activity
20152022
most citedD2C 2.0: Decoupled Data-Based Approach for Learning to Control Stochastic Nonlinear Systems via Model-Free ILQR

2 citations · 3 across the 5 of their papers we have counts for

collaborators

9 papers

eess.SY2022

Optimal Control of Material Micro-Structures

Aayushman Sharma, Zirui Mao, Haiying Yang +3

In this paper, we consider the optimal control of material micro-structures. Such material micro-structures are modeled by the so-called phase field model. We study the underlying…

cs.LG2020

On the Convergence of Reinforcement Learning in Nonlinear Continuous State Space Problems

Raman Goyal, Suman Chakravorty, Ran Wang +1

We consider the problem of Reinforcement Learning for nonlinear stochastic dynamical systems. We show that in the RL setting, there is an inherent ``Curse of Variance" in addition…

math.OC20202 cited

D2C 2.0: Decoupled Data-Based Approach for Learning to Control Stochastic Nonlinear Systems via Model-Free ILQR

Karthikeya S Parunandi, Aayushman Sharma, Suman Chakravorty +1

In this paper, we propose a structured linear parameterization of a feedback policy to solve the model-free stochastic optimal control problem. This parametrization is corroborated…

math.OC2020

Experiments with Tractable Feedback in Robotic Planning under Uncertainty: Insights over a wide range of noise regimes (Extended Report)

Mohamed Naveed Gul Mohamed, Suman Chakravorty, Dylan A. Shell

We consider the problem of robotic planning under uncertainty. This problem may be posed as a stochastic optimal control problem, complete solution to which is fundamentally intrac…

eess.SY2020

A Belief Space Perspective of RFS based Multi-Target Tracking and its Relationship to MHT

S. Chakravorty, W. R. Faber, Islam I. Hussein +1

In this paper, we establish a connection between Reid{'}s HOMHT and the modern Random Finite Set (RFS)/ Finite Set Statistics (FISST) based methods for Multi-Target Tracking. We st…

eess.SY2019

Decoupling stochastic optimal control problems for efficient solution: insights from experiments across a wide range of noise regimes

Mohamed Naveed Gul Mohamed, Suman Chakravorty, Dylan A. Shell

We consider the problem of robotic planning under uncertainty in this paper. This problem may be posed as a stochastic optimal control problem, a solution to which is fundamentally…