90 citations · 910 across the 140 of their papers we have counts for
31 papers · 1 filter
Distributed Covariance Steering via Non-Convex ADMM for Large-Scale Multi-Agent Systems
Augustinos D. Saravanos, Isin M. Balci, Arshiya Taj Abdul +2
This paper studies the problem of steering large-scale multi-agent stochastic linear systems between Gaussian distributions under probabilistic collision avoidance constraints. We…
Nonlinear Robust Optimization for Planning and Control
Arshiya Taj Abdul, Augustinos D. Saravanos, Evangelos A. Theodorou
This paper presents a novel robust trajectory optimization method for constrained nonlinear dynamical systems subject to unknown bounded disturbances. In particular, we seek optima…
Barrier-Riccati Synthesis for Nonlinear Safe Control with Expanded Region of Attraction
Hassan Almubarak, Maitham F. AL-Sunni, Justin T. Dubbin +3
We present a Riccati-based framework for safety-critical nonlinear control that integrates the barrier states (BaS) methodology with the State-Dependent Riccati Equation (SDRE) app…
Barrier States Theory for Safety-Critical Multi-Objective Control
Hassan Almubarak, Nader Sadegh, Evangelos A. Theodorou
Multi-objective safety-critical control entails a diligent design to avoid possibly conflicting scenarios and ensure safety. This paper addresses multi-objective safety-critical co…
Safe Importance Sampling in Model Predictive Path Integral Control
Manan Gandhi, Hassan Almubarak, Evangelos Theodorou
We introduce the notion of importance sampling under embedded barrier state control, titled Safety Controlled Model Predictive Path Integral Control (SC-MPPI). For robotic systems…
Gaussian Process Barrier States for Safe Trajectory Optimization and Control
Hassan Almubarak, Manan Gandhi, Yuichiro Aoyama +2
This paper proposes embedded Gaussian Process Barrier States (GP-BaS), a methodology to safely control unmodeled dynamics of nonlinear system using Bayesian learning. Gaussian Proc…
Distributed Differential Dynamic Programming Architectures for Large-Scale Multi-Agent Control
Augustinos D. Saravanos, Yuichiro Aoyama, Hongchang Zhu +1
In this paper, we propose two novel decentralized optimization frameworks for multi-agent nonlinear optimal control problems in robotics. The aim of this work is to suggest archite…
Safety in Augmented Importance Sampling: Performance Bounds for Robust MPPI
Manan Gandhi, Hassan Almubarak, Yuichiro Aoyama +1
This work explores the nature of augmented importance sampling in safety-constrained model predictive control problems. When operating in a constrained environment, sampling based…
Barrier States Embedded Iterative Dynamic Game for Robust and Safe Trajectory Optimization
Hassan Almubarak, Evangelos A. Theodorou, Nader Sadegh
Considering uncertainties and disturbances is an important, yet challenging, step in successful decision making. The problem becomes more challenging in safety-constrained environm…
Generalization of Safe Optimal Control Actions on Networked Multi-Agent Systems
Lin Song, Neng Wan, Aditya Gahlawat +3
We propose a unified framework to fast generate a safe optimal control action for a new task from existing controllers on Multi-Agent Systems (MASs). The control action composition…
Deep Stochastic Optimal Control Policies for Planetary Soft-landing
Marcus A. Pereira, Camilo A. Duarte, Ioannis Exarchos +1
In this paper, we introduce a novel deep learning based solution to the Powered-Descent Guidance (PDG) problem, grounded in principles of nonlinear Stochastic Optimal Control (SOC)…
HJB Based Optimal Safe Control Using Control Barrier Functions
Hassan Almubarak, Evangelos A. Theodorou, Nader Sadegh
This work proposes an optimal safe controller minimizing an infinite horizon cost functional subject to control barrier functions (CBFs) safety conditions. The constrained optimal…
Robust Model Predictive Path Integral Control: Analysis and Performance Guarantees
Manan Gandhi, Bogdan Vlahov, Jason Gibson +2
In this paper we propose a novel decision making architecture for Robust Model Predictive Path Integral control (RMPPI) and investigate its performance guarantees and applicability…
Safety Embedded Control of Nonlinear Systems via Barrier States
Hassan Almubarak, Nader Sadegh, Evangelos A. Theodorou
In many safety-critical control systems, possibly opposing safety restrictions and control performance objectives arise. To confront such a conflict, this letter proposes a novel m…
Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs
Marcus Aloysius Pereira, Ziyi Wang, Ioannis Exarchos +1
This paper introduces a new formulation for stochastic optimal control and stochastic dynamic optimization that ensures safety with respect to state and control constraints. The pr…
Cooperative Path Integral Control for Stochastic Multi-Agent Systems
Neng Wan, Aditya Gahlawat, Naira Hovakimyan +2
A distributed stochastic optimal control solution is presented for cooperative multi-agent systems. The network of agents is partitioned into multiple factorial subsystems, each of…
Compositionality of Linearly Solvable Optimal Control in Networked Multi-Agent Systems
Lin Song, Neng Wan, Aditya Gahlawat +2
In this paper, we discuss the methodology of generalizing the optimal control law from learned component tasks to unlearned composite tasks on Multi-Agent Systems (MASs), by using…
Contraction -Adaptive Control using Gaussian Processes
Aditya Gahlawat, Arun Lakshmanan, Lin Song +4
We present -, a control framework that enables safe simultaneous learning and control for systems subject to uncertainties. The two main constituents…
-: Adaptive Control with Bayesian Learning
Aditya Gahlawat, Pan Zhao, Andrew Patterson +2
We present -, an architecture based on adaptive control and Gaussian Process Regression (GPR) for safe simultaneous control and learnin…
High-Relative Degree Stochastic Control Lyapunov and Barrier Functions
Meenakshi Sarkar, Debasish Ghose, Evangelos A. Theodorou
We introduce High-Relative Degree Stochastic Control Lyapunov functions and Barrier Functions as a means to ensure asymptotic stability of the system and incorporate state dependen…
L1-Adaptive MPPI Architecture for Robust and Agile Control of Multirotors
Jintasit Pravitra, Kasey A. Ackerman, Chengyu Cao +2
This paper presents a multirotor control architecture, where Model Predictive Path Integral Control (MPPI) and L1 adaptive control are combined to achieve both fast model predictiv…
Nonlinear Covariance Control via Differential Dynamic Programming
Zeji Yi, Zhefeng Cao, Evangelos Theodorou +1
We consider covariance control problems for nonlinear stochastic systems. Our objective is to find an optimal control strategy to steer the state from an initial distribution to a…
Bayesian Learning-Based Adaptive Control for Safety Critical Systems
David D. Fan, Jennifer Nguyen, Rohan Thakker +3
Deep learning has enjoyed much recent success, and applying state-of-the-art model learning methods to controls is an exciting prospect. However, there is a strong reluctance to us…
Pseudospectral Model Predictive Control under Partially Learned Dynamics
Manan Gandhi, Yunpeng Pan, Evangelos Theodorou
Trajectory optimization of a controlled dynamical system is an essential part of autonomy, however many trajectory optimization techniques are limited by the fidelity of the underl…