Rocco Jude Barletta
Aerospace engineering
Hometown: Scottsdale, Arizona, United States
Graduation date: Spring 2027
Additional details: Honors student
FURI | Fall 2025
GNN-MPC for Path Following of Deformable Bodies
Current methodologies in robotics can handle rigid parts, but struggle with deformable structures like ropes and cables. High-fidelity models are too slow for real-time control, while hand-tuned models break when conditions change, limiting real-world application. This is fixed by training a Graph Neural Network (GNN) on Discrete Elastic Rod (DER) simulations and embedding this into a model predictive controller (MPC). The GNN captures the dynamics while the MPC guides the system to follow a prescribed path. This makes it possible to achieve real-time tracking and control with outstanding accuracy at a fraction of the computational effort, improving robustness/reproducibility.
Mentor: Leixin Ma
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