Use of neural networks in an undergraduate robotics course

Author

Clement, William I.

Author_Institution

US Naval Acad. Annapolis, MD, USA

fYear

1993

fDate

6-9 Nov 1993

Firstpage

705

Lastpage

709

Abstract

Within the Systems Engineering major at the US Naval Academy, the two-course robotics sequence introduces students to basic robotics terminology, geometry, components, and kinematics, as well as to machine vision and simple pattern recognition. The use of artificial neural networks in this course is discussed. The teachers stress the fundamentals of neural network theory and practice and try to give students some insight into problems that may arise. Particular attention is given to feedforward neural networks as functional mappings, neural network pruning, and neural network software for the laboratory

Keywords

control engineering computing; control engineering education; educational courses; feedforward neural nets; robots; Systems Engineering major; US Naval Academy; feedforward neural networks; functional mappings; machine vision; neural network pruning; neural network software; neural network theory; neural networks; pattern recognition; robotics components; robotics geometry; robotics kinematics; robotics terminology; undergraduate robotics course; Artificial neural networks; Computational geometry; Educational robots; Feedforward neural networks; Kinematics; Machine vision; Neural networks; Robot vision systems; Systems engineering and theory; Terminology;

fLanguage

English

Publisher

ieee

Conference_Titel

Frontiers in Education Conference, 1993. Twenty-Third Annual Conference. 'Engineering Education: Renewing America's Technology', Proceedings.

Conference_Location

Washington, DC

ISSN

0190-5848

Print_ISBN

0-7803-1482-4

Type

conf

DOI

10.1109/FIE.1993.405432

Filename

405432