In this paper an evolutionary algorithm is developed to learn a fuzzy knowledge base for the control of a soccer playing micro-robot from any configuration belonging to a grid of initial configurations to hit the ball along the ball to goal line of sight. The knowledge base uses a relative co-ordinate system including left and right wheel velocities of the robot. Final path positions allow forward and reverse facing robot to ball and include its physical dimensions. A wheel lift constraint is now included in determining the controller
This paper is described one of the intelligent control method in Autonomous systems, which is called...
[[abstract]]A GA-based fuzzy controller design method is proposed for a two-wheeled mobile robot to ...
This paper describes a design method for mobile robot behaviours that employs a variety of soft comp...
In this paper an evolutionary algorithm is developed to learn a fuzzy knowledge base for the control...
In this chapter an evolutionary algorithm is developed to learn a fuzzy knowledge base for the contr...
In this paper, an evolutionary algorithm is developed to learn a three layer hierarchical fuzzy know...
"Robot soccer provides a fertile environment for the development of artificial intelligence techniqu...
In this paper we use an evolutionary algorithm to evolve paths using robot velocity profiles from an...
This paper provides an overview on evolutionary learning methods for the automated design and optimi...
AbstractThis paper presents a learning method which automatically designs fuzzy logic controllers (F...
This paper presents an automatic design method for fuzzy systems using genetic algorithms. A flexibl...
Fuzzy control has shown to be a very useful tool in the eld of autonomous mobile robotics, character...
AbstractFuzzy logic controllers (FLCs) consitute knowledge-based systems that include fuzzy rules an...
This paper develops the applicability of using fuzzy logic controller and incorporates it with other...
An autonomous mobile robot operating in an unstructured environment must be able to learn with dynam...
This paper is described one of the intelligent control method in Autonomous systems, which is called...
[[abstract]]A GA-based fuzzy controller design method is proposed for a two-wheeled mobile robot to ...
This paper describes a design method for mobile robot behaviours that employs a variety of soft comp...
In this paper an evolutionary algorithm is developed to learn a fuzzy knowledge base for the control...
In this chapter an evolutionary algorithm is developed to learn a fuzzy knowledge base for the contr...
In this paper, an evolutionary algorithm is developed to learn a three layer hierarchical fuzzy know...
"Robot soccer provides a fertile environment for the development of artificial intelligence techniqu...
In this paper we use an evolutionary algorithm to evolve paths using robot velocity profiles from an...
This paper provides an overview on evolutionary learning methods for the automated design and optimi...
AbstractThis paper presents a learning method which automatically designs fuzzy logic controllers (F...
This paper presents an automatic design method for fuzzy systems using genetic algorithms. A flexibl...
Fuzzy control has shown to be a very useful tool in the eld of autonomous mobile robotics, character...
AbstractFuzzy logic controllers (FLCs) consitute knowledge-based systems that include fuzzy rules an...
This paper develops the applicability of using fuzzy logic controller and incorporates it with other...
An autonomous mobile robot operating in an unstructured environment must be able to learn with dynam...
This paper is described one of the intelligent control method in Autonomous systems, which is called...
[[abstract]]A GA-based fuzzy controller design method is proposed for a two-wheeled mobile robot to ...
This paper describes a design method for mobile robot behaviours that employs a variety of soft comp...