FURI | Fall 2024, Summer 2024

Real-time Dynamics and Control of Soft Robots with Physics-informed Dynamic Mode Decomposition

Existing methods for soft robotic control rely on either large quantities of data or computationally expensive numerical simulations, which makes real-time control intractable and potentially dangerous to human operators. In this research, a new method is proposed that combines the efficiency of data-driven methods with the physical accuracy of numerical simulations, thereby reducing necessary data requirements while improving prediction accuracy. This enables soft robots to function effectively in real-time scenarios, improving their overall utility and safety when working near human operators. Future work involves integrations of this method into more complicated soft robotic systems where their governing physical equations are not necessarily fully known.

Eron Ristich was selected as an Outstanding Student Researcher for his fall 2024 FURI work.