Jump to main content
Jump to site search


Architectures of soft robotic locomotion enabled by simple mechanical principles

Author affiliations

Abstract

In nature, a variety of limbless locomotion patterns flourish, from the small or basic life forms (Escherichia coli, amoebae, etc.) to the large or intelligent creatures (e.g., slugs, starfishes, earthworms, octopuses, jellyfishes, and snakes). Many bioinspired soft robots based on locomotion have been developed in the past few decades. In this work, based on the kinematics and dynamics of two representative locomotion modes (i.e., worm-like crawling and snake-like slithering), we propose a broad set of innovative designs for soft mobile robots through simple mechