8 papers
Uncertainty Quantification via Invariant-Measure Conformal Prediction
Mohammadhossein Bakhtiaridoust, Dominik Baumann, Shankar Deka
Uncertainty quantification for learned stochastic dynamical systems is essential in safety-critical tasks such as control and monitoring. Standard conformal prediction provides fin…
Data-driven Reachability Verification with Probabilistic Guarantees under Koopman Spectral Uncertainty
Jianqiang Ding, Shankar A. Deka
Providing rigorous reachability guarantees for unknown complex systems is a crucial and challenging task. In this paper, we present a novel data-driven framework that addresses thi…
Differential Geometric Conditions for Koopman Linearizability of Control-Affine Systems
Shankar A. Deka
Koopman linearization opens many possibilities for control synthesis and analysis of nonlinear systems. Whether or not any given nonlinear control system admits a finite-dimensiona…
Reach-Avoid Model Predictive Control with Guaranteed Recursive Feasibility via Input Constrained Backstepping
Jianqiang Ding, Nishant Jayesh Bhave, Shankar A. Deka
This letter proposes a novel sampled-data model predictive control framework for continuous control-affine nonlinear systems that provides rigorous reach-avoid and recursive feasib…
Time-to-reach Bounds for Verification of Dynamical Systems Using the Koopman Spectrum
Jianqiang Ding, Shankar A. Deka
In this work, we present a novel Koopman spectrum-based reachability verification method for nonlinear systems. Contrary to conventional methods that focus on characterizing all po…
Robotic Trail Maker Platform for Rehabilitation in Neurological Conditions: Clinical Use Cases
Srikar Annamraju, Harris Nisar, Dayu Xia +4
Patients with neurological conditions require rehabilitation to restore their motor, visual, and cognitive abilities. To meet the shortage of therapists and reduce their workload,…