Control of Deformable Systems Using Structure-Aware Density Models and Density Steering Algorithms

NSF Award Search · 01002526DB NSF RESEARCH & RELATED ACTIVIT · $300,000 · view on nsf.gov ↗

Abstract

This award supports research that seeks to enable new theory and algorithms for modeling and control of deformable systems with an emphasis on soft robots, thereby advancing the national health, promoting the progress of science, advancing prosperity and welfare, and securing the national defense. Deformable systems are infinite-dimensional systems that can undergo continuous deformations while moving in their configuration space. Control methods for deformable systems are scarce and their applicability is limited to certain types of systems (e.g., rod-like soft robots). In principle, one can design (model-based) controllers for deformable systems by using Finite Element Models (FEMs). Model reduction methods and/or local linearization techniques can reduce the complexity of FEMs but also lead to the design of unreliable controllers. This project looks to solve this challenge by developing a coarse deterministic FEM whereas its state is represented by a multi-modal density model and synthesizing control methods leveraging multi-modal density steering problems and Koopman operator theory. The special property of deformable systems allows them to find many applications in manufacturing (e.g., handling fragile objects during assembly and packaging), healthcare (e.g., soft robotic prosthetics), search and rescue (e.g., reaching locations under the ruins of collapsed buildings), and agriculture (e.g., soft gripping and harvesting of fruits and vegetables), to name but a few. In ad

Key facts

NSF award ID
2523754
Awardee
University of Texas at Austin (TX)
SAM.gov UEI
V6AFQPN18437
PI
Efstathios Bakolas
Primary program
01002526DB NSF RESEARCH & RELATED ACTIVIT
All programs
CONTROL SYSTEMS, Dynamical systems, ROBOTICS
Estimated total
$300,000
Funds obligated
$300,000
Transaction type
Standard Grant
Period
08/15/2025 → 07/31/2027