Harnessing Nonuniform Pressure Distributions in Soft Robotic Actuators

Abstract

Herein, complex motion in soft, fluid‐driven actuators composed of elastomer bladders arranged around a neutral plane and connected by slender tubes is demonstrated. Rather than relying on complex feedback control or multiple inputs, the motion is generated with a single pressure input, leveraging viscous flows within the actuator to produce nonuniform pressure between bladders. Using an accurate predictive model coupling with a large deformation Cosserat rod model and low‐Reynolds‐number flow, all dominating dynamic interactions including extension and curvature are captured with two governing equations. Given insights from this model, five design elements are described and demonstrated in practice. By choosing the relative timescales between the solid, fluid, and input pressure cycles, the tip of the actuator can obtain almost any desired trajectory and can be placed anywhere temporarily within its 2D workspace. Finally, the benefits of viscous‐driven soft actuators are showcased in a six‐legged untethered robot able to walk 0.05 body lengths per second. The foundation is laid for a new class of morphologically intelligent, soft robotic actuators that enables complex deformations and multifunctionality without explicit drivers; whereby generating nonuniform pressure distributions, their infinite degrees of freedom can be exploited.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 20, 2023
Source ID
10.1002/aisy.202200330

Entities

People

  • Amir D Gat
  • Gregory H. Kaiser
  • Kirstin Petersen
  • Nathan Lazarus
  • Robert F Shepherd
  • Yoav Matia

Organizations

  • Cornell University
  • David and Lucile Packard Foundation
  • National Science Foundation
  • Oak Ridge Associated Universities
  • Technion – Israel Institute of Technology
  • United States Army Research Laboratory
  • University of Delaware

Tags

Fields of Study

  • Physics

Readers

  • Robotics and Automation.
  • Structural Dynamics.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • Autonomy