24 citations · 24 across the 2 of their papers we have counts for
2 papers
cs.RO2024
Context-Based Echo State Networks with Prediction Confidence for Human-Robot Shared Control
Negin Amirshirzad, Mehmet Arda Eren, Erhan Oztop
In this paper, we propose a novel lightweight learning from demonstration (LfD) model based on reservoir computing that can learn and generate multiple movement trajectories with p…
cs.RO2020★ 24 cited
DeepSym: Deep Symbol Generation and Rule Learning from Unsupervised Continuous Robot Interaction for Planning
Alper Ahmetoglu, M. Yunus Seker, Justus Piater +2
We propose a novel general method that finds action-grounded, discrete object and effect categories and builds probabilistic rules over them for non-trivial action planning. Our ro…