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08/16/2023
Differentiable Robust Model Predictive Control
Deterministic model predictive control (MPC), while powerful, is often i...
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05/30/2023
Distributed Hierarchical Distribution Control for Very-Large-Scale Clustered Multi-Agent Systems
As the scale and complexity of multi-agent robotic systems are subject t...
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05/03/2023
A Multi-step Dynamics Modeling Framework For Autonomous Driving In Multiple Environments
Modeling dynamics is often the first step to making a vehicle autonomous...
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03/06/2023
Improved Exploration for Safety-Embedded Differential Dynamic Programming Using Tolerant Barrier States
In this paper, we introduce Tolerant Discrete Barrier States (T-DBaS), a...
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03/03/2023
Deep Momentum Multi-Marginal Schrödinger Bridge
Reconstructing population dynamics using only samples from distributions...
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02/12/2023
I^2SB: Image-to-Image Schrödinger Bridge
We propose Image-to-Image Schrödinger Bridge (I^2SB), a new class of con...
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12/01/2022
Distributed Model Predictive Covariance Steering
This paper proposes Distributed Model Predictive Covariance Steering (DM...
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12/01/2022
Gaussian Process Barrier States for Safe Trajectory Optimization and Control
This paper proposes embedded Gaussian Process Barrier States (GP-BaS), a...
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10/19/2022
MPOGames: Efficient Multimodal Partially Observable Dynamic Games
Game theoretic methods have become popular for planning and prediction i...
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09/30/2022
Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian
Incorporating the Hamiltonian structure of physical dynamics into deep l...
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09/20/2022
Deep Generalized Schrödinger Bridge
Mean-Field Game (MFG) serves as a crucial mathematical framework in mode...
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04/07/2022
Parameterized Differential Dynamic Programming
Differential Dynamic Programming (DDP) is an efficient trajectory optimi...
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04/05/2022
Deep Graphic FBSDEs for Opinion Dynamics Stochastic Control
In this paper, we present a scalable deep learning approach to solve opi...
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02/22/2022
Decentralized Safe Multi-agent Stochastic Optimal Control using Deep FBSDEs and ADMM
In this work, we propose a novel safe and scalable decentralized solutio...
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01/30/2022
Multimodal Maximum Entropy Dynamic Games
Environments with multi-agent interactions often result a rich set of mo...
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01/17/2022
Spatiotemporal Costmap Inference for MPC via Deep Inverse Reinforcement Learning
It can be difficult to autonomously produce driver behavior so that it a...
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11/17/2021
Optimal-Horizon Model-Predictive Control with Differential Dynamic Programming
We present an algorithm, based on the Differential Dynamic Programming f...
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10/21/2021
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory
Schrödinger Bridge (SB) is an optimal transport problem that has receive...
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10/13/2021
Maximum Entropy Differential Dynamic Programming
In this paper, we present a novel maximum entropy formulation of the Dif...
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09/29/2021
Second-Order Neural ODE Optimizer
We propose a novel second-order optimization framework for training the ...
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09/01/2021
Deep ℒ^1 Stochastic Optimal Control Policies for Planetary Soft-landing
In this paper, we introduce a novel deep learning based solution to the ...
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07/25/2021
Learning Risk-aware Costmaps for Traversability in Challenging Environments
One of the main challenges in autonomous robotic exploration and navigat...
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05/30/2021
Safety Embedded Differential Dynamic Programming using Discrete Barrier States
Certified safe control is a growing challenge in robotics, especially wh...
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05/08/2021
Dynamic Game Theoretic Neural Optimizer
The connection between training deep neural networks (DNNs) and optimal ...
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04/01/2021
Variational Inference MPC using Tsallis Divergence
In this paper, we provide a generalized framework for Variational Infere...
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02/18/2021
Stochastic Spatio-Temporal Optimization for Control and Co-Design of Systems in Robotics and Applied Physics
Correlated with the trend of increasing degrees of freedom in robotic sy...
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02/18/2021
Distributed Algorithms for Linearly-Solvable Optimal Control in Networked Multi-Agent Systems
Distributed algorithms for both discrete-time and continuous-time linear...
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11/21/2020
Multi-agent Deep FBSDE Representation For Large Scale Stochastic Differential Games
In this paper, we present a deep learning framework for solving large-sc...
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09/30/2020
Cooperative Path Integral Control for Stochastic Multi-Agent Systems
A distributed stochastic optimal control solution is presented for coope...
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09/28/2020
Compositionality of Linearly Solvable Optimal Control in Networked Multi-Agent Systems
In this paper, we discuss the methodology of generalizing the optimal co...
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09/02/2020
Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs
This paper introduces a new formulation for stochastic optimal control a...
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09/02/2020
Adaptive CVaR Optimization for Dynamical Systems with Path Space Stochastic Search
We present a general framework for optimizing the Conditional Value-at-R...
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07/17/2020
A Differential Game Theoretic Neural Optimizer for Training Residual Networks
Connections between Deep Neural Networks (DNNs) training and optimal con...
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06/22/2020
Non-convex Optimization via Adaptive Stochastic Search for End-to-End Learning and Control
In this work we propose the use of adaptive stochastic search as a build...
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04/17/2020
Approximate Inverse Reinforcement Learning from Vision-based Imitation Learning
In this work, we present a method for obtaining an implicit objective fu...
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02/20/2020
Differential Dynamic Programming Neural Optimizer
Interpretation of Deep Neural Networks (DNNs) training as an optimal con...
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02/05/2020
Deep Learning Tubes for Tube MPC
Learning-based control aims to construct models of a system to use for p...
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01/07/2020
Aggressive Perception-Aware Navigation using Deep Optical Flow Dynamics and PixelMPC
Recently, vision-based control has gained traction by leveraging the pow...
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10/05/2019
Bayesian Learning-Based Adaptive Control for Safety Critical Systems
Deep learning has enjoyed much recent success, and applying state-of-the...
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08/28/2019
Deep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective
Attempts from different disciplines to provide a fundamental understandi...
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06/11/2019
Deep Forward-Backward SDEs for Min-max Control
This paper presents a novel approach to numerically solve stochastic dif...
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06/11/2019
Deep 2FBSDEs for Systems with Control Multiplicative Noise
We present a deep recurrent neural network architecture to solve a class...
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05/13/2019
Locally Weighted Regression Pseudo-Rehearsal for Online Learning of Vehicle Dynamics
We consider the problem of online adaptation of a neural network designe...
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04/26/2019
Perceptual Attention-based Predictive Control
In this paper, we present a novel information processing architecture fo...
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02/11/2019
Neural Network Architectures for Stochastic Control using the Nonlinear Feynman-Kac Lemma
In this paper we propose a new methodology for decision-making under unc...
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12/05/2018
Vision-Based High Speed Driving with a Deep Dynamic Observer
In this paper we present a framework for combining deep learning-based r...
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11/30/2018
Ensemble Bayesian Decision Making with Redundant Deep Perceptual Control Policies
This work presents a novel ensemble of Bayesian Neural Networks (BNNs) f...
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10/07/2018