Veröffentlichungen

@inproceedings{Sichelschmidt2010,

title = {Pedestrian crossing detecting as a part of an urban pedestrian safety system},

author = {Sebastian Sichelschmidt and Anselm Haselhoff and Anton Kummert and Martin Roehder and Björn Elias and Karsten Berns},

year  = {2010},

date = {2010-01-01},

booktitle = {2010 IEEE Intelligent Vehicles Symposium},

pages = {840--844},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Pirkkalainen2010a,

title = {Internationalization processes for open educational resources},

author = {Henri Pirkkalainen and Stefan Thalmann and Jan Martin Pawlowski and Markus Bick and Philipp Holtkamp and Kyung-Hun Ha},

year  = {2010},

date = {2010-01-01},

booktitle = {Workshop on Competencies for the Globalization of Information Systems in Knowledge-Intensive Settings, ICSOB},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Pulkkinen2010,

title = {Software and Standards in an Emerging Domain},

author = {Mirja Pulkkinen and Denis Kozlov and Jan Martin Pawlowski},

year  = {2010},

date = {2010-01-01},

booktitle = {International Conference of Software Business},

pages = {217--222},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Eimler2010b,

title = {Following the white rabbit--a robot rabbit as vocabulary trainer for beginners of English},

author = {Sabrina C. Eimler and Astrid Marieke von der Pütten and Ulrich Schächtle and Lucas Carstens and Nicole Krämer},

year  = {2010},

date = {2010-01-01},

urldate = {2010-01-01},

booktitle = {Symposium of the Austrian HCI and Usability Engineering Group},

pages = {322--339},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Luyten2010,

title = {Engineering patterns for multi-touch interfaces},

author = {Kris Luyten and Davy Vanacken and Malte Hanno Weiß and Jan Oliver Borchers and Shahram Izadi and Daniel Wigdor},

year  = {2010},

date = {2010-01-01},

booktitle = {Proceedings of the 2nd ACM SIGCHI symposium on Engineering interactive computing systems},

pages = {365--366},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Zibner2010,

title = {Scenes and tracking with dynamic neural fields: How to update a robotic scene representation},

author = {S K U Zibner and Christian Faubel and Ioannis Iossifidis and G Schöner and J P Spencer},

doi = {10.1109/DEVLRN.2010.5578837},

isbn = {9781424469024},

year  = {2010},

date = {2010-01-01},

urldate = {2010-01-01},

booktitle = {2010 IEEE 9th International Conference on Development and Learning, ICDL-2010 - Conference Program},

abstract = {We present an architecture based on the Dynamic Field Theory for the problem of scene representation. At the core of this architecture are three-dimensional neural fields linking feature to spatial information. These three-dimensional fields are coupled to lower-dimensional fields that provide both a close link to the sensory surface and a close link to motor behavior. We highlight the updating mechanism of this architecture, both when a single object is selected and followed by the robot's head in smooth pursuit and in multi-item tracking when several items move simultaneously. textcopyright 2010 IEEE.},

keywords = {Autonomous robotics, dynamic field theory (DFT), Dynamical systems, embodied cognition, neural processing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Zibner2010b,

title = {Scene representation for anthropomorphic robots: A dynamic neural field approach},

author = {S K U Zibner and Christian Faubel and Ioannis Iossifidis and G Schöner},

isbn = {9781617387197},

year  = {2010},

date = {2010-01-01},

urldate = {2010-01-01},

booktitle = {Joint 41st International Symposium on Robotics and 6th German Conference on Robotics 2010, ISR/ROBOTIK 2010},

volume = {2},

abstract = {For autonomous robotic systems, the ability to represent a scene, to memorize and track objects and their associated features is a prerequisite for reasonable interactive behavior. In this paper, we present a biologically inspired architecture for scene representation that is based on Dynamic Field Theory. At the core of the architecture we make use of three-dimensional Dynamic Neural Fields for representing space-feature associations. These associations are built up autonomously in a sequential way and they are maintained and continuously updated. We demonstrate these capabilities in two experiments on an anthropomorphic robotic platform. In the first experiment we show the sequential scanning of a scene. The second experiment demonstrates the maintenance of associations for objects, which get out of view, and the correct update of the scene representation, if such objects are removed.},

