I. Fürst-Walter, A. Nappi, T. Harbaum and J. Becker, "Design Space Exploration on Efficient and Accurate Human Pose Estimation from Sparse IMU-Sensing", in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
J. Gao, Z. Tao, N. Jaquier and T. Asfour, "K-VIL: Keypoint-based Visual Imitation Learning", in IEEE Transactions on Robotics, vol. 39, no. 5, pp. 3888-3908, 2023
S. Helmstetter and S. Matthiesen, "Human Posture Estimation: A Systematic Review on Force-Based Methods - Analyzing the Differences in Required Expertise and Result Benefits for Their Utilization", in MDPI Sensors, vol. 23, no. 21, Art.-No. 8997, 2023
N. Hemken, F. Jacob, F. Peller-Konrad, R. Kartmann, T. Asfour and H. Hartenstein, "Poster: How to Raise a Robot - Beyond Access Control Constraints in Assistive Humanoid Robots, in ACM Symposium on Access Control Models and Technologies (SACMAT), pp. 55-57, 2023
M. Herzog, F. C. Krafft, B. J. Stetter, A. d'Avella, L. H. Sloot and T. Stein, "Rollator usage lets young individualy switch movement strategies in sit-to-stand and stand-to-sit tasks", in Scientific Reports, vol. 13, no. 1, art.-no. 1, 2023
R. Kartmann and T. Asfour, "Interactive and Incremental Learning of Spatial Object Relations from Human Demonstrations", in Frontiers in Robotics and AI, vol. 10, pp. 1-14, 2023
C. Klas and T. Asfour, "Reaching Torque-Velocity Profiles of Human Muscles: The Adaptive Cycloidal Linear Drive", in IEEE/ASME Transactions on Mechatronics, pp.1-10, 2023
H. Klein, N. Jaquier, A. Meixner and T. Asfour, "On the Design of Region-Avoiding Metrics for Collision-Safe Motion Generation on Riemannian Manifolds", in IEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
M. Li, O. Celik, P. Becker, D. Blessing, R. Lioutikov and G. Neumann, "Curriculum-Based Imitation of Versatile Skills", in IEEE International Conference on Robotics and Automation (ICRA), pp. 2951-2957, 2023.
T. Möller, F. Möhler, J. Krell-Rösch, M. Dežman, C. Marquardt, T. Asfour, T. Stein and A. Woll, "Use of Lower Limb Exoskeletons as an Assessment Tool for Human Motor Performance: A Systematic Review," in Sensors, vol. 23, no. 6, art.-no. 3032, 2023
T.-B. Nguyen, L. D. Minh Nhat, Q. Minh Nguyen, Q. Truong Do, C. Mai Luong and A. Waibel, "AdapITN: a Fast, Reliable, and Dynamic Adaptive Inverse Text Normalization," presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023. URL: Binh_ICASSP-2023_AdapITN.pdf
N. Riedel, M. Herzog, T. Stein and B. Deml, "Effects of modified leg mechanics on cognitive performance and workload during dual-task walking", presented at the Human Factors and Ergonomics Society Europe Chapter Annual Conference, pp. 197-211, 2023
Z. Zhong, D. Schneider, M. Voit, R. Stiefelhagen, and J. Beyerer, “Anticipative Feature Fusion Transformer for Multi-Modal Action Anticipation,” in Proceedings of the IEEE/CVF winter conference on applications of computer vision (WACV), 2023. URL: https://openaccess.thecvf.com/content/WACV2023/html/Zhong_Anticipative_Feature_Fusion_Transformer_for_Multi-Modal_Action_Anticipation_WACV_2023_paper.html
S. Bayreuther, F. Jacob, M. Grotz, R. Kartmann, F. Peller-Konrad, F. Paus, H. Hartenstein and T. Asfour, “Combining Task Planning and Activity-Centric Access Control for Assistive Humanoid Robots,” in Symposium on Access Control Models and Technologies (SACMAT), 2022. DOI: 10.1145/3532105.3535018.
M. Dežman, T. Asfour, A. Ude, and A. Gams, “Mechanical design and friction modelling of a cable-driven upper-limb exoskeleton,” in Mechanism and Machine Theory, 2022, vol. 171, p. 104746. DOI: 10.1016/j.mechmachtheory.2022.104746.
C. Dreher and T. Asfour, "Learning Temporal Task Models from Human Bimanual Demonstrations", in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022.
N. Freymuth, N. Schreiber, P. Becker, A. Taranovic and G. Neumann, "Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors", in Conference on Robot Learning (CoRL), 2022.
S. Helmstetter, S. Sutschet, C. Sprengler, F. Möhler, M. Herzog, S. Matthiesen, T. Stein, “Parametric scaling of a Lower Limb Model according to body height in OpenSim,” in International Virtual Conference on Human Interaction and Emerging Technologies (IHIET), 2022.
F. Jacob, S. Bayreuther, and H. Hartenstein, “On CRDTs in byzantine environments,” SICHERHEIT, 2022.
N. Jaquier and T. Asfour, “Riemannian geometry as a unifying theory for robot motion learning and control,” in International Symposium on Robotics Research (ISRR), 2022. URL: https://h2t.anthropomatik.kit.edu/pdf/Jaquier2022b.pdf
N. Jaquier, Y. Zhou, J. Starke, and T. Asfour, “Learning to sequence and blend robot skills via differentiable optimization,” IEEE Robotics and Automation Letters (RA-L), vol. 7, no. 3, pp. 8431–8438, 2022.
