Intelligent control of humanoid robots using neural networks

Author

Katic, D. ; Vukobratovic, Miomk

Author_Institution

Robotics Lab., Mihailo Pupin Inst., Belgrade, Serbia

fYear

2004

fDate

23-25 Sept. 2004

Firstpage

31

Lastpage

35

Abstract

This paper focusses on the application of connectionist (neural networks) control techniques and their hybrid forms (neuro-fuzzy networks and neuro-genetic algorithms) in the area of humanoid robotic systems. It represents an attempt to cover the basic principles and concepts of connectionist learning control in humanoid robotics, with an outline of a number of recent algorithms used in advanced control of humanoid robots. Overall, this survey covers a selection of examples that serve to demonstrate the advantages and disadvantages of the application of connectionist control techniques.

Keywords

fuzzy control; fuzzy neural nets; genetic algorithms; humanoid robots; intelligent robots; learning (artificial intelligence); legged locomotion; neurocontrollers; connectionist control techniques; connectionist learning control; humanoid robotic systems; humanoid robots; hybrid forms; intelligent control; neural networks; neuro-fuzzy networks; neuro-genetic algorithms; Control systems; Humanoid robots; Intelligent control; Intelligent robots; Intelligent sensors; Legged locomotion; Medical robotics; Neural networks; Robot control; Robot sensing systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Network Applications in Electrical Engineering, 2004. NEUREL 2004. 2004 7th Seminar on

Print_ISBN

0-7803-8547-0

Type

conf

DOI

10.1109/NEUREL.2004.1416526

Filename

1416526