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Dr. Nils Rottmann

Ph.D. Student at the University of Luebeck

Short bio: With January 2018, Nils Rottmann is a PhD student and research scientist at the Institute for Robotics and Cognitive Systems at the University of Luebeck. In his doctoral study, with the title “Smart Sensor, Navigation and Learning Strategies for low-cost lawn care Systems”, he develops low-cost sensor systems and investigates probabilistic learning and modeling approaches. His research addresses the challenges of learning adaptive control strategies from few and sparse data and to predict and plan complex motions in dynamical systems.

He holds a master’s degree in Theoretical Mechanical Engineering from the Hamburg University of Technology, Germany. Nils Rottmann graduated with honors in December 2017 with a thesis entitled „Geometric Control and Stochastic Trajectory Planning for Underwater Robotic Systems“.

Research Interests

  • Robotics: Mobile Robotics, Sensor Development, Robot-Operating-System (ROS), Mobile Navigation, Path Planning, Complete Coverage Path Planning, Probabilistic Robotics.
  • Machine Learning: Non-Linear Regression, Graphical Models, Probabilistic Inference, Variational Inference, Gaussian Processes, Bayesian Optimization.

Contact & Quick Links

M.Sc. Nils Rottmann
Doctoral Student supervised by Univ.-Prof. Dr. Elmar Rueckert since March 2018.
Ratzeburger Allee 160,
23562 Lübeck,
Deutschland

Phone:  +49 451 3101 – 5222 
Email:   rottmann@rob.uni-luebeck.de
Web:  https://nrottmann.github.io

CV of M.Sc. Nils Rottmann
DBLP
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GitHub
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ORCID
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Publcations

2024

Lygerakis, Fotios; Dave, Vedant; Rueckert, Elmar

M2CURL: Sample-Efficient Multimodal Reinforcement Learning via Self-Supervised Representation Learning for Robotic Manipulation Proceedings Article

In: IEEE International Conference on Ubiquitous Robots (UR 2024), 2024.

Links | BibTeX

M2CURL: Sample-Efficient Multimodal Reinforcement Learning via Self-Supervised Representation Learning for Robotic Manipulation

Feith, Nikolaus; Rueckert, Elmar

Integrating Human Expertise in Continuous Spaces: A Novel Interactive Bayesian Optimization Framework with Preference Expected Improvement Proceedings Article

In: IEEE International Conference on Ubiquitous Robots (UR 2024), IEEE 2024.

Links | BibTeX

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

Feith, Nikolaus; Rueckert, Elmar

Advancing Interactive Robot Learning: A User Interface Leveraging Mixed Reality and Dual Quaternions Proceedings Article

In: IEEE International Conference on Ubiquitous Robots (UR 2024), IEEE 2024.

Links | BibTeX

Advancing Interactive Robot Learning: A User Interface Leveraging Mixed Reality and Dual Quaternions

Neubauer, Melanie; Rueckert, Elmar

Semi-Autonomous Fast Object Segmentation and Tracking Tool for Industrial Applications Proceedings Article

In: IEEE International Conference on Ubiquitous Robots (UR 2024), IEEE 2024.

Links | BibTeX

Semi-Autonomous Fast Object Segmentation and Tracking Tool for Industrial Applications

Kunavar, Tjasa; Jamšek, Marko; Avila-Mireles, Edwin Johnatan; Rueckert, Elmar; Peternel, Luka; Babič., Jan

The Effects of Different Motor Teaching Strategies on Learning a Complex Motor Task Journal Article

In: Sensors (MDPI), vol. 24, no. 4, pp. 1–17, 2024.

Links | BibTeX

The Effects of Different Motor Teaching Strategies on Learning a Complex Motor Task

Dave*, Vedant; Lygerakis*, Fotios; Rueckert, Elmar

Multimodal Visual-Tactile Representation Learning through Self-Supervised Contrastive Pre-Training Proceedings Article

In: IEEE International Conference on Robotics and Automation (ICRA 2024)., 2024, (* equal contribution).

