Motion planning of hyper redundant manipulators based on a new geometrical method

Yahya, Samer; Moghavvemi, Mahmoud; Yang, Shuai; Mohamed, Haider A. F.

doi:10.1109/icit.2009.4939569

Cited by 16 publications

(10 citation statements)

References 15 publications

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“…This is a complex problem since the mapping between sensory and motor spaces is generally highly nonlinear and depends on the constraints imposed by the physical features of the human or robotic hand/finger as well as by the environment. In order to solve the inverse kinematic problem, various neural models were proposed; but many of these models did not integrate specific neurophysiological substrate resulting in a very limited biological plausibility (e.g., [4]). Conversely, other computational works proposed biologically plausible neural network models including specific brain structures/functions such as the Cerebellum [5]-[7] or the population vector coding processes found in motor/premotor areas [8]-[11].…”

Section: Introductionmentioning

confidence: 99%

Cortical network modeling for inverse kinematic computation of an anthropomorphic finger

Gentili

Molina

et al. 2011

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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The performance of reaching movements to visual targets requires complex kinematic mechanisms such as redundant, multijointed, anthropomorphic actuators and thus is a difficult problem since the relationship between sensory and motor coordinates is highly nonlinear. In this article, we present a neural model able to learn the inverse kinematics of a simulated anthropomorphic robot finger (ShadowHand™ finger) having four degrees of freedom while performing 3D reaching movements. The results revealed that this neural model was able to control accurately and robustly the finger when performing single 3D reaching movements as well as more complex patterns of motion while generating kinematics comparable to those observed in human. The long term goal of this research is to design a bio-mimetic controller providing adaptive, robust and flexible control of dexterous robotic/prosthetics hands.

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Section: Introductionmentioning

confidence: 99%

Cortical network modeling for inverse kinematic computation of an anthropomorphic finger

Gentili

Molina

et al. 2011

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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“…Sin embargo, en el caso de los robots hiper-redundantes, el espacio articular es de dimensión muy grande, por lo que el coste computacional de esos métodos es inviable. Por este motivo, en el caso de los robots hiper-redundantes discretos, este problema se ha intentado resolver mediante otras técnicas como diagramas de Voronoi (Shkolnik and Tedrake 2009), mediante métodos geométricos (Yahya, Moghavvemi et al 2009), algoritmos basados en RRT (Lee, Koo et al 2015), o mediante optimización de enjambre de partículas (Taherifar, Alasty et al 2013, Collins andShen 2016).…”

Section: Planificación De Movimientosunclassified

Robots Hiper-Redundantes: Clasificación, Estado del Arte y Problemática

Martín-Barrio

Terrile

Barrientos

et al. 2018

Rev. iberoam. autom. inform. ind.

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Los robots hiper-redundantes son aquellos que tienen un número muy elevado de grados de libertad. En su uso cotidiano, la redundancia es referida para indicar una repetición o un uso excesivo de un concepto. En el campo de la robótica, la redundancia puede ofrecer numerosos beneficios frente a los robots convencionales. Los robots hiper-redundantes poseen una mayor habilidad para sortear obstáculos, son tolerantes a fallos en algunas de sus articulaciones y también pueden ofrecer ventajas cinemáticas. En este artículo se presentan los conceptos generales para entender este tipo de robots, así como una clasificación de los mismos, su potencial, su problemática y su evolución a lo largo de la historia.

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“…Several algorithms in addition to the ones discussed above have been proposed for solving the obstacle avoidance problem [27], [28], [31], [33], [34]. Other techniques use the idea of considering the free space as tunnels in the obstacle filled workspace and use differential kinematics as done by Chirikjian and Burdick [36], [37]; while other techniques, as presented by Ma and Konno [38], separate the desired path into close points and for each step the manipulator tries to avoid the obstacles.…”

Section: A Related Workmentioning

confidence: 99%

Dynamically efficient kinematics for hyper-redundant manipulators

Xanthidis

Kyriakopoulos

Rekleitis

2016

2016 24th Mediterranean Conference on Control and Automation (MED)

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A hyper-redundant robotic arm is a manipulator with many degrees of freedom, capable of executing tasks in cluttered environments where robotic arms with fewer degrees of freedom are unable to operate. This paper introduces a new method for modeling those manipulators in a completely dynamic way. The proposed method enables online changes of the kinematic structure with the use of a special function; termed "meta-controlling function". This function can be used to develop policies to reduce drastically the computational cost for a single task, and to robustly control the robotic arm, even in the event of partial damage. The direct and inverse kinematics are solved for a generic three-dimensional articulated hyperredundant arm, that can be used as a proof of concept for more specific structures. To demonstrate the robustness of our method, experimental simulation results, for a basic "metacontrolling" function, are presented.

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Motion planning of hyper redundant manipulators based on a new geometrical method

Cited by 16 publications

References 15 publications

Cortical network modeling for inverse kinematic computation of an anthropomorphic finger

Cortical network modeling for inverse kinematic computation of an anthropomorphic finger

Robots Hiper-Redundantes: Clasificación, Estado del Arte y Problemática

Dynamically efficient kinematics for hyper-redundant manipulators

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