A crucial design decision for any robot learning pipeline is the choice ...
We address a benchmark task in agile robotics: catching objects thrown a...
Training complex machine learning (ML) architectures requires a compute ...
We present a differentiable formulation of rigid-body contact dynamics f...
We propose a framework to enable multipurpose assistive mobile robots to...
Despite decades of research, existing navigation systems still face
real...
Though robot learning is often formulated in terms of discrete-time Mark...
We present a framework for bi-level trajectory optimization in which a
s...
We propose a novel framework for learning stabilizable nonlinear dynamic...
Modern Machine Translation (MT) systems perform consistently well on cle...
In the pursuit of real-time motion planning, a commonly adopted practice...
We propose a novel framework for learning stabilizable nonlinear dynamic...
The literature on Inverse Reinforcement Learning (IRL) typically assumes...