M. Rosenfelder, H. Ebel, and P. Eberhard. Dataset, (2023)Related to: Rosenfelder, M., Ebel, H., Eberhard, P. (2023). Force-based organization and control scheme for the non-prehensile cooperative transportation of objects. Robotica, pp. 1-14, 2023. doi: 10.1017/S0263574723001704.
L. Mehl, J. Schmalfuss, A. Jahedi, Y. Nalivayko, and A. Bruhn. Dataset, (2023)Related to: Lukas Mehl, Jenny Schmalfuss, Azin Jahedi, Yaroslava Nalivayko, Andrés Bruhn: Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo. Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023. arXiv: 2303.01943.
M. Rosenfelder, H. Ebel, and P. Eberhard. Dataset, (2023)Related to: Rosenfelder, M., Ebel, H., Eberhard, P. (2023). A Force-Based Formation Synthesis Approach for the Cooperative Transportation of Objects. In: Petrič, T., Ude, A., Žlajpah, L. (eds) Advances in Service and Industrial Robotics. RAAD 2023. Mechanisms and Machine Science, vol 135. Springer, Cham. doi: 10.1007/978-3-031-32606-6_37.
D. Lee, F. Weinhardt, J. Hommel, H. Class, and H. Steeb. Dataset, (2023)Related to: Lee, D., Weinhardt, F., Hommel, J., Piotrovski, J., Class, H., and Steeb, H. (2022). Machine Learning assists in increasing the time resolution of X-Ray Computed Tomography applied to mineral precipitation on porous media. Scientific Reports, to be submitted.