Biblio
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2008. Long-Term Evaluation of a Visual Fall Detection System in a Real Home Environment. 1. Gemeinsamer Kongress der DGG / ÖGGG und der DGGG / SGG.
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2011. A Locally Deformable Statistical Shape Model. MLMI 2011, LNCS. 7009:51–58.
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2010. Localization of Mobile Robots Using Incremental Local Maps. Proc. of IEEE Int. Conf. on Robotics and Automation. :4873–4880.
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2002. Local structural stability of recurrent networks with time-varying weights. Neurocomputing. 48:39–51.
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2000. Local input-output stability of recurrent networks with time-varying weights. Proc. European Symposium Artificial Neural Networks. :281–286.
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2011. LMI BASED Anti-Windup Controller Designing for Ball and Beam Control System. International Bhurban Conference on Applied Sciences and Technology.
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2020. Let's Work Together: A Meta-Analysis on Robot Design Features that Enable Successful Human–Robot Interaction at Work. Human Factors.
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2024. Lessons Learned from Investigating Robotics-Based, Human-like Testing of an Upper-Body Exoskeleton . Applied Sciences. 14(6)
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2013. Lernen und Sicherheit in Interaktion mit Robotern aus Maschinensicht. Robotik und Gesetzgebung. 2:51–71.
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2012. Learning Whole Upper Body Control with Dynamic Redundancy Resolution in Coupled Associative Radial Basis Function Networks. IROS. :1487–1492.
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2012. Learning visuo-motor coordination for pointing without depth calculation. Proc. European Symposium on Artificial Neural Networks. :91–96.
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2015. Learning the stiffness of a continuous soft manipulator from multiple demonstrations. International Conference on Intelligent Robotics and Applications.
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2013. Learning the rules of a game: neural conditioning in human-robot interaction with delayed rewards.
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2015. Learning Robot Motions with Stable Dynamical Systems under Diffeomorphic Transformations. Robotics and Autonomous Systems. 70:1–15.
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2015. Learning Movement Primitives for Force Interaction Tasks. ICRA. :3192–3199.
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2006. Learning Lateral Interactions for Feature Binding and Sensory Segmentation from Prototypic Basis Interactions. IEEE Trans. Neural Networks. 17:843–862.
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2011. Learning Lab - Physical Interaction with Humanoid Robots for Pupils. Proc. Robotics in Education. :21–28.
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2018. Learning Inverse Statics Models Efficiently with Symmetry-Based Exploration. Frontiers in Neurorobotics.
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2017. Learning Inverse Statics Models Efficiently. arXiv.
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2010. Learning Inverse Kinematics for Pose-Constraint Bi-Manual Movements. From Animals to Animats 11. 11th International Conference on Simulation of Adaptive Behavior, SAB 2010. Proceedings. 6226
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2016. Learning from demonstration with partially observable task parameters using dynamic movement primitives and Gaussian process regression. 2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM).
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2018. Learning Forward and Inverse Kinematics Maps Efficiently. IROS 2018.
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2010. Learning Flexible Full Body Kinematics for Humanoid Tool Use. Int. Symp. Learning and Adaptive Behavior in Robotic Systems (Best Paper Award). :171–176.
