AI training for application to industrial robotics: trajectory generation for neural network tuning
Fecha
2023Versión
Acceso abierto / Sarbide irekia
Tipo
Contribución a congreso / Biltzarrerako ekarpena
Versión
Versión publicada / Argitaratu den bertsioa
Identificador del proyecto
Gobierno de Navarra//0011–1365-2021–000080 Gobierno de Navarra//0011–1411-2021–000023
Impacto
|
10.1007/978-3-031-38563-6_59
Resumen
In the present work robot trajectories are generated and kinematically simulated. Different data (joint coordinates, end effector position and orientation, images, etc.) are obtained in order to train a neural network suited for applications in robotics. The neural network has the goal of automatically generating trajectories based on a set of images and coordinates. For this purpose, trajectorie ...
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In the present work robot trajectories are generated and kinematically simulated. Different data (joint coordinates, end effector position and orientation, images, etc.) are obtained in order to train a neural network suited for applications in robotics. The neural network has the goal of automatically generating trajectories based on a set of images and coordinates. For this purpose, trajectories are designed in two separate sections which are conveniently connected using Bezier curves, ensuring continuity up to accelerations. In addition, among the possible trajectories that can be carried out due to the different configurations of the robot, the most suitable ones have been selected avoiding collisions and singularities. The designed algorithm can be used in multiple applications by adapting its different parameters. [--]
Materias
Industrial robotics,
Trajectory planning,
Artificial intelligence
Editor
Springer
Publicado en
Vizán Idoipe, A., García Prada, J.C. (eds). Proceedings of the XV Ibero-American Congress of Mechanical Engineering. IACME 2022. Springer, 2023
Departamento
Universidad Pública de Navarra. Departamento de Ingeniería /
Nafarroako Unibertsitate Publikoa. Ingeniaritza Saila /
Universidad Pública de Navarra/Nafarroako Unibertsitate Publikoa. Institute of Smart Cities - ISC
Versión del editor
Entidades Financiadoras
This work was funded by the “Convocatoria de ayudas a proyectos de I+D del Gobierno de Navarra” under the projects with Ref. 0011–1365-2021–000080 and Ref. 0011–1411-2021–000023.