Adaptive behavior navigation of a mobile robot

Author

Zalama, Eduardo ; Gómez, Jaime ; Paul, Mariano ; Perán, José Ramón

Author_Institution

Instituto de las Tecnologias de la Produccion, Valladolid Univ., Spain

Volume

32

Issue

1

fYear

2002

fDate

1/1/2002 12:00:00 AM

Firstpage

160

Lastpage

169

Abstract

Describes a neural network model for the reactive behavioral navigation of a mobile robot. From the information received through the sensors the robot can elicit one of several behaviors (e.g., stop, avoid, stroll, wall following), through a competitive neural network. The robot is able to develop a control strategy depending on sensor information and learning operation. Reinforcement learning improves the navigation of the robot by adapting the eligibility of the behaviors and determining the linear and angular robot velocities

Keywords

mobile robots; neurocontrollers; path planning; recurrent neural nets; sensor fusion; unsupervised learning; adaptive behavior navigation; angular velocities; competitive neural network; control strategy; learning control; learning operation; linear velocities; mobile robot; neural network model; obstacle avoidance; reactive behavioral navigation; reinforcement learning; sensor information; Control systems; Humans; Infrared sensors; Learning; Mobile robots; Navigation; Neural networks; Psychology; Robot control; Robot sensing systems;

fLanguage

English

Journal_Title

Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on

Publisher

ieee

ISSN

1083-4427

Type

jour

DOI

10.1109/3468.995537

Filename

995537