Links | BibTeX

Multimodal Visual-Tactile Representation Learning through Self-Supervised Contrastive Pre-Training

Nwankwo, Linus; Rueckert, Elmar

The Conversation is the Command: Interacting with Real-World Autonomous Robot Through Natural Language Proceedings Article

In: ACM/IEEE International Conference on Human-Robot Interaction (HRI ’24 Companion)., IEEE 2024, (Published as late breaking results. Supplementary video: https://cloud.cps.unileoben.ac.at/index.php/s/fRE9XMosWDtJ339 ).

Links | BibTeX

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

2023

Lygerakis, Fotios; Rueckert, Elmar

CR-VAE: Contrastive Regularization on Variational Autoencoders for Preventing Posterior Collapse Proceedings Article

In: Asian Conference of Artificial Intelligence Technology (ACAIT)., IEEE, 2023.

Links | BibTeX

CR-VAE: Contrastive Regularization on Variational Autoencoders for Preventing Posterior Collapse

Yadav, Harsh; Xue, Honghu; Rudall, Yan; Bakr, Mohamed; Hein, Benedikt; Rueckert, Elmar; Nguyen, Ngoc Thinh

Deep Reinforcement Learning for Mapless Navigation of Autonomous Mobile Robot Proceedings Article

In: International Conference on System Theory, Control and Computing (ICSTCC), 2023, (October 11-13, 2023, Timisoara, Romania.).

Links | BibTeX

Deep Reinforcement Learning for Mapless Navigation of Autonomous Mobile Robot

Nwankwo, Linus; Rueckert, Elmar

Understanding why SLAM algorithms fail in modern indoor environments Proceedings Article

In: International Conference on Robotics in Alpe-Adria-Danube Region (RAAD). , pp. 186 - 194, Cham: Springer Nature Switzerland., 2023.

Abstract | Links | BibTeX

Understanding why SLAM algorithms fail in modern indoor environments

Nwankwo, Linus; Fritze, Clemens; Bartsch, Konrad; Rueckert, Elmar

ROMR: A ROS-based Open-source Mobile Robot Journal Article

In: HardwareX, vol. 15, pp. 1–29, 2023.

Abstract | Links | BibTeX

ROMR: A ROS-based Open-source Mobile Robot

Yadav, Harsh; Xue, Honghu; Rudall, Yan; Bakr, Mohamed; Hein, Benedikt; Rueckert, Elmar; Nguyen, Thinh

Deep Reinforcement Learning for Autonomous Navigation in Intralogistics Workshop

2023, (European Control Conference (ECC) Workshop, Extended Abstract.).

Abstract | Links | BibTeX

Deep Reinforcement Learning for Autonomous Navigation in Intralogistics

Keshavarz, Sahar; Vita, Petr; Rueckert, Elmar; Ortner, Ronald; Thonhauser, Gerhard

A Reinforcement Learning Approach for Real-Time Autonomous Decision-Making in Well Construction Proceedings Article

In: Society of Petroleum Engineers - SPE Symposium: Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, AIS 2023, Society of Petroleum Engineers., 2023, ISBN: 9781613999882.

Links | BibTeX

A Reinforcement Learning Approach for Real-Time Autonomous Decision-Making in Well Construction

2022

Dave, Vedant; Rueckert, Elmar

Can we infer the full-arm manipulation skills from tactile targets? Workshop

International Conference on Humanoid Robots (Humanoids 2022), 2022.

Abstract | Links | BibTeX

Can we infer the full-arm manipulation skills from tactile targets?

Xue, Honghu; Song, Rui; Petzold, Julian; Hein, Benedikt; Hamann, Heiko; Rueckert, Elmar

End-To-End Deep Reinforcement Learning for First-Person Pedestrian Visual Navigation in Urban Environments Proceedings Article

In: International Conference on Humanoid Robots (Humanoids 2022), 2022.

Abstract | Links | BibTeX

End-To-End Deep Reinforcement Learning for First-Person Pedestrian Visual Navigation in Urban Environments

Dave, Vedant; Rueckert, Elmar

Predicting full-arm grasping motions from anticipated tactile responses Proceedings Article

In: International Conference on Humanoid Robots (Humanoids 2022), 2022.

