Publication detail
Aproximation of walking robot stability model
KREJSA, J. GREPL, R. VĚCHET, S.
Czech title
Aproximation of walking robot stability model
English title
Aproximation of walking robot stability model
Type
conference paper
Language
en
Original abstract
Abstract: The paper compares global and local approximation methods used for walking robot stability model. Global approximators are represented by feedforward multilayer neural network (FFNN) trained by gradient method; local approximators are represented by Locally Weighted Regression (LWR) and Receptive Field Weighted Regression (RFWR) methods.
Czech abstract
Abstract: The paper compares global and local approximation methods used for walking robot stability model. Global approximators are represented by feedforward multilayer neural network (FFNN) trained by gradient method; local approximators are represented by Locally Weighted Regression (LWR) and Receptive Field Weighted Regression (RFWR) methods.
English abstract
Abstract: The paper compares global and local approximation methods used for walking robot stability model. Global approximators are represented by feedforward multilayer neural network (FFNN) trained by gradient method; local approximators are represented by Locally Weighted Regression (LWR) and Receptive Field Weighted Regression (RFWR) methods.
Keywords in English
Stability, Walking robot, Aproximation
RIV year
2004
Released
10.05.2004
Publisher
Institute of Thermomechanics, Academy of Sciences of the Czec Republic
Location
Svratka
ISBN
80-85918-88-9
Book
Enigneering Mechanics 2004, National Conference with International Participation
Pages count
2
BIBTEX
@inproceedings{BUT12326,
author="Jiří {Krejsa} and Robert {Grepl} and Stanislav {Věchet},
title="Aproximation of walking robot stability model",
booktitle="Enigneering Mechanics 2004, National Conference with International Participation",
year="2004",
month="May",
publisher="Institute of Thermomechanics, Academy of Sciences of the Czec Republic",
address="Svratka",
isbn="80-85918-88-9"
}