3 citations · 4 across the 8 of their papers we have counts for
3 papers · 1 filter
Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery
Amin Abyaneh, Mahrokh G. Boroujeni, Hsiu-Chin Lin +1
Imitation learning is a data-driven approach to learning policies from expert behavior, but it is prone to unreliable outcomes in out-of-sample (OOS) regions. While previous resear…
Single-Shot Learning of Stable Dynamical Systems for Long-Horizon Manipulation Tasks
Alexandre St-Aubin, Amin Abyaneh, Hsiu-Chin Lin
Mastering complex sequential tasks continues to pose a significant challenge in robotics. While there has been progress in learning long-horizon manipulation tasks, most existing a…
Globally Stable Neural Imitation Policies
Amin Abyaneh, Mariana Sosa Guzmán, Hsiu-Chin Lin
Imitation learning presents an effective approach to alleviate the resource-intensive and time-consuming nature of policy learning from scratch in the solution space. Even though t…