Publications

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Book Chapter
Steil JJ, Krüger S. Lernen und Sicherheit in Interaktion mit Robotern aus Maschinensicht. In: Robotik und Gesetzgebung. Vol. 2. Robotik und Gesetzgebung. Nomos; 2013. pp. 51-71.
Conference Paper
Karklinsky M, Flash T. The 2/3 power law originates in the motor plan. In: Computational motor Control workshop 9. Computational motor Control workshop 9. Beer-sheva, Isreal.; 2013.
Karklinsky M, Flash T. The 2/3 power law originates in the motor plan: a motor imagery study. In: Neural control of movement (NCM 2014). Neural control of movement (NCM 2014). Amsterdam, Netherlands; 2013.
Degrave J, wyffels F, Waegeman T, Kindermans P-J, Schrauwen B. Applying morphological changes during the evolution of quadruped robots results in robust gaits. In: De Baets B, Manderick B, Rademaker Ml, Waegeman W Proceedings of the 21st Belgian-Dutch Conference on Machine Learning. Proceedings of the 21st Belgian-Dutch Conference on Machine Learning. University Press; 2012.
Chiovetto E, Mukovskiy A, Reinhart RF, Khansari-Zadeh SMohammad, Billard A, Steil JJ, Giese MA. Assessment of human-likeness and naturalness of interceptive arm reaching movement accomplished by a humanoid robot. In: European Conference on Visual Perception (ECVP 2014); 2014. Available from: http://www.perceptionweb.com/abstract.cgi?id=v1412968
Kormushev P, Ugurlu B, Calinon S, Tsagarakis NG, Caldwell DG. Bipedal Walking Energy Minimization by Reinforcement Learning with Evolving Policy Paramerization. In: International Conference on Intelligent Robots and Systems (IROS). International Conference on Intelligent Robots and Systems (IROS). San Francisco, California; 2011. Available from: http://programming-by-demonstration.org/papers/Kormushev-IROS2011.pdf
Khansari-Zadeh SM, Billard A. BM: An Iterative Algorithm to Learn Stable Non-Linear Dynamical Systems with Gaussian Mixture Models. In: Proceeding of the International Conference on Robotics and Automation (ICRA). Proceeding of the International Conference on Robotics and Automation (ICRA). ; 2010. pp. 2381-2388. Available from: http://www.researchgate.net/publication/224156439_BM_An_iterative_algorithm_to_learn_stable_non-linear_dynamical_systems_with_Gaussian_mixture_models/file/9c960517160383ff2c.pdf
D K, Karklinsky M, Flash T, Shmuelof L. The building blocks of curved trajectories: studying the effect of shortened preparation time on movement planning and execution. In: ISFN. ISFN. Eilat, Israel; 2013.
Velychko D, Endres D, Taubert N, Giese MA. Coupling Gaussian Process Dynamical Models with Product-of-Experts Kernels. In: Wermter S, Weber C, Duch W, Honkela T, Koprinkova-Hristova P, Magg S, Palm G, Villa AEP Artificial Neural Networks and Machine Learning – ICANN 2014. Artificial Neural Networks and Machine Learning – ICANN 2014. Springer International Publishing; 2014. Available from: http://dx.doi.org/10.1007/978-3-319-11179-7_76
Dallali H, Mosadeghzad M, Medrano-Cerda G, Docquier N, Kormushev P, Tsagarakis NG, Li Z, Caldwell DG. Development of a Dynamic Simulator for a Compliant Human-oid Robot Based on a Symbolic Multibody Approach. In: IEEE International Conference on Mechatronics. IEEE International Conference on Mechatronics. ; 2013. Available from: http://kormushev.com/papers/Dallali_ICM-2013.pdf
Khansari-Zadeh SM, Billard A. Imitation Learning of Globally Stable Non-Linear Point-to-Point Robot Motions using Nonlinear Programming. In: Proceeding of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Proceeding of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). ; 2010. pp. 2676-2683. Available from: http://homepages.inf.ed.ac.uk/s0565544/0146.pdf
Kuppuswamy N, Carbajal JP. Learning a curvature dynamic model of an octopus-inspired soft robot arm using flexure sensors. In: The European Future Technologies Conference and Exhibition. The European Future Technologies Conference and Exhibition. ; 2011. Available from: http://www.sciencedirect.com/science/article/pii/S1877050911006065
Kim S, Gribovskaya E, Billard A. Learning motion dynamics to catch a moving object. In: 10th IEEE-RAS International Conference on Humanoid Robots (Humanoids). 10th IEEE-RAS International Conference on Humanoid Robots (Humanoids). Nashville, TN; 2010. pp. 106-111. Available from: http://www.academia.edu/download/30230251/humanoids2010_ready.pdf
Sproewitz A, Kuechler L, Tuleu A, Ajallooeian M, D’Haene M, Moeckel R, Ijspeert A. Oncilla Robot, A Light-weight Bio-inspired Quadruped Robot for Fast Locomotion in Rough Terrain. In: Symposium on Adaptive Motion of Animals and Machines (AMAM2011). Symposium on Adaptive Motion of Animals and Machines (AMAM2011). ; 2011. pp. 63-64. Available from: http://adaptivemotion.org/AMAM2011/papers/s323.pdf
Khansari-Zadeh SMohammad, Billard A. Realtime Avoidance of Fast Moving Objects: A Dynamical System-based Approach. In: Electronic proc. of the Workshop on Robot Motion Planning: Online, Reactive, and in Real-Time, Int. Conf. on Intelligent Robots and Systems (IROS). Electronic proc. of the Workshop on Robot Motion Planning: Online, Reactive, and in Real-Time, Int. Conf. on Intelligent Robots and Systems (IROS). ; 2012. Available from: http://www.reflexxes.com/iros2012ws/Paper_04.pdf
Kohen D, Karklinsky M, Meirovitch Y, Flash T, Shmuelof L. Shortening preparation time for curved trajectories reveals an ongoing control of movement segments. In: Neural control of movement (NCM 2014). Neural control of movement (NCM 2014). Amsterdam, Netherlands; 2014.
