Elmar Rueckert

Orcid: 0000-0003-1221-8253

Affiliations:
  • University of Lübeck, Institute for Robotics and Cognitive Systems, Germany
  • TU Darmstadt, Intelligent Autonomous Systems Lab, Germany
  • Graz University of Technology, Institute for Theoretical Computer Science, Austria


According to our database1, Elmar Rueckert authored at least 51 papers between 2012 and 2024.

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Bibliography

2024
The Effects of Different Motor Teaching Strategies on Learning a Complex Motor Task.
Sensors, February, 2024

Multimodal Human-Autonomous Agents Interaction Using Pre-Trained Language and Visual Foundation Models.
CoRR, 2024

M2CURL: Sample-Efficient Multimodal Reinforcement Learning via Self-Supervised Representation Learning for Robotic Manipulation.
CoRR, 2024

Integrating Human Expertise in Continuous Spaces: A Novel Interactive Bayesian Optimization Framework with Preference Expected Improvement.
CoRR, 2024

Multimodal Visual-Tactile Representation Learning through Self-Supervised Contrastive Pre-Training.
CoRR, 2024

The Conversation is the Command: Interacting with Real-World Autonomous Robot Through Natural Language.
CoRR, 2024

The Conversation is the Command: Interacting with Real-World Autonomous Robots Through Natural Language.
Proceedings of the Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, 2024

2023
CR-VAE: Contrastive Regularization on Variational Autoencoders for Preventing Posterior Collapse.
CoRR, 2023

Understanding why SLAM algorithms fail in modern indoor environments.
CoRR, 2023

Deep Reinforcement Learning for Mapless Navigation of Autonomous Mobile Robot.
Proceedings of the 27th International Conference on System Theory, Control and Computing, 2023

2022
O2S: Open-source open shuttle.
CoRR, 2022

Using Deep Reinforcement Learning with Automatic Curriculum earning for Mapless Navigation in Intralogistics.
CoRR, 2022

End-To-End Deep Reinforcement Learning for First-Person Pedestrian Visual Navigation in Urban Environments.
Proceedings of the 21st IEEE-RAS International Conference on Humanoid Robots, 2022

Predicting full-arm grasping motions from anticipated tactile responses.
Proceedings of the 21st IEEE-RAS International Conference on Humanoid Robots, 2022

2021
SKID RAW: Skill Discovery From Raw Trajectories.
IEEE Robotics Autom. Lett., 2021

Predictive Exoskeleton Control for Arm-Motion Augmentation Based on Probabilistic Movement Primitives Combined With a Flow Controller.
IEEE Robotics Autom. Lett., 2021

Using Probabilistic Movement Primitives in Analyzing Human Motion Differences Under Transcranial Current Stimulation.
Frontiers Robotics AI, 2021

Using Probabilistic Movement Primitives in Analyzing Human Motion Difference under Transcranial Current Stimulation.
CoRR, 2021

Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience.
Adv. Intell. Syst., 2021

A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning.
Proceedings of the 20th International Conference on Advanced Robotics, 2021

A Probabilistic Approach for Complete Coverage Path Planning with low-cost Systems.
Proceedings of the 10th European Conference on Mobile Robots, 2021

2020
Evolutionary training and abstraction yields algorithmic generalization of neural computers.
Nat. Mach. Intell., 2020

Parameter Optimization for Loop Closure Detection in Closed Environments.
CoRR, 2020

ROS-Mobile: An Android application for the Robot Operating System.
CoRR, 2020

Learning Hierarchical Acquisition Functions for Bayesian Optimization.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Exploiting Chlorophyll Fluorescense for building robust low-cost Mowing Area Detectors.
Proceedings of the 2020 IEEE Sensors, Rotterdam, The Netherlands, October 25-28, 2020, 2020

2019
Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks.
Neural Networks, 2019

Learning Algorithmic Solutions to Symbolic Planning Tasks with a Neural Computer.
CoRR, 2019

Learning walk and trot from the same objective using different types of exploration.
CoRR, 2019

REAL-2019: Robot open-Ended Autonomous Learning competition.
Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019

Experience Reuse with Probabilistic Movement Primitives.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Loop Closure Detection in Closed Environments.
Proceedings of the 2019 European Conference on Mobile Robots, 2019

Cataglyphis Ant Navigation Strategies Solve the Global Localization Problem in Robots with Binary Sensors.
Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019), 2019

2018
Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling.
J. Mach. Learn. Res., 2018

Probabilistic movement primitives under unknown system dynamics.
Adv. Robotics, 2018

2017
Efficient online adaptation with stochastic recurrent neural networks.
Proceedings of the 17th IEEE-RAS International Conference on Humanoid Robotics, 2017

A comparison of distance measures for learning nonparametric motor skill libraries.
Proceedings of the 17th IEEE-RAS International Conference on Humanoid Robotics, 2017

Learning inverse dynamics models in O(n) time with LSTM networks.
Proceedings of the 17th IEEE-RAS International Conference on Humanoid Robotics, 2017

Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2016
A low-cost sensor glove with vibrotactile feedback and multiple finger joint and hand motion sensing for human-robot interaction.
Proceedings of the 25th IEEE International Symposium on Robot and Human Interactive Communication, 2016

Learning soft task priorities for control of redundant robots.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Deep spiking networks for model-based planning in humanoids.
Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots, 2016

Model estimation and control of compliant contact normal force.
Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots, 2016

2015
Low-cost Sensor Glove with Force Feedback for Learning from Demonstrations using Probabilistic Trajectory Representations.
CoRR, 2015

Model-free Probabilistic Movement Primitives for physical interaction.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Extracting low-dimensional control variables for movement primitives.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Learning inverse dynamics models with contacts.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014
Robust policy updates for stochastic optimal control.
Proceedings of the 14th IEEE-RAS International Conference on Humanoid Robots, 2014

2013
Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems.
Frontiers Comput. Neurosci., 2013

Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation.
Artif. Life, 2013

2012
Learned graphical models for probabilistic planning provide a new class of movement primitives.
Frontiers Comput. Neurosci., 2012


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