Publications

Conferences

C1

Lea Steffen, Tobias Weyer, Stefan Ulbrich, Arne Roennau, and Rüdiger Dillmann. Reactive Neural Path Planning with Dynamic Obstacle Avoidance in a Condensed Configuration Space. In Int. Conf. Intelligent Robots and Systems (IROS). 2022.

C2

Lea Steffen, Tobias Weyer, Katharina Glueck, Stefan Ulbrich, Arne Roennau, and Rüdiger Dillmann. Comparing SONN Types for Efficient Robot Motion Planning in the Configuration Space. In Int. Conf. Intelligent Autonomous Systems (IAS). 2022.

C3

Lea Steffen, Katharina Glueck, Tobias Weyer, Stefan Ulbrich, Arne Roennau, and Rüdiger Dillmann. A Comparison of Self-Organizing Neural Networks to Reduce the High Dimensionality of the Configuration Space of Robots. In Intl. Conf. Advanced Robotics. 2021.

C4

Lea Steffen, Katharina Glück, S. Ulbrich, A. Rönnau, and R. Dillmann. Reducing the Dimension of the Configuration Space with Self Organizing Neural Networks. In IEEE Intl. Conf. Advanced Robotics and Mechatronics (ICARM). 2021.

C5

Lea Steffen, Rafael Kübler da Silva, Stefan Ulbrich, Vasquez Tieck J. C., Arne Rönnau, and Rüdiger Dillmann. Networks of Place Cells for Representing 3D Environments and Path Planning. In IEEE Intl. Conf Biomedical Robotics and Biomechatronics (BioRob), 1158–1165. 2020.

C6

Lea Steffen, Artur Liebert, Stefan Ulbrich, Arne Rönnau, and Rüdiger Dillmann. Adaptive, Neural Robot Control—Path Planning on 3D Spiking Neural Networks. In 29th Intl. Conf. Artificial Neural Networks (ICANN). 2020.

C7

Lea Steffen, Stefan Ulbrich, A. Rönnau, and Rüdiger Dillmann. Multi-view 3d reconstruction with self-organizing maps. In Intl.. Conf. on Advanced Robotics (ICAR), 501–508. 2019.

C8

Lea Steffen, Benedict Hauck, Jacques Kaiser, Jakob Weinland, Stefan Ulbrich, Daniel Reichard, Arne Rönnau, and Rüdiger Dillmann. Creating an obstacle memory through event-based stereo vision and robotic proprioception. In 15th IEEE Intl.. Conf. Automation Science and Engineering, 1829–1836. 2019.

C9

Marc René Zofka, Stefan Ulbrich, Daniel Karl, Tobias Fleck, Ralf Kohlhaas, Arne Rönnau, Rüdiger Dillmann, and Johann Marius Zöllner. Traffic participants in the loop: A mixed reality-based interaction testbed for the verification and validation of autonomous vehicles. In Intl. Conf. Intelligent Transportation Systems (ITSC), 3583–3590. 11 2018.

C10

Stefan Ulbrich, Terrance Steward, Igor Perić, Igor Rönnau, Johann Marius Zöllner, and Rüdiger Dillmann. Model-based polynomial function approximation with spiking neural networks. In IEEE 16th Intl. Conf. Cognitive Informatics Cognitive Computing (ICCI*CC), 22–27. 7 2017. Best paper award.

C11

J. Camilo Vasquez Tieck, Heiko Donat, Jacques Kaiser, Igor Perić, Stefan Ulbrich, Arne Rönnau, Marius Zöllner, and Rüdiger Dillmann. Towards grasping with spiking neural networks for anthropomorphic robot hands. In Alessandra Lintas, Stefano Rovetta, Paul F.M.J. Verschure, and Alessandro E.P. Villa, editors, 26th Intl. Conf. Artificial Neural Networks (ICANN), Part II Artificial Neural Networks and Machine Learning, 43–51. Springer Intl. Publishing, 2017.

C12

Igor Perić, Robert Hangu, Jacques Kaiser, Stefan Ulbrich, Arne Rönnau, J Zöllner, and Rüdiger Dillmann. Semi-supervised spiking neural network for one-shot object appearance learning. In Proc. of the 5th Intl. Congress on Neurotechnology, Electronics and Informatics, (NEUROTECHNIX). 10 2017.

