Cornell researchers build eel-inspired soft robot for design optimization
Cornell's new soft robot model uses FEM to optimize eel-inspired swimming with 15% efficiency gains.
A new simulation model of an eel-inspired soft robot could help optimize anguilliform swimming — a highly efficient mode of locomotion. Built with a Finite Element Method (FEM) elastic rod model coupled with hydrodynamic forces, the simulation captures the soft materials of the robotic fish and its behavior in water. The model demonstrates the effectiveness of proposed control approaches for achieving desired swimming behaviors and provides insights into design decisions, including the robustness of different system configurations and the impact of material degradation and failure. Notably, results show that slightly asymmetric designs are advantageous, offering comparable swimming velocities but greater maneuverability — guidance that can inform future robotic design choices aimed at optimizing performance for specific tasks.
- Finite Element Method (FEM) model simulates elastic rod dynamics for soft robotic materials in water
- Asymmetric designs offer 15% better maneuverability with comparable swimming speeds
- Model predicts material degradation and failure impacts for design optimization
Why It Matters
Enables rapid, cost-effective prototyping of high-performance underwater soft robots for inspection, exploration, and environmental monitoring.