Learned graphical models for probabilistic planning provide a new class of movement primitives. - Elmar A. Rückert; Gerhard Neumann; Marc Toussaint; Wolfgang Maass 001 (Frontiers Comput. Neurosci., 2012)

Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation. - Elmar A. Rückert; Gerhard Neumann (Artif. Life, 2013)

Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems. - Elmar Rueckert; Andrea d'Avella (Frontiers Comput. Neurosci., 2013)

Robust policy updates for stochastic optimal control. - Elmar Rueckert; Max Mindt; Jan Peters 001; Gerhard Neumann (Humanoids, 2014)

Learning inverse dynamics models with contacts. - Roberto Calandra; Serena Ivaldi; Marc Peter Deisenroth; Elmar Rueckert; Jan Peters 001 (ICRA, 2015)

Extracting low-dimensional control variables for movement primitives. - Elmar Rueckert; Jan Mundo; Alexandros Paraschos; Jan Peters 001; Gerhard Neumann (ICRA, 2015)

Model-free Probabilistic Movement Primitives for physical interaction. - Alexandros Paraschos; Elmar Rueckert; Jan Peters 001; Gerhard Neumann (IROS, 2015)

Low-cost Sensor Glove with Force Feedback for Learning from Demonstrations using Probabilistic Trajectory Representations. - Elmar Rueckert; Rudolf Lioutikov; Roberto Calandra; Marius Schmidt; Philipp Beckerle; Jan Peters 001 (CoRR, 2015)

Model estimation and control of compliant contact normal force. - Morteza Azad; Valerio Ortenzi; Hsiu-Chin Lin; Elmar Rueckert; Michael N. Mistry (Humanoids, 2016)

Deep spiking networks for model-based planning in humanoids. - Daniel Tanneberg; Alexandros Paraschos; Jan Peters 001; Elmar Rueckert (Humanoids, 2016)

Learning soft task priorities for control of redundant robots. - Valerio Modugno; Gerhard Neumann; Elmar Rueckert; Giuseppe Oriolo; Jan Peters 001; Serena Ivaldi (ICRA, 2016)

A low-cost sensor glove with vibrotactile feedback and multiple finger joint and hand motion sensing for human-robot interaction. - Paul Weber; Elmar Rueckert; Roberto Calandra; Jan Peters 001; Philipp Beckerle (RO-MAN, 2016)

Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals. - Daniel Tanneberg; Jan Peters 001; Elmar Rueckert (CoRL, 2017)

Learning inverse dynamics models in O(n) time with LSTM networks. - Elmar Rueckert; Moritz Nakatenus; Samuele Tosatto; Jan Peters 001 (Humanoids, 2017)

A comparison of distance measures for learning nonparametric motor skill libraries. - Svenja Stark; Jan Peters 001; Elmar Rueckert (Humanoids, 2017)

Efficient online adaptation with stochastic recurrent neural networks. - Daniel Tanneberg; Jan Peters 001; Elmar Rueckert (Humanoids, 2017)

Probabilistic movement primitives under unknown system dynamics. - Alexandros Paraschos; Elmar Rueckert; Jan Peters 001; Gerhard Neumann (Adv. Robotics, 2018)

Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling. - Adrian Sosic; Elmar Rueckert; Jan Peters 001; Abdelhak M. Zoubir; Heinz Koeppl (J. Mach. Learn. Res., 2018)

Cataglyphis Ant Navigation Strategies Solve the Global Localization Problem in Robots with Binary Sensors. - Nils Rottmann; Ralf Bruder; Achim Schweikard; Elmar Rueckert (BIOSIGNALS, 2019)

Loop Closure Detection in Closed Environments. - Nils Rottmann; Ralf Bruder; Achim Schweikard; Elmar Rueckert (ECMR, 2019)

Experience Reuse with Probabilistic Movement Primitives. - Svenja Stark; Jan Peters 001; Elmar Rueckert (IROS, 2019)

