Systematic Review on Wearable Lower Extremity Robotic Exoskeletons for Assisted Locomotion

Lower extremity robotic exoskeletons(LEEX)can not only improve the ability of the human body but also provide healing treatment for people with lower extremity dysfunction.There are a wide range of application needs and development prospects in the military,industry,medical treatment,consumption and other felds,which has aroused widespread concern in society.This paper attempts to review LEEX technical development.First,the history of LEEX is briefy traced.Second,based on existing research,LEEX is classifed according to auxiliary body parts,structural forms,functions and felds,and typical LEEX prototypes and products are introduced.Then,the latest key technologies are analyzed and summarized,and the research contents,such as bionic structure and driving characteristics,human–robot interaction(HRI)and intentawareness,intelligent control strategy,and evaluation method of power-assisted walking efciency,are described in detail.Finally,existing LEEX problems and challenges are analyzed,a future development trend is proposed,and a multidisciplinary development direction of the key technology is provided.

Adaptive Robust Control with Leakage-Type Control Law for Trajectory Tracking of Exoskeleton Robots

This paper investigates the trajectory following problem of exoskeleton robots with numerous constraints. However, as a typical nonlinear system with variability and parameter uncertainty, it is difficult to accurately achieve the trajectory tracking control for exoskeletons. In this paper, we present a robust control of trajectory tracking control based on servo constraints. Firstly, we consider the uncertainties (e.g., modelling errors, initial condition deviations, structural vibrations, and other unknown external disturbances) in the exoskeleton system, which are time-varying and bounded. Secondly, we establish the dynamic model and formulate a close-loop connection between the dynamic model and the real world. Then, the trajectory tracking issue is regarded as a servo constraint problem, and an adaptive robust control with leakage-type adaptive law is proposed with the guaranteed Lyapunov stability. Finally, we conduct numerical simulations to verify the performance of the proposed controller.

Fixed-time constrained acceleration reconstruction scheme for robotic exoskeleton via neural networks

Accurate acceleration acquisition is a critical issue in the robotic exoskeleton system,but it is difficult to directly obtain the acceleration via the existing sensing systems.The existing algorithm-based acceleration acquisition methods put more attention on finite-time convergence and disturbance suppression but ignore the error constraint and initial state irrelevant techniques.To this end,a novel radical bias function neural network(RBFNN)based fixed-time reconstruction scheme with error constraints is designed to realize high-performance acceleration estimation.In this scheme,a novel exponential-type barrier Lyapunov function is proposed to handle the error constraints.It also provides a unified and concise Lyapunov stability-proof template for constrained and non-constrained systems.Moreover,a fractional power sliding mode control law is designed to realize fixed-time convergence,where the convergence time is irrelevant to initial states or external disturbance,and depends only on the chosen parameters.To further enhance observer robustness,an RBFNN with the adaptive weight matrix is proposed to approximate and attenuate the completely unknown disturbances.Numerical simulation and human sub ject experimental results validate the unique properties and practical robustness.

WALK-ASSISTING BALANCE SYSTEM OF THE EXOSKELETON ROBOT FOR DISABLED PEOPLE

A novel methodology for a walk-assisting balance system of the exoskeleton robot for dis-abled people is presented. The experiment on the walk-assisting balance system is implemented using amini-type ropewalker robot. The mechanism of the ropewalker robot is designed, its dynamic model isbuilt, and its control system based on PWM is developed. The emulations in Matlab and the results ofexperiments prove that this methodology is effective.

Review of Power-Assisted Lower Limb Exoskeleton Robot

Power-assisted lower limb exoskeleton robot is a wearable intelligent robot system involving mechanics,materials,electronics,control,robotics,and many other fields.The system can use external energy to provide additional power to humans,enhance the function of the human body,and help the wearer to bear weight that is previously unbearable.At the same time,employing reasonable structure design and passive energy storage can also assist in specific actions.First,this paper introduces the research status of power-assisted lower limb exoskeleton robots at home and abroad,and analyzes several typical prototypes in detail.Then,the key technologies such as structure design,driving mode,sensing technology,control method,energy management,and human-machine coupling are summarized,and some common design methods of the exoskeleton robot are summarized and compared.Finally,the existing problems and possible solutions in the research of power-assisted lower limb exoskeleton robots are summarized,and the prospect of future development trend has been analyzed.

