2009 IEEE International Conference on Industrial Technology 2009
DOI: 10.1109/icit.2009.4939569
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Motion planning of hyper redundant manipulators based on a new geometrical method

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Cited by 17 publications
(10 citation statements)
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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%
“…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%
“…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
“…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%