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  • 1.
    Conte, Gianpaolo
    et al.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Duranti, Simone
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    Merz, Torsten
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    Dynamic 3D path following for an autonomous helicopter2004Inngår i: Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV), Elsevier , 2004Konferansepaper (Fagfellevurdert)
    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.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Hempel, Maria
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Rudol, Piotr
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Lundström, David
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Fluid och mekanisk systemteknik.
    Duranti, Simone
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    Wzorek, Mariusz
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Doherty, Patrick
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    High Accuracy Ground Target Geo-Location Using Autonomous Micro Aerial Vehicle Platforms2008Inngår i: Proceedings of the AIAA Guidance, Navigation, and Control Conference (GNC), AIAA , 2008Konferansepaper (Fagfellevurdert)
    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.
    Linköpings universitet, Institutionen för datavetenskap, UASTECH – Teknologier för autonoma obemannade flygande farkoster. Linköpings universitet, Tekniska högskolan.
    Conte, Gianpaolo
    Linköpings universitet, Institutionen för datavetenskap, UASTECH – Teknologier för autonoma obemannade flygande farkoster. Linköpings universitet, Tekniska högskolan.
    In-flight Identification of the Augmented Flight Dynamics of the Rmax Unmanned Helicopter2007Inngår i: 17th IFAC Symposium on Automatic Control in Aerospace, International Federation of Automatic Control , 2007Konferansepaper (Annet vitenskapelig)
    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.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    Conte, Gianpaolo
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Lundström, David
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    Rudol, Piotr
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Wzorek, Mariusz
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Doherty, Patrick
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    LinkMAV, a prototype rotary wing micro aerial vehicle.2007Inngår i: 17th IFAC Symposium on Automatic Control in Aerospace,2007, Oxford: Elsevier , 2007Konferansepaper (Fagfellevurdert)
  • 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
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Tekniska högskolan.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Tekniska högskolan.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Tekniska högskolan.
    Conte, Gianpaolo
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Tekniska högskolan.
    Duranti, Simone
    Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group. Linköpings universitet, Tekniska högskolan.
    Lundström, David
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Tekniska högskolan.
    RoboCupRescue - Robot League Team RescueRobots Freiburg (Germany)2006Inngår i: RoboCup 2006 (CDROM Proceedings), Team Description Paper, Rescue Robot League, 2006Konferansepaper (Fagfellevurdert)
    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.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    Duranti, Simone
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    Conte, Gianpaolo
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Autonomous landing of an unmanned helicopter based on vision and inertial sensing2006Inngår i: Proceedings of the 9th International Symposium on Experimental Robotics / [ed] Marcelo H. Ang and Oussama Khatib, Springer , 2006, Vol. 21, s. 343-352Konferansepaper (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.

  • 7.
    Wzorek, Mariusz
    et al.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Conte, Gianpaolo
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Rudol, Piotr
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Merz, Torsten
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    Duranti, Simone
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    Doherty, Patrick
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    From Motion Planning to Control - A Navigation Framework for an Autonomous Unmanned Aerial Vehicle2006Inngår i: Proceedings of the 21st Bristol UAV Systems Conference (UAVS), 2006Konferansepaper (Fagfellevurdert)
    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.

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