1 citations · 1 across the 8 of their papers we have counts for
9 papers
Structured World-State Reasoning for Agentic Robotic Search
Finley R. Holt, Luis A. Pabon, John Irvin Alora +2
Long-horizon robotic search must resolve natural language against heterogeneous, incomplete, and often ambiguous evidence: textual information, prior maps, and observations arrivin…
Learning Actuator-Aware Spectral Submanifolds for Precise Control of Continuum Robots
Paul Leonard Wolff, Hugo Buurmeijer, Luis Pabon +6
Continuum robots exhibit high-dimensional, nonlinear dynamics which are often coupled with their actuation mechanism. Spectral submanifold (SSM) reduction has emerged as a leading…
Taming High-Dimensional Dynamics: Learning Optimal Projections onto Spectral Submanifolds
Hugo Buurmeijer, Luis A. Pabon, John Irvin Alora +3
High-dimensional nonlinear systems pose considerable challenges for modeling and control across many domains, from fluid mechanics to advanced robotics. Such systems are typically…
Data-Driven Soft Robot Control via Adiabatic Spectral Submanifolds
Roshan S. Kaundinya, John Irvin Alora, Jonas G. Matt +3
The mechanical complexity of soft robots creates significant challenges for their model-based control. Specifically, linear data-driven models have struggled to control soft robots…
RoboMorph: In-Context Meta-Learning for Robot Dynamics Modeling
Manuel Bianchi Bazzi, Asad Ali Shahid, Christopher Agia +6
The landscape of Deep Learning has experienced a major shift with the pervasive adoption of Transformer-based architectures, particularly in Natural Language Processing (NLP). Nove…
Perfecting Periodic Trajectory Tracking: Model Predictive Control with a Periodic Observer (-MPC)
Luis Pabon, Johannes Köhler, John Irvin Alora +4
In Model Predictive Control (MPC), discrepancies between the actual system and the predictive model can lead to substantial tracking errors and significantly degrade performance an…
Robust Nonlinear Reduced-Order Model Predictive Control
John Irvin Alora, Luis A. Pabon, Johannes Köhler +5
Real-world systems are often characterized by high-dimensional nonlinear dynamics, making them challenging to control in real time. While reduced-order models (ROMs) are frequently…
Data-Driven Spectral Submanifold Reduction for Nonlinear Optimal Control of High-Dimensional Robots
John Irvin Alora, Mattia Cenedese, Edward Schmerling +2
Modeling and control of high-dimensional, nonlinear robotic systems remains a challenging task. While various model- and learning-based approaches have been proposed to address the…
Using Spectral Submanifolds for Nonlinear Periodic Control
Florian Mahlknecht, John Irvin Alora, Shobhit Jain +4
Very high dimensional nonlinear systems arise in many engineering problems due to semi-discretization of the governing partial differential equations, e.g. through finite element m…