C13

Igor Perić, Felix Schneider, Cameron H. Price, Stefan Ulbrich, Arne Rönnau, Marius Zöllner, and R\"diger Dillmann. Exact spike timing computational model of convolutional associative memories. In IEEE 16th Intl. Conf. Cognitive Informatics Cognitive Computing (ICCI*CC), 182–190. 7 2017.

C14

Igor Perić, Alexandru Lesi, Daniel Spies, Stefan Ulbrich, Arne Rönnau, Marius Zöllner, and Rüdiger Dillmann. Probabilistic symbol encoding for convolutional associative memories. In Proc. of the 5th Intl. Congress on Neurotechnology, Electronics and Informatics, (NEUROTECHNIX), 22–29. 10 2017. Best paper award.

C15

Jacques Kaiser, David Zimmerer, J Camilo Vasquez Tieck, Stefan Ulbrich, Arne Rönnau, and Rüdiger Dillmann. Spiking convolutional deep belief networks. In 26th Intl. Conf. Artificial Neural Networks (ICANN), Part II Artificial Neural Networks and Machine Learning. Springer, 9 2017. Best paper award.

C16

Alessandro Ambrosano, Lorenzo Vannucci, Ugo Albanese, Murat Kirtay, Egidio Falotico, Georg Hinkel, Jacques Kaiser, Stefan Ulbrich, Paul Levi, Christian Morillas, and others. Retina color-opponency based pursuit implemented through spiking neural networks in the neurorobotics platform. In Conf. on Biomimetic and Biohybrid Systems, 16–27. Springer, 2016.

C17

Lorenzo Vannucci, Alessandro Ambrosano, Nino Cauli, Ugo Albanese, Egidio Falotico, Stefan Ulbrich, Lars Pfotzer, Georg Hinkel, Oliver Denninger, Daniel Peppicelli, and others. A visual tracking model implemented on the iCub robot as a use case for a novel neurorobotic toolkit integrating brain and physics simulation. In IEEE/RAS Intl. Conf. Humanoid Robots, 1179–1184. 2015.

C18

Stefan Ulbrich. Sensorimotor learning for neural robot control based on the Kinematic Bézier Maps and spiking neural networks. In EuroAsianPacific Joint Conf. Cognitive Science (EAP CogSci. 9 2015. URL: http://ceur-ws.org/Vol-1419/section0009.pdf.

C19

Georg Hinkel, Henning Groenda, Lorenzo Vannucci, Oliver Denninger, Nino Cauli, and Stefan Ulbrich. A domain-specific language (DSL) for integrating neuronal networks in robot control. In MORSE/VAO Workshop on Model-Driven Robot Software Engineering and View-based Software Engineering. 2015.

C20

Stefan Ulbrich and Tamim Asfour. Novel representations for sensorimotor learning for an artificial body schema on humanoid robots. In Intl. Conf. Development, Learning and Epigenetic Robotics (ICDL-EpiRob), Workshop: Development of body representations in humans and robots. 2014.

C21

Ömer Terlemez, Stefan Ulbrich, Christian Mandery, Martin Do, Nikolaus Vahrenkamp, and Tamim Asfour. Master Motor Map (mmm) – framework and toolkit for capturing, representing, and reproducing human motion on humanoid robots. In IEEE/RAS Intl. Conf. Humanoid Robots, 894–901. 2014.

C22

S. Ulbrich and T. Asfour. Improving body schema learning with Kinematic Bézier Maps by symmetry constraints. In Workshop Autonom. Learning, IEEE Intl. Conf. Robot. Autom. (ICRA). 5 2013.

C23

Nikolaus Vahrenkamp, Manfred Kröhnert, Stefan Ulbrich, Tamim Asfour, Giorgio Metta, Rüdiger Dillmann, and Giulio Sandini. Simox: a robotics toolbox for simulation, motion and grasp planning. In Intl. Conf. Intell. Auton. Syst. (IAS). 2012.

C24

S. Ulbrich, M. Bechtel, T. Asfour, and R. Dillmann. Learning robot dynamics with Kinematic Bézier Maps. In IEEE/RSJ Intl. Conf. Intell. Robots, Syst. (IROS). 10 2012.

