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  • 1.
    Andersson, Olov
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Deep Learning Quadcopter Control via Risk-Aware Active Learning2017Inngår i: Proceedings of The Thirty-first AAAI Conference on Artificial Intelligence (AAAI) / [ed] Satinder Singh and Shaul Markovitch, AAAI Press, 2017, Vol. 5, s. 3812-3818Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Modern optimization-based approaches to control increasingly allow automatic generation of complex behavior from only a model and an objective. Recent years has seen growing interest in fast solvers to also allow real-time operation on robots, but the computational cost of such trajectory optimization remains prohibitive for many applications. In this paper we examine a novel deep neural network approximation and validate it on a safe navigation problem with a real nano-quadcopter. As the risk of costly failures is a major concern with real robots, we propose a risk-aware resampling technique. Contrary to prior work this active learning approach is easy to use with existing solvers for trajectory optimization, as well as deep learning. We demonstrate the efficacy of the approach on a difficult collision avoidance problem with non-cooperative moving obstacles. Our findings indicate that the resulting neural network approximations are least 50 times faster than the trajectory optimizer while still satisfying the safety requirements. We demonstrate the potential of the approach by implementing a synthesized deep neural network policy on the nano-quadcopter microcontroller.

  • 2.
    Andersson, Olov
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Model-Predictive Control with Stochastic Collision Avoidance using Bayesian Policy Optimization2016Inngår i: IEEE International Conference on Robotics and Automation (ICRA), 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, s. 4597-4604Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Robots are increasingly expected to move out of the controlled environment of research labs and into populated streets and workplaces. Collision avoidance in such cluttered and dynamic environments is of increasing importance as robots gain more autonomy. However, efficient avoidance is fundamentally difficult since computing safe trajectories may require considering both dynamics and uncertainty. While heuristics are often used in practice, we take a holistic stochastic trajectory optimization perspective that merges both collision avoidance and control. We examine dynamic obstacles moving without prior coordination, like pedestrians or vehicles. We find that common stochastic simplifications lead to poor approximations when obstacle behavior is difficult to predict. We instead compute efficient approximations by drawing upon techniques from machine learning. We propose to combine policy search with model-predictive control. This allows us to use recent fast constrained model-predictive control solvers, while gaining the stochastic properties of policy-based methods. We exploit recent advances in Bayesian optimization to efficiently solve the resulting probabilistically-constrained policy optimization problems. Finally, we present a real-time implementation of an obstacle avoiding controller for a quadcopter. We demonstrate the results in simulation as well as with real flight experiments.

  • 3.
    Berger, Cyrille
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Kleiner, Alexander
    iRobot, Pasadena, CA, USA.
    Evaluation of Reactive Obstacle Avoidance Algorithms for a Quadcopter2016Inngår i: Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision 2016 (ICARCV), IEEE conference proceedings, 2016, artikkel-id Tu31.3Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this work we are investigating reactive avoidance techniques which can be used on board of a small quadcopter and which do not require absolute localisation. We propose a local map representation which can be updated with proprioceptive sensors. The local map is centred around the robot and uses spherical coordinates to represent a point cloud. The local map is updated using a depth sensor, the Inertial Measurement Unit and a registration algorithm. We propose an extension of the Dynamic Window Approach to compute a velocity vector based on the current local map. We propose to use an OctoMap structure to compute a 2-pass A* which provide a path which is converted to a velocity vector. Both approaches are reactive as they only make use of local information. The algorithms were evaluated in a simulator which offers a realistic environment, both in terms of control and sensors. The results obtained were also validated by running the algorithms on a real platform.

  • 4.
    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.

  • 5.
    Conte, Gianpaolo
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Kleiner, Alexander
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Korwel, Karol
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Performance evaluation of a light weight multi-echo LIDAR for unmanned rotorcraft applications2013Inngår i: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W2, Copernicus Gesellschaft MBH , 2013Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The paper presents a light-weight and low-cost airborne terrain mapping system. The developed Airborne LiDAR Scanner (ALS) sys- tem consists of a high-precision GNSS receiver, an inertial measurement unit and a magnetic compass which are used to complement a LiDAR sensor in order to compute the terrain model. Evaluation of the accuracy of the generated 3D model is presented. Additionally, a comparison is provided between the terrain model generated from the developed ALS system and a model generated using a commer- cial photogrammetric software. Finally, the multi-echo capability of the used LiDAR sensor is evaluated in areas covered with dense vegetation. The ALS system and camera systems were mounted on-board an industrial unmanned helicopter of around 100 kilograms maximum take-off weight. Presented results are based on real flight-test data.