Abstract | Links | BibTeX

Predicting full-arm grasping motions from anticipated tactile responses

Herzog, Rebecca; Berger, Till M; Pauly, Martje Gesine; Xue, Honghu; Rueckert, Elmar; Munchau, Alexander; B"aumer, Tobias; Weissbach, Anne

Cerebellar transcranial current stimulation-an intraindividual comparison of different techniques Journal Article

In: Frontiers in Neuroscience, 2022.

Links | BibTeX

Cerebellar transcranial current stimulation-an intraindividual comparison of different techniques

Rottmann, Nils; Studt, Nico; Ernst, Floris; Rueckert, Elmar

ROS-Mobile: An Android™ application for the Robot Operating System Journal Article

In: Arxiv, 2022.

Links | BibTeX

ROS-Mobile: An Android™ application for the Robot Operating System

Xue, Honghu; Hein, Benedikt; Bakr, Mohamed; Schildbach, Georg; Abel, Bengt; Rueckert, Elmar

Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics Journal Article

In: Applied Sciences (MDPI), Special Issue on Intelligent Robotics, 2022, (Supplement: https://cloud.cps.unileoben.ac.at/index.php/s/Sj68rQewnkf4ppZ).

Abstract | Links | BibTeX

Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics

Leonel, Rozo*; Vedant, Dave*

Orientation Probabilistic Movement Primitives on Riemannian Manifolds Proceedings Article

In: Conference on Robot Learning (CoRL), pp. 11, 2022, (* equal contribution).

Abstract | Links | BibTeX

Orientation Probabilistic Movement Primitives on Riemannian Manifolds

2021

Denz, R.; Demirci, R.; Cansev, E.; Bliek, A.; Beckerle, P.; Rueckert, E.; Rottmann, N.

A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning Proceedings Article

In: International Conference on Advanced Robotics , pp. 7, 2021.

Links | BibTeX

A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning

Rottmann, N.; Denz, R.; Bruder, R.; Rueckert, E.

Probabilistic Approach for Complete Coverage Path Planning with low-cost Systems Proceedings Article

In: European Conference on Mobile Robots (ECMR 2021), 2021.

Links | BibTeX

Probabilistic Approach for Complete Coverage Path Planning with low-cost Systems

Xue, Honghu; Herzog, Rebecca; Berger, Till M.; Bäumer, Tobias; Weissbach, Anne; Rueckert, Elmar

Using Probabilistic Movement Primitives in analyzing human motion differences under Transcranial Current Stimulation Journal Article

In: Frontiers in Robotics and AI , vol. 8, 2021, ISSN: 2296-9144.

Abstract | Links | BibTeX

Using Probabilistic Movement Primitives in analyzing human motion differences under Transcranial Current Stimulation

Lygerakis, Fotios; Dagioglou, Maria; Karkaletsis, Vangelis

Accelerating Human-Agent Collaborative Reinforcement Learning Conference

In Proceedings of the 14th PErvasive Technologies Related to Assistive Environments Conference (PETRA '21), Association for Computing Machinery, New York, NY, USA, 90–92, 2021.

Links | BibTeX

Accelerating Human-Agent Collaborative Reinforcement Learning

Banerjee, Debapriya; Lygerakis, Fotios; Makedon, Fillia

Sequential Late Fusion Technique for Multi-modal Sentiment Analysis Conference

In Proceedings of the 14th PErvasive Technologies Related to Assistive Environments Conference (PETRA '21), Association for Computing Machinery, New York, NY, USA, 264–265. , 2021.

Links | BibTeX

Sequential Late Fusion Technique for Multi-modal Sentiment Analysis

Tanneberg, Daniel; Ploeger, Kai; Rueckert, Elmar; Peters, Jan

SKID RAW: Skill Discovery from Raw Trajectories Journal Article

In: IEEE Robotics and Automation Letters (RA-L), pp. 1–8, 2021, ISSN: 2377-3766, (© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.).

Links | BibTeX

SKID RAW: Skill Discovery from Raw Trajectories

Jamsek, Marko; Kunavar, Tjasa; Bobek, Urban; Rueckert, Elmar; Babic, Jan

Predictive exoskeleton control for arm-motion augmentation based on probabilistic movement primitives combined with a flow controller Journal Article

In: IEEE Robotics and Automation Letters (RA-L), pp. 1–8, 2021, ISSN: 2377-3766, (© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.).

