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Autonomous landing of an unmanned helicopter based on vision and inertial sensing
Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
2006 (engelsk)Inngår i: Proceedings of the 9th International Symposium on Experimental Robotics / [ed] Marcelo H. Ang and Oussama Khatib, Springer , 2006, Vol. 21, s. 343-352Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

In this paper we propose an autonomous precision landing method for an unmanned helicopter based on an on-board visual navigation system consisting of a single pan-tilting camera, off-the-shelf computer hardware and inertial sensors. Compared to existing methods, the system doesn't depend on additional sensors (in particular not on GPS), offers a wide envelope of starting points for the autonomous approach, and is robust to different weather conditions. Helicopter position and attitude is estimated from images of a specially designed landing pad. We provide results from both simulations and flight tests, showing the performance of the vision system and the overall quality of the landing. © Springer-Verlag Berlin/Heidelberg 2006.

sted, utgiver, år, opplag, sider
Springer , 2006. Vol. 21, s. 343-352
Serie
Springer Tracts in Advanced Robotics, ISSN 1610-7438 ; 21
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-50036DOI: 10.1007/11552246_33ISBN: 978-3-540-28816-9 (tryckt)OAI: oai:DiVA.org:liu-50036DiVA, id: diva2:270932
Tilgjengelig fra: 2009-10-11 Laget: 2009-10-11 Sist oppdatert: 2011-03-08bibliografisk kontrollert
Inngår i avhandling
1. Navigation Functionalities for an Autonomous UAV Helicopter
Åpne denne publikasjonen i ny fane eller vindu >>Navigation Functionalities for an Autonomous UAV Helicopter
2007 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
Abstract [en]

This thesis was written during the WITAS UAV Project where one of the goals has been the development of a software/hardware architecture for an unmanned autonomous helicopter, in addition to autonomous functionalities required for complex mission scenarios. The algorithms developed here have been tested on an unmanned helicopter platform developed by Yamaha Motor Company called the RMAX. The character of the thesis is primarily experimental and it should be viewed as developing navigational functionality to support autonomous flight during complex real world mission scenarios. This task is multidisciplinary since it requires competence in aeronautics, computer science and electronics. The focus of the thesis has been on the development of a control method to enable the helicopter to follow 3D paths. Additionally, a helicopter simulation tool has been developed in order to test the control system before flight-tests. The thesis also presents an implementation and experimental evaluation of a sensor fusion technique based on a Kalman filter applied to a vision based autonomous landing problem. Extensive experimental flight-test results are presented.

sted, utgiver, år, opplag, sider
Linköping: Linköping University Electronic Press, 2007. s. 74
Serie
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1307
Emneord
Unmanned Aerial Vehicle, Control System, Path Following, Path Planning, Sensor Fusion, Vision Based Landing, Kalman Filter, Real-Time
HSV kategori
Identifikatorer
urn:nbn:se:liu:diva-21966 (URN)LiU-Tek-Lic-2007:16 (Lokal ID)978-91-85715-35-0 (ISBN)LiU-Tek-Lic-2007:16 (Arkivnummer)LiU-Tek-Lic-2007:16 (OAI)
Presentation
2007-03-30, Alan Turing, hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2009-10-15 Laget: 2009-10-07 Sist oppdatert: 2009-10-16bibliografisk kontrollert

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Totalt: 334 treff
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