  • 6.
    Danelljan, Martin
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska högskolan.
    Khan, Fahad Shahbaz
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Felsberg, Michael
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Granström, Karl
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Kvarnström, Jonas
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    A Low-Level Active Vision Framework for Collaborative Unmanned Aircraft Systems2015Inngår i: COMPUTER VISION - ECCV 2014 WORKSHOPS, PT I / [ed] Lourdes Agapito, Michael M. Bronstein and Carsten Rother, Springer Publishing Company, 2015, Vol. 8925, s. 223-237Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Micro unmanned aerial vehicles are becoming increasingly interesting for aiding and collaborating with human agents in myriads of applications, but in particular they are useful for monitoring inaccessible or dangerous areas. In order to interact with and monitor humans, these systems need robust and real-time computer vision subsystems that allow to detect and follow persons.

    In this work, we propose a low-level active vision framework to accomplish these challenging tasks. Based on the LinkQuad platform, we present a system study that implements the detection and tracking of people under fully autonomous flight conditions, keeping the vehicle within a certain distance of a person. The framework integrates state-of-the-art methods from visual detection and tracking, Bayesian filtering, and AI-based control. The results from our experiments clearly suggest that the proposed framework performs real-time detection and tracking of persons in complex scenarios

  • 7.
    Doherty, Patrick
    et al.
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem.
    Kvarnström, Jonas
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Conte, Gianpaolo
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Berger, Cyrille
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Hinzmann, Timo
    Stastny, Thomas
    A Collaborative Framework for 3D Mapping using Unmanned Aerial Vehicles2016Inngår i: PRIMA 2016: Principles and Practice of Multi-Agent Systems / [ed] Baldoni, M., Chopra, A.K., Son, T.C., Hirayama, K., Torroni, P., Springer Publishing Company, 2016, s. 110-130Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper describes an overview of a generic framework for collaboration among humans and multiple heterogeneous robotic systems based on the use of a formal characterization of delegation as a speech act. The system used contains a complex set of integrated software modules that include delegation managers for each platform, a task specification language for characterizing distributed tasks, a task planner, a multi-agent scan trajectory generation and region partitioning module, and a system infrastructure used to distributively instantiate any number of robotic systems and user interfaces in a collaborative team. The application focusses on 3D reconstruction in alpine environments intended to be used by alpine rescue teams. Two complex UAV systems used in the experiments are described. A fully autonomous collaborative mission executed in the Italian Alps using the framework is also described.

  • 8.
    Doherty, Patrick
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Kvarnström, Jonas
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Conte, Gianpaolo
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    HDRC3 - A Distributed Hybrid Deliberative/Reactive Architecture for Unmanned Aircraft Systems2014Inngår i: Handbook of Unmanned Aerial Vehicles / [ed] Kimon P. Valavanis, George J. Vachtsevanos, Dordrecht: Springer Science+Business Media B.V., 2014, s. 849-952Kapittel i bok, del av antologi (Annet vitenskapelig)
    Abstract [en]

    This chapter presents a distributed architecture for unmanned aircraft systems that provides full integration of both low autonomy and high autonomy. The architecture has been instantiated and used in a rotorbased aerial vehicle, but is not limited to use in particular aircraft systems. Various generic functionalities essential to the integration of both low autonomy and high autonomy in a single system are isolated and described. The architecture has also been extended for use with multi-platform systems. The chapter covers the full spectrum of functionalities required for operation in missions requiring high autonomy.  A control kernel is presented with diverse flight modes integrated with a navigation subsystem. Specific interfaces and languages are introduced which provide seamless transition between deliberative and reactive capability and reactive and control capability. Hierarchical Concurrent State Machines are introduced as a real-time mechanism for specifying and executing low-level reactive control. Task Specification Trees are introduced as both a declarative and procedural mechanism for specification of high-level tasks. Task planners and motion planners are described which are tightly integrated into the architecture. Generic middleware capability for specifying data and knowledge flow within the architecture based on a stream abstraction is also described. The use of temporal logic is prevalent and is used both as a specification language and as an integral part of an execution monitoring mechanism. Emphasis is placed on the robust integration and interaction between these diverse functionalities using a principled architectural framework.  The architecture has been empirically tested in several complex missions, some of which are described in the chapter.

  • 9.
    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)
  • 10.
    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.

