Neural Networks in Robotics, 1993 The Springer International Series in Engineering and Computer Science Series, Vol. 202
Coordonnateurs : Bekey George A., Goldberg Kenneth Y.
On the other hand, connectionist (artificial neural network) formulations are attractive for the computation of inverse kinematics and dynamics of robots, because they can be trained for this purpose without explicit programming. Some of the computational advantages and problems of this approach are also presented.
For any serious student of robotics, Neural Networks in Robotics provides an indispensable reference to the work of major researchers in the field. Similarly, since robotics is an outstanding application area for artificial neural networks, Neural Networks in Robotics is equally important to workers in connectionism and to students for sensormonitor control in living systems.
Date de parution : 10-2012
Ouvrage de 563 p.
15.5x23.5 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 210,99 €
Ajouter au panierMots-clés :
expert system; kinematics; learning; mobile robot; optimization; programming; proving; robot; robotics; sensing; sensor