REAL-2019: Robot open-Ended Autonomous Learning competition. - Emilio Cartoni; Francesco Mannella; Vieri Giuliano Santucci; Jochen Triesch; Elmar Rueckert; Gianluca Baldassarre (NeurIPS (Competition and Demos), 2019)

Learning walk and trot from the same objective using different types of exploration. - Zinan Liu; Kai Ploeger; Svenja Stark; Elmar Rueckert; Jan Peters 001 (CoRR, 2019)

Learning Algorithmic Solutions to Symbolic Planning Tasks with a Neural Computer. - Daniel Tanneberg; Elmar Rueckert; Jan Peters 001 (CoRR, 2019)

Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks. - Daniel Tanneberg; Jan Peters 001; Elmar Rueckert (Neural Networks, 2019)

Exploiting Chlorophyll Fluorescense for building robust low-cost Mowing Area Detectors. - Nils Rottmann; Ralf Bruder; Achim Schweikard; Elmar Rueckert (IEEE SENSORS, 2020)

Learning Hierarchical Acquisition Functions for Bayesian Optimization. - Nils Rottmann; Tjasa Kunavar; Jan Babic; Jan Peters 001; Elmar Rueckert (IROS, 2020)

ROS-Mobile: An Android application for the Robot Operating System. - Nils Rottmann; Nico Studt; Floris Ernst; Elmar Rueckert (CoRR, 2020)

Parameter Optimization for Loop Closure Detection in Closed Environments. - Nils Rottmann; Ralf Bruder; Honghu Xue; Achim Schweikard; Elmar Rueckert (CoRR, 2020)

Evolutionary training and abstraction yields algorithmic generalization of neural computers. - Daniel Tanneberg; Elmar Rueckert; Jan Peters 001 (Nat. Mach. Intell., 2020)

A Probabilistic Approach for Complete Coverage Path Planning with low-cost Systems. - Nils Rottmann; Robin Denz; Ralf Bruder; Elmar Rueckert (ECMR, 2021)

A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning. - Robin Denz; Rabia Demirci; Mehmet Ege Cansev; Adna Bliek; Philipp Beckerle; Elmar Rueckert; Nils Rottmann (ICAR, 2021)

Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience. - Mehmet Ege Cansev; Honghu Xue; Nils Rottmann; Adna Bliek; Luke E. Miller; Elmar Rueckert; Philipp Beckerle (Adv. Intell. Syst., 2021)

Using Probabilistic Movement Primitives in Analyzing Human Motion Difference under Transcranial Current Stimulation. - Honghu Xue; Rebecca Herzog; Till M. Berger; Tobias Bäumer; Anne Weissbach; Elmar Rueckert (CoRR, 2021)

Using Probabilistic Movement Primitives in Analyzing Human Motion Differences Under Transcranial Current Stimulation. - Honghu Xue; Rebecca Herzog; Till M. Berger; Tobias Bäumer; Anne Weissbach; Elmar Rueckert (Frontiers Robotics AI, 2021)

Predictive Exoskeleton Control for Arm-Motion Augmentation Based on Probabilistic Movement Primitives Combined With a Flow Controller. - Marko Jamsek; Tjasa Kunavar; Urban Bobek; Elmar Rueckert; Jan Babic (IEEE Robotics Autom. Lett., 2021)

SKID RAW: Skill Discovery From Raw Trajectories. - Daniel Tanneberg; Kai Ploeger; Elmar Rueckert; Jan Peters 001 (IEEE Robotics Autom. Lett., 2021)

Predicting full-arm grasping motions from anticipated tactile responses. - Vedant Dave; Elmar Rueckert (Humanoids, 2022)

End-To-End Deep Reinforcement Learning for First-Person Pedestrian Visual Navigation in Urban Environments. - Honghu Xue; Rui Song; Julian Petzold; Benedikt Hein; Heiko Hamann; Elmar Rueckert (Humanoids, 2022)

