2.50
Hdl Handle:
http://hdl.handle.net/10547/279176
Title:
Probabilistic search with agile UAVs
Authors:
Waharte, Sonia; Symington, Andrew; Trigoni, Niki
Abstract:
Through their ability to rapidly acquire aerial imagery, Unmanned Aerial Vehicles (UAVs) have the potential to aid target search tasks. Many of the core algorithms which are used to plan search tasks use occupancy grid-based representations and are often based on two main assumptions. Firstly, the altitude of the UAV is constant. Secondly, the onboard sensors can measure the entire state of an entire grid cell. Although these assumptions are sufficient for fixed-wing, high speed UAVs, we do not believe that they are appropriate for small, lightweight, low speed and agile UAVs such as quadrotors. These platforms have the ability to change altitude and their low speed means that multiple measurements may easily overlap multiple cells for substantial periods of time. In this paper we extend a framework for probabilistic search based on decision making to incorporate multiple observations of grid cells and changes in UAV altitude. We account for observation areas that completely and partially cover multiple grid cells. We show the resultant impact on a number of simulation examples.
Citation:
Waharte, S.; Symington, A.; Trigoni, N., (2010) 'Probabilistic search with agile UAVs,' Robotics and Automation (ICRA), IEEE International Conference on: 2840-2845
Publisher:
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date:
2010
URI:
http://hdl.handle.net/10547/279176
DOI:
10.1109/ROBOT.2010.5509962
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5509962
Type:
Conference papers, meetings and proceedings
Language:
en
ISBN:
9781424450381
Appears in Collections:
Centre for Research in Distributed Technologies (CREDIT)

Full metadata record

DC FieldValue Language
dc.contributor.authorWaharte, Soniaen_GB
dc.contributor.authorSymington, Andrewen_GB
dc.contributor.authorTrigoni, Nikien_GB
dc.date.accessioned2013-04-07T16:35:41Z-
dc.date.available2013-04-07T16:35:41Z-
dc.date.issued2010-
dc.identifier.citationWaharte, S.; Symington, A.; Trigoni, N., (2010) 'Probabilistic search with agile UAVs,' Robotics and Automation (ICRA), IEEE International Conference on: 2840-2845en_GB
dc.identifier.isbn9781424450381-
dc.identifier.doi10.1109/ROBOT.2010.5509962-
dc.identifier.urihttp://hdl.handle.net/10547/279176-
dc.description.abstractThrough their ability to rapidly acquire aerial imagery, Unmanned Aerial Vehicles (UAVs) have the potential to aid target search tasks. Many of the core algorithms which are used to plan search tasks use occupancy grid-based representations and are often based on two main assumptions. Firstly, the altitude of the UAV is constant. Secondly, the onboard sensors can measure the entire state of an entire grid cell. Although these assumptions are sufficient for fixed-wing, high speed UAVs, we do not believe that they are appropriate for small, lightweight, low speed and agile UAVs such as quadrotors. These platforms have the ability to change altitude and their low speed means that multiple measurements may easily overlap multiple cells for substantial periods of time. In this paper we extend a framework for probabilistic search based on decision making to incorporate multiple observations of grid cells and changes in UAV altitude. We account for observation areas that completely and partially cover multiple grid cells. We show the resultant impact on a number of simulation examples.en_GB
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_GB
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5509962en_GB
dc.subjectcontrol systemsen_GB
dc.subjectrobotics and automationen_GB
dc.subjectPath planningen_GB
dc.subjectroboticsen_GB
dc.titleProbabilistic search with agile UAVsen
dc.typeConference papers, meetings and proceedingsen
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