  • 11.
    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)
  • 12.
    Pandzic, Igor S.
    et al.
    Faculty of electrical engineering and computing, Zagreb University, Zagreb, Croatia.
    Ahlberg, Jörgen
    Visage Technologies AB, Linköping.
    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.
    Mosmondor, Miran
    Faculty of electrical engineering and computing, Zagreb University, Zagreb, Croatia.
    Faces Everywhere: Towards Ubiquitous Production and Delivery of Face Animation2003Inngår i: MUM 2003. Proceedings of the 2nd International Conference on Mobile and Ubiquitous Multimedia, 10–12 December, 2003, Norrköping, Sweden, Linköping: Linköping University Electronic Press, 2003, s. 49-56Konferansepaper (Fagfellevurdert)
    Abstract [en]

    While face animation is still considered one of the toughesttasks in computer animation, its potential application range israpidly moving from the classical field of film production intogames, communications, news delivery and commerce. Tosupport such novel applications, it is important to enableproduction and delivery of face animation on a wide range ofplatforms, from high-end animation systems to the web, gameconsoles and mobile phones. Our goal is to offer a frameworkof tools interconnected by standard formats and protocols andcapable of supporting any imaginable application involvingface animation with the desired level of animation quality,automatic production wherever it is possible, and delivery ona wide range of platforms. While this is clearly an ongoingtask, we present the current state of development along withseveral case studies showing that a wide range of applicationsis already enabled.

  • 13.
    Rudol, Piotr
    et al.
    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.
    Conte, Gianpaolo
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Tekniska högskolan.
    Micro unmanned aerial vehicle visual servoing for cooperative indoor exploration2008Inngår i: Proceedings of the IEEE Aerospace Conference, IEEE conference proceedings , 2008Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Recent advances in the field of micro unmanned aerial vehicles (MAVs) make flying robots of small dimensions suitable platforms for performing advanced indoor missions. In order to achieve autonomous indoor flight a pose estimation technique is necessary. This paper presents a complete system which incorporates a vision-based pose estimation method to allow a MAV to navigate in indoor environments in cooperation with a ground robot. The pose estimation technique uses a lightweight light emitting diode (LED) cube structure as a pattern attached to a MAV. The pattern is observed by a ground robot's camera which provides the flying robot with the estimate of its pose. The system is not confined to a single location and allows for cooperative exploration of unknown environments. It is suitable for performing missions of a search and rescue nature where a MAV extends the range of sensors of the ground robot. The performance of the pose estimation technique and the complete system is presented and experimental flights of a vertical take-off and landing (VTOL) MAV are described.

  • 14.
    Rudol, Piotr
    et al.
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Tekniska högskolan.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Tekniska högskolan.
    Vision-based Pose Estimation for Autonomous Indoor Navigation of Micro-scale Unmanned Aircraft Systems2010Inngår i: Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA), IEEE conference proceedings , 2010, s. 1913-1920Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We present a navigation system for autonomous indoor flight of micro-scale Unmanned Aircraft Systems (UAS) which is based on a method for accurate monocular vision pose estimation. The method makes use of low cost artificial landmarks placed in the environment and allows for fully autonomous flight with all computation done on-board a UAS on COTS hardware. We provide a detailed description of all system components along with an accuracy evaluation and a time profiling result for the pose estimation method. Additionally, we show how the system is integrated with an existing micro-scale UAS and provide results of experimental autonomous flight tests. To our knowledge, this system is one of the first to allow for complete closed-loop control and goal-driven navigation of a micro-scale UAS in an indoor setting without requiring connection to any external entities.

  • 15.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, UASTECH – Teknologier för autonoma obemannade flygande farkoster. Linköpings universitet, Tekniska högskolan.
    Selected Aspects of Navigation and Path Planning in Unmanned Aircraft Systems2011Licentiatavhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    Unmanned aircraft systems (UASs) are an important future technology with early generations already being used in many areas of application encompassing both military and civilian domains. This thesis proposes a number of integration techniques for combining control-based navigation with more abstract path planning functionality for UASs. These techniques are empirically tested and validated using an RMAX helicopter platform used in the UASTechLab at Linköping University. Although the thesis focuses on helicopter platforms, the techniques are generic in nature and can be used in other robotic systems.

    At the control level a navigation task is executed by a set of control modes. A framework based on the abstraction of hierarchical concurrent state machines for the design and development of hybrid control systems is presented. The framework is used to specify  reactive behaviors and for sequentialisation of control modes. Selected examples of control systems deployed on UASs are presented. Collision-free paths executed at the control level are generated by path planning algorithms.We propose a path replanning framework extending the existing path planners to allow dynamic repair of flight paths when new obstacles or no-fly zones obstructing the current flight path are detected. Additionally, a novel approach to selecting the best path repair strategy based on machine learning technique is presented. A prerequisite for a safe navigation in a real-world environment is an accurate geometrical model. As a step towards building accurate 3D models onboard UASs initial work on the integration of a laser range finder with a helicopter platform is also presented.

    Combination of the techniques presented provides another step towards building comprehensive and robust navigation systems for future UASs.

