Generation of an optimal architecture of neuro force
controllers for robot manipulators in unknown
environments using genetic programming with fuzzy
fitness evaluation
we have applied genetic programming to generate an
optimal architecture of neuro force controllers for
robot manipulators in any environment. In order to
perform precise force control in unknown environments,
the optimal structured neuro force controller is
generated using genetic programming with fuzzy fitness
evaluation. After the architecture of the neuro
controller has been optimised for any kinds of
environments, it can be applied for a robot contact
task with an unknown environment in on-line manner
using its own adaptation ability. An effective
crossover operation is proposed for the efficient
evolution of the controllers. The simulation has been
carried out to evaluate the effectiveness of the
proposed robot force controller.
%0 Journal Article
%1 kiguchi:2001:SC
%A Kiguchi, K.
%A Miyaji, H.
%A Watanabe, K.
%A Izumi, K.
%A Fukuda, T.
%D 2001
%J Soft Computing - A Fusion of Foundations,
Methodologies and Applications
%K Force Fuzzy Neuro Robot algorithms, control, controller, evaluation genetic manipulator, programming,
%N 3
%P 237--242
%T Generation of an optimal architecture of neuro force
controllers for robot manipulators in unknown
environments using genetic programming with fuzzy
fitness evaluation
%V 5
%X we have applied genetic programming to generate an
optimal architecture of neuro force controllers for
robot manipulators in any environment. In order to
perform precise force control in unknown environments,
the optimal structured neuro force controller is
generated using genetic programming with fuzzy fitness
evaluation. After the architecture of the neuro
controller has been optimised for any kinds of
environments, it can be applied for a robot contact
task with an unknown environment in on-line manner
using its own adaptation ability. An effective
crossover operation is proposed for the efficient
evolution of the controllers. The simulation has been
carried out to evaluate the effectiveness of the
proposed robot force controller.
@article{kiguchi:2001:SC,
abstract = {we have applied genetic programming to generate an
optimal architecture of neuro force controllers for
robot manipulators in any environment. In order to
perform precise force control in unknown environments,
the optimal structured neuro force controller is
generated using genetic programming with fuzzy fitness
evaluation. After the architecture of the neuro
controller has been optimised for any kinds of
environments, it can be applied for a robot contact
task with an unknown environment in on-line manner
using its own adaptation ability. An effective
crossover operation is proposed for the efficient
evolution of the controllers. The simulation has been
carried out to evaluate the effectiveness of the
proposed robot force controller.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Kiguchi, K. and Miyaji, H. and Watanabe, K. and Izumi, K. and Fukuda, T.},
biburl = {https://www.bibsonomy.org/bibtex/2f27a91e86fe5cc5f7aa7979b06d5cde7/brazovayeye},
interhash = {7eeba9aaad18105902cc1713544f2bf0},
intrahash = {f27a91e86fe5cc5f7aa7979b06d5cde7},
issn = {1432-7643},
journal = {Soft Computing - A Fusion of Foundations,
Methodologies and Applications},
keywords = {Force Fuzzy Neuro Robot algorithms, control, controller, evaluation genetic manipulator, programming,},
month = {June},
number = 3,
pages = {237--242},
timestamp = {2008-06-19T17:43:16.000+0200},
title = {Generation of an optimal architecture of neuro force
controllers for robot manipulators in unknown
environments using genetic programming with fuzzy
fitness evaluation},
volume = 5,
year = 2001
}