The Deterministic Design of an Origami-Based Tentacle for Stochastic Robust Gripping

Abstract

Soft robotic grippers help create safe interactions for grasping, manipulation, and object capture, especially in complex or unknown environments. However, challenges are present in the creation of such robust grippers that can successfully adapt to grasp various objects in differing environments without major design changes. This work aims to create such a gripper, through the design of a deterministic origami-inspired tentacle and discovering its emergent stochastic behaviors in a collective manner. By reducing the origami tentacle into basic kinematic models, rigid-body robotic principles can be used to understand this tentacles behavior. Furthermore, by optimizing the tentacle fabrication process and defining systematic parameters, repeatable single tentacle results can inform collective gripper trends. Results show that helical coiling can be generated for target object grasping through altering tendon hole positions and origami fold lines, and an increase in coiling behavior correlates to a more robust gripper system. This approach introduces the synergistic relationship between a deterministic single tentacle and stochastic collective behavior, giving insights into how to better create multi-tentacle soft robotic grippers for all use cases.