Dynamic Generation and Switching of Object Handling Behaviors by a Humanoid Robot Using a Recurrent Neural Network Model

Autor:	Kuniaki Noda, Yukiko Hoshino, Masato Ito, Jun Tani
Rok vydání:	2006
Předmět:	Artificial neural network Computer science business.industry Robotics Virtual reality Computer Science::Robotics Recurrent neural network Robot Artificial intelligence business Recurrent neural network model Humanoid robot Simulation Parametric statistics
Zdroj:	From Animals to Animats 9 ISBN: 9783540386087 SAB
DOI:	10.1007/11840541_16
Popis:	The present study describes experiments on a ball handling behavior learning that is realized by a small humanoid robot with a dynamic neural network model, the recurrent neural network with parametric bias (RNNPB) The present experiments show that after the robot learned different types of behaviors through direct human teaching, the robot was able to switch between two types of behaviors based on the ball motion dynamics We analyzed the parametric bias (PB) space to show that each of the multiple dynamic structures acquired in the RNNPB corresponds with taught multiple behavior patterns and that the behaviors can be switched by adjusting the PB values.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c14864e9c38c407498607ecb3528e8d4 https://doi.org/10.1007/11840541_16 Zobrazit plný text záznamu