Links | BibTeX

Predictive exoskeleton control for arm-motion augmentation based on probabilistic movement primitives combined with a flow controller

Cansev, Mehmet Ege; Xue, Honghu; Rottmann, Nils; Bliek, Adna; Miller, Luke E.; Rueckert, Elmar; Beckerle, Philipp

Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience Journal Article

In: Advanced Intelligent Systems, pp. 1–28, 2021.

Links | BibTeX

Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience

Kyrarini, Maria; Lygerakis, Fotios; Rajavenkatanarayanan, Akilesh; Sevastopoulos, Christos; Nambiappan, Harish Ram; Chaitanya, Kodur Krishna; Babu, Ashwin Ramesh; Mathew, Joanne; Makedon, Fillia

A Survey of Robots in Healthcare Journal Article

In: Technologies, vol. 9, iss. 8, 2021.

Links | BibTeX

 A Survey of Robots in Healthcare

2020

Akbulut, M Tuluhan; Oztop, Erhan; Seker, M Yunus; Xue, Honghu; Tekden, Ahmet E; Ugur, Emre

ACNMP: Skill Transfer and Task Extrapolation through Learning from Demonstration and Reinforcement Learning via Representation Sharing Proceedings Article

In: 2020.

Abstract | Links | BibTeX

ACNMP: Skill Transfer and Task Extrapolation through Learning from Demonstration and Reinforcement Learning via Representation Sharing

Rottmann, N.; Bruder, R.; Schweikard, A.; Rueckert, E.

Exploiting Chlorophyll Fluorescense for Building Robust low-Cost Mowing Area Detectors Proceedings Article

In: IEEE SENSORS , pp. 1–4, 2020.

Links | BibTeX

Exploiting Chlorophyll Fluorescense for Building Robust low-Cost Mowing Area Detectors

Rottmann, N.; Kunavar, T.; Babič, J.; Peters, J.; Rueckert, E.

Learning Hierarchical Acquisition Functions for Bayesian Optimization Proceedings Article

In: International Conference on Intelligent Robots and Systems (IROS’ 2020), 2020.

Links | BibTeX

Learning Hierarchical Acquisition Functions for Bayesian Optimization

Rottmann, N.; Bruder, R.; Xue, H.; Schweikard, A.; Rueckert, E.

Parameter Optimization for Loop Closure Detection in Closed Environments Proceedings Article

In: Workshop Paper at the International Conference on Intelligent Robots and Systems (IROS), pp. 1–8, 2020.

Links | BibTeX

Parameter Optimization for Loop Closure Detection in Closed Environments

Rottmann, N.; Bruder, R.; Schweikard, A.; Rueckert, E.

A novel Chlorophyll Fluorescence based approach for Mowing Area Classification Journal Article

In: IEEE Sensors Journal, 2020.

Links | BibTeX

A novel Chlorophyll Fluorescence based approach for Mowing Area Classification

Tanneberg, Daniel; Rueckert, Elmar; Peters, Jan

Evolutionary training and abstraction yields algorithmic generalization of neural computers Journal Article

In: Nature Machine Intelligence, pp. 1–11, 2020.

Links | BibTeX

Evolutionary training and abstraction yields algorithmic generalization of neural computers

Tolga-Can Çallar, Elmar Rueckert; Böttger, Sven

Efficient Body Registration Using Single-View Range Imaging and Generic Shape Templates Proceedings Article

In: 54th Annual Conference of the German Society for Biomedical Engineering (BMT 2020), 2020.

Links | BibTeX

Efficient Body Registration Using Single-View Range Imaging and Generic Shape Templates

Xue, H.; Boettger, S.; Rottmann, N.; Pandya, H.; Bruder, R.; Neumann, G.; Schweikard, A.; Rueckert, E.

Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks Proceedings Article

In: International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI’ 2020), 2020.