keywords = {Autonomous robotics, dynamic field theory (DFT), Dynamical systems, embodied cognition, neural processing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Reimannd,

title = {End-effector obstacle avoidance using multiple dynamic variables},

author = {Hendrik Reimann and Ioannis Iossifidis and Gregor Schöner},

year  = {2010},

date = {2010-01-01},

booktitle = {ISR / ROBOTIK 2010},

address = {Munich, Germany},

abstract = {The avoidance of obstacles is a crucial part of the generation of behavior for autonomos robotic agents. A standard method to produce trajectories to a given target that avoids a number of possibly mobile obstacles is the potential field approach introduced by Khatib, where an artificial potential field is constructed around target and obstacles, with the target acting as a global minimum and the obstacles as local maxima, the gradient of which is used to determine the (artificial) force acting on the robot at any moment. While the potential field approach has been used extensively for vehicle motion in a plane, applications for robotic manipulators suffer from a high level of complexity due to the formulation of constraints as forces necessitating the inclusion of dynamic properties of the manipulator into the system. We pursue a different solution to the problem of manipulator obstacle avoidance based on the dynamic approach to robotics, which states that all behavioral constraints for the generation of movement should be formulated as attractors or repellors of a dynamical systems. The problem of behavior design is thus separated from the control problem of how to realize the designed behavior, bringing the advantage of simplicity in the formulation of the former.},

keywords = {arm movement model, Autonomous robotics, behavior generation, Dynamical systems, movement model, obstacle avoidance},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Grimm2010b,

title = {Behavioral Organization for Mobile Robotic Systems: An Attractor Dynamics Approach},

author = {Matthias Grimm and Ioannis Iossifidis},

year  = {2010},

date = {2010-01-01},

booktitle = {ISR / ROBOTIK 2010},

address = {Munich, Germany},

abstract = {Autonomous systems generate different behaviors based on the perceived environmental situation. The organization of a set of behaviors plays an important role in the field of autonomous robotics. The organization architecture must be flexible, so that behavioral changes are possible if the sensory information changes. Furthermore, behavioral organization must be stable, so that small changes in sensory information do not lead to oscillations. To achieve this, all behaviors, but also the underlying organization architecture, are based on continuous dynamical systems. They are characterized by a set of dynamical variables, also referred to as state variables. These variables represent the activation or deactivation of a particular behavior. Elementary behaviors are dependent on the sensor input in a way, that changes of the sensorial information lead to qualitatively different behaviors. The so-called sensor context denotes whether a behavior is applicable in the current sensor situation or not. However, for complex systems consisting of many elementary behaviors, it is necessary to take logical conditions into account to generate a sequence of behaviors. Furthermore, some elementary behaviors can or even must run in parallel, while others exclude each other. This internal information requires knowledge about the logical interaction of the behaviors and is stored within binary matrices. This makes the overall organization structure very flexible and easy to extend. We present the architecture using the example of approaching and passing a door. The robot has to navigate from one room to another while simultaneously avoiding obstacles in its pathway.},

keywords = {Autonomous robotics, behavior generation, Dynamical systems, movement model, movile robot},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Luoma2010,

title = {Creating Individual Journal Rankings Based on a Community Approach},

author = {Eetu Luoma and Jan Martin Pawlowski and Riikka Ahlgren},

year  = {2010},

date = {2010-01-01},

booktitle = {2010 43rd Hawaii International Conference on System Sciences},

pages = {1--10},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Sandamirskayasubmitted,

title = {Natural human-robot interaction through spatial language: a dynamic neural fields approach},

author = {Yulia Sandamirskaya and John Lipinski and Ioannis Iossifidis and G Schöner},

url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5598671},

issn = {1944-9445},

year  = {2010},

date = {2010-01-01},

booktitle = {Proc. 19th IEEE International Workshop on Robot and Human Interactive Communication (ROMAN 2010)},

pages = {600--607},

publisher = {IEEE},

keywords = {arm movement model, Autonomous robotics, behavior generation, Dynamical systems, man machine interaction, movement model, speech recognition},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Zibner2010ab,