Bioinspired Musculoskeletal Model-based Soft Wrist Exoskeleton for Stroke Rehabilitation

Exoskeleton robots have demonstrated the potential to rehabilitate stroke dyskinesia.Unfortunately,poor human-machine physiological coupling causes unexpected damage to human of muscles and joints.Moreover,inferior humanoid kinematics control would restrict human natural kinematics.Failing to deal with these problems results in bottlenecks and hinders its application.In this paper,the simplified muscle model and muscle-liked kinematics model were proposed,based on which a soft wrist exoskeleton was established to realize natural human interaction.Firstly,we simplified the redundant muscular system related to the wrist joint from ten muscles to four,so as to realize the human-robot physiological coupling.Then,according to the above human-like musculoskeletal model,the humanoid distributed kinematics control was established to achieve the two DOFs coupling kinematics of the wrist.The results show that the wearer of an exoskeleton could reduce muscle activation and joint force by 43.3%and 35.6%,respectively.Additionally,the humanoid motion trajectories similarity of the robot reached 91.5%.Stroke patients could recover 90.3%of natural motion ability to satisfy for most daily activities.This work provides a fundamental understanding on human-machine physiological coupling and humanoid kinematics control of the exoskeleton robots for reducing the post-stroke complications.

A Rhythmic Motion Control Method Inspired by Board Shoe Racing for a Weight-Bearing Exoskeleton

To ensure the flexible walking of the weight-bearing exoskeleton robot,most researchers control the exoskeleton to follow the wearer’s movements and provide force to maintain the current dynamic state.However,due to the limitation of sensing information and computing power,it is difficult for the exoskeleton to provide the wearer reasonable and stable force only based on the dynamic model,especially in switching between swing phase and stance phase.Inspired by China’s traditional sport named board shoe racing,a walking control method based on the cooperation of the human and the exoskeleton is proposed in this paper for a lower-limb exoskeleton named PALExo.Under certain conditions,the exoskeleton itself can walk stably depending on the rhythm signals generated by the Central Pattern Generator(CPG).With certain initiative during walking,it can make proper adjustments according to the human movement.With the help of dynamic simulation software and Genetic Algorithm(GA),the optimized CPG parameters are obtained.Impedance control is introduced to increase the comfort of the wearer.The impedance parameters as well as the CPG parameters are tuned in real time based on feedback.The experiments were conducted with PALExo.The results demonstrate that PALExo can effectively assist the wearer walking with a 45-kg payload benefiting from the proposed method.

Radial basis function‐based exoskeleton robot controller development

The realisation of a model‐based controller for a robot with a higher degree of freedom requires a substantial amount of computational power.A high‐speed CPU is required to maintain a higher sampling rate.Multicore processors cannot boost the performance or reduce the execution time as the programs are sequentially structured.The neural network is a great tool to convert a sequentially structured program to an equivalent parallel architecture program.In this study,a radial basis function(RBF)neural network is developed for controlling 7 degrees of freedom of the human lower extremity exoskel-eton robot.A realistic friction model is used for modelling joint friction.High trajectory tracking accuracies have been obtained.Evidence of computational efficiency has been observed.The stability analysis of the developed controller is presented.Analysis of variance is used to assess the controller's resilience to parameter variation.To show the effectiveness of the developed controller,a comparative study was performe between the developed RBF network‐based controller and Sliding Mode Controller,Computed Tor-que Controller,Adaptive controller,Linear Quadratic Regulator and Model Reference Computed Torque Controller.

Study on Control Technology of Tendon Bionic Driving Robot System

Although traditional position-controlled industrial robots can be competent for most assembly tasks,they cannot complete complex tasks that frequently interact with the external environment.The current research on exoskeleton robots also has problems such as excessive inertia of exoskeleton robots,poor system integration and difficult human–computer interaction control.To solve these problems,this paper independently develops a tendon driving robotic system composed of a tendon driving robotic arm and an upper limb exoskeleton,and studies its control technology.First,the robot system is selected,configured,and constructed.Second,the kinematics of the robot is analyzed,and then the dynamics are studied,and the parameter identification experiment of single degree of freedom is completed.Finally,the research on zero-force control and impedance control of the robot has effectively improved the robot’s human–machine integration ability,ensured the flexibility and compliance in the process of human–computer interaction.The compliant control problem expands the usage scenarios and application scope of robots and contributes to the realization of complex operations of this group of robots in unstructured environments.

Review of human–robot coordination control for rehabilitation based on motor function evaluation

As a wearable and intelligent system, a lower limb exoskeleton rehabilitation robot can provide auxiliary rehabilitation training for patients with lower limb walking impairment/loss and address the existing problem of insufficient medical resources. One of the main elements of such a human–robot coupling system is a control system to ensure human–robot coordination. This review aims to summarise the development of human–robot coordination control and the associated research achievements and provide insight into the research challenges in promoting innovative design in such control systems. The patients’ functional disorders and clinical rehabilitation needs regarding lower limbs are analysed in detail, forming the basis for the human–robot coordination of lower limb rehabilitation robots. Then, human–robot coordination is discussed in terms of three aspects: modelling, perception and control. Based on the reviewed research, the demand for robotic rehabilitation, modelling for human–robot coupling systems with new structures and assessment methods with different etiologies based on multi-mode sensors are discussed in detail, suggesting development directions of human–robot coordination and providing a reference for relevant research.