10 citations · 14 across the 9 of their papers we have counts for
6 papers · 2 filters
From Optical Flow to Safety: Visual Safety Certification via Scale-Free Relative Motion
Bazeela Banday, Jishnu Keshavan
Safe autonomous navigation using monocular vision remains challenging because explicit obstacle states are not directly observable. This letter introduces a visual safety-certifica…
Adversarially Robust Geometric Safety Certificates for Nonholonomic Robots Against Maneuvering Obstacles
Chandan Kumar Sah, Bazeela Banday, Jishnu Keshavan
Safe navigation against obstacles that can actively maneuver within bounded capabilities remains challenging: robust control barrier function methods typically treat obstacle actio…
Port-Hamiltonian Koopman Operator Synthesis for Mechanical Systems
Rajpal Singh, Aditya Singh, Jishnu Keshavan
Finite-dimensional Koopman models enable efficient linear prediction and control of nonlinear robotic systems. However, models learned purely from trajectory data may violate the e…
Exact Feasibility Certification and Optimal Responsibility Allocation for Multi-Robot CBF Safety Filters
Chandan Kumar Sah, Jishnu Keshavan
Multi-robot Control Barrier Function (CBF) safety filters can become infeasible, but a failed quadratic program (QP) does not indicate why the conflict occurred or how to resolve i…
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…
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…