C25

Stefan Ulbrich, Daniel Kappler, Tamim Asfour, Nikolaus Vahrenkamp, Alexander Bierbaum, Markus Przybylski, and Rüdiger Dillmann. The OpenGRASP Benchmarking Suite: an environment for the comparative analysis of grasping and dexterous manipulation. In IEEE/RSJ Intl. Conf. Intell. Robots, Syst. (IROS), 1761–1767. 9 2011.

C26

B. Léon, S. Ulbrich, R. Diankov, G. Puche, M. Przybylski, A. Morales, T. Asfour, S. Moisio, J. Bohg, J. Kuffner, and R. Dillmann. OpenGRASP: a toolkit for robot grasping simulation. In Intl. Conf. Simulation, Modeling, Programming for Autonomous Robots (SIMPAR), 109–120. 11 2010. Best paper award.

C27

S. Ulbrich, V. Ruiz de Angulo, T. Asfour, C. Torras, and R. Dillmann. Rapid learning of humanoid body schemas with Kinematic Bézier Maps. In IEEE/RAS Intl. Conf. Humanoid Robots, 431–438. 12 2009.

Journals

J1

Lea Steffen, Robin Koch, Stefan Ulbrich, Sven Nitzsche, Arne Roennau, and Rüdiger Dillmann. Benchmarking Highly Parallel Hardware for Spiking Neural Networks in Robotics. Front. in Neuroscience, 15:790, 2021.

J2

Lea Steffen, M. Elfgen, S. Ulbrich, A. Rönnau, and R. Dillmann. A Benchmark Environment for Neuromorphic Stereo Vision. Frontiers Robotics and AI, 2021.

J3

Georg Hinkel, Henning Groenda, Sebastian Krach, Lorenzo Vannucci, Oliver Denninger, Nino Cauli, Stefan Ulbrich, Arne Rönnau, Egidio Falotico, Marc-Oliver Gewaltig, and others. A framework for coupled simulations of robots and spiking neuronal networks. Journal of Intelligent & Robotic Systems, 85(1):71–91, 2017.

J4

Egidio Falotico, Lorenzo Vannucci, Alessandro Ambrosano, Ugo Albanese, Stefan Ulbrich, Juan Camilo Vasquez Tieck, Georg Hinkel, Jacques Kaiser, Igor Perić, Oliver Denninger, and Nino Cauli. Connecting artificial brains to robots in a comprehensive simulation framework: the neurorobotics platform. Frontiers in Neurorobotics, 11:2, 2017.

J5

S. Ulbrich, V. Ruiz de Angulo, T. Asfour, C. Torras, and R. Dillmann. Kinematic Bézier Maps. IEEE Trans. Syst., Man, Cybern. B, 42(4):1215–1230, 8 2012.

J6

S. Ulbrich, V. Ruiz de Angulo, T. Asfour, C. Torras, and R. Dillmann. General robot kinematics decomposition without intermediate markers. IEEE Trans. Neural Netw., Learning Syst., 23(4):620–630, 4 2012.

J7

Razif. R. Gabdoulline, S Ulbrich, S. Richter, and R. C. Wade. Prosat2—protein structure annotation server. Nucleic acids research, 34(suppl 2):79–83, 2006.

Patents

P1

Shahrokh Shahidzadeh and Stefan Ulbrich. Identification (ID) proofing and risk engine integration system and method. U.S. Patent US11329998B1, SecureAuth Corp, Mai 10, 2022.

P2

Shahrokh Shahidzadeh, Nahal Shahidzadeh, Haitham Akkary, Stefan Ulbrich, and Mani Malekmohammadi. System and method for secure pair and unpair processing using a dynamic level of assurance (LOA) score. U.S. Patent US11367323B1, SecureAuth Corp, Jun 21, 2022.

P3

Shahrokh Shahidzadeh, Nahal Shahidzadeh, Haitham Akkary, Stefan Ulbrich, and Mani Malekmohammadi. Authentication and authorization through derived behavioral credentials using secured paired communication devices. U.S. Patent US11101993B1, SecureAuth Corp, Aug 24, 2021.