Biblio

Found 234 results
Author Title [ Type(Desc)] Year
Conference Paper
Schiller U.D, Steil JJ.  2003.  On the weight dynamcis of recurrent learning. Proc. European Symposium Artificial Neural Networks. :73–78.
Steil JJ.  2011.  What do humanoid robots offer to experimental psychology ? Connectionist models of neurocognition and emergent behavior : from theory to applications ; proceedings of the 12th Neural Computation and Psychology Workshop, Birkbeck, University of London, 8 - 10 April 2010. 20:361–371.
Cognetti M., Mohammadi P., Oriolo G..  2015.  Whole-body motion planning for humanoids based on CoM movement primitives. 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).
Ötting S, Gopinathan S, Maier GW, Steil JJ.  2017.  Why Criteria of Decision Fairness Should be Considered in Robot Design. Workshop Robots in Groups and Teams at ACM Conference on Computer Supported Cooperative Work and Social Computing.
Bongardt B.  2018.  A Workspace Scaling Method for Motion Synchronization in SE(3). 22nd CISM IFToMM Symposium on Robot Design, Dynamics and Control (Romansy).
Conference Proceedings
Adnan SAtif, Muhammad A, Shareef Z.  2011.  Development of a low cost thermal feedback system for basic control education. IEEE 14th International Multitopic Conference.
Shareef Z, Ahmed A.  2011.  LMI BASED Anti-Windup Controller Designing for Ball and Beam Control System. International Bhurban Conference on Applied Sciences and Technology.
Shareef Z, Ahmed A, Iqbal N.  2013.  Mixed sensitivity based dynamical Anti-Windup Compensator design using LMI: An application to constrained hot air blower system. IEEE XXIV International Symposium on Information, Communication and Automation Technologies.
Malekzadeh MS, Bruno D, Calinon S, Nanayakkara T, Caldwell DG.  2013.  Skills transfer across dissimilar robots by learning context-dependent rewards. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems (IROS).
Journal Article
Steil JJ, Götting M, Wersing H, Körner E, Ritter H.  2007.  Adaptive scene dependent filters for segmentation and online learning of visual objects. Neurocomputing. 70:1235–1246.
Liu W, Chen D, Steil JJ.  2017.  Analytical Inverse Kinematics Solver for Anthropomorphic 7-DOF Redundant Manipulators with Human-Like Configuration Constraints. Journal of Intelligent & Robotic Systems. 86(1):63-79.
Schiller UD, Steil JJ.  2005.  Analyzing the weight dynamics of recurrent learning algorithms. Neurocomputing. 63:5–23.
Queißer J, Steil JJ.  2018.  Bootstrapping of Parameterized Skills Through Hybrid Optimization in Task and Policy Spaces. Frontiers in Robotics and AI, section Humanoid Robotics. 5
Wersing H, Steil JJ, Ritter H.  2001.  A Competitive Layer Model for Feature Binding and Sensory Segmentation. Neural Computation. 13:357–387.
Reinhart F, Steil JJ.  2011.  A constrained regularization approach for input-driven recurrent neural networks. Differential Equations and Dynamical Systems. 19:27–46.
Shareef Z, Just V, Teichrieb H, Trächtler A.  2017.  Design and control of cooperative ball juggling DELTA robots without visual guidance. Robotica. 35(2)
Kumar S, Bongardt B, Simnofske M, Kirchner F.  2018.  Design and kinematic analysis of the novel almost spherical parallel mechanism Active Ankle. Journal of Intelligent and Robotic Systems.
He H, Chawla N, Chen H, Choe Y, Engelbrecht A, Deva J, Long L, Minai A, Nie F, Ozertem U et al..  2016.  Editorial IEEE Transactions on Neural Networks and Learning Systems 2016 and Beyond. IEEE Transactions on Neural Networks and Learning Systems. 27:1–7.
Kopp S, Steil J.  2011.  Editorial Special Corner on Cognitive Robotics. Cognitive Processing. 12:317–318.
Rolf M, Steil JJ.  2014.  Efficient exploratory learning of inverse kinematics on a bionic elephant trunk. IEEE Trans. Neural Networks and Learning Systems. 25:1147–1160.
Reinhart F, Steil JJ.  2015.  Efficient Policy Search in Low-dimensional Embedding Spaces by Generalizing Motion Primitives with a Parameterized Skill Memory. Autonomous Robots. 38:331–348.
Rolf M, Steil JJ.  2013.  Explorative learning of right inverse functions: theoretical implications of redundancy. Neurocomputing.
Rolf M, Steil JJ, Gienger M..  2010.  Goal Babbling permits direct learning of inverse kinematics. IEEE Trans. Autonomous Mental Development. 2:216–229.

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