activity
20222024
most citedA Learn-and-Control Strategy for Jet-Based Additive Manufacturing

7 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2024

Robotic Wire Arc Additive Manufacturing with Variable Height Layers

John Marcotte, Sandipan Mishra, John T. Wen

Robotic wire arc additive manufacturing has been widely adopted due to its high deposition rates and large print volume relative to other metal additive manufacturing processes. Fo…

eess.SY2024

Generalized two-point visual control model of human steering for accurate state estimation

Rene Mai, Katherine Sears, Grace Roessling +2

We derive and validate a generalization of the two-point visual control model, an accepted cognitive science model for human steering behavior. The generalized model is needed as c…

cs.LG20241 cited

Adaptive Primal-Dual Method for Safe Reinforcement Learning

Weiqin Chen, James Onyejizu, Long Vu +5

Primal-dual methods have a natural application in Safe Reinforcement Learning (SRL), posed as a constrained policy optimization problem. In practice however, applying primal-dual m…

eess.SY2023

Control-Oriented Modeling and Layer-to-Layer Spatial Control of Powder Bed Fusion Processes

Xin Wang, Bumsoo Park, Robert G. Landers +2

Powder Bed Fusion (PBF) is an important Additive Manufacturing (AM) process that is seeing widespread utilization. However, due to inherent process variability, it is still very co…

eess.SY20227 cited

A Learn-and-Control Strategy for Jet-Based Additive Manufacturing

Uduak Inyang-Udoh, Alvin Chen, Sandipan Mishra

In this paper, we develop a predictive geometry control framework for jet-based additive manufacturing (AM) based on a physics-guided recurrent neural network (RNN) model. Because…