Para acceder a los documentos con el texto completo, por favor, siga el siguiente enlace:

Kinematic Bézier maps
Ulbrich, Stefan; Ruiz de Angulo García, Vicente; Torras, Carme; Asfour, Tamim; Dillmann, Rudiger
Universitat Politècnica de Catalunya. Institut de Robòtica i Informàtica Industrial; Universitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI
The kinematics of a robot with many degrees of freedom is a very complex function. Learning this function for a large workspace with a good precision requires a huge number of training samples, i.e., robot movements. In this paper, we introduce the Kinematic Bézier Map (KB-Map), a parameterizable model without the generality of other systems but whose structure readily incorporates some of the geometric constraints of a kinematic function. In this way, the number of training samples required is drastically reduced. Moreover, the simplicity of the model reduces learning to solving a linear least squares problem. Systematic experiments have been carried out showing the excellent interpolation and extrapolation capabilities of KB-Maps and their relatively low sensitivity to noise.
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
Artificial intelligence
learning (artificial intelligence) robot kinematics robots PARAULES AUTOR: learning
robot kinematics
humanoid robots
Intel·ligència artificial
Classificació INSPEC::Cybernetics::Artificial intelligence
Attribution-NonCommercial-NoDerivs 3.0 Spain
Artículo - Borrador

Mostrar el registro completo del ítem

Documentos relacionados

Otros documentos del mismo autor/a

Ulbrich, Stefan; Ruiz de Angulo García, Vicente; Asfour, Tamim; Torras, Carme; Dillmann, Rüdiger
Krüger, Norbert; Geib, Cristopher; Piater, Justus; Petrick, Ronald; Steedman, Mark; Wörgötter, Florentin; Ude, Ales; Asfour, Tamim; Kraft, Dirk; Omrcen, Damir; Agostini, Alejandro Gabriel; Dillmann, Rudiger
Ruiz de Angulo García, Vicente; Torras, Carme
Ruiz de Angulo García, Vicente; Torras, Carme