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  • 1.
    Conte, Gianpaolo
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Duranti, Simone
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group .
    Merz, Torsten
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group .
    Dynamic 3D path following for an autonomous helicopter2004In: Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV), Elsevier , 2004Conference 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.

  • 2.
    Conte, Gianpaolo
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Hempel, Maria
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Rudol, Piotr
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Lundström, David
    Linköping University, The Institute of Technology. Linköping University, Department of Management and Engineering, Fluid and Mechanical Engineering Systems.
    Duranti, Simone
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group .
    Wzorek, Mariusz
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Doherty, Patrick
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    High Accuracy Ground Target Geo-Location Using Autonomous Micro Aerial Vehicle Platforms2008In: Proceedings of the AIAA Guidance, Navigation, and Control Conference (GNC), AIAA , 2008Conference paper (Refereed)
    Abstract [en]

    This paper presents a method for high accuracy ground target localization using a Micro Aerial Vehicle (MAV) equipped with a video camera sensor. The proposed method is based on a satellite or aerial image registration technique. The target geo-location is calculated by registering the ground target image taken from an on-board video camera with a geo- referenced satellite image. This method does not require accurate knowledge of the aircraft position and attitude, therefore it is especially suitable for MAV platforms which do not have the capability to carry accurate sensors due to their limited payload weight and power resources.  The paper presents results of a ground target geo-location experiment based on an image registration technique. The platform used is a MAV prototype which won the 3rd US-European Micro Aerial Vehicle Competition (MAV07). In the experiment a ground object was localized with an accuracy of 2.3 meters from a ight altitude of 70 meters.

  • 3.
    Duranti, Simone
    et al.
    Linköping University, Department of Computer and Information Science, UASTECH - Autonomous Unmanned Aircraft Systems Technologies. Linköping University, The Institute of Technology.
    Conte, Gianpaolo
    Linköping University, Department of Computer and Information Science, UASTECH - Autonomous Unmanned Aircraft Systems Technologies. Linköping University, The Institute of Technology.
    In-flight Identification of the Augmented Flight Dynamics of the Rmax Unmanned Helicopter2007In: 17th IFAC Symposium on Automatic Control in Aerospace, International Federation of Automatic Control , 2007Conference paper (Other academic)
    Abstract [en]

    The flight dynamics of the Yamaha RMAX unmanned helicopter has been investigated, and mapped into a six degrees of freedom mathematical model. The model has been obtained by a combined black-box system identification technique and a classic model-based parameter identification approach. In particular, the closed-loop behaviour of the built-in attitude control system has been studied, to support the decision whether to keep it as inner stabilization loop or to develop an own stability augmentation system. The flight test method and the test instrumentation are described in detail; some samples of the flight test data are compared to the model outputs as validation, and an overall assessment of the built-in stabilization system is supplied.

  • 4.
    Duranti, Simone
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group .
    Conte, Gianpaolo
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Lundström, David
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group .
    Rudol, Piotr
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Wzorek, Mariusz
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Doherty, Patrick
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    LinkMAV, a prototype rotary wing micro aerial vehicle.2007In: 17th IFAC Symposium on Automatic Control in Aerospace,2007, Oxford: Elsevier , 2007Conference paper (Refereed)
  • 5.
    Kleiner, Alexander
    et al.
    University of Freiburg.
    Dornhege, Christian
    University of Freiburg.
    Kümmerle, Rainer
    University of Freiburg.
    Ruhnke, Michael
    University of Freiburg.
    Steder, Bastian
    University of Freiburg.
    Nebel, Bernhard
    University of Freiburg.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Wzorek, Mariusz
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Rudol, Piotr
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Conte, Gianpaolo
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Duranti, Simone
    Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group . Linköping University, The Institute of Technology.
    Lundström, David
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    RoboCupRescue - Robot League Team RescueRobots Freiburg (Germany)2006In: RoboCup 2006 (CDROM Proceedings), Team Description Paper, Rescue Robot League, 2006Conference paper (Refereed)
    Abstract [en]

    This paper describes the approach of the RescueRobots Freiburg team, which is a team of students from the University of Freiburg that originates from the former CS Freiburg team (RoboCupSoccer) and the ResQ Freiburg team (RoboCupRescue Simulation). Furthermore we introduce linkMAV, a micro aerial vehicle platform. Our approach covers RFID-based SLAM and exploration, autonomous detection of relevant 3D structures, visual odometry, and autonomous victim identification. Furthermore, we introduce a custom made 3D Laser Range Finder (LRF) and a novel mechanism for the active distribution of RFID tags.

  • 6.
    Merz, Torsten
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group .
    Duranti, Simone
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group .
    Conte, Gianpaolo
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Autonomous landing of an unmanned helicopter based on vision and inertial sensing2006In: Proceedings of the 9th International Symposium on Experimental Robotics / [ed] Marcelo H. Ang and Oussama Khatib, Springer , 2006, Vol. 21, p. 343-352Conference 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.

  • 7.
    Wzorek, Mariusz
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Conte, Gianpaolo
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Rudol, Piotr
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Merz, Torsten
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group .
    Duranti, Simone
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group .
    Doherty, Patrick
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    From Motion Planning to Control - A Navigation Framework for an Autonomous Unmanned Aerial Vehicle2006In: Proceedings of the 21st Bristol UAV Systems Conference (UAVS), 2006Conference 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.

1 - 7 of 7
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  • nn-NO
  • nn-NB
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