2019/10/29 by Wei‐Hsi Chen, Wei-Hsi Chen, Shivangi Misra +14
Computer Science · Engineering · Mathematics · #Advanced Materials and Mechanics #Advanced Sensor and Energy Harvesting Materials #Artificial intelligence #Ball (mathematics) #Ball screw #Computer science #Control theory (sociology) #Engineering #FOS: Computer and information sciences #Geometry #Hinge #Mathematics #Mechanical engineering #Mechanism (biology) #Physics #Robot #Robotics (cs.RO) #Simulation #Soft Robotics and Applications #Stiffness #Structural engineering #cs.RO
paper · pdf · doi:10.48550/arxiv.1910.13584
published in arXiv (Cornell University) (Cornell University) · This paper is submitted to the IEEE Robotics and Automation Letters, in review
arxiv created 2019/10/29 · openalex publication_date 2019/10/29 · arxiv updated 2019/10/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
We present an approach to overcoming challenges in dynamical dexterity for robots through tunable origami structures. Our work leverages a one-parameter family of flat sheet crease patterns that folds into origami bellows, whose axial compliance can be tuned to select desired stiffness. Concentrically arranged cylinder pairs reliably manifest additive stiffness, extending the tunable range by nearly an order of magnitude and achieving bulk axial stiffness spanning 200-1500 N/m using 8 mil thick polyester-coated paper. Accordingly, we design origami energy-storing springs with a stiffness of 1035 N/m each and incorporate them into a three degree-of-freedom (DOF) tendon-driven spatial pointing mechanism that exhibits trajectory tracking accuracy less than 15% rms error within a ~2 cm3 volume. The origami springs can sustain high power throughput, enabling the robot to achieve asymptotically stable juggling for both highly elastic (1~kg resilient shot put ball) and highly damped ("medicine ball") collisions in the vertical direction with apex heights approaching 10 cm. The results demonstrate that "soft" robotic mechanisms are able to perform a controlled, dynamically actuated task.