6 papers
Constricting Tubes for Prescribed-Time Safe Control
Darshan Gadginmath, Ahmed Allibhoy, Fabio Pasqualetti
We propose a constricting Control Barrier Function (CBF) framework for prescribed-time control of control-affine systems with input constraints. Given a system starting outside a t…
Geometric SSM: LTI State Space Models for Selective Tasks
Umberto Casti, Giacomo Baggio, Sandro Zampieri +1
A key claim in recent work on Selective State Space Models is that selectivity, the ability to focus on relevant information while filtering irrelevant inputs, requires breaking th…
Score Matching Diffusion Based Feedback Control and Planning of Nonlinear Systems
Karthik Elamvazhuthi, Darshan Gadginmath, Fabio Pasqualetti
In this paper, we propose a deterministic diffusion-based framework for controlling the probability density of nonlinear control-affine systems, with theoretical guarantees for dri…
Provably Safe Generative Sampling with Constricting Barrier Functions
Darshan Gadginmath, Ahmed Allibhoy, Fabio Pasqualetti
Flow-based generative models, such as diffusion models and flow matching models, have achieved remarkable success in learning complex data distributions. However, a critical gap re…
Dynamics-aware Diffusion Models for Planning and Control
Darshan Gadginmath, Fabio Pasqualetti
This paper addresses the problem of generating dynamically admissible trajectories for control tasks using diffusion models, particularly in scenarios where the environment is comp…
Active Probing with Multimodal Predictions for Motion Planning
Darshan Gadginmath, Farhad Nawaz, Minjun Sung +5
Navigation in dynamic environments requires autonomous systems to reason about uncertainties in the behavior of other agents. In this paper, we introduce a unified framework that c…