12 citations · 33 across the 13 of their papers we have counts for
6 papers · 1 filter
Active Learning of Dynamics Using Prior Domain Knowledge in the Sampling Process
Kevin S. Miller, Adam J. Thorpe, Ufuk Topcu
We present an active learning algorithm for learning dynamics that leverages side information by explicitly incorporating prior domain knowledge into the sampling process. Our prop…
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control
Adam J. Thorpe, Cyrus Neary, Franck Djeumou +2
Data-driven control algorithms use observations of system dynamics to construct an implicit model for the purpose of control. However, in practice, data-driven techniques often req…
Characterizing Within-Driver Variability in Driving Dynamics During Obstacle Avoidance Maneuvers
Kendric R. Ortiz, Adam J. Thorpe, AnaMaria Perez +3
Variability in human response creates non-trivial challenges for modeling and control of human-automation systems. As autonomy becomes pervasive, methods that can accommodate human…
Data-Driven Chance Constrained Control using Kernel Distribution Embeddings
Adam J. Thorpe, Thomas Lew, Meeko M. K. Oishi +1
We present a data-driven algorithm for efficiently computing stochastic control policies for general joint chance constrained optimal control problems. Our approach leverages the t…
Trust-based user-interface design for human-automation systems
Abraham P. Vinod, Adam J. Thorpe, Philip A. Olaniyi +2
We present a method for dynamics-driven, user-interface design for a human-automation system via sensor selection. We define the user-interface to be the output of a MIMO LTI syste…
Approximate Stochastic Reachability for High Dimensional Systems
Adam J. Thorpe, Vignesh Sivaramakrishnan, Meeko M. K. Oishi
We present a method to compute the stochastic reachability safety probabilities for high-dimensional stochastic dynamical systems. Our approach takes advantage of a nonparametric l…