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20242026
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cs.RO2026

SACK : Safe Active Continual Koopman Learning for Uncertain Systems with Contractive Guarantees

Chandan Kumar Sah, Rajpal Singh, Jishnu Keshavan

Koopman operator theory provides a powerful framework for representing nonlinear dynamics through a linear operator acting on lifted observables, enabling the use of linear control…

cs.RO2026

Deep Robust Koopman Learning from Noisy Data

Aditya Singh, Rajpal Singh, Jishnu Keshavan

Koopman operator theory has emerged as a leading data-driven approach that relies on a judicious choice of observable functions to realize global linear representations of nonlinea…

cs.RO2025

Generalized Momenta-Based Koopman Formalism for Robust Control of Euler-Lagrangian Systems

Rajpal Singh, Aditya Singh, Chidre Shravista Kashyap +1

This paper presents a novel Koopman operator formulation for Euler Lagrangian dynamics that employs an implicit generalized momentum-based state space representation, which decoupl…

cs.RO2024

Adaptive Koopman Embedding for Robust Control of Complex Nonlinear Dynamical Systems

Rajpal Singh, Chandan Kumar Sah, Jishnu Keshavan

The discovery of linear embedding is the key to the synthesis of linear control techniques for nonlinear systems. In recent years, while Koopman operator theory has become a promin…

cs.RO20244 cited

A Collision Cone Approach for Control Barrier Functions

Manan Tayal, Bhavya Giri Goswami, Karthik Rajgopal +5

This work presents a unified approach for collision avoidance using Collision-Cone Control Barrier Functions (CBFs) in both ground (UGV) and aerial (UAV) unmanned vehicles. We prop…