5 papers
From Local to Global: Sheaf-Theoretic Control Barrier Functions on Manifolds
Keith A. Currier, Wilmer Leal, Brandon C. Fallin +2
Control barrier functions (CBFs) provide formal safety guarantees for dynamical systems by rendering a safe set forward-invariant via pointwise-optimal feedback control. While the…
Skeletons in Flow: Graph Structured Flow Matching for Human Motion Prediction
Yixuan Wang, Brandon C. Fallin, Warren E. Dixon
Human motion prediction requires diverse future trajectories that remain consistent with observed motion and the articulated physical structure of the body. Skeletal constraints re…
Collaborative Indirect Influencing and Control on Graphs using Graph Neural Networks
Max L. Gardenswartz, Brandon C. Fallin, Cristian F. Nino +1
This paper presents a novel approach to solving the indirect influence problem in networked systems, in which cooperative nodes must regulate a target node with uncertain dynamics…
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…