IJCAI-2001 Workshop on

Reasoning with Uncertainty in Robotics

On-line proceedings

[ Workshop homepage ]


Foreword

Uncertainty plays an important role in robot navigation at many levels, such as sensor interpretation, environment modeling, spatial reasoning, planning and decision making, self-localization, and motion control. As mobile robots are going to be used for increasingly complex tasks and environments, they are faced with the problem of how to deal with the increasing amount of uncertainty that affects the available knowledge. Dealing with uncertainty also constitutes the focus of a large research effort in AI, which has led to a large number of new theories and new techniques. However, it is only recently that the field of robot navigation has started to import some of the several techniques developed in AI for dealing with uncertain information.

The Workshop on Reasoning with Uncertainty in Robotics (RUR) aims at providing a forum to present and discuss new approaches to dealing with uncertainty in robotic applications. The first RUR workshop, held in Amsterdam, NL, on December 1995, was probably the first event to bring together researchers in the field of robotics and of uncertainty in AI. The second RUR workshop was held in Stokholm, SE, on August 1999, as part of IJCAI'99. The IJCAI-2001 Workshop on Reasoning with Uncertainty in Robotics is the third workshop in this series.

In addition to novel applications of known uncertainty methods, this year RUR will put a special emphasis on the problem of understanding the intended semantics of the uncertainty representations used in robotic applications. This understanding is essential if we want to be able to assess the relative merits and demerits of different uncertainty representations (e.g., probability theory, evidence theory, fuzzy sets) when used to solve different aspects of the robot navigation problem. Papers comparing different approaches to manage uncertainty, or reporting and analyzing negative results, are especially welcome.

This workshop will interest all people working in mobile robotics, both from academy and from industry. It will also interest researchers working in the area of uncertainty in AI, since it will offer them the possibility to apply their techniques to real and challenging problems.

Dieter Fox and Alessandro Saffiotti
Workshop Chairs

Contributed papers

The following papers are available in either PDF or PostScript format. PostScript files are compressed using gzip. File size is indicated on the left.

[137K]  Tracking People from a Moving Platform
D. Beymer and K. Konolige
IBM Almaden Research Center and SRI International, USA

[155K]  Simultaneous Localization and Mapping - a new algorithm for a compass-equipped mobile robot
T. Duckett, S. Marsland, and J. Shapiro
University of Orebro, Sweden and University of Manchester, UK

[147K]   Simultaneous Localization and Mapping - A Discussion
Udo Frese Email and Gerd Hirzing Email
Institute of Robotics und Mechatronics, Wessling, Germany

[120K]   Belief Update and Probabilistic Projection in the pGolog Framework
H. Grosskreutz Email and G. Lakemeyer Email
Aachen University of Technology, Germany

[90K]   A strategy for robot surveillance using the geometrical structure of the environment
N. Massios, L. Dorst, and F. Voorbraak
University of Amsterdam, The Netherlands

[728K]   Task, Situation and User Models for Personal Robots
Y. Motomura, I. Hara, K. Itoh, H. Asoh, and T. Sato
Nat. Inst. of Advanced Industrial Science and Technology, Tsukuba, Japan

[249K]  Avoidance of mobile obstacles in real environments
M. Mucientes, M. Rodriguez, C.V. Regueiro, R. Iglesias, A. Bugarin, and S. Barro
University of Santiago de Compostela, Spain

[2024K]  Dempster-Shafer weight of conflict metric as an indicator of mapping errors
R. Murphy, B. Sjoberg, A. Schultz, and B. Adams
University of South Florida, USA

[287K]  A hybrid approach to solve the global localization problem for indoor mobile robots considering sensor's perceptual limitations
L. Romero, E. Morales, and E. Sucar
ITESM Campus Cuernavaca, Mexico

[305]  Tracking multiple moving objects with a mobile robot
D. Schulz, W. Burgard, and D. Fox
Univertisy of Bonn, Germany

[784K]  A Programming Language Extension for Probabilistic Robot Programming
S. Thrun
Carnegie Mellon University, USA
Statements of Interest
M.T. Escrig Monferrer Jaume I Univ, Spain
B. Lamine Sherbrooke Univ, Canada
K. Murphy Berkeley Univ, USA
R. St-Aubin Univ of British Columbia, Canada
R. Washington ARC Nasa, USA

 

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Last updated on Aug 16, 2001