Passalis, N. (author), Pedrazzi, S. (author), Babuska, R. (author), Burgard, W. (author), Ferro, F. (author), Gabbouj, M. (author), Kayacan, E. (author), Kober, J. (author), Pieters, RRGM (author), Valada, A. (author) Existing Deep Learning (DL) frameworks typically do not provide ready-to-use solutions for robotics, where very specific learning, reasoning, and embodiment problems exist. Their relatively steep learning curve and the different methodologies employed by DL compared to traditional approaches, along with the high complexity of DL models, which...
conference paper 2022