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Multi-UAV Trajectory Planning for Guaranteed Search
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology. (Collaborative Robotics)
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology. (Collaborative Robotics)
2013 (English)In: Proc. of the 12th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2013), The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) , 2013, p. 79-86Conference paper, Published paper (Refereed)
Abstract [en]

We consider the problem of detecting all moving and evading targets in 2.5D environments with teams of UAVs. Targets are assumed to be fast and omniscient while UAVs are only equipped with limited range detection sensors and have no prior knowledge about the location of targets. We present an algorithm that, given an elevation map of the environment, computes synchronized trajectories for the UAVs to guarantee the detection of all targets. The approach is based on coordinating the motion of multiple UAVs on sweep lines to clear the environment from contamination, which represents the possibility of an undetected target being located in an area. The goal is to compute trajectories that minimize the number of UAVs needed to execute the guaranteed search. This is achieved by converting 2D strategies, computed for a polygonal representation of the environment, to 2.5D strategies. We present methods for this conversion and consider cost of motion and visibility constraints. Experimental results demonstrate feasibility and scalability of the approach. Experiments are carried out on real and artificial elevation maps and provide the basis for future deployments of large teams of real UAVs for guaranteed search.

Place, publisher, year, edition, pages
The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) , 2013. p. 79-86
National Category
Computer Sciences Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-87289ISBN: 978-1-4503-1993-5 (print)OAI: oai:DiVA.org:liu-87289DiVA, id: diva2:588779
Conference
12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013)
Projects
ELLIIT; CADICS; CUAS; SHERPA
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications, 1025Available from: 2013-01-16 Created: 2013-01-15 Last updated: 2019-07-03Bibliographically approved

Open Access in DiVA

AAMAS-2013-Multi-UAV-Motion-Planning-for-Guaranteed-Search.pdf(3256 kB)915 downloads
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Type fulltextMimetype application/pdf

Authority records

Kolling, AndreasKleiner, Alexander

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • text
  • asciidoc
  • rtf