Modeling and dynamic analysis of the biped robot

Rameez, Muhammad; Khan, Liaqat Ali

doi:10.1109/iccas.2015.7364800

Cited by 7 publications

(5 citation statements)

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“…Therefore, only 2 degrees of freedom (DOF) were considered: 1 DOF for the hip joint and 1 for the knee [ 39 , 57 – 62 ]. Moreover, the base was assumed fixed, making it two serial-link manipulators in which one manipulator is moved 180° out of phase with the other one [ 61 – 64 ]. The average thigh clearance given in the literature for a man is 0.78 in, and for women, 0.90 in [ 65 , 66 ].…”

Section: Methodsmentioning

confidence: 99%

fNIRS-based Neurorobotic Interface for gait rehabilitation

Khan

Naseer

Qureshi

et al. 2018

J NeuroEngineering Rehabil

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BackgroundIn this paper, a novel functional near-infrared spectroscopy (fNIRS)-based brain-computer interface (BCI) framework for control of prosthetic legs and rehabilitation of patients suffering from locomotive disorders is presented.MethodsfNIRS signals are used to initiate and stop the gait cycle, while a nonlinear proportional derivative computed torque controller (PD-CTC) with gravity compensation is used to control the torques of hip and knee joints for minimization of position error. In the present study, the brain signals of walking intention and rest tasks were acquired from the left hemisphere’s primary motor cortex for nine subjects. Thereafter, for removal of motion artifacts and physiological noises, the performances of six different filters (i.e. Kalman, Wiener, Gaussian, hemodynamic response filter (hrf), Band-pass, finite impulse response) were evaluated. Then, six different features were extracted from oxygenated hemoglobin signals, and their different combinations were used for classification. Also, the classification performances of five different classifiers (i.e. k-Nearest Neighbour, quadratic discriminant analysis, linear discriminant analysis (LDA), Naïve Bayes, support vector machine (SVM)) were tested.ResultsThe classification accuracies obtained from SVM using the hrf were significantly higher (p < 0.01) than those of the other classifier/ filter combinations. Those accuracies were 77.5, 72.5, 68.3, 74.2, 73.3, 80.8, 65, 76.7, and 86.7% for the nine subjects, respectively.ConclusionThe control commands generated using the classifiers initiated and stopped the gait cycle of the prosthetic leg, the knee and hip torques of which were controlled using the PD-CTC to minimize the position error. The proposed scheme can be effectively used for neurofeedback training and rehabilitation of lower-limb amputees and paralyzed patients.

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Section: Methodsmentioning

confidence: 99%

fNIRS-based Neurorobotic Interface for gait rehabilitation

Khan

Naseer

Qureshi

et al. 2018

J NeuroEngineering Rehabil

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“…The input signals were the position error e(t) and velocity error e (t) of the joints generated from comparing quantities that define the robot's motion trajectory represented by the joint coordinates qd and their derivative d q , with response values of the corresponding quantities, q, q . These quantities were determined according to Equation (13). The output signal of the controller was the value of driving moments U(t) at the driven joints, which ensured the motion trajectory of the robot-i.e., with the errors e(t), e (t) as small as possible, relative to the desired value-and ensures the relative equilibrium.…”

Section: The Input Output Signals and Physical Value Domainsmentioning

confidence: 99%

“…q. These quantities were determined according to Equation (13). The output signal of the controller was the value of driving moments U(t) at the driven joints, which ensured the motion trajectory of the robot-i.e., with the errors e(t), .…”

Section: The Input Output Signals and Physical Value Domainsmentioning

confidence: 99%

“…The first important problem is the dynamics of bipedal robots. Although there have been many studies on the problem of dynamics [8][9][10][11][12][13][14][15][16], because the structure is very diverse for each field of application, this is still an open problem. Normally, Newton-Euler equations and Lagrange equations of the 2nd kind are widely applied when investigating the dynamics of bipedal robots.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy Logic-Based Controller for Bipedal Robot