  • 16.
    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.

  • 17.
    Wzorek, Mariusz
    et al.
    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.
    A framework for reconfigurable path planning for autonomous unmanned aerial vehicles.2007Manuskript (preprint) (Annet (populærvitenskap, debatt, mm))
  • 18.
    Wzorek, Mariusz
    et al.
    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.
    Preliminary report: Reconfigurable path planning for an autonomous unmanned aerial vehicle2005Inngår i: Proceedings of the 24th Annual Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG), 2005Konferansepaper (Fagfellevurdert)
  • 19.
    Wzorek, Mariusz
    et al.
    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.
    Reconfigurable Path Planning for an Autonomous Unmanned Aerial Vehicle2006Inngår i: Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling (ICAPS) / [ed] Derek Long, Stephen F. Smith, Daniel Borrajo, Lee McCluskey, AAAI Press, 2006, s. 438-441Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, we present a motion planning framework for a fully deployed autonomous unmanned aerial vehicle which integrates two sample-based motion planning techniques, Probabilistic Roadmaps and Rapidly Exploring Random Trees. Additionally, we incorporate dynamic reconfigurability into the framework by integrating the motion planners with the control kernel of the UAV in a novel manner with little modification to the original algorithms. The framework has been verified through simulation and in actual flight. Empirical results show that these techniques used with such a framework offer a surprisingly efficient method for dynamically reconfiguring a motion plan based on unforeseen contingencies which may arise during the execution of a plan. The framework is generic and can be used for additional platforms.

  • 20.
    Wzorek, Mariusz
    et al.
    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.
    Reconfigurable Path Planning for an Autonomous Unmanned Aerial Vehicle2006Inngår i: ICHIT 2006 - International Conference on Hybrid Information Technology,2006, 2006Konferansepaper (Fagfellevurdert)
  • 21.
    Wzorek, Mariusz
    et al.
    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.
    Reconfigurable path planning for an autonomous unmanned aerial vehicle2005Inngår i: National Swedish Workshop on Autonomous Systems, SWAR 05,2005, 2005Konferansepaper (Fagfellevurdert)
  • 22.
    Wzorek, Mariusz
    et al.
    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.
    The WITAS UAV Ground System Interface Demonstration with a Focus on Motion and Task Planning2006Inngår i: Software Demonstrations at the International Conference on Automated Planning Scheduling (ICAPS-SD), 2006, s. 36-37Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    The Autonomous UAV Technologies Laboratory at Linköping University, Sweden, has been developing fully autonomous rotor-based UAV systems in the mini- and micro-UAV class. Our current system design is the result of an evolutionary process based on many years of developing, testing and maintaining sophisticated UAV systems. In particular, we have used the Yamaha RMAX helicopter platform(Fig. 1) and developed a number of micro air vehicles from scratch.

  • 23.
    Wzorek, Mariusz
    et al.
    Linköpings universitet, Institutionen för datavetenskap, UASTECH – Teknologier för autonoma obemannade flygande farkoster. Linköpings universitet, Tekniska högskolan.
    Kvarnström, Jonas
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Institutionen för datavetenskap, UASTECH – Teknologier för autonoma obemannade flygande farkoster. Linköpings universitet, Tekniska högskolan.
    Choosing Path Replanning Strategies for Unmanned Aircraft Systems2010Inngår i: Proceedings of the Twentieth International Conference on Automated Planning and Scheduling (ICAPS) / [ed] Ronen Brafman, Héctor Geffner, Jörg Hoffmann, Henry Kautz, Toronto, Canada: AAAI Press , 2010, s. 193-200Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Unmanned aircraft systems use a variety of techniques to plan collision-free flight paths given a map of obstacles and no- fly zones. However, maps are not perfect and obstacles may change over time or be detected during flight, which may in- validate paths that the aircraft is already following. Thus, dynamic in-flight replanning is required.Numerous strategies can be used for replanning, where the time requirements and the plan quality associated with each strategy depend on the environment around the original flight path. In this paper, we investigate the use of machine learn- ing techniques, in particular support vector machines, to choose the best possible replanning strategy depending on the amount of time available. The system has been implemented, integrated and tested in hardware-in-the-loop simulation with a Yamaha RMAX helicopter platform.

  • 24.
    Wzorek, Mariusz
    et al.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning.
    Landén, David
    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.
    GSM Technology as a Communication Media for an Autonomous Unmanned Aerial Vehicle2006Inngår i: Proceedings of the 21st Bristol International UAV Systems Conference (UAVS), Bristol: University of Bristol, Department of Aerospace engineering , 2006Konferansepaper (Fagfellevurdert)
1 - 24 of 24
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