Modeling, sensing, and control for agile trajectory tracking of soft robots

Accurate, agile trajectory tracking is important for modern soft robotic applications. This requires models that accurately represent dynamic behavior, soft sensors for state estimation, and dynamic controllers. In this work, first, different model-based and data-driven modeling approaches for soft robots are presented and evaluated in terms of accuracy and efficiency. Second, curvature sensors that can be integrated into the soft robot body to measure its configuration are presented and evaluated experimentally. Third, feedforward and feedback control approaches for soft robots are presented and evaluated in simulations and experiments.