ZMP based gait generation of AIT's Leg Exoskeleton

Aphiratsakun, Narong; Chairungsarpsook, Kittipat; Parnichkun, Manukid

doi:10.1109/iccae.2010.5451901

Cited by 14 publications

(8 citation statements)

References 6 publications

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“…By assuming that the target is always reachable, the only case when there is no solution in two circle interaction will be that the centers of the two circles are too close. As a result, a condition is designed to prevent no solution in (13) and (14). The reason of having max and min function in (15) and ( 16) is because certain π 2 − ψ(φ 1 , p 5 ) can reach the target in the 5-link model but the human joint cannot operate at that range, so the max and min function will ensure that the range of φ max and φ min will be always within human range.…”

Section: B Inverse Kinematicmentioning

confidence: 99%

“…After obtaining φ 2 , p 2 can be computed by (18) and p 4 can use two circle intersection to obtain the solution similar to (13). Absolute angle of all joints can be computed by (11) after all joint positions are obtained for both torque analysis and motor control. Therefore, with the aid of IK and dynamical model, the relationship between the optimized parameter (x 5 , y 5 ), r 2 and φ 3 and torque of ankle joint T θ1 can be established which can be used in the optimization in the next section.…”

Section: B Inverse Kinematicmentioning

confidence: 99%

“…Many trajectory generation algorithms have been proposed to provide efficient and robust implementation to drive the exoskeleton. Some researchers have implemented the gait generation technology developed in bipedal humanoid on lower limb exoskeleton; for instance, linear inverted pendulum (LIP) [13] and zero moment point (ZMP) [14]. The resulting gait generated from the humanoid robot theory did not consider the human muscle dynamic and could be uncomfortable for the pilot.…”

Section: Introductionmentioning

confidence: 99%

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Upper Extremity Load Reduction for Lower LimbExoskeleton Trajectory Generation Using AnkleTorque Minimization

Wong¹,

Chen²,

Tsang³

et al. 2020

Preprint

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Recently, the lower limb exoskeletons which provide mobility for paraplegic patients to support their daily life have drawn much attention. However, the pilots are required to apply excessive force through a pair of crutches to maintain balance during walking. This paper proposes a novel gait trajectory generation algorithm for exoskeleton locomotion on flat ground and stair which aims to minimize the force applied by the pilot without increasing the degree of freedom (DoF) of the system. First, the system is modelled as a five-link mechanism dynamically for torque computing. Then, an optimization approach is used to generate the trajectory minimizing the ankle torque which is correlated to the supporting force. Finally, experiment is conducted to compare the different gait generation algorithms through measurement of ground reaction force (GRF) applied on the crutches.

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Section: B Inverse Kinematicmentioning

confidence: 99%

Section: B Inverse Kinematicmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Upper Extremity Load Reduction for Lower LimbExoskeleton Trajectory Generation Using AnkleTorque Minimization

Wong¹,

Chen²,

Tsang³

et al. 2020

Preprint

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“…Lower limb exoskeleton can also help the lower limb disabled maintain balance and walk [1,2]. It can be widely used in the medical rehabilitation and orthopedic fields [3]. Nowadays, the lower limb exoskeleton has become an international research hotspot in the field of robotics.…”

Section: Introductionmentioning

confidence: 99%

Study on the control algorithm for lower limb exoskeleton based on ADAMS/Simulink co-simulation

Wu¹,

Jia²,

Li³

et al. 2017

J. vibroeng.

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A sliding mode control algorithm based on proportional switching function was developed to make the lower limb exoskeleton more fit the human walking gait trajectory. It could improve the comfort of the exoskeleton wearer and enhance the reliability of the system. The three-dimensional mechanical model of the exoskeleton built using software SolidWorks was introduced to ADAMS and then the model parameters were set. The model was combined with the software MATLAB so that the human-machine cooperation control algorithm for lower limb exoskeleton based on ADAMS and Simulink co-simulation was developed. The simulation result was compared with the desired trajectory and the trajectory under PID control. The research discovered that the ability of trajectory tracking under the sliding mode control was much better than that under PID control. It provided an important theoretical basis for the research on human-machine cooperation control algorithm.