Khôi

Xuan

2021

Applied Sciences

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In this paper, the problem of controlling a human-like bipedal robot while walking is studied. The control method commonly applied when controlling robots in general and bipedal robots in particular, was based on a dynamical model. This led to the need to accurately define the dynamical model of the robot. The activities of bipedal robots to replace humans, serve humans, or interact with humans are diverse and ever-changing. Accurate determination of the dynamical model of the robot is difficult because it is difficult to fully and accurately determine the dynamical quantities in the differential equations of motion of the robot. Additionally, another difficulty is that because the robot’s operation is always changing, the dynamical quantities also change. There have been a number of works applying fuzzy logic-based controllers and neural networks to control bipedal robots. These methods can overcome to some extent the uncertainties mentioned above. However, it is a challenge to build appropriate rule systems that ensure the control quality as well as the controller’s ability to perform easily and flexibly. In this paper, a method for building a fuzzy rule system suitable for bipedal robot control is proposed. The design of the motion trajectory for the robot according to the human gait and the analysis of dynamical factors affecting the equilibrium condition and the tracking trajectory were performed to provide informational data as well as parameters. Based on that, a fuzzy rule system and fuzzy controller was proposed and built, allowing a determination of the control force/moment without relying on the dynamical model of the robot. For evaluation, an exact controller based on the assumption of an accurate dynamical model, which was a two-feedback loop controller based on integrated inverse dynamics with proportional integral derivative, is also proposed. To confirm the validity of the proposed fuzzy rule system and fuzzy controller, computation and numerical simulation were performed for both types of controllers. Comparison of numerical simulation results showed that the fuzzy rule system and the fuzzy controller worked well. The proposed fuzzy rule system is simple and easy to apply.

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“…En la construcción del prototipo de robot equino se consideró el análisis cinemático como el primer paso para describir el modelo geométrico en forma paramétrica. [1] En ésta construcción al igual que en un modelo industrial se presentaron errores de fabricación en el mecanizado y acople de eslabones y actuadores que generaron discrepancias entre los parámetros de diseño y la estructura física, por lo cual se buscó la identificación de los modelos individuales de la cadena cinemática con el fin de aproximarse a los parámetros reales y así tener un buen rendimiento del prototipo desde el punto de vista de la precisión de posicionamiento [2], [3] Con el fin establecer un comportamiento acertado del prototipo propuesto que desencadene en la obtención de la información de ubicación de cada una de las partes mecánicas del robot se utilizó la metodología de Denavit-Hartenberg y se deja el estudio presente como base para estudios posteriores del análisis dinámico de trayectorias y de control [4], [5] Adicionalmente se consideró como efector final la nariz del modelo (punto de control de rienda sobre un equino real) y a partir de la base (sistema de referencia) obtener la relación entre todos los subsistemas partiendo del eslabón cero hasta el punto central del efector final "TCP" [6].…”

Section: Introductionunclassified

Análisis cinemático del prototipo de robot equino desarrollado para el simulador de prácticas de tiro montado en la Escuela Nacional de Carabineros

Pumarejo

2018

LogosC&T

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Este escrito de investigación comprende de forma aproximada el modelamiento cinemático directo del robot equino de seis grados de libertad “6-DOF” desarrollado como producto de la investigación en curso titulada “Simulador equino para prácticas de tiro montado en la ESCAR”. El manipulador diseñado tiene fines educativos y será utilizado en las prácticas de tiro montado, como herramienta de apoyo didáctico en los cursos de carabineros de la policía nacional. Se presenta la propuesta de diseño del manipulador robótico adaptado a las necesidades educativas. Se utilizan actuadores eléctricos lineales de potencia que acoplan los eslabones de la cadena cinemática propuesta. Se aproxima la cinemática directa del robot, utilizando el algoritmo de Denavit-Hartenberg “DH” y se calcula el modelo dinámico del manipulador. Finalmente se valida el prototipo realizando pruebas de simulación del comportamiento del manipulador mediante la creación de segmentos de programa en Matlab® y se comparan con los resultados obtenidos mediante el control del mecanismo desde una aplicación de software desarrollada para tal fin en Microsoft Visual C# 2013®.

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Modeling and dynamic analysis of the biped robot

Cited by 7 publications

References 2 publications

fNIRS-based Neurorobotic Interface for gait rehabilitation

fNIRS-based Neurorobotic Interface for gait rehabilitation

Fuzzy Logic-Based Controller for Bipedal Robot

Análisis cinemático del prototipo de robot equino desarrollado para el simulador de prácticas de tiro montado en la Escuela Nacional de Carabineros

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