10 citations · 20 across the 7 of their papers we have counts for
8 papers
Constrained Differential Dynamic Programming Revisited
Yuichiro Aoyama, George Boutselis, Akash Patel +1
Differential Dynamic Programming (DDP) has become a well established method for unconstrained trajectory optimization. Despite its several applications in robotics and controls how…
Spatio-Temporal Stochastic Optimization: Theory and Applications to Optimal Control and Co-Design
Ethan N. Evans, Andrew P. Kendall, George I. Boutselis +1
There is a rising interest in Spatio-temporal systems described by Partial Differential Equations (PDEs) among the control community. Not only are these systems challenging to cont…
Constrained Sampling-based Trajectory Optimization using Stochastic Approximation
George I. Boutselis, Ziyi Wang, Evangelos A. Theodorou
We propose a sampling-based trajectory optimization methodology for constrained problems. We extend recent works on stochastic search to deal with box control constraints,as well a…
Variational Optimization Based Reinforcement Learning for Infinite Dimensional Stochastic Systems
Ethan N. Evans, Marcus A. Pereira, George I. Boutselis +1
Systems involving Partial Differential Equations (PDEs) have recently become more popular among the machine learning community. However prior methods usually treat infinite dimensi…
Leveraging Stochasticity for Open Loop and Model Predictive Control of Complex Fluid Systems
George I. Boutselis, Ethan N. Evans, Marcus A. Pereira +1
Stochastic Spatio-Temporal processes are prevalent across domains ranging from modeling of plasma to the turbulence in fluids to the wave function of quantum systems. This letter s…
Differential Dynamic Programming on Lie Groups: Derivation, Convergence Analysis and Numerical Results
George I. Boutselis, Evangelos Theodorou
We develop a discrete-time optimal control framework for systems evolving on Lie groups. Our work generalizes the original Differential Dynamic Programming method, by employing a c…
Variational Inference for Stochastic Control of Infinite Dimensional Systems
George I. Boutselis, Marcus Pereira, Evangelos A. Theodorou
This paper develops a variational inference framework for control of infinite dimensional stochastic systems. We employ a measure theoretic approach which relies on the generalizat…
Stochastic trajectory optimization for mechanical systems with parametric uncertainties
George I. Boutselis, Yunpeng Pan, Gerardo De La Tore +1
In this paper we develop a novel, discrete-time optimal control framework for mechanical systems with uncertain model parameters. We consider finite-horizon problems where the perf…