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Model estimation and control of compliant contact normal force
Azad, M., Ortenzi, V., Lin, H. C., Rueckert, E. & Mistry, M., 30 Dez. 2016, IEEE-RAS International Conference on Humanoid Robots. S. 442-447 6 S. (IEEE-RAS International Conference on Humanoid Robots).
Publikationen: Beitrag in Buch/Bericht/Konferenzband › Beitrag in Konferenzband
Medical robotics simulation framework for application-specific optimal kinematics
Böttger, S., Çallar, T. C., Schweikard, A. & Rückert, E., 18 Sept. 2019, in: Current directions in biomedical engineering. 5.2019, 1, S. 145-148 4 S.
Publikationen: Beitrag in Fachzeitschrift › Artikel › Forschung › (peer-reviewed)
Veröffentlicht
Learning inverse dynamics models with contacts
Calandra, R., Ivaldi, S., Deisenroth, M. P., Rueckert, E. & Peters, J., 29 Juni 2015, in: Proceedings / IEEE International Conference on Robotics and Automation. 2015-June, June, S. 3186-3191 6 S., 7139638.
Publikationen: Beitrag in Fachzeitschrift › Konferenzartikel › (peer-reviewed)
Efficient Body Registration Using Single-View Range Imaging and Generic Shape Templates
Çallar, T. C., Rueckert, E. & Böttger, S., 1 Sept. 2020, in: Current directions in biomedical engineering. 6.2020, 3, 4 S., 20203031.
Publikationen: Beitrag in Fachzeitschrift › Artikel › Forschung › (peer-reviewed)
Veröffentlicht
Interactive Human–Robot Skill Transfer: A Review of Learning Methods and User Experience
Cansev, M. E., Xue, H., Rottmann, N., Bliek, A., Miller, L. E., Rückert, E. & Beckerle, P., 6 Mai 2021, in: Advanced Intelligent Systems. 3.2021, 7, 11 S., 2000247.
Publikationen: Beitrag in Fachzeitschrift › Artikel › Forschung › (peer-reviewed)
Veröffentlicht
REAL-2019: Robot open-Ended Autonomous Learning competition
Cartoni, E., Mannella, F., Santucci, V. G., Triesch, J., Rückert, E. & Baldassarre, G., 2019, Proceedings of Machine Learning Research: 3rd Annual Conference on Neural Information Processing Systems, NeurIPS 2019. Band 123.2019. S. 142-152 11 S. (Proceedings of Machine Learning Research).
Publikationen: Beitrag in Buch/Bericht/Konferenzband › Beitrag in Konferenzband
Veröffentlicht
Multimodal Visual-Tactile Representation Learning through Self-Supervised Contrastive Pre-Training
Dave, V., Lygerakis, F. & Rückert, E., 28 Jan. 2024, in: Proceedings / IEEE International Conference on Robotics and Automation.
Publikationen: Beitrag in Fachzeitschrift › Konferenzartikel › (peer-reviewed)
Veröffentlicht
Predicting full-arm grasping motions from anticipated tactile responses
Dave, V. & Rueckert, E., 26 Sept. 2022, IEEE-RAS International Conference on Humanoid Robots. (IEEE-RAS International Conference on Humanoid Robots).
Publikationen: Beitrag in Buch/Bericht/Konferenzband › Beitrag in Konferenzband
Veröffentlicht
Can we infer the full-arm manipulation skills from tactile targets?
Dave, V. & Rückert, E., 26 Sept. 2022, IEEE-RAS International Conference on Humanoid Robots. (IEEE-RAS International Conference on Humanoid Robots).
Publikationen: Beitrag in Buch/Bericht/Konferenzband › Beitrag in Konferenzband
Veröffentlicht
A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning
Denz, R., Demirci, R., Cansev, M. E., Bliek, A., Beckerle, P., Rueckert, E. & Rottmann, N., 6 Dez. 2021, in: Proceedings of the International Conference on Advanced Robotics. S. 1109-1115 7 S.
Publikationen: Beitrag in Fachzeitschrift › Konferenzartikel › (peer-reviewed)

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Forschungsportal

Publikationen

Model estimation and control of compliant contact normal force

Medical robotics simulation framework for application-specific optimal kinematics

Learning inverse dynamics models with contacts

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

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

REAL-2019: Robot open-Ended Autonomous Learning competition

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

Predicting full-arm grasping motions from anticipated tactile responses

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

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

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