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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.
    Doherty, Patrick
    et al.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Haslum, Patrik
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Heintz, Fredrik
    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.
    Nyblom, Per
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Persson, Tommy
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    Wingman, Björn
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    A Distributed Architecture for Autonomous Unmanned Aerial Vehicle Experimentation2004Inngår i: 7th International Symposium on Distributed Autonomous Robotic Systems,2004, Toulouse: LAAS , 2004, s. 221-Konferansepaper (Fagfellevurdert)
  • 3.
    Merz, Torsten
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group.
    Building a System for Autonomous Aerial Robotics Research2004Inngår i: Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV), Amsterdam: Elsevier , 2004Konferansepaper (Fagfellevurdert)
  • 4.
    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.

  • 5.
    Merz, Torsten
    et al.
    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.
    Control System Framework for Autonomous Robots Based on Extended State Machines2006Inngår i: Proceedings of the International Conference on Autonomic and Autonomous Systems (ICAS), 2006Konferansepaper (Fagfellevurdert)
  • 6.
    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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