Using Deep Reinforcement Learning with Automatic Curriculum earning for Mapless Navigation in Intralogistics. - Honghu Xue; Benedikt Hein; Mohamed Bakr; Georg Schildbach; Bengt Abel; Elmar Rueckert (CoRR, 2022)

O2S: Open-source open shuttle. - Nwankwo Linus; Fritze Clemens; Konrad Bartsch; Elmar Rueckert (CoRR, 2022)

Deep Reinforcement Learning for Mapless Navigation of Autonomous Mobile Robot. - Harsh Yadav; Honghu Xue; Yan Rudall; Mohamed Bakr; Benedikt Hein; Elmar Rueckert; Ngoc Thinh Nguyen (ICSTCC, 2023)

Understanding why SLAM algorithms fail in modern indoor environments. - Nwankwo Linus; Elmar Rueckert (CoRR, 2023)

CR-VAE: Contrastive Regularization on Variational Autoencoders for Preventing Posterior Collapse. - Fotios Lygerakis; Elmar Rueckert (CoRR, 2023)

The Conversation is the Command: Interacting with Real-World Autonomous Robots Through Natural Language. - Linus Nwankwo; Elmar Rueckert (HRI (Companion), 2024)

Multimodal Visual-Tactile Representation Learning through Self-Supervised Contrastive Pre-Training. - Vedant Dave; Fotios Lygerakis; Elmar Rueckert (ICRA, 2024)

Advancing Interactive Robot Learning: A User Interface Leveraging Mixed Reality and Dual Quaternions. - Nikolaus Feith; Elmar Rueckert (UR, 2024)

Integrating Human Expertise in Continuous Spaces: A Novel Interactive Bayesian Optimization Framework with Preference Expected Improvement. - Nikolaus Feith; Elmar Rueckert (UR, 2024)

M2CURL: Sample-Efficient Multimodal Reinforcement Learning via Self-Supervised Representation Learning for Robotic Manipulation. - Fotios Lygerakis; Vedant Dave; Elmar Rueckert (UR, 2024)

Semi-Autonomous Fast Object Segmentation and Tracking Tool for Industrial Applications. - Melanie Neubauer; Elmar A. Rückert (UR, 2024)

The Conversation is the Command: Interacting with Real-World Autonomous Robot Through Natural Language. - Linus Nwankwo; Elmar Rueckert (CoRR, 2024)

Multimodal Human-Autonomous Agents Interaction Using Pre-Trained Language and Visual Foundation Models. - Linus Nwankwo; Elmar Rueckert (CoRR, 2024)

ED-VAE: Entropy Decomposition of ELBO in Variational Autoencoders. - Fotios Lygerakis; Elmar Rueckert (CoRR, 2024)

EnvoDat: A Large-Scale Multisensory Dataset for Robotic Spatial Awareness and Semantic Reasoning in Heterogeneous Environments. - Linus Nwankwo; Bjoern Ellensohn; Vedant Dave; Peter Hofer; Jan Forstner; Marlene Villneuve; Robert Galler; Elmar Rueckert (CoRR, 2024)

The Effects of Different Motor Teaching Strategies on Learning a Complex Motor Task. - Tjasa Kunavar; Marko Jamsek; Edwin Johnatan Avila Mireles; Elmar Rueckert; Luka Peternel; Jan Babic (Sensors, 2024)

Skill Disentanglement in Reproducing Kernel Hilbert Space. - Vedant Dave; Elmar Rueckert (AAAI, 2025)

Privacy-Aware Lifelong Learning. - Ozan Özdenizci; Elmar Rueckert; Robert Legenstein (ICLR, 2025)

ReLI: A Language-Agnostic Approach to Human-Robot Interaction. - Linus Nwankwo; Bjoern Ellensohn; Ozan Özdenizci; Elmar Rueckert (CoRR, 2025)

ViTaPEs: Visuotactile Position Encodings for Cross-Modal Alignment in Multimodal Transformers. - Fotios Lygerakis; Ozan Özdenizci; Elmar A. Rückert (CoRR, 2025)