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Maurer Michael Saffari Amir Schulter Samuel Seichter Hartmut Zeisl Bernhard Lex Alexander Arth Clemens Barakonyi István Bauer Joachim Beichel Reinhard Bischof Horst Bornik Alexander Reitinger Bernhard Bauer Christian Gruber Lukas Kainz Bernhard Pirchheim Christian Wagner Daniel Kalkofen Denis Donoser Michael Elbischger Pierre Ferstl David Fraundorfer Friedrich Reitmayr Gerhard Godec Martin Graber Gottfried Grabner Markus Grubert Jens Hartl Andreas Hauswiesner Stefan Riemenschneider Hayko Grabner Helmut Hirzer Martin Hofer Manuel Hoppe Christof Irschara Arnold Newman Joseph Junghanns Sebastian Khan Inayatullah Kalkusch Michael Karner Konrad Khlebnikov Rostislav Klaus Andreas Klopschitz Manfred Kluckner Stefan Köstinger Martin Kontschieder Peter Pirker Katrin Kruijff Ernst Langlotz Tobias Langs Georg Leberl Franz Lee Felix Leistner Christian Leitner Raimund Lenz Martin Mauthner Thomas Meixner Philipp Mendez Erick Grabner Michael Heber Markus Mühl Judith Mulloni Alessandro Ober Sandra Pacher Georg Partl Christian Pflugfelder Roman Pinz Axel Roth Peter M. Pock Thomas Puff Werner Pan Qi Ram Surinder Grasset Raphael Recky Michal Regenbrecht Holger Reinbacher Christian Rüther Matthias Rumpler Markus Santner Jakob Sareika Markus Schall Gerhard Schmalstieg Dieter Schulz Hans-Jörg Sormann Mario Steinberger Markus Sternig Sabine Storer Markus Straka Matthias Streit Marc Tatzgern Markus Nguyen Thanh Nguyen Thuy Trobin Werner Unger Markus Uray Martina Urschler Martin Veas Eduardo Waldner Manuela Wendel Andreas Werlberger Manuel Winter Martin Wohlhart Paul Zach Christopher Zebedin Lukas Zollmann Stefanie
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  Title     Abstract     Start     End  
CONSTRUCT: Construction Site Monitoring and Change Detection using UAVs
(details)

The goal of the project is to develop methods for modeling and surveying large construction sites. The project will make use of unmanned aerial vehicles and existing stationary or pan-tilt zoom cameras at the construction site. The goal is to provide accurate 3D models on a regular basis of the whole site. This will generate a 4D data set (3D+time). This data can then be used for documentation, visualization (we will use a mobile augmented reality system to overlay e.g. the plan or a model of the building) as well as measurement (e.g., how much material has been transported). From a scientific point of view we will have to solve following tasks:

  • Dense 3D reconstruction from highly overlapping data, we will use variational methods implemented on the GPU.
  • Accurate registration of subsequent models over time. Since the 3D reconstruction is changing (per definition) the method needs to handle this. This is an instance of the highly relevant 3D model updating problem.
  • Integration of multiple camera sources. Using the 3D model and additional cameras poses the problem of localization of the additional cameras with respect to the 3D model which is again an instance the registration problem.
  • Development of a handheld AR platform for visualization. In order to use AR technology the pose of the platform with respect to the model and the reconstruction needs to be determined.
2011 2014
PEGASUS: Autonomous Inspection of Overhead Power Lines using an Unmanned Aerial Vehicle
(details)

The aim of the PEGASUS project is to develop a mobile vision system for overhead power line inspection to be mounted on an unmanned aerial vehicle (UAV). The long term goal is to develop a fully autonomous aerial vehicle which is able to perform power line inspection in an automated manner. This goal requires innovative solutions to a number of problems such as visual navigation, visual tracking and obstacle detection, model-based inspection under harsh conditions etc. In addition, due to the use of a small scale UAV (e.g. a quad-rotor helicopter) we have restricted computational resources for algorithms that need to be executed on the UAV (especially for navigation and tracking). Within PEGASUS we want to make significant progress towards this long term goal. In particular, PEGASUS will provide a set of tools for the inspector. The project is organized in four phases: First, an inspection system for a single power tower is developed. Used in ground-based inspection, the UAV provides close-up views of all points of interest from an optimal viewpoint. Second, we want to implement an automatic visual inspection system which highlights possible faulty components. In a third step, the system is extended towards multiple towers (still in the sight of the operator). Finally, the system will be used as a handheld system in manned helicopters by power line inspectors, where it should dramatically reduce the time needed for inspection. From a research perspective we will develop novel solutions for model-based recognition and pose estimation, visual navigation including obstacle avoidance and automated model-based visual inspection. All of these problems are extremely challenging because of the uncontrolled conditions (illumination etc.) and the real-time requirements. If successful, the methods developed in PEGASUS will be usable beyond the task of power line inspection.