Links | BibTeX

Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks

Lygerakis, Fotios; Tsitos, Athanasios C; Dagioglou, Maria; Makedon, Fillia; Karkaletsis, Vangelis

Evaluation of 3D markerless pose estimation accuracy using openpose and depth information from a single RGB-D camera Conference

In Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '20), Article 75, 1–6 Association for Computing Machinery, New York, NY, USA, 2020.

Links | BibTeX

Evaluation of 3D markerless pose estimation accuracy using openpose and depth information from a single RGB-D camera

Cartoni, E.; Mannella, F.; Santucci, V. G.; Triesch, J.; Rueckert, E.; Baldassarre, G.

REAL-2019: Robot open-Ended Autonomous Learning competition Journal Article

In: Proceedings of Machine Learning Research, vol. 123, pp. 142-152, 2020, (NeurIPS 2019 Competition and Demonstration Track).

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REAL-2019: Robot open-Ended Autonomous Learning competition

Diakoloukas, Vassilios; Lygerakis, Fotios; Lagoudakis, Michail G; Kotti, Margarita

Variational Denoising Autoencoders and Least-Squares Policy Iteration for Statistical Dialogue Manager Journal Article

In: IEEE Signal Processing Letters , vol. 27, pp. 960-964, 2020.

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Variational Denoising Autoencoders and Least-Squares Policy Iteration for Statistical Dialogue Manager

2019

Lygerakis, Fotios; Diakoloulas, Vassilios; Lagoudakis, Michail; Kotti, Margarita

Robust Belief State Space Representation for Statistical Dialogue Managers Using Deep Autoencoders Conference

2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2019.

Links | BibTeX

Robust Belief State Space Representation for Statistical Dialogue Managers Using Deep Autoencoders

Stark, Svenja; Peters, Jan; Rueckert, Elmar

Experience Reuse with Probabilistic Movement Primitives Proceedings Article

In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), 2019., 2019.

Links | BibTeX

Experience Reuse with Probabilistic Movement Primitives

Boettger, S.; Callar, T. C.; Schweikard, A.; Rueckert, E.

Medical robotics simulation framework for application-specific optimal kinematics Proceedings Article

In: Current Directions in Biomedical Engineering 2019, pp. 1–5, 2019.

Links | BibTeX

Medical robotics simulation framework for application-specific optimal kinematics

Rottmann, N.; Bruder, R.; Schweikard, A.; Rueckert, E.

Loop Closure Detection in Closed Environments Proceedings Article

In: European Conference on Mobile Robots (ECMR 2019), 2019, ISBN: 978-1-7281-3605-9.

Links | BibTeX

Loop Closure Detection in Closed Environments

Rottmann, N.; Bruder, R.; Schweikard, A.; Rueckert, E.

Cataglyphis ant navigation strategies solve the global localization problem in robots with binary sensors Proceedings Article

In: Proceedings of International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS), Prague, Czech Republic , 2019, ( February 22-24, 2019).

Links | BibTeX

Cataglyphis ant navigation strategies solve the global localization problem in robots with binary sensors

Rueckert, Elmar; Jauer, Philipp; Derksen, Alexander; Schweikard, Achim

Dynamic Control Strategies for Cable-Driven Master Slave Robots Proceedings Article

In: Keck, Tobias (Ed.): Proceedings on Minimally Invasive Surgery, Luebeck, Germany, 2019, (January 24-25, 2019).

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Dynamic Control Strategies for Cable-Driven Master Slave Robots

Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar

Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks Journal Article

In: Neural Networks - Elsevier, vol. 109, pp. 67-80, 2019, ISBN: 0893-6080, (Impact Factor of 7.197 (2017)).

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Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks

2018

Gondaliya, Kaushikkumar D.; Peters, Jan; Rueckert, Elmar

Learning to Categorize Bug Reports with LSTM Networks Proceedings Article

In: Proceedings of the International Conference on Advances in System Testing and Validation Lifecycle (VALID)., pp. 6, XPS (Xpert Publishing Services), Nice, France, 2018, ISBN: 978-1-61208-671-2, ( October 14-18, 2018).

