Stochastic Entanglement of Deterministic Origami Tentacles For Universal Robotic Gripping
Alec Boron, Bokun Zheng, Ziyang Zhou, Noel Naughton, Suyi Li

TL;DR
This paper introduces a tendon-driven origami tentacle gripper that combines deterministic deformation programming with stochastic entanglement to achieve universal object gripping in various environments.
Contribution
It presents a novel origami tentacle design that leverages both programmed deformation and emergent entanglement for robust, adaptable grasping.
Findings
Successfully demonstrated grasping of objects with random shapes.
Developed a simulation model linking origami design, tendon actuation, and gripping performance.
Validated the gripper's effectiveness in gravity and water environments, including in-orbit deployment.
Abstract
Origami-inspired robotic grippers have shown promising potential for object manipulation tasks due to their compact volume and mechanical flexibility. However, robust capture of objects with random shapes in dynamic working environments often comes at the cost of additional actuation channels and control complexity. Here, we introduce a tendon-driven origami tentacle gripper capable of universal object gripping by exploiting a synergy between local, deterministic deformation programming and global, stochastic entanglements. Each origami tentacle is made by cutting thin Mylar sheets; It features carefully placed holes for routing an actuation tendon, origami creases for controlling the deformation, and a tapered shape. By tailoring these design features, one can prescribe the shrinking, bending, and twisting deformation, eventually creating deterministic coiling with a simple tendon…
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