Machine Learning of Robot Assembly Plans [Segre 2011-10-05].pdf

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MACHINE LEARNING OF ROBOT ASSEMBLY PLANS
THE KLUWER INTERNATIONAL SERIES
IN ENGINEERING AND COMPUTER SCIENCE
KNOWLEDGE REPRESENTATION,
LEARNING AND EXPERT SYSTEMS
Consulting Editor
Tom Mitchell
Carnegie Mellon University
Other books in the series:
Universal Subgoaling and Chunking of Goal Hierarchies.
J.
Laird, P. Rosenbloom, A. Newell.
ISBN 0-89838-213-0.
Machine Learning: A Guide to Current Research.
T. Mitchell,
J.
Carbonell, R. Michalski.
ISBN 0-89838-214-9.
Machine Learning of Inductive Bias.
P. Utgoff. ISBN 0-89838-223-8.
A Connectionist Machine for Genetic Hillclimbing.
D. H. Ackley. ISBN 0-89838-236-X.
Learning From Good and Bad Data.
P. D. Laird. ISBN 0-89838-263-7.
MACHINE LEARNING OF ROBOT
ASSEMBLY PLANS
by
Alberto Maria Segre
Cornell University
KLUWER ACADEMIC PUBLISHERS
Boston/Dordrecht/Lancaster
"
~.
Distributors for North America:
Kluwer Academic Publishers
101 Philip Drive
Assinippi Park
Norwell, Massachusetts 02061, USA
Distributors for the UK and Ireland:
Kluwer Academic Publishers
Falcon House, Queen Square
Lancaster LAI IRN, UNITED KINGDOM
Distributors for all other countries:
Kluwer Academic Publishers Group
Distribution Centre
Post Office Box 322
3300 AH Dordrecht, THE NETHERLANDS
Library of Congress Cataloging-in-Publication Data
Segre, Alberto Maria.
Machine learning of robot assembly plans
I
by Alberto Maria Segre.
p. em. - (Kluwer international series in engineering and
computer science. Knowledge representation, learning, and expert
systems)
Bibliography: p.
Includes index.
e-ISBN-13: 978-1-4613-1691-6
ISBN-13: 978-1-4612-8954-8
DOl: 10.1007/978-1-4613-1691-6
I. Robotics. 2. Robots, Industrial.
TJ211.S43 1988
670.42 '7-dcI9
I.
Title.
II. Series.
88-2652
CIP
Copyright © 1988 by Kluwer Academic Publishers
Softcover reprint of the hardcover 1st edition 1988
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or
transmitted in any form or by any means, mechanical, photocopying, recording, or otherwise,
without the prior written permission of the publisher, Kluwer Academic Publishers, 101 Philip
Drive, Assinippi Park, Norwell, Massachusetts 02061.
Table of Contents
Preface ................................................................................................
Acknowledgements ................................ .... .................................... ....
Chapter 1 Introduction ......... ................. ....................................... ....
1.1. Machine Learning ..................................................................
1.2. Robotics ...................................................................................
1.2.1. Why Can't Robbie Learn? ...............................................
1.2.2. Teach-By-Guiding Systems ..............................................
1.2.3. Robot Programming Systems ....... ... ....... ....... .......... .........
1.2.4. Myopia on the Road to Intelligent Robots ......................
1.3. About the Book .......... ...... ........... ..... ..... .................... ..... ........
1.3.1. Organization ......................................................................
1.3.2. On the Use of the
$
Symbol.............................................
Chapter 2 Scenario ........................................... ................... ....... ......
2.1. Preliminaries ..........................................................................
2.1.1. The Widget ... ..... .......... ..... ....... ..... ..... ...... ..... ..... .......... ......
2.1.2. Moving the Robot Arm .....................................................
2.2. Specifying the Problem .. .............. ..... ...... ................ ..............
2.2.1. Describing the Initial State .............................................
2.2.2. Specifying the Goal State .................................................
2.3. Attempting to Solve the Problem .........................................
2.4. Observing the Expert's Plan ...... ..... ...................... ....... .... .....
2.5. Generalizing the Solution .....................................................
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