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Learning to Categorize Bug Reports with LSTM Networks

Sosic, Adrian; Zoubir, Abdelhak M.; Rueckert, Elmar; Peters, Jan; Koeppl, Heinz

Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling Journal Article

In: Journal of Machine Learning Research (JMLR), vol. 19, no. 69, pp. 1-45, 2018.

Links | BibTeX

Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling

Paraschos, Alexandros; Rueckert, Elmar; Peters, Jan; Neumann, Gerhard

Probabilistic Movement Primitives under Unknown System Dynamics Journal Article

In: Advanced Robotics (ARJ), vol. 32, no. 6, pp. 297-310, 2018.

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Probabilistic Movement Primitives under Unknown System Dynamics

2017

Rueckert, Elmar; Nakatenus, Moritz; Tosatto, Samuele; Peters, Jan

Learning Inverse Dynamics Models in O(n) time with LSTM networks Proceedings Article

In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017.

Links | BibTeX

Learning Inverse Dynamics Models in O(n) time with LSTM networks

Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar

Efficient Online Adaptation with Stochastic Recurrent Neural Networks Proceedings Article

In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017.

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Efficient Online Adaptation with Stochastic Recurrent Neural Networks

Stark, Svenja; Peters, Jan; Rueckert, Elmar

A Comparison of Distance Measures for Learning Nonparametric Motor Skill Libraries Proceedings Article

In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017.

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A Comparison of Distance Measures for Learning Nonparametric Motor Skill Libraries

Thiem, Simon; Stark, Svenja; Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar

Simulation of the underactuated Sake Robotics Gripper in V-REP Proceedings Article

In: Workshop at the International Conference on Humanoid Robots (HUMANOIDS), 2017.

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Simulation of the underactuated Sake Robotics Gripper in V-REP

Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar

Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals Proceedings Article

In: Proceedings of the Conference on Robot Learning (CoRL), 2017.

Links | BibTeX

Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals

2016

Tanneberg, Daniel; Paraschos, Alexandros; Peters, Jan; Rueckert, Elmar

Deep Spiking Networks for Model-based Planning in Humanoids Proceedings Article

In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2016.

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Deep Spiking Networks for Model-based Planning in Humanoids

Azad, Morteza; Ortenzi, Valerio; Lin, Hsiu-Chin; Rueckert, Elmar; Mistry, Michael

Model Estimation and Control of Complaint Contact Normal Force Proceedings Article

In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2016.

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Model Estimation and Control of Complaint Contact Normal Force

Rueckert, Elmar; Camernik, Jernej; Peters, Jan; Babic, Jan

Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control Journal Article

In: Nature Publishing Group: Scientific Reports, vol. 6, no. 28455, 2016.

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Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control

Rueckert, Elmar; Kappel, David; Tanneberg, Daniel; Pecevski, Dejan; Peters, Jan

Recurrent Spiking Networks Solve Planning Tasks Journal Article

In: Nature Publishing Group: Scientific Reports, vol. 6, no. 21142, 2016.

Links | BibTeX

Recurrent Spiking Networks Solve Planning Tasks

Kohlschuetter, Jan; Peters, Jan; Rueckert, Elmar

Learning Probabilistic Features from EMG Data for Predicting Knee Abnormalities Proceedings Article

In: Proceedings of the XIV Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON), 2016.

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Learning Probabilistic Features from EMG Data for Predicting Knee Abnormalities

Modugno, Valerio; Neumann, Gerhard; Rueckert, Elmar; Oriolo, Giuseppe; Peters, Jan; Ivaldi, Serena

Learning soft task priorities for control of redundant robots Proceedings Article

In: Proceedings of the International Conference on Robotics and Automation (ICRA), 2016.

Links | BibTeX

Learning soft task priorities for control of redundant robots

Sharma, David; Tanneberg, Daniel; Grosse-Wentrup, Moritz; Peters, Jan; Rueckert, Elmar

Adaptive Training Strategies for BCIs Proceedings Article

In: Cybathlon Symposium, 2016.

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Adaptive Training Strategies for BCIs

Weber, Paul; Rueckert, Elmar; Calandra, Roberto; Peters, Jan; Beckerle, Philipp

A Low-cost Sensor Glove with Vibrotactile Feedback and Multiple Finger Joint and Hand Motion Sensing for Human-Robot Interaction Proceedings Article

In: Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2016.

