8 citations · 9 across the 5 of their papers we have counts for
5 papers
XRZero-G0: Pushing the Frontier of Dexterous Robotic Manipulation with Interfaces, Quality and Ratios
James Wang, Primo Pu, Zephyr Fung +19
The acquisition of high-quality, action-aligned demonstration data remains a fundamental bottleneck in scaling foundation models for dexterous robot manipulation. Although robot-fr…
DiLQR: Differentiable Iterative Linear Quadratic Regulator via Implicit Differentiation
Shuyuan Wang, Philip D. Loewen, Michael Forbes +2
While differentiable control has emerged as a powerful paradigm combining model-free flexibility with model-based efficiency, the iterative Linear Quadratic Regulator (iLQR) remain…
Guiding Reinforcement Learning with Incomplete System Dynamics
Shuyuan Wang, Jingliang Duan, Nathan P. Lawrence +4
Model-free reinforcement learning (RL) is inherently a reactive method, operating under the assumption that it starts with no prior knowledge of the system and entirely depends on…
Deep Hankel matrices with random elements
Nathan P. Lawrence, Philip D. Loewen, Shuyuan Wang +2
Willems' fundamental lemma enables a trajectory-based characterization of linear systems through data-based Hankel matrices. However, in the presence of measurement noise, we ask:…
Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior
Nathan P. Lawrence, Philip D. Loewen, Shuyuan Wang +2
We propose a framework for the design of feedback controllers that combines the optimization-driven and model-free advantages of deep reinforcement learning with the stability guar…