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09/07/2023
A Tutorial on the Non-Asymptotic Theory of System Identification
This tutorial serves as an introduction to recently developed non-asympt...
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08/16/2023
Safety Filter Design for Neural Network Systems via Convex Optimization
With the increase in data availability, it has been widely demonstrated ...
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08/08/2023
Meta-Learning Operators to Optimality from Multi-Task Non-IID Data
A powerful concept behind much of the recent progress in machine learnin...
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07/31/2023
Learning Safe and Stable Motion Plans with Neural Ordinary Differential Equations
A learning-based modular motion planning pipeline is presented that is c...
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07/25/2023
A Data-Driven Approach to Synthesizing Dynamics-Aware Trajectories for Underactuated Robotic Systems
We consider joint trajectory generation and tracking control for under-a...
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05/18/2023
The noise level in linear regression with dependent data
We derive upper bounds for random design linear regression with dependen...
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05/16/2023
The Power of Learned Locally Linear Models for Nonlinear Policy Optimization
A common pipeline in learning-based control is to iteratively estimate a...
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12/01/2022
Multi-Task Imitation Learning for Linear Dynamical Systems
We study representation learning for efficient imitation learning over l...
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11/24/2022
Learning-enhanced Nonlinear Model Predictive Control using Knowledge-based Neural Ordinary Differential Equations and Deep Ensembles
Nonlinear model predictive control (MPC) is a flexible and increasingly ...
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10/05/2022
Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning
We consider how to most efficiently leverage teleoperator time to collec...
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09/12/2022
Statistical Learning Theory for Control: A Finite Sample Perspective
This tutorial survey provides an overview of recent non-asymptotic advan...
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06/14/2022
How are policy gradient methods affected by the limits of control?
We study stochastic policy gradient methods from the perspective of cont...
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05/30/2022
TaSIL: Taylor Series Imitation Learning
We propose Taylor Series Imitation Learning (TaSIL), a simple augmentati...
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05/28/2022
Risk of Stochastic Systems for Temporal Logic Specifications
The wide availability of data coupled with the computational advances in...
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05/27/2022
Learning to Control Linear Systems can be Hard
In this paper, we study the statistical difficulty of learning to contro...
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02/24/2022
Uncertainty-driven Planner for Exploration and Navigation
We consider the problems of exploration and point-goal navigation in pre...
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02/16/2022
Single Trajectory Nonparametric Learning of Nonlinear Dynamics
Given a single trajectory of a dynamical system, we analyze the performa...
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01/04/2022
Linear Variational State Space Filtering
We introduce Variational State-Space Filters (VSSF), a new method for un...
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12/20/2021
Adversarially Robust Stability Certificates can be Sample-Efficient
Motivated by bridging the simulation to reality gap in the context of sa...
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11/18/2021
Learning Robust Output Control Barrier Functions from Safe Expert Demonstrations
This paper addresses learning safe control laws from expert demonstratio...
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04/28/2021
Communication Topology Co-Design in Graph Recurrent Neural Network Based Distributed Control
When designing large-scale distributed controllers, the information-shar...
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04/03/2021
STL Robustness Risk over Discrete-Time Stochastic Processes
We present a framework to interpret signal temporal logic (STL) formulas...
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04/02/2021
How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?
The difficulty of optimal control problems has classically been characte...
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02/18/2021
Closing the Closed-Loop Distribution Shift in Safe Imitation Learning
Commonly used optimization-based control strategies such as model-predic...
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01/16/2021
Learning Robust Hybrid Control Barrier Functions for Uncertain Systems
The need for robust control laws is especially important in safety-criti...
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11/20/2020
Data-Driven System Level Synthesis
We establish data-driven versions of the System Level Synthesis (SLS) pa...
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11/08/2020
Learning Hybrid Control Barrier Functions from Data
Motivated by the lack of systematic tools to obtain safe control laws fo...
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08/13/2020
Learning Stability Certificates from Data
Many existing tools in nonlinear control theory for establishing stabili...
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07/08/2020
Evaluating Robust, Perception Based Control with Quadrotors
Traditionally, controllers and state estimators in robotic systems are d...
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04/07/2020
Learning Control Barrier Functions from Expert Demonstrations
Inspired by the success of imitation and inverse reinforcement learning ...
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03/13/2020
Action for Better Prediction
Good prediction is necessary for autonomous robotics to make informed de...
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12/31/2019
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
We propose an algorithm combining calibrated prediction and generalizati...
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12/27/2019
Sample Complexity of Kalman Filtering for Unknown Systems
In this paper, we consider the task of designing a Kalman Filter (KF) fo...
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09/21/2019
Efficient Learning of Distributed Linear-Quadratic Controllers
In this work, we propose a robust approach to design distributed control...
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07/08/2019
Robust Guarantees for Perception-Based Control
Motivated by vision based control of autonomous vehicles, we consider th...
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06/27/2019
A Tutorial on Concentration Bounds for System Identification
We provide a brief tutorial on the use of concentration inequalities as ...
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06/27/2019
From self-tuning regulators to reinforcement learning and back again
Machine and reinforcement learning (RL) are being applied to plan and co...
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04/20/2019
Learning Sparse Dynamical Systems from a Single Sample Trajectory
This paper addresses the problem of identifying sparse linear time-invar...
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09/26/2018
Safely Learning to Control the Constrained Linear Quadratic Regulator
We study the constrained linear quadratic regulator with unknown dynamic...
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05/23/2018
Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator
We consider adaptive control of the Linear Quadratic Regulator (LQR), wh...
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03/25/2018
Finite-Data Performance Guarantees for the Output-Feedback Control of an Unknown System
As the systems we control become more complex, first-principle modeling ...
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10/04/2017
On the Sample Complexity of the Linear Quadratic Regulator
This paper addresses the optimal control problem known as the Linear Qua...
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01/15/2014
