sharing adaptive precision assist control strategy, which can adapt to different time-state characteristics and has switchable target assist requirements, is as follows: Figure 5 As shown.

[0118] It should be noted that although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0119] Furthermore, in this example embodiment, a time-sharing adaptive precision assistance device that adapts to changes in target assistance needs is also provided. (Refer to...) Figure 6 As shown, the time-sharing adaptive precision assist device 200 that adapts to the switching of target assist demand may include: a calibration and initialization module 210, a gait feature generation module 220, a target assist demand generation module 230, a controller establishment module 240, and an assist control module 250. Wherein:

[0120] The calibration and initialization module 210 is used to perform calibration and initialization processing on the linkage posture sensor, joint interaction force sensor, power assist motor driver, and plantar film contact force sensor of the exoskeleton wearer coupling system.

[0121] The gait feature generation module 220 is used to collect multimodal sensing features of the exoskeleton and features of the plantar contact array to generate feature sequences, and to identify the wearer's gait features based on the feature sequences.

[0122] The target assistance demand generation module 230 is used to predict the current wearer's target assistance demand through gait characteristics, joint interaction force characteristics, and center of mass motion characteristics, and to match the joint controller parameters of each leg in the swing phase and the support phase.

[0123] The controller establishment module 240 is used to establish an exoskeleton swing phase enhancement torque controller that adapts to the amplitude and frequency of joint movement, and to establish an exoskeleton support phase enhancement torque controller that dynamically pulls with the coupled potential field of the centroid target.

[0124] The assist control module 250 is used to switch the exoskeleton swing phase enhancement torque controller and the exoskeleton support phase enhancement torque controller based on the target assist demand, so as to realize the time-sharing adaptive assist of the exoskeleton to adapt to the switching of the target assist demand.

[0125] The specific details of each of the above-mentioned time-sharing adaptive precision assist device modules that adapt to the switching of target assist requirements have been described in detail in the corresponding time-sharing adaptive precision assist method, so they will not be repeated here.

[0126] It should be noted that although several modules or units of the time-sharing adaptive precision assist device 200 that adapts to the switching of target assist requirements are mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0127] Furthermore, in an exemplary embodiment of this disclosure, an electronic device capable of implementing the above-described method is also provided.

[0128] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented as entirely hardware embodiments, entirely software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, collectively referred to herein as “circuit,” “module,” or “system.”

[0129] The following reference Figure 7 To describe an electronic device 300 according to such an embodiment of the present invention. Figure 7 The electronic device 300 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0130] like Figure 7 As shown, the electronic device 300 is presented in the form of a general-purpose computing device. The components of the electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one storage unit 320, a bus 330 connecting different system components (including storage unit 320 and processing unit 310), and a display unit 340.

[0131] The storage unit stores program code that can be executed by the processing unit 310, causing the processing unit 310 to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of the present invention. For example, the processing unit 310 can perform actions such as... Figure 1 Steps S110 to S150 are shown in the diagram.

[0132] Storage unit 320 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 3201 and / or cache memory 3202, and may further include a read-only memory (ROM) 3203.

[0133] Storage unit 320 may also include a program / utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0134] Bus 330 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0135] Electronic device 300 can also communicate with one or more external devices 370 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 300, and / or with any device that enables electronic device 300 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 350. Furthermore, electronic device 300 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 360. As shown, network adapter 360 communicates with other modules of electronic device 300 via bus 330. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0136] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0137] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the invention may also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the invention described in the "Exemplary Methods" section above.

[0138] refer to Figure 8 As shown, a program product 400 for implementing the above-described method according to an embodiment of the present invention is described. This product may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0139] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0140] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0141] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0142] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0143] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0144] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0145] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A time-sharing adaptive precision assistance method that adapts to changing target assistance needs, characterized in that, The method includes: Calibration and initialization are performed on the linkage posture sensor, joint interaction force sensor, power assist motor driver, and plantar film contact force sensor of the exoskeleton wearer coupling system. The wearer's gait characteristics are identified based on the multimodal sensing features of the exoskeleton and the features of the foot contact array. The target assistance needs of the current wearer are predicted by gait characteristics, joint interaction force characteristics, and center of mass motion characteristics, and the joint controller parameters of each leg in the swing phase and the support phase are matched. An exoskeleton swing phase enhanced torque controller that adapts to the amplitude and frequency of joint movement is established, and an exoskeleton support phase enhanced torque controller based on the coupling traction of the transient capture point ICP equilibrium potential field and the gravitational potential field is established based on an adaptive fuzzy strategy. Based on the target assistance requirements, the exoskeleton swing phase enhancement torque controller and the exoskeleton support phase enhancement torque controller are switched to achieve time-sharing adaptive assistance of the exoskeleton to adapt to the switching of target assistance requirements.

2. The method as described in claim 1, characterized in that, The method further includes: Zero-point calibration and initialization are performed on the linkage posture sensor and joint interaction force sensor of the exoskeleton wearer coupling system. Initialize the power assist motor driver and the plantar diaphragm contact force sensor.

3. The method as described in claim 2, characterized in that, The method further includes: The target's exoskeleton multimodal sensing features are acquired based on the linkage pose sensor; The target's foot contact array characteristics are collected based on the foot film contact force sensor. The joint interaction force characteristics of the target are collected based on the joint interaction force sensor; The target's center of mass motion characteristics are acquired based on the assist motor driver.

4. The method as described in claim 1, characterized in that, The method further includes: Collect the exoskeleton multimodal sensing features and foot contact array features at the current moment and the n previous periods to generate a feature sequence; The wearer's gait characteristics are identified based on the feature sequence, and the gait characteristics include gait pattern and gait phase.

5. The method as described in claim 1, characterized in that, The method further includes: The target assistance needs of the current wearer are predicted by gait characteristics, joint interaction force characteristics, and center of mass motion characteristics. The target assistance needs include the degree of intervention of target assistance needs in the support phase and the degree of intervention of target assistance needs in the swing phase.

6. The method as described in claim 1, characterized in that, The method further includes: Based on the Lyapunov stability requirements, an exoskeleton swing phase enhancement torque controller based on adaptive fuzzy system dynamic adjustment is established, which adaptively approximates the joint motion amplitude and motion frequency.

7. A time-sharing adaptive precision assist device that adapts to changing target assist needs, characterized in that, The device includes: The calibration and initialization module is used to calibrate and initialize the linkage posture sensor, joint interaction force sensor, power assist motor driver, and plantar film contact force sensor of the exoskeleton wearer coupling system. The gait feature generation module is used to collect multimodal sensing features of the exoskeleton and foot contact array features to generate feature sequences, and to identify the wearer's gait features based on the feature sequences; The target assistance demand generation module is used to predict the current wearer's target assistance demand through gait characteristics, joint interaction force characteristics, and center of mass motion characteristics, and to match the joint controller parameters of each leg in the swing phase and the support phase. The controller establishment module is used to establish an exoskeleton swing phase enhancement torque controller that adapts to the amplitude and frequency of joint movement, and to establish an exoskeleton support phase enhancement torque controller based on the coupling traction of the transient capture point ICP equilibrium potential field and the gravitational potential field based on an adaptive fuzzy strategy. The assist control module is used to switch the exoskeleton swing phase enhancement torque controller and the exoskeleton support phase enhancement torque controller based on the target assist demand, so as to realize the time-sharing adaptive assist of the exoskeleton to adapt to the switching of the target assist demand.

8. An electronic device, characterized in that, include Processor; and A memory storing computer-readable instructions that, when executed by the processor, implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 6.

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