Elephant trunk-Inspired Reaching and Grasping Strategies for Soft Robots Control

This Ph.D. thesis investigates biologically inspired modeling and control of soft continuum robots, informed by the functional principles of reaching movements and grasping behaviors observed in the elephant trunk. The research is structured around two main contributions. The first focuses on the development of a three-dimensional dynamic model of the elephant trunk using rod theory, capturing its structure as a segmented system with muscle-like actuation. Using experimental motion data, the model enables accurate simulation of planar reaching tasks and allows the derivation of linear force–shape mappings, termed stereotypical laws, which relate desired trunk configurations to internal actuation forces. The extracted laws reveal that trunk postures are associated with repeatable internal force patterns, offering a framework to determine actuation strategies for generating specific shapes during planar reaching. By distilling the trunk’s complex dynamics into simple, linear relationships, this work takes a first step toward bridging the gap between desired configurations and the forces required to realize them. The second contribution concerns the design of whole-arm grasping strategies for soft robotic arms, inspired by the grasping behavior of the elephant trunk. The strategy is implemented in a simulation framework combining Finite Element Modeling (FEM) and Reinforcement Learning (RL), and tested in the context of space debris capture. By introducing space dynamics concepts, such as free-floating behavior and relative motion between robot and target, the simulations demonstrate the effectiveness of the strategy and its robustness to perturbations. Curriculum learning techniques further improve policy convergence and generalization. Overall, the thesis establishes a methodology for deeper exploration of elephant trunk motion strategies and their translation into advanced robotic control frameworks, while also demonstrating the possibility of developing simplified grasping strategies for soft robotic arms operating in complex and unstructured environments, such as space debris capture.