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dc.creatorVillate, Cristian
dc.creatorPeña Cortes, Cesar Augusto
dc.creatorGualdron Guerrero, Oscar Eduardo
dc.date.accessioned2019-02-12T01:39:10Z
dc.date.available2019-02-12T01:39:10Z
dc.date.issued2018-01-01
dc.identifier.citationVillate, C., Peña Cortes, C., & Gualdron Guerrero, O. (2018). Algoritmo estocástico para la generación automática de trayectorias de un robot humanoide. INGE CUC, 14(1), 30-40. https://doi.org/10.17981/ingecuc.14.1.2018.03spa
dc.identifier.issn0122-6517, 2382-4700 electrónico
dc.identifier.urihttp://hdl.handle.net/11323/2400
dc.description.abstractIntroducción: La incorporación de sistemas de aprendizaje autónomos en la robótica permitirá la resolución de una gran cantidad de problemas. Uno de ellos es la marcha autónoma para el caso de los robots humanoides debido a la complejidad que tiene por la gran cantidad de variables que influyen en este proceso.Objetivo: Desarrollar algoritmos que generen marchas autónomas en un robot humanoide con varios grados de libertad.Metodología: El estudio inicia con el desarrollo de algoritmos estocásticos con pocas dimensiones; luego, se extiende a situaciones n-dimensionales. Posteriormente, se realizan pruebas en simulación, y, por último, las pruebas experimentales. Resultados: Se generó un algoritmo basado en el modelo físico del robot para crear las trayectorias de marcha estocásticamente.Se implementó un simulador que contempla las restricciones cinemáticas incluyendo colisiones para verificar los resultados. Adicionalmente, se realizaron cien pruebas experimentales donde se verificó el correcto funcionamiento de las trayectorias.Conclusiones: Se pudo corroborar que es posible crear un algoritmo estocástico que mezcla reglas determinantes y aleatorias para generar marchas automáticamente en robots humanoides, extendiendo conceptos generados en espacios bidimensionales y tridimensionales a coordenadas articulares n-dimensionales.spa
dc.description.abstractIntroduction− The incorporation of an autonomous learning system in robotics will allow the resolution of a large number of problems. One is the autonomous march of the humanoid robots due to its complexity in the great number of variables regarding this process.Objective−Develop algorithms that generate autono-mous paths in a humanoid robot with various degrees of freedom. Methodology−The study begins with the develop-ment of stochastic algorithms with few dimensions. Then, it will be extended to n-dimensional situations. Afterwards, simulation tests will be carried out. And finally, the experimental tests are performed. Results− An algorithm was generated based on the physical model of the robot to create walking paths sto-chastically. A simulator that contemplates the kinematic constraints, including collisions, was implemented to ve-rify the results. In addition, one hundred experimental tests were done. With these tests, the correct operation of the trajectories was verified. Conclusions−It was verified that it is possible to crea-te a stochastic algorithm that mixes determinant and random rules to automatically generate paths in hu-manoid robots, hence, extending concepts generated in two-dimensional and three-dimensional spaces to n-di-mensional articulated coordinates.eng
dc.format.mimetypeapplication/pdf
dc.language.isospaspa
dc.publisherCorporación Universidad de la Costaspa
dc.relation.ispartofseries1;
dc.sourceINGE CUCspa
dc.subjectRobots humanoidesspa
dc.subjectPlanificación de trayectoriasspa
dc.subjectRobots autónomosspa
dc.titleAlgoritmo estocástico para la generación automática de trayectorias de un robot humanoidespa
dc.typeArticlespa
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dc.source.urlhttps://revistascientificas.cuc.edu.co/ingecuc/article/view/1615
dc.identifier.eissn2382-4700
dc.identifier.pissn0122-6517


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