Publikationen von: Elmar Rückert


2023

Harsh Yadav, Honghu Xue, Yan Rudall, Bakr Mohamed, Benedikt Hein, Elmar Rueckert and Ngoc Thinh Nguyen, Deep Reinforcement Learning for Autonomous Navigation in Intralogistics, 2023
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2022

Rebecca Herzog, Till M Berger, Martje Gesine Pauly, Honghu Xue, Elmar Rueckert, Alexander Münchau, Tobias Bäumer and Anne Weissbach, Cerebellar transcranial current stimulation-an intraindividual comparison of different techniques (2022), in: Frontiers Neuroscience
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Honghu Xue, Rui Song, Julian Petzold, Benedikt Hein, Heiko Hamann and Elmar Rueckert, End-To-End Deep Reinforcement Learning for First-Person Pedestrian Visual Navigation in Urban Environments, The 2022 IEEE-RAS International Conference on Humanoid Robots, 2022
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Honghu Xue, Benedikt Hein, Bakr Mohamed, Georg Schildbach, Bengt Abel and Elmar Rueckert, Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics (2022), in: Applied Sciences special issue "Intelligent Robotics", 12:6(3153)
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2021

Mehmet Cansev, Honghu Xue, Nils Rottmann, Adna Bliek, Luke E Miller, Elmar Rueckert and Philipp Beckerle, Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience (2021), in: Advanced Intelligent Systems
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Marko Jamsek, Tjasa Kunavar, Urban Bobek, Elmar Rueckert and Jan Babic, Predictive exoskeleton control for arm-motion augmentation based on probabilistic movement primitives combined with a flow controller (2021), in: IEEE Robotics and Automation Letters (RA-L)(1--8)
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Daniel Tanneberg, Kai Ploeger, Elmar Rueckert and Jan Peters, SKID RAW: Skill Discovery from Raw Trajectories (2021), in: IEEE Robotics and Automation Letters (RA-L)(1--8)
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Honghu Xue, Rebecca Herzog, Till M Berger, Tobias Bäumer, Anne Weissbach and Elmar Rueckert, Using Probabilistic Movement Primitives in analyzing human motion differences under Transcranial Current Stimulation (2021), in: Frontiers Robot. AI - Humanoid Robotics
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2020

Nils Rottmann, Ralf Bruder, Achim Schweikard and Elmar Rueckert, A novel Chlorophyll Fluorescence based approach for Mowing Area Classification (2020), in: IEEE Sensors Journal
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Tolga-Can Çallar, Elmar Rueckert and Sven Böttger, Efficient Body Registration Using Single-View Range Imaging and Generic Shape Templates (2020), in: 54th Annual Conference of the German Society for Biomedical Engineering (BMT 2020), 6:3(119-122)
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Daniel Tanneberg, Elmar Rueckert and Jan Peters, Evolutionary training and abstraction yields algorithmic generalization of neural computers (2020), in: Nature Machine Intelligence
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Nils Rottmann, Ralf Bruder, Achim Schweikard and Elmar Rueckert, Exploiting Chlorophyll Fluorescense for Building Robust low-Cost Mowing Area Detectors (2020), in: IEEE SENSORS Conference(4)
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Nils Rottmann, Tjasa Kunavar, Jan Babic, Jan Peters and Elmar Rueckert, Learning Hierarchical Acquisition Functions for Bayesian Optimization, Las Vegas, USA, Proceedings of International Conference on Intelligent Robots and Systems (IROS), 2020
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Nils Rottmann, Ralf Bruder, Honghu Xue, Achim Schweikard and Elmar Rueckert, Parameter Optimization for Loop Closure Detection in Closed Environments (2020), in: Workshop Paper at the International Conference on Intelligent Robots and Systems (IROS)(8)
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Emilio Cartoni, Franscesco Mannella, Vieri Giuliano Santucci, Jochen Triesch, Elmar Rueckert and Gianluca Baldassarre, REAL-2019: Robot open-Ended Autonomous Learning competition (2020), in: Proceedings of Machine Learning Research(142-152)
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Honghu Xue, Sven Böttger, Nils Rottmann, Harit Pandya, Ralf Bruder, Gerdhard Neumann and Elmar Rueckert, Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks, Berlin, Germany, Proceedings of International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI), 2020
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2019

Nils Rottmann, Ralf Bruder, Achim Schweikard and Elmar Rueckert, Cataglyphis ant navigation strategies solve the global localization problem in robots with binary sensors, Prague, Czech Republic, Proceedings of International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS), 2019
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Elmar Rueckert, Philipp Jauer, Alexander Derksen and Achim Schweikard, Dynamic Control Strategies for Cable-Driven Master Slave Robots, in: Proceedings on Minimally Invasive Surgery, Luebeck, Germany, Luebeck, Germany, 2019
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Daniel Tanneberg, Jan Peters and Elmar Rueckert, Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks (2019), in: Neural Networks - Elsevier, 109(67-80)
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Nils Rottmann, Ralf Bruder, Achim Schweikard and Elmar Rueckert, Loop Closure Detection in Closed Environments, European Conference on Mobile Robots (ECMR 2019), 2019
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Sven Böttger, Tolga-Can Çallar, Elmar Rueckert and Achim Schweikard, Medical robotics simulation framework for application-specific optimal kinematics (2019), in: Current Directions in Biomedical Engineering, 5:1(145-148)
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2018

Adrian Sosic, Elmar Rueckert, Jan Peters and Abdelhak M Zoubir, Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling (2018), in: Journal of Machine Learning Research (JMLR)
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Elmar Rueckert, Learning to Categorize Bug Reports with LSTM Networks, in: Proceedings of the International Conference on Advances in System Testing and Validation Lifecycle (VALID), Nice, France, pages 6, XPS (Xpert Publishing Services), 2018
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