2 citations · 2 across the 19 of their papers we have counts for
8 papers · 1 filter
Factorizing Diffusion Policies for Observation Modality Prioritization
Omkar Patil, Prabin Rath, Kartikay Pangaonkar +2
Diffusion models have been extensively leveraged for learning robot skills from demonstrations. These policies are conditioned on several observational modalities such as proprioce…
LyLA-Therm: Lyapunov-based Langevin Adaptive Thermodynamic Neural Network Controller
Saiedeh Akbari, Omkar Sudhir Patil, Warren E. Dixon
Thermodynamic principles can be employed to design parameter update laws that address challenges such as the exploration vs. exploitation dilemma. In this paper, inspired by the La…
System Identification and Control Using Lyapunov-Based Deep Neural Networks without Persistent Excitation: A Concurrent Learning Approach
Rebecca G. Hart, Omkar Sudhir Patil, Zachary I. Bell +1
Deep Neural Networks (DNNs) are increasingly used in control applications due to their powerful function approximation capabilities. However, many existing formulations focus prima…
Learning Sequential Kinematic Models from Demonstrations for Multi-Jointed Articulated Objects
Anmol Gupta, Weiwei Gu, Omkar Patil +2
As robots become more generalized and deployed in diverse environments, they must interact with complex objects, many with multiple independent joints or degrees of freedom (DoF) r…
Lyapunov-Based Graph Neural Networks for Adaptive Control of Multi-Agent Systems
Brandon C. Fallin, Cristian F. Nino, Omkar Sudhir Patil +2
Graph neural networks (GNNs) have a message-passing framework in which vector messages are exchanged between graph nodes and updated using feedforward layers. The inclusion of dist…
Bounds on Deep Neural Network Partial Derivatives with Respect to Parameters
Omkar Sudhir Patil, Brandon C. Fallin, Cristian F. Nino +2
Deep neural networks (DNNs) have emerged as a powerful tool with a growing body of literature exploring Lyapunov-based approaches for real-time system identification and control. T…
Distributed RISE-based Control for Exponential Heterogeneous Multi-Agent Target Tracking of Second-Order Nonlinear Systems
Cristian F. Nino, Omkar Sudhir Patil, Sage C. Edwards +1
A distributed implementation of a Robust Integral of the Sign of the Error (RISE) controller is developed for multi-agent target tracking problems with exponential convergence guar…
Collaborative Spacecraft Servicing under Partial Feedback using Lyapunov-based Deep Neural Networks
Cristian F. Nino, Omkar Sudhir Patil, Christopher D. Petersen +2
Multi-agent systems are increasingly applied in space missions, including distributed space systems, resilient constellations, and autonomous rendezvous and docking operations. A c…