Gait trajectory planning and simulation for the powered gait orthosis

This paper presents a new trajectory tracking control strategy for a novel lower-limb rehabilitant robot, AirGait, which is a parallel mechanism with three degrees of freedom and is actuated with four pneumatic artificial muscles (PAMs). Compared with the existing control methods, the feature of this approach is that it combines the feedforward/feedback (FF) controller based on the length-pressure hysteresis compensation of PAMs with a joint space control method on the trajectory tracking control of a parallel mechanism. For the controller design, the inverse and forward kinematic formulas of AirGait are developed firstly based on the structure analysis. Then, a lower-limb kinematic model of humans is developed and the human-like trajectory of time is obtained by using a Fourier series method. Finally, the control scheme is introduced and the trajectory tracking control of AirGait with two reference input signals is presented. The comparative experimental results indicate that the performance of this control approach is strong and this robot holds great promise for assisting lower-limb locomotion. INDEX TERMS Trajectory tracking control, hysteresis compensation, feedforward/feedback (FF) control, lower-limb rehabilitation robot, pneumatic artificial muscle (PAM), joint space control. SHENGLONG XIE was born in Anqing, China, in 1988. He received the B.S. degree in mechanical design, manufacturing, and automation and the M.S. degree in mechatronic engineering from the

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“…In order to obtain the human-like trajectory, the hip, knee, and ankle joint data presented in the literature [31] is substituted into Eq. (11).…”

Section: B Trajectory Designmentioning

confidence: 99%

A Trajectory Tracking Control of a Robot Actuated With Pneumatic Artificial Muscles Based on Hysteresis Compensation

et al. 2020

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“…Human gait phases and periods The clinical gait data used are obtained from the independent source of Clinical Gait Analysis (CGA) Normative Gait Database [12]. According to the CGA data, the hip joint angle and knee joint angle of the lower limbs are given and utilized for the analysis and design of the walking aids.…”

Section: Clinical Gait Analysis (Cga) Datamentioning

confidence: 99%

On the design and evaluation of wheeled walking aids for the elderly

Gao

Sun

Zhong

2013

IEEE Conference Anthology

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Most of the walking aids are designed for military program or gait rehabilitation, however, there is lack of research on walking aids for daily life even they are necessary. In this study, we designed a wheeled walking aid based on the body parameters of Chinese elderly, which consists on both assistive seat and walking assist. Some pressure and sEMG sensors were set up for developing the control algorithm according to the biomechanical models. Using the Ergonomics Simulation System, we evaluated the operating ranges, the viewing angles, and the joint torque of the equipment to prove the available of the design.

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“…According to Miskon et al [3], there are three strategies for generating a trajectory for robot applications: off-line, on-line, and combined or hybrid. The off-line strategy is a strategy that uses either a mathematical model such as a polynomial equation [4], Fourier Transform [5], Central Pattern Generation (CPG) [6], Neural Oscillator [7], or uses recorded or normalized human motion data [8]. The advantage of this strategy is that it does not require any dynamic relationship between the robot and the environment.…”

Section: Introductionmentioning

confidence: 99%

High Accuracy Human Motion Trajectory Generation for Exoskeleton Robot Using Curve Fitting Technique

Jalil

Miskon

Bahar

2023

IIUMEJ

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Robotic systems often require trajectory planning algorithms that can generate natural human-like movements for tasks such as grasping and manipulation. However, conventional trajectory planning methods may not accurately capture the complex movement patterns observed in humans. In this paper, we present a trajectory planning algorithm based on polynomial curve fitting that aims to address this issue. The algorithm determines the polynomial coefficient values that accurately match the natural human trajectory profile and is evaluated using MATLAB simulations. We compare the proposed algorithm to the conventional quintic polynomial trajectory method, analysing the accuracy, precision, and via-point continuity. The result shows that the algorithm has the ability to generate a trajectory profile with accuracy of 99.8% and a precision of 0.002°. However, the result for via-point continuity shows an error on every sub-phase transition, with the lowest error of 0.0031 between the transition of sub-phases 1 and 2. The result also shows that the lowest fitting error recorded is 0.00014°. The results demonstrate that our algorithm can generate trajectory profiles with higher accuracy and naturalness, potentially improving the performance and usability of robotic systems. ABSTRAK: Sistem robotik sering memerlukan algoritma perancangan trajektori yang dapat menghasilkan gerakan semulajadi seperti manusia bagi tugas seperti memegang dan memanipulasi objek. Walau bagaimanapun, kaedah perancangan trajektori konvensional mungkin tidak dapat merekodkan pola gerakan kompleks seperti yang dihasilkan manusia secara tepat. Kajian ini adalah berkenaan algoritma perancangan lintasan berdasarkan penyepaduan lengkung polinomial bagi menyelesaikan masalah ini. Algoritma ini menentukan nilai pekali polinomial yang sepadan dengan profil gerakan semulajadi manusia dan dinilai menggunakan simulasi MATLAB. Algoritma yang dicadangkan ini telah dibandingkan dengan kaedah perancangan lintasan polinomial kuintik konvensional, dianalisis kejituan, ketepatan, dan keberterusan titik lalu. Keputusan menunjukkan bahawa algoritma tersebut mampu menghasilkan profil lintasan dengan kejituan sebanyak 99.8% dan ketepatan sebanyak 0.002°. Walau bagaimanapun, dapatan kajian mengenai keberterusan titik lalu menunjukkan ralat pada setiap peralihan fasa-sub dengan ralat terendah sebanyak 0.0031 pada peralihan antara fasa-sub 1 dan fasa-sub 2. Dapatan kajian juga menunjukkan bahawa ralat penyepaduan terendah yang direkodkan adalah sebanyak 0.00014°. Keputusan ini menunjukkan bahawa algoritma ini mampu menghasilkan profil lintasan dengan ketepatan dan sifat semula jadi yang lebih tinggi, berpotensi meningkatkan prestasi dan kegunaan sistem robotik.

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Gait trajectory planning and simulation for the powered gait orthosis

Cited by 13 publications

References 9 publications

A Trajectory Tracking Control of a Robot Actuated With Pneumatic Artificial Muscles Based on Hysteresis Compensation

A Trajectory Tracking Control of a Robot Actuated With Pneumatic Artificial Muscles Based on Hysteresis Compensation

On the design and evaluation of wheeled walking aids for the elderly

High Accuracy Human Motion Trajectory Generation for Exoskeleton Robot Using Curve Fitting Technique

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