C. Klas and T. Asfour, “A Compact, Lightweight and Singularity-Free Wrist Joint Mechanism for Humanoid Robots,” presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022. URL: https://h2t.anthropomatik.kit.edu/pdf/Klas2022.pdf
H. Klein, N. Jaquier, A. Meixner, and T. Asfour, “A Riemannian Take on Human Motion Analysis and Retargeting,” presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022.
F. Krebs and T. Asfour, “A Bimanual Manipulation Taxonomy,” in IEEE Robotics and Automation Letters (RA-L), 2022. DOI: 10.1109/LRA.2022.3196158.
F. Kreß, J. Hoefer, T. Hotfilter, I. Walter, E. El Mahdi, T. Harbaum, J. Becker, “Automated search for deep neural network inference partitioning on embedded FPGA,” presented at the Machine learning and principles and practice of knowledge discovery in databases (ECML PKDD), 2022.
Z. Marinov, A. Roitberg, D. Schneider, and R. Stiefelhagen, “ModSelect: Automatic modality selection for synthetic-to-real domain generalization,” in European Conference on Computer Vision (ECCV) Workshops, 2022.
Z. Marinov, D. Schneider, A. Roitberg, and R. Stiefelhagen, “Multimodal Generation of Novel Action Appearances for Synthetic-to-Real Recognition of Activities of Daily Living,” presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022.
C. Marquardt, P. Weiner, M. Dežman, and T. Asfour, “Embedded barometric pressure sensor unit for force myography in exoskeletons,” presented at the IEEE/RAS International Conference on Humanoid Robots (Humanoids), 2022.
T. Möller, J. Krell-Roesch, A. Woll, and T. Stein, “Effects of Upper-Limb Exoskeletons Designed for Use in the Working Environment - A Literature Review,” in Frontiers in Robotics and AI, 2022, p. 82. DOI: 10.3389/frobt.2022.858893
T. Möller, F. Möhler, J. Krell-Rösch, T. Stein and A. Woll, "Lower limb exoskeletons as an assessment tool for motor performance: A systematic review", in Jahrestagung der dvs-Sektion Sportmotorik, 2022.
T. Röddiger et al., “Sensing with Earables: A Systematic Literature Review and Taxonomy of Phenomena,” Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 6, no. 3, Sep. 2022, DOI: 10.1145/3550314.
M. P. Sartorius and P. von Both, "Rule-Based Design for the integration of Humanoid Assistance Robotics into the Living Environment of Senior Citizens", in Co-Creating the Future: Inclusion in and through Design (eCAADe), pp. 367-376, 2022.
D. Schneider, S. Sarfraz, A. Roitberg, and R. Stiefelhagen, “Pose-based contrastive learning for domain agnostic activity representations,” in CVPR workshop on robustness in sequential data (ROSE), 2022. URL: https://openaccess.thecvf.com/content/CVPR2022W/RoSe/html/Schneider_Pose-Based_Contrastive_Learning_for_Domain_Agnostic_Activity_Representations_CVPRW_2022_paper.html
P. Weiner, J. Starke, S. Rader, F. Hundhausen, and T. Asfour, “Designing Prosthetic Hands with Embodied Intelligence: The KIT Prosthetic Hands,” in Frontiers in Neurorobotics, 2022, vol. 16. DOI: 10.3389/fnbot.2022.815716.
H. Zhao, A. Scholz, M. Beigl, S. Ni, S. A. Singaraju and J. Aghassi-Hagmann, "Printed Electrodermal Activity Sensor with Optimized Filter for Stress Detection", in ACM International Symposium on Wearable Computers, pp. 112-114, 2022
H. Zhao, Y. Zhou, T. Riedel, M. Hefenbrock and M. Beigl, "Improving Human Activity Recognition Models by Learnable Sparse Wavelet Layer", in ACM International Symposium on Wearable Computers, pp. 84-88, 2022
Y. Zhou, H. Zhao, Y. Huang, M. Hefenbrock, T. Riedel, and M. Beigl, “TinyHAR: A Lightweight Deep Learning Model Designed for Human Activity Recognition,” presented at the International Symposium on Wearable Computers (ISWC), 2022.
N. Jaquier, V. Borovitskiy, A. Smolensky, A. Terenin, T. Asfour, and L. Rozo, “Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels,” in Conference on Robot Learning, 2021, vol. 5, pp. 794–805. URL: https://proceedings.mlr.press/v164/jaquier22a.html
A. Roitberg, D. Schneider, A. Djamal, C. Seibold, S. Reiß, and R. Stiefelhagen, “Let’s play for action: Recognizing activities of daily living by learning from life simulation video games,” in IEEE/RSJ international conference on intelligent robots and systems (IROS), 2021, pp. 8563-8569. DOI: 10.1109/IROS51168.2021.9636381.
J. Starke, M. Keller, and A. Asfour, “Temporal Force Synergies in Human Grasping,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021, pp. 3963–3970. DOI: 10.1109/IROS51168.2021.9636223.
P. Weiner, F. Hundhausen, R. Grimm, and T. Asfour, “Detecting Grasp Phases and Adaption of Object-Hand Interaction Forces of a Soft Humanoid Hand Based on Tactile Feedback,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021, pp. 3979–3986. DOI: 10.1109/IROS51168.2021.9636484.
Z. Weng, F. Paus, A. Varava, H. Yin, T. Asfour, and D. Kragic, “Graph-based Task-specific Prediction Models for Interactions between Deformable and Rigid Objects,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021, pp. 5741–5748. DOI: 10.1109/IROS51168.2021.9636660.