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“…Marey was soon reflected in the work of other authors like E. Muybridge [96] or W. Braune and O. Fischer [97]. Their assumptions in novel analyses of gait in humans have withstood a century of progress and similar oscillatory movements are studied in the design of modern exoskeletons, such us in [98]- [100]. On the other hand, the technologies applied by E. Muybridge [101] capturing S. Gardner at a Gallop were revolutionary in the field of art.…”

mentioning

confidence: 99%

Modelling activities of daily living applied to cognitive rehabilitation

Lacal¹,

Ignácio²

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AgradecimientosHace tiempo que decidí embarcarme en esta aventura y es imposible evitar mirar atrás y hacer balance de lo acontecido en este tiempo. Si de todas las personas que han desfilado por mi vida tuviera que nombrar a la precursora de todo esto, esa persona sería sin duda D. Ramón Galán. Todos los éxitos y la motivación de esta tesis parten de una visita trivial a un departamento de robótica y son responsabilidad directa tuya.Tampoco me olvido del día en el que Rafael Aracil y Manuel Ferre se acercaron al puesto en el que trabajaba y me ofrecían participar en algo que a posteriori supuso un giro a mi vida. A ellos también les agradezco haber llegado a mi actual situación.Desde entonces hasta ahora sólo puedo valorar la suerte de haber podido aprender y formarme en aquello que es mi vocación. Gracias por aportarme tanto. Siempre sabré valorar la oportunidad recibida. De mi director, Manuel Ferre, siempre agradeceré su eterna paciencia y tolerancia.Quiero agradecer a todos los compañeros que han pasado por el departamento de Este trabajo no habría sido posible tampoco sin la colaboración de todas y cada una de las personas que formaron parte del desarrollo del proyecto CogWatch. Quiero agradecer a cada uno de los compañeros que participaron en este proyecto ya que, sin la cooperación y estrecha colaboración que ofrecieron, nunca habría llegado hasta este punto. A partir de vuestro trabajo cobran sentido las famosas palabras de Bernard de Chartres y es que, sin vosotros, nunca podría haberme planteado el reto.Gracias a todos y cada una de las personas que formasteis parte del proyecto por aportar diferentes puntos de vista y soluciones, he aprendido mucho de todos. viii Nunca olvidaré los meses que pude disfrutar en Munich, donde conocí a gente maravillosa. Gracias al profesor Joachim Hermsdörfer por permitirme, durante mi estancia, ser uno más en su departamento y ser testigo de su día a día y buen hacer. ¡No se puede ser más acogedor!, debo dar las gracias en especial a Elvira Salazar, a Marta Bienkewich y a Kerstin Laimgruber por toda su ayuda y consejos para instalarme en Munich. Aprendí y disfruté mucho con vosotros y quiero darles las gracias, Yi-Huang, Marie-Luise, MaFe, "Bro" J, Philipp, Saskia, Alan y Ferdinand.Os agradezco a todos vosotros los buenos momentos vividos en Munich, nunca olvidaré ese picnic en Walchensee.Quiero tener también una mención especial a María Teresa Arredondo y su grupo Life Supporting Technologies, por haberme permitido seguir adelante con el trabajo aquí iniciado, qué es mi actual pasión. Y por supuesto a Matteo Pastorino y Alessio Fioravanti por ser tan buenos compañeros, por los buenos momentos vividos y el apoyo dado durante los momentos menos buenos. Es de recibo agradecerles, también, que me enseñaran, por descuido, algo de italiano, Butta n'…! En un terreno más personal, quiero dar las gracias a las personas que más me han apoyado, empezando por mis amigos.A mi familia por su continuo apoyo. La dedicación y las ganas nunca me han faltado gracias a la ilusión y actit...

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ZMP based gait generation of AIT's Leg Exoskeleton

Cited by 14 publications

References 6 publications

Upper Extremity Load Reduction for Lower LimbExoskeleton Trajectory Generation Using AnkleTorque Minimization

Upper Extremity Load Reduction for Lower LimbExoskeleton Trajectory Generation Using AnkleTorque Minimization

Study on the control algorithm for lower limb exoskeleton based on ADAMS/Simulink co-simulation

Modelling activities of daily living applied to cognitive rehabilitation

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