title = {Scene Representation for Anthropomorphic Robots: A Dynamic Neural Field Approach},

author = {Stephan S K U Zibner and Christian Faubel and Ioannis Iossifidis and Gregor Schöner},

url = {http://www.vde-verlag.de/proceedings-en/453273138.html},

year  = {2010},

date = {2010-01-01},

booktitle = {ISR / ROBOTIK 2010},

number = {Isr},

publisher = {VDE VERLAG GmbH},

address = {Munich, Germany},

abstract = {An internal representation of a scene is essential to generate actions on scene objects. A stabilized storage of object location and features offers the flexibility to process queries phrased in human-based terms relating to objects, which may not be in the current camera view. Scene representation is therefore an internal representation of the surrounding world that is stabilized against head and body movement. It contains associated information about location and features of objects. Because objects and bodies move, scene representation is not a one-time process, but a constantly scene- adapting mechanism of scanning for, storing, updating, and deleting information. 

 

 Our novel architecture incorporates the generation of autonomous scanning sequences on real-time camera images. The head can then be oriented towards a selected object and the color feature can be extracted. Object location and feature information are associatively stored in a three-dimensional Dynamic Neural Field. Changes in the scene, even for multiple objects, can be tracked simultaneously. The stored information is used to generate behavior for cued recall. Cues can be table regions, features, or object labels. The robot demonstrates a successful recall by centering its gaze on the stated object.},

keywords = {Autonomous robotics, dynamic neural field, Dynamical systems, man machine interaction, scene representation, speech recognition},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Noth2010,

title = {Using ego motion feedback to improve the immersion in virtual reality environments},

author = {Sebastian Noth and Eva Schrowangen and Ioannis Iossifidis},

year  = {2010},

date = {2010-01-01},

booktitle = {ISR / ROBOTIK 2010},

address = {Munich, Germany},

abstract = {To study driver behavior we set up a lab with fixed base driving simulators. In order to compensate for the lack of physical feedback in this scenario, we aimed for another means of increasing the realism of our system. In the following, we propose an efficient method of head tracking and its integration in our driving simulation. Furthermore, we illuminate why this is a promising boost of the subjects immersion in the virtual world. Our idea for increasing the feeling of immersion is to give the subject feedback on head movements relative to the screen. A real driver sometimes moves his head in order to see something better or to look behind an occluding object. In addition to these intentional movements, a study conducted by Zirkovitz and Harris has revealed that drivers involuntarily tilt their heads when they go around corners in order to maximize the use of visual information available in the scene. Our system reflects the visual changes of any head movement and hence gives feedback on both involuntary and intentional motion. If, for example, subjects move to the left, they will see more from the right-hand side of the scene. If, on the other hand, they move upwards, a larger fraction of the engine hood will be visible. The same holds for the rear view mirror.},

keywords = {{Autonomous Robotics, head tracking, Simulation, virtual reality}},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Zibner2010c,

title = {Scenes and Tracking with Dynamic Neural Fields: How to Update a Robotic Scene Representation},

author = {Stephan K U Zibner and Christian Faubel and John P Spencer and Ioannis Iossifidis and Gregor Schöner},

year  = {2010},

date = {2010-01-01},

booktitle = {Proc. Int. Conf. on Development and Learning (ICDL10)},

keywords = {Autonomous robotics, dynamic neural field, Dynamical systems, man machine interaction, scene representation, speech recognition},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Zibnersubmittedb,

title = {Scene Representation with Dynamic Neural Fields: An Example of Complex Cognitive Architectures Based on Dynamic Neural Field Theory},

author = {Stephan K U Zibner and Christian Faubel and Ioannis Iossifidis and Gregor Schöner},

year  = {2010},

date = {2010-01-01},

booktitle = {Proc. Int. Conf. on Development and Learning (ICDL10)},

keywords = {Autonomous robotics, dynamic neural field, Dynamical systems, man machine interaction, scene representation, speech recognition},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Zibneri,

title = {Scene and Tracking with Dynamic Neural Field Approach},

author = {Stephan Zibner and Christian Faubel and Ioannis Iossifidis and Gregor Schöner and John P Spencer},

year  = {2010},

date = {2010-01-01},

booktitle = {ISR / ROBOTIK 2010},

address = {Munich, Germany},

abstract = {An internal representation of a scene is essential to generate actions on scene objects. A stabilized storage of object location and features offers the flexibility to process queries phrased in human-based terms relating to objects, which may not be in the current camera view. Scene representation is therefore an internal representation of the surrounding world that is stabilized against head and body movement. It contains associated information about location and features of objects. Because objects and bodies move, scene representation is not a one-time process, but a constantly scene- adapting mechanism of scanning for, storing, updating, and deleting information. 

