Book reviews / Automatica 39 (2003) 1113 – 1124 1121
Overall, this is a dicult book to read. The grammar
and phrasing is often awkward and the main contributions
tend to be obscured by confusing explanations. Also, the
notation and equation style are unusual and some eort is
required, on behalf of the reader, to become accustomed to
their appropriate interpretation.
The book is the revision of a doctoral thesis, and so it is
not an introductory text or a survey. Rather, it presents a
particular novel approach to several aspects of the SLAM
problem. As such, the audience for this book will be re-
searchers in the ÿeld, familiar with the mobile robot navi-
gation literature, and specially with stochastic SLAM.
Finally, mobile robot navigation is a fast-moving area of
research, and some contributions in the book are already
dated. As mentioned above, the batch data association algo-
rithms have recently been superseded. On the other hand,
the SP-model and SP-map (presented also in Castellanos,
Montiel, Neira, & TardÃos, 1999) comprise the most promis-
ing aspects of the book, and provide an interesting avenue
for further research. Particularly, it is important to demon-
strate the advantages of the SP-map in terms of numerical
stability, ease of implementation (e.g., bookkeeping for dis-
parate feature types), and susceptibility to bias.
Tim Bailey
E-mail address: tbailey@acfr.usyd.edu.au
Hugh Durrant-Whyte
Australian Centre for Field Robotics;
The University of Sydney;
The Rose Street Building J04
Sydney NSW 2006; Australia
doi:10.1016/S0005-1098(03)00066-9
References
Bailey, T. (2002). Mobile robot localisation and mapping in extensive
outdoor environments. Ph.D. Thesis, University of Sydney, Australian
Centre for Field Robotics.
Ballard, D. H., & Brown, C. M. (1982). Computer vision. Englewood
Clis, NJ: Prentice-Hall.
Burns, J. B., Hanson, A. R., & Riseman, E. M. (1986). Extracting
straight lines. IEEE Transactions on Pattern Analysis and Machine
Intelligence, 8(4), 425–455.
Castellanos, J. A. (1998). Mobile robot localization and map building:
A multisensor fusion approach. Ph.D. Thesis, Department of
Computer Science and Systems Engineering, University of Zaragoza,
1998.
Castellanos, J. A., Montiel, J. M. M., Neira, J., & TardÃos, J. D. (1999).
The SPmap: A probabilistic framework for simultaneous localization
and map building. IEEE Transactions on Robotics and Automation,
15(5), 948–952.
Moutarlier, P., & Chatila, R. (1989). Stochastic multisensory data fusion
for mobile robot location and environmental modelling. In Fifth
international symposium of robotics research (pp. 85–94).
Neira, J., & TardÃos, J. D. (2001). Data association in stochastic mapping
using the joint compatibility test. IEEE Transactions on Robotics and
Automation, 17(6), 890–897.
Neira, J., TardÃos, J. D., & Castellanos, J. A. (2002). Linear time vehicle
relocation in SLAM. Technical Report, Department of Computer
Science and Systems Engineering, University of Zaragoza.
Smith, R., Self, M., & Cheeseman, P. (1987). A stochastic map for
uncertain spatial relationships. In Fourth international symposium of
robotics research (pp. 467–474).
About the reviewers
Tim Bailey is a postdoctoral researcher, and Hugh Durrant-Whyte is
a Professor at the Australian Centre for Field Robotics (ACFR) at
The University of Sydney, Australia. They both have an interest in
SLAM.
Analytic feedback system design: an interpolation
approach
Peter Dorato; Brooks and Cole, Paciÿc Grove, CA,
2000, ISBN: 0-534-36917-0
1. Introduction
Control has been referred to as the “hidden technology”
because of its essential importance to many devices and sys-
tems while being mainly out of sight. The evolution of cheap
and powerful digital computers as well as computer-aided
design tools have had a major impact on control system
design and controller implementation. At the moment, the
ÿeld is going through fundamental transformations. Signi-
ÿcant interactions with communications, computer science,
and biotechnology are adding to the already existing appli-
cations in aerospace and process control. One thing is for
sure: our ÿeld is much more interdisciplinary than ever be-
fore. I can personally attest to this ÿrst hand working closely
with aerospace, mechanical, electrical, and materials engi-
neers as well as physicists and chemists. The developments
in this decade are set to re-invigorate the ÿeld as a dynamic
multi-disciplinary one.
Over the last three decades, numerous introductory
control textbooks have been written. The control theory af-
ter World War II was nicely summarized in the book by
Truxal (1955), and many introductory control textbooks are
now available (Franklin, Powell, & Emami-Naeini, 2002;
BÃelanger, 1995; D’Azzo & Houpis, 1995; Dorf & Bishop,
2001; Kuo, 1995; Nise, 2000; Ogata, 2002; Phillips &
Harbor, 2000), but the essential classical control theory
content do not dier much from that of Truxal’s. One no-
table trend has been to include more state-space material
and promote the use of digital control (Franklin, Powell, &
Workman, 1998), and computer-aided design tools where
MATLAB
J
is now the standard tool.
There has been a healthy discussion among our colleagues
in academia and industry on the suitable contents of an in
troductory course in control. The traditional curriculum has
been criticized as not keeping up with the times. The crit-
icisms range from questioning the need to even teach con-