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A Low-cost Sensor Glove with Vibrotactile Feedback and Multiple Finger Joint and Hand Motion Sensing for Human-Robot Interaction

2015

Calandra, Roberto; Ivaldi, Serena; Deisenroth, Marc; Rueckert, Elmar; Peters, Jan

Learning Inverse Dynamics Models with Contacts Proceedings Article

In: Proceedings of the International Conference on Robotics and Automation (ICRA), 2015.

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Learning Inverse Dynamics Models with Contacts

Rueckert, Elmar; Mundo, Jan; Paraschos, Alexandros; Peters, Jan; Neumann, Gerhard

Extracting Low-Dimensional Control Variables for Movement Primitives Proceedings Article

In: Proceedings of the International Conference on Robotics and Automation (ICRA), 2015.

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Extracting Low-Dimensional Control Variables for Movement Primitives

Paraschos, Alexandros; Rueckert, Elmar; Peters, Jan; Neumann, Gerhard

Model-Free Probabilistic Movement Primitives for Physical Interaction Proceedings Article

In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), 2015.

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Model-Free Probabilistic Movement Primitives for Physical Interaction

Rueckert, Elmar; Lioutikov, Rudolf; Calandra, Roberto; Schmidt, Marius; Beckerle, Philipp; Peters, Jan

Low-cost Sensor Glove with Force Feedback for Learning from Demonstrations using Probabilistic Trajectory Representations Proceedings Article

In: ICRA 2015 Workshop on Tactile and force sensing for autonomous compliant intelligent robots, 2015.

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

2014

Rueckert, Elmar

Biologically inspired motor skill learning in robotics through probabilistic inference PhD Thesis

Technical University Graz, 2014.

Links | BibTeX

Biologically inspired motor skill learning in robotics through probabilistic inference

Rueckert, Elmar; Mindt, Max; Peters, Jan; Neumann, Gerhard

Robust Policy Updates for Stochastic Optimal Control Proceedings Article

In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2014.

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Robust Policy Updates for Stochastic Optimal Control

2013

Rueckert, Elmar; d'Avella, Andrea

Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems Journal Article

In: Frontiers in Computational Neuroscience, vol. 7, no. 138, 2013.

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Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems

Rueckert, Elmar; Neumann, Gerhard; Toussaint, Marc; Maass, Wolfgang

Learned graphical models for probabilistic planning provide a new class of movement primitives Journal Article

In: Frontiers in Computational Neuroscience, vol. 6, no. 97, 2013.

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 Learned graphical models for probabilistic planning provide a new class of movement primitives

Rueckert, Elmar; d'Avella, Andrea

Learned Muscle Synergies as Prior in Dynamical Systems for Controlling Bio-mechanical and Robotic Systems Proceedings Article

In: Abstracts of Neural Control of Movement Conference (NCM), Conference Talk, pp. 27–28, 2013.

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Learned Muscle Synergies as Prior in Dynamical Systems for Controlling Bio-mechanical and Robotic Systems

2012

Rueckert, Elmar; Neumann, Gerhard

Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation Journal Article

In: Artificial Life, vol. 19, no. 1, 2012.

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Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation

2011

Rueckert, Elmar; Neumann, Gerhard

A study of Morphological Computation by using Probabilistic Inference for Motor Planning Proceedings Article

In: Proceedings of the 2nd International Conference on Morphological Computation (ICMC), pp. 51–53, 2011.

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A study of Morphological Computation by using Probabilistic Inference for Motor Planning

2010

Rueckert, Elmar

Simultaneous localisation and mapping for mobile robots with recent sensor technologies Masters Thesis

Technical University Graz, 2010.

Links | BibTeX

Simultaneous localisation and mapping for mobile robots with recent sensor technologies

0000

Dave, Vedant; Lygerakis, Fotios; Rueckert, Elmar

Multimodal Visual-Tactile Representation Learning through Self-Supervised Contrastive Pre-Training Proceedings Forthcoming

Forthcoming, (Website: https://sites.google.com/view/mvitac/home).

Abstract | Links | BibTeX