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Umesh Vaidya

6 accepted papers

2023

Data-Driven Modeling and Experimental Validation of Autonomous Vehicles Using Koopman Operator

IROS 2023poster

This paper presents a data-driven framework to discover underlying dynamics on a scaled F1TENTH vehicle using the Koopman operator linear predictor. Traditionally, a range of white, gray, or black-box models are used to develop controllers for vehicle path tracking. However, these models are constra…

Cited by 6SourceScholar
2023

Data-Driven Modeling and Experimental Validation of Autonomous Vehicles Using Koopman Operator: Distribution A: Approved for Public Release; Distribution Unlimited. OPSEC # 7248

IROS 2023

This paper presents a data-driven framework to discover underlying dynamics on a scaled F1TENTH vehicle using the Koopman operator linear predictor. Traditionally, a range of white, gray, or black-box models are used to develop controllers for vehicle path tracking. However, these models are constra

Cited by 2SourceScholar
2023

Data-driven optimal control under safety constraints using sparse Koopman approximation

ICRA 2023poster

In this work we approach the dual optimal reach-safe control problem using sparse approximations of Koopman operator. Matrix approximation of Koopman operator needs to solve a least-squares (LS) problem in the lifted function space, which is computationally intractable for fine discretizations and h…

Cited by 3SourceScholar
2023

Sparse Learning of Dynamical Systems in RKHS: An Operator-Theoretic Approach

ICML 2023poster

Transfer operators provide a rich framework for representing the dynamics of very general, nonlinear dynamical systems. When interacting with reproducing kernel Hilbert spaces (RKHS), descriptions of dynamics often incur prohibitive data storage requirements, motivating dataset sparsification as a p…

Cited by 16SourcePDFScholar