
Communication Topology CoDesign in Graph Recurrent Neural Network Based Distributed Control
When designing largescale distributed controllers, the informationshar...
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STL Robustness Risk over DiscreteTime Stochastic Processes
We present a framework to interpret signal temporal logic (STL) formulas...
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How Are Learned PerceptionBased Controllers Impacted by the Limits of Robust Control?
The difficulty of optimal control problems has classically been characte...
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Closing the ClosedLoop Distribution Shift in Safe Imitation Learning
Commonly used optimizationbased control strategies such as modelpredic...
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Learning Robust Hybrid Control Barrier Functions for Uncertain Systems
The need for robust control laws is especially important in safetycriti...
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DataDriven System Level Synthesis
We establish datadriven versions of the System Level Synthesis (SLS) pa...
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Learning Hybrid Control Barrier Functions from Data
Motivated by the lack of systematic tools to obtain safe control laws fo...
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Learning Stability Certificates from Data
Many existing tools in nonlinear control theory for establishing stabili...
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Evaluating Robust, Perception Based Control with Quadrotors
Traditionally, controllers and state estimators in robotic systems are d...
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Learning Control Barrier Functions from Expert Demonstrations
Inspired by the success of imitation and inverse reinforcement learning ...
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Action for Better Prediction
Good prediction is necessary for autonomous robotics to make informed de...
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PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
We propose an algorithm combining calibrated prediction and generalizati...
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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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Efficient Learning of Distributed LinearQuadratic Controllers
In this work, we propose a robust approach to design distributed control...
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Robust Guarantees for PerceptionBased Control
Motivated by vision based control of autonomous vehicles, we consider th...
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A Tutorial on Concentration Bounds for System Identification
We provide a brief tutorial on the use of concentration inequalities as ...
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From selftuning regulators to reinforcement learning and back again
Machine and reinforcement learning (RL) are being applied to plan and co...
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Learning Sparse Dynamical Systems from a Single Sample Trajectory
This paper addresses the problem of identifying sparse linear timeinvar...
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Safely Learning to Control the Constrained Linear Quadratic Regulator
We study the constrained linear quadratic regulator with unknown dynamic...
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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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FiniteData Performance Guarantees for the OutputFeedback Control of an Unknown System
As the systems we control become more complex, firstprinciple modeling ...
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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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Convex Relaxations of SE(2) and SE(3) for Visual Pose Estimation
This paper proposes a new method for rigid body pose estimation based on...
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Nikolai Matni
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