Mihaylova, L.S. orcid.org/0000-0001-5856-2223, Lefebvre, T., Bruyninckx, H. et al. (2 more authors) (2003) A Comparison of Decision Making Criteria and Optimization Methods for Active Robotic Sensing. In: Dimov, I., Lirkov, I., Margenov, S. and Zlatev, Z., (eds.) Numerical Methods and Applications. 5th International Conference on Numerical Methods and Applications, 20-24 Aug 2002, Borovets, Bulgaria. Lecture Notes in Computer Science, 2542 . Springer Berlin Heidelberg , pp. 316-324. ISBN 978-3-540-00608-4
Abstract
This work presents a comparison of decision making criteria and optimization methods for active sensing in robotics. Active sensing incorporates the following aspects: (i) where to position sensors, and (ii) how to make decisions for next actions, in order to maximize information gain and minimize costs. We concentrate on the second aspect: \Where should the robot move at the next time step?". Pros and cons of the most often used statistical decision making strategies are discussed. Simulation results from a new multisine approach for active sensing of a nonholonomic mobile robot are given.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2003 Springer Verlag. This is an author produced version of a paper subsequently published in Numerical Methods and Applications. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 29 Sep 2016 09:20 |
Last Modified: | 22 Mar 2018 18:00 |
Published Version: | https://dx.doi.org/10.1007/3-540-36487-0_35 |
Status: | Published |
Publisher: | Springer Berlin Heidelberg |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/3-540-36487-0_35 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:82257 |