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Navigation Functionalities for an Autonomous UAV Helicopter
Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group . Linköping University, The Institute of Technology.
2007 (English)Licentiate thesis, comprehensive summary (Other academic)
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.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press , 2007. , p. 107
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1307
Keywords [en]
Unmanned Aerial Vehicle, Control System, Path Following, Path Planning, Sensor Fusion, Vision Based Landing, Kalman Filter, Real-Time
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-21966Local ID: LiU-Tek-Lic-2007:16ISBN: 9789185715350 (print)OAI: oai:DiVA.org:liu-21966DiVA, id: diva2:242149
Presentation
2007-03-30, Alan Turing, hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2009-10-15 Created: 2009-10-07 Last updated: 2020-07-03Bibliographically approved
List of papers
1. Dynamic 3D path following for an autonomous helicopter
Open this publication in new window or tab >>Dynamic 3D path following for an autonomous helicopter
2004 (English)In: Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV), Elsevier , 2004Conference paper, Published paper (Refereed)
Abstract [en]

A hybrid control system for dynamic path following for an autonomous helicopter is described. The hierarchically structured system combines continuous control law execution with event-driven state machines. Trajectories are defined by a sequence of 3D path segments and velocity profiles, where each path segment is described as a parametric curve. The method can be used in combination with a path planner for flying collision-free in a known environment. Experimental flight test results are shown.

Place, publisher, year, edition, pages
Elsevier, 2004
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-22974 (URN)2345 (Local ID)008-044237-4 (ISBN)2345 (Archive number)2345 (OAI)
Available from: 2009-10-07 Created: 2009-10-07 Last updated: 2018-01-13Bibliographically approved
2. Autonomous landing of an unmanned helicopter based on vision and inertial sensing
Open this publication in new window or tab >>Autonomous landing of an unmanned helicopter based on vision and inertial sensing
2006 (English)In: Proceedings of the 9th International Symposium on Experimental Robotics / [ed] Marcelo H. Ang and Oussama Khatib, Springer , 2006, Vol. 21, p. 343-352Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
Springer, 2006
Series
Springer Tracts in Advanced Robotics, ISSN 1610-7438 ; 21
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-50036 (URN)10.1007/11552246_33 (DOI)978-3-540-28816-9 (ISBN)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2011-03-08Bibliographically approved
3. From Motion Planning to Control - A Navigation Framework for an Autonomous Unmanned Aerial Vehicle
Open this publication in new window or tab >>From Motion Planning to Control - A Navigation Framework for an Autonomous Unmanned Aerial Vehicle
Show others...
2006 (English)In: Proceedings of the 21st Bristol UAV Systems Conference (UAVS), 2006Conference paper, Published paper (Refereed)
Abstract [en]

The use of Unmanned Aerial Vehicles (UAVs) which can operate autonomously in dynamic and complex operational environments is becoming increasingly more common. While the application domains in which they are currently used are still predominantly military in nature, in the future we can expect wide spread usage in thecivil and commercial sectors. In order to insert such vehicles into commercial airspace, it is inherently important that these vehicles can generate collision-free motion plans and also be able to modify such plans during theirexecution in order to deal with contingencies which arise during the course of operation. In this paper, wepresent a fully deployed autonomous unmanned aerial vehicle, based on a Yamaha RMAX helicopter, whichis capable of navigation in urban environments. We describe a motion planning framework which integrates two sample-based motion planning techniques, Probabilistic Roadmaps and Rapidly Exploring Random Treestogether with a path following controller that is used during path execution. Integrating deliberative services, suchas planners, seamlessly with control components in autonomous architectures is currently one of the major open problems in robotics research. We show how the integration between the motion planning framework and thecontrol kernel is done in our system.

Additionally, we incorporate a dynamic path reconfigurability scheme. It offers a surprisingly efficient method for dynamic replanning of a motion plan based on unforeseen contingencies which may arise during the execution of a plan. Those contingencies can be inserted via ground operator/UAV interaction to dynamically change UAV flight paths on the fly. The system has been verified through simulation and in actual flight. We present empirical results of the performance of the framework and the path following controller.

National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-36792 (URN)32592 (Local ID)32592 (Archive number)32592 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2023-05-25Bibliographically approved

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Conte, Gianpaolo

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