Kohen D, Karklinsky M, Meirovitch Y, Flash T, Shmuelof L. Shortening preparation time for curved trajectories reveals an ongoing control of movement segments. In: Neural control of movement (NCM 2014). Neural control of movement (NCM 2014). Amsterdam, Netherlands; 2014.
Kindermans P-J, wyffels F, Caluwaerts K, Guns B, Schrauwen B. Towards incorporation of hierarchical Bayesian models into evolution strategies for quadruped gait generation. In: Proceedings of the 21st Belgian-Dutch Conference on Machine Learning. Proceedings of the 21st Belgian-Dutch Conference on Machine Learning. ; 2012. Available from: https://biblio.ugent.be/publication/2134106/file/2134110.pdf
Journal Article
Khansari-Zadeh SM, Billard A. A dynamical system approach to realtime obstacle avoidance. Autonomous Robots [Internet]. 2012 ;32:433-454. Available from: http://dx.doi.org/10.1007/s10514-012-9287-y
Klampfl S, Maass W. Emergence of Dynamic Memory Traces in Cortical Microcircuit Models through STDP. The Journal of Neuroscience [Internet]. 2013 ;33:11515-11529. Available from: http://www.jneurosci.org/content/33/28/11515.abstract
Kim S, Billard A. Estimating the non-linear dynamics of free-flying objects. Robotics and Autonomous Systems. 2012 ;60:1108–-1122.
Kim S, Billard A. Estimating the non-linear dynamics of free-flying objects. Robotics and Autonomous Systems. 2012 :–.
Dallali H, Kormushev P, Li Z, Caldwell DG. On Global Optimization of Walking Gaits for the Compliant Humanoid Robot, COMAN Using Reinforcement Learning. Journal of Cybernetics and Information Technologies. 2012 ;vol. 12, no. 3:pp. 39-52.
Selionov V, Solopova I, Zhvansky D, Karabanov A, Chernikova L, Gurfinkel V, Ivanenko YP. Lack of non-voluntary stepping responses in Parkinson’s disease. Neurosci [Internet]. 2013 ;235:96-108. Available from: http://www.researchgate.net/publication/234141776_Lack_of_non-voluntary_stepping_responses_in_Parkinson’s_disease/file/9fcfd50ff1360a7554.pdf
Khansari-Zadeh SMohammad, Billard A. Learning Control Lyapunov Function to Ensure Stability of Dynamical System-based Robot Reaching Motions. Robotics and Autonomous Systems. 2014 .
Khansari-Zadeh SM, Billard A. Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models. Robotics, IEEE Transactions on [Internet]. 2011 ;27:943 -957. Available from: http://lasa.epfl.ch/publications/publications.php
Khansari-Zadeh SM, Kronander K, Billard A. Learning to Play Minigolf: A Dynamical System-based Approach. Advanced Robotics [Internet]. 2012 . Available from: http://infoscience.epfl.ch/record/181052/files/MiniGolf_AR12.pdf
Khansari-Zadeh SM, Kronander K, Billard A. Learning to Play Minigolf: A Dynamical System-based Approach. Advanced Robotics [Internet]. 2012 . Available from: http://infoscience.epfl.ch/record/181052/files/MiniGolf_AR12.pdf
Schack T, Essig K, Frank C, Koester D. Mental Representation and Motor Imagery Training. Frontiers in Human Neuroscience [Internet]. 2014 ;8. Available from: http://www.frontiersin.org/human_neuroscience/10.3389/fnhum.2014.00328/abstract
Lemme A, Meirovitch Y, Khansari-Zadeh SMohammad, Flash T, Billard A, Steil JJ. Open-source benchmarking for learned reaching motion generation in robotics. Paladyn J. Behavioral Robotics [Internet]. 2015 ;6(1):30-41. Available from: http://www.degruyter.com/dg/viewarticle.fullcontentlink:pdfeventlink/$002fj$002fpjbr.2015.6.issue-1$002fpjbr-2015-0002$002fpjbr-2015-0002.pdf?format=INT\&t:ac=j$002fpjbr.2015.6.issue-1$002fpjbr-2015-0002$002fpjbr-2015-0002.xml
Kappel D, Nessler B, Maass W. STDP Installs in Winner-Take-All Circuits an Online Approximation to Hidden Markov Model Learning. PLoS Computational Biology. 2014 .

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