 

 Our novel architecture incorporates the generation of autonomous scanning sequences on real-time camera images. The head can then be oriented towards a selected object and the color feature can be extracted. Object location and feature information are associatively stored in a three-dimensional Dynamic Neural Field. Changes in the scene, even for multiple objects, can be tracked simultaneously. The stored information is used to generate behavior for cued recall. Cues can be table regions, features, or object labels. The robot demonstrates a successful recall by centering its gaze on the stated object.},

keywords = {Autonomous robotics, dynamic neural field, Dynamical systems, man machine interaction, scene representation, speech recognition},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Gedikli2010,

title = {Neighborhood-restricted mining and weighted application of association rules for recommenders},

author = {Fatih Gedikli and Dietmar Jannach},

year  = {2010},

date = {2010-01-01},

booktitle = {International Conference on Web Information Systems Engineering},

pages = {157--165},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Gedikli2010a,

title = {Rating items by rating tags},

author = {Fatih Gedikli and Dietmar Jannach},

year  = {2010},

date = {2010-01-01},

booktitle = {Proceedings of the 2010 Workshop on Recommender Systems and the Social Web at ACM RecSys},

pages = {25--32},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Gedikli2010b,

title = {Recommending based on rating frequencies: Accurate enough?},

author = {Fatih Gedikli and Dietmar Jannach},

year  = {2010},

date = {2010-01-01},

booktitle = {Proceedings of the 8th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems at UMAP'10 (ITWP'10)},

pages = {65--70},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Stricker2010,

title = {Realtime user attention and emotion estimation on a mobile robot},

author = {Ronny Stricker and Sebastian Hommel and Christian Martin and Horst-Michael Gross},

year  = {2010},

date = {2010-01-01},

booktitle = {Proceedings of 55th Ilmenau International Scientific Colloquium},

pages = {13--17},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Haselhoff2010,

title = {On visual crosswalk detection for driver assistance systems},

author = {Anselm Haselhoff and Anton Kummert},

year  = {2010},

date = {2010-01-01},

booktitle = {2010 IEEE Intelligent Vehicles Symposium},

pages = {883--888},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Weiss2010,

title = {BendDesk: dragging across the curve},

author = {Malte Hanno Weiß and Simon Voelker and Christine Sutter and Jan Oliver Borchers},

year  = {2010},

date = {2010-01-01},

booktitle = {ACM International Conference on Interactive Tabletops and Surfaces},

pages = {1--10},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Weiss2010a,

title = {Madgets: actuating widgets on interactive tabletops},

author = {Malte Hanno Weiß and Florian Schwarz and Simon Jakubowski and Jan Oliver Borchers},

year  = {2010},

date = {2010-01-01},

booktitle = {Proceedings of the 23nd annual ACM symposium on User interface software and technology},

pages = {293--302},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Tuma2009b,

title = {Temporal stabilization of discrete movement in variable environments: An attractor dynamics approach},

author = {M Tuma and Ioannis Iossifidis and G Schöner},

url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5152562},

doi = {10.1109/ROBOT.2009.5152562},

isbn = {978-1-4244-2788-8},

year  = {2009},

date = {2009-05-01},

urldate = {2009-05-01},

booktitle = {2009 IEEE International Conference on Robotics and Automation},

pages = {863--868},

publisher = {IEEE},

abstract = {The ability to generate discrete movement with distinct and stable time courses is important for interaction scenarios both between different robots and with human partners, for catching and interception tasks, and for timed action sequences. In dynamic environments, where trajectories are evolving online, this is not a trivial task. The dynamical systems approach to robotics provides a framework for robust incorporation of fluctuating sensor information, but control of movement time is usually restricted to rhythmic motion and realized through stable limit cycles. The present work uses a Hopf oscillator to produce discrete motion and formulates an online adaptation rule to stabilize total movement time against a wide range of disturbances. This is integrated into a dynamical systems framework for the sequencing of movement phases and for directional navigation, using 2D-planar motion as an example. The approach is demonstrated on a Khepera mobile unit in order to show its reliability even when depending on low-level sensor information.},

