90 citations · 910 across the 140 of their papers we have counts for
38 papers · 1 filter
Pareto-Optimal Entropy-Regularized Trajectory Optimization
Dimitrios S. Georgiou, Augustinos D. Saravanos, Evangelos A. Theodorou
Trajectory optimization (TO) under nonlinear dynamics, actuation limits and collision avoidance constraints is a fundamental problem in robotics, albeit especially challenging due…
Deep-Unfolded Coordination
Hunter Kuperman, Minchan Jung, Rahul V. Ghosh +2
Distributed optimization is a highly scalable and structurally transparent technique to solve multi-agent robotics problems; however, such methods often suffer from the need for hi…
Beyond Pure Sampling: Hybrid Optimization Mechanisms for Non-Convex Model Predictive Control
Yuichiro Aoyama, Minchan Jung, Akash Ratheesh +1
This paper investigates the optimization mechanisms of non-convex Model Predictive Control (MPC) using the Maximum Entropy Differential Dynamic Programming (ME-DDP) framework. Navi…
Multistep Belief Space Dynamics Learning For Risk-Aware Control
Jason Gibson, Bogdan Vlahov, Patrick Spieler +1
As autonomous vehicles move from a simplified research setting to practical use, there exists a large gap between the dynamic behavior of a human driving and an autonomous system.…
Sampling-Based Control via Entropy-Regularized Optimal Transport
Vincent Pacelli, Akash Ratheesh, Evangelos A. Theodorou
Sampling-based model predictive control methods like MPPI and CEM are essential for real-time control of nonlinear robotic systems, particularly where discontinuous dynamics preclu…
cuNRTO: GPU-Accelerated Nonlinear Robust Trajectory Optimization
Jiawei Wang, Arshiya Taj Abdul, Evangelos A. Theodorou
Robust trajectory optimization enables autonomous systems to operate safely under uncertainty by computing control policies that satisfy the constraints for all bounded disturbance…
Asynchronous Distributed Multi-Robot Motion Planning Under Imperfect Communication
Ardalan Tajbakhsh, Augustinos Saravanos, James Zhu +3
This paper addresses the challenge of coordinating multi-robot systems under realistic communication delays using distributed optimization. We focus on consensus ADMM as a scalable…
Meta-Learning Online Dynamics Model Adaptation in Off-Road Autonomous Driving
Jacob Levy, Jason Gibson, Bogdan Vlahov +4
High-speed off-road autonomous driving presents unique challenges due to complex, evolving terrain characteristics and the difficulty of accurately modeling terrain-vehicle interac…
Dynamics Modeling using Visual Terrain Features for High-Speed Autonomous Off-Road Driving
Jason Gibson, Anoushka Alavilli, Erica Tevere +2
Rapid autonomous traversal of unstructured terrain is essential for scenarios such as disaster response, search and rescue, or planetary exploration. As a vehicle navigates at the…
Operator Splitting Covariance Steering for Safe Stochastic Nonlinear Control
Akash Ratheesh, Vincent Pacelli, Augustinos D. Saravanos +1
This paper presents a novel algorithm for solving distribution steering problems featuring nonlinear dynamics and chance constraints. Covariance steering (CS) is an emerging method…
Low Frequency Sampling in Model Predictive Path Integral Control
Bogdan Vlahov, Jason Gibson, David D. Fan +3
Sampling-based model-predictive controllers have become a powerful optimization tool for planning and control problems in various challenging environments. In this paper, we show h…
Scaling Robust Optimization for Multi-Agent Robotic Systems: A Distributed Perspective
Arshiya Taj Abdul, Augustinos D. Saravanos, Evangelos A. Theodorou
This paper presents a novel distributed robust optimization scheme for steering distributions of multi-agent systems under stochastic and deterministic uncertainty. Robust optimiza…
Distributed Hierarchical Distribution Control for Very-Large-Scale Clustered Multi-Agent Systems
Augustinos D. Saravanos, Yihui Li, Evangelos A. Theodorou
As the scale and complexity of multi-agent robotic systems are subject to a continuous increase, this paper considers a class of systems labeled as Very-Large-Scale Multi-Agent Sys…
A Multi-step Dynamics Modeling Framework For Autonomous Driving In Multiple Environments
Jason Gibson, Bogdan Vlahov, David Fan +4
Modeling dynamics is often the first step to making a vehicle autonomous. While on-road autonomous vehicles have been extensively studied, off-road vehicles pose many challenging m…
Improved Exploration for Safety-Embedded Differential Dynamic Programming Using Tolerant Barrier States
Joshua E. Kuperman, Hassan Almubarak, Augustinos D. Saravanos +1
In this paper, we introduce Tolerant Discrete Barrier States (T-DBaS), a novel safety-embedding technique for trajectory optimization with enhanced exploratory capabilities. The pr…
Distributed Model Predictive Covariance Steering
Augustinos D. Saravanos, Isin M. Balci, Efstathios Bakolas +1
This paper proposes Distributed Model Predictive Covariance Steering (DiMPCS) for multi-agent control under stochastic uncertainty. The scope of our approach is to blend covariance…
Spatiotemporal Costmap Inference for MPC via Deep Inverse Reinforcement Learning
Keuntaek Lee, David Isele, Evangelos A. Theodorou +1
It can be difficult to autonomously produce driver behavior so that it appears natural to other traffic participants. Through Inverse Reinforcement Learning (IRL), we can automate…
Optimal-Horizon Model-Predictive Control with Differential Dynamic Programming
Kyle Stachowicz, Evangelos A. Theodorou
We present an algorithm, based on the Differential Dynamic Programming framework, to handle trajectory optimization problems in which the horizon is determined online rather than f…
Trajectory Distribution Control for Model Predictive Path Integral Control using Covariance Steering
Ji Yin, Zhiyuan Zhang, Evangelos Theodorou +1
This paper presents a novel control approach for autonomous systems operating under uncertainty. We combine Model Predictive Path Integral (MPPI) control with Covariance Steering (…
Learning Risk-aware Costmaps for Traversability in Challenging Environments
David D. Fan, Sharmita Dey, Ali-akbar Agha-mohammadi +1
One of the main challenges in autonomous robotic exploration and navigation in unknown and unstructured environments is determining where the robot can or cannot safely move. A sig…
Safety Embedded Differential Dynamic Programming Using Discrete Barrier States
Hassan Almubarak, Kyle Stachowicz, Nader Sadegh +1
Certified safe control is a growing challenge in robotics, especially when performance and safety objectives must be concurrently achieved. In this work, we extend the barrier stat…
Stochastic Spatio-Temporal Optimization for Control and Co-Design of Systems in Robotics and Applied Physics
Ethan N. Evans, Andrew P. Kendall, Evangelos A. Theodorou
Correlated with the trend of increasing degrees of freedom in robotic systems is a similar trend of rising interest in Spatio-Temporal systems described by Partial Differential Equ…
Autonomous Hybrid Ground/Aerial Mobility in Unknown Environments
David D. Fan, Rohan Thakker, Tara Bartlett +4
Hybrid ground and aerial vehicles can possess distinct advantages over ground-only or flight-only designs in terms of energy savings and increased mobility. In this work we outline…
Approximate Inverse Reinforcement Learning from Vision-based Imitation Learning
Keuntaek Lee, Bogdan Vlahov, Jason Gibson +2
In this work, we present a method for obtaining an implicit objective function for vision-based navigation. The proposed methodology relies on Imitation Learning, Model Predictive…