25 citations · 53 across the 18 of their papers we have counts for
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cs.RO2017★ 25 cited
An Inversion-Based Learning Approach for Improving Impromptu Trajectory Tracking of Robots with Non-Minimum Phase Dynamics
Siqi Zhou, Mohamed K. Helwa, Angela P. Schoellig
This paper presents a learning-based approach for impromptu trajectory tracking for non-minimum phase systems, i.e., systems with unstable inverse dynamics. Inversion-based feedfor…
cs.RO2017★ 6 cited
Design of Deep Neural Networks as Add-on Blocks for Improving Impromptu Trajectory Tracking
Siqi Zhou, Mohamed K. Helwa, Angela P. Schoellig
This paper introduces deep neural networks (DNNs) as add-on blocks to baseline feedback control systems to enhance tracking performance of arbitrary desired trajectories. The DNNs…