keywords = {attractor dynamics approach, Autonomous robotics, Dynamical systems, hopf oscillator},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Tuma2009,

title = {Temporal Stabilization of Discrete Movement in Variable Environments: An Attractor Dynamics Approach},

author = {Matthias Tuma and Ioannis Iossifidis and Gregor Schöner},

year  = {2009},

date = {2009-01-01},

booktitle = {Proc. IEEE International Conference on Robotics and Automation ICRA '09},

pages = {863--868},

address = {Kobe, Japan},

abstract = {The ability to generate discrete movement with distinct and stable time courses 

 

 is important for interaction scenarios both between different robots and with human partners, 

 

 for catching and interception tasks, and for timed action sequences. 

 

 In dynamic environments, where trajectories are evolving on-line, this is not a trivial task. 

 

 The dynamical systems approach to robotics provides a framework for robust 

 

 incorporation of fluctuating sensor information, but control of movement time is usually 

 

 restricted to rhythmic motion and realized through stable limit cycles. The present work 

 

 uses a Hopf oscillator to produce discrete motion and formulates an on-line adaptation rule 

 

 to stabilize total movement time against a wide range of disturbances. This is integrated into 

 

 a dynamical systems framework for the sequencing of movement phases and for directional navigation, using 2D-planar motion 

 

 as an example. The approach is demonstrated on a Khepera mobile unit in order to show its 

 

 reliability even when depending on low-level sensor information.},

keywords = {attractor dynamics approach, Autonomous robotics, Dynamical systems, hopf oscillator},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Iossifidis2009,

title = {Reaching while avoiding obstacles: a neuronally inspired attractor dynamics approach},

author = {Ioannis Iossifidis and Gregor Schöner},

doi = {10.3389/conf.neuro.10.2009.14.007},

year  = {2009},

date = {2009-01-01},

booktitle = {Bernstein Conference on Computational Neuroscience (BCCN 2009)},

keywords = {anthropomorphic arm, central nervous system, collision avoidance, Dynamical systems, manipulator dynamics, obstacle avoidance, redundant manipulators, redundant robot arm},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Dogan2008b,

title = {Towards a Driver Model: Preliminary Study of Lane Change Behavior},

author = {Ueruen Dogan and Hannes Edelbrunner and Ioannis Iossifidis},

url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4732700},

doi = {10.1109/ITSC.2008.4732700},

isbn = {978-1-4244-2111-4},

year  = {2008},

date = {2008-10-01},

booktitle = {2008 11th International IEEE Conference on Intelligent Transportation Systems},

pages = {931--937},

publisher = {IEEE},

abstract = {The presented work formulates an framework in which early prediction of drivers lane change behavior is realized. We aim to build a representation of drivers lane change behavior in order to recognize and to predict driver's intentions as a first step towards a realistic driver model. In the test bed of the Institute of Neuroinformatik, based on the traffic simulator NISYS TRS 1, 10 individuals have driven in the experiments and they performed more then 150 lane change maneuvers. Lane-offset, distance to the front car and time to contact, were recorded. The acquired data was used to train - in parallel- a recurrent neural network, a feed forward neural network and a set of support vector machines. In the followed test drives the system was able of performing a lane change prediction time of 1.5 sec beforehand. The proposed approach describes a framework for lane-change detection and prediction, which will serve as a prerequisite for a successful driver model.},

keywords = {driver information systems, driver model, drivers lane change behavior prediction, feed forward neural network, feedforward neural nets, lane change maneuvers, Machine Learning, recurrent neural nets, recurrent neural network, support vector machines, traffic simulator},

pubstate = {published},

tppubtype = {inproceedings}

}