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Probability-Based Robot Search Paths

Title data

Deiterding, Jan ; Henrich, Dominik:
Probability-Based Robot Search Paths.
In: Kröger, Torsten ; Wahl, Friedrich M. (ed.): Advances in Robotics Research : Theory, Implementation, Application. - Berlin : Springer , 2009 . - pp. 31-42
ISBN 978-3-642-01213-6
DOI: https://doi.org/10.1007/978-3-642-01213-6_4

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Project information

Project title:
Project's official title
Project's id
A-BOT
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Abstract in another language

The aim of this work is to show that robots can be improved using knowledge present or gained in previous executions of the task. Here, this knowledge is used to create search paths tailored to the problem at hand. We describe two approaches to create such paths automatically which enable robots to find an unknown position faster than standard paths. The solution presented here is not limited to the robotic domain, but can also be used for other purposes such as searching for injured persons after accidents. Our approach is evaluated through simulations and we show that these paths perform adequately well or even better than standard paths.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: adaptive systems; assembly; Industrial robots; motion planning; on-line algorithms; search algorithms
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science III > Chair Applied Computer Science III - Univ.-Prof. Dr. Dominik Henrich
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science III
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 24 Feb 2025 08:43
Last Modified: 24 Mar 2025 13:53
URI: https://eref.uni-bayreuth.de/id/eprint/92532