2010 2013
Vision Based Kinematic Calibration and Error Compensation of Articulated Robot Arms
(details)

Development of a vision system for accurate calibration of the kinematic chain of an articulated robot arm.

The absolute positioning error of articulated robot arms is typically by an order of ten higher than their repeatability error. Inaccurate blueprint kinematic models typically account for 90% of this discrepancy. In this work a calibration procedure is developed which calibrates the kinematic model of a robot arm using fixed stereo rig and a calibration target mounted on the robot hand. In a single calibration framework the following parameters are automatically determined:

  • DH-parameters of the robot arm
  • Relative pose of calibration target and tooltip
  • Relative pose of stereo rig and robot coordinate frame
  • Interior camera parameters
  • Lens distortion parameters of both cameras
  • Relative pose of the stereo cameras
  • Inaccuracies/deformation of the calibration target

The procedure is fully automatic and does not require expensive, precalibrated equipment.

2005 2006
Robotics and Computer Vision Laboratory
(details)

The Robot Vision Laboratory was established in 2004 to provide a common platform for experiments, demos and prototyping in the field of computer vision. Among other things, the lab inventory contains a 6DOF articulated robot arm, a PeopleBot mobile robot platform, several imaging and illumination devices.

2004 2010
CONEX
(details)

Robust and Adaptive Approaches to Scene and Object Recognition: The goal of this joint project is to investigate new robust and adaptive approaches in the area of object and scene recognition. Object and scene recognition is a necessary requirement for developing truly cognitive systems as well as for the development of advanced and novel multimodal interfaces leading to ambient intelligence. Having a robust object and scene recognition system the following applications will greatly benefit: novel user interfaces which understand human activities, intelligent surveillance, indexing multi-media databases and content analysis of images, autonomous mobile systems and robotics, industrial inspection and robotics, etc. The goal is to develop computer vision based systems that can recognize objects, and in the context of environment perform localization and navigation. The major challenge is to develop systems and methods that can work under realistic unconstrained conditions (i.e., outside the lab). The three partners proposing this project (Center for Machine Perception, Czech Technical University Prague, CMP, Computer Vision Lab, Faculty of Computer and Information Science, University of Ljubljana, CVL, and Institute for Computer Graphics and Vision, Graz University of Technology ICG) have considerable expertise in this area and developed complementary methods and techniques. The goal of the project is to join the efforts and combine the expertise. In particular, we do the following activities:

  • Organization of joint workshops and colloquia
  • Exchange of PhD. students
  • Joint research/joint papers
2003 2005
Visual Pose Determination by a Robot in six degrees of freedom
(details)

We propose to develop a robotic system for the exact pose estimation of rigid objects in six degrees of freedom (DoF). Our approach is based on the following scenario: Given be a set of unordered objects in arbitrary position which come from a small variety (<10) of different types as may happen on a conveyor belt during an assembly process. We assume the objects to be mostly un-occluded and their CAD-model given. Our goal is to pick with a robot a specific object in such a way that it has a defined position. The robot is equipped with multiple black and white cameras (e.g., 2-3). In order to achieve maximum generality we do not intend to use range information nor calculate a 3D-representation from stereo images. This task requires a solution for the following sub-problems: Recognition and initial pose estimation, which will be approached using robust appearance-based recognition methods; Pose refinement will be handled by model-based methods; Movement planning to enhance the accuracy of the pose estimation.

Partnerlist:

M&R Holding GmbH

2001 2002
Mobile Robotics
(details)

Research topics on mobile robotics:

-Visual localisation and map building

-Usage of local visual landmarks

-Localisation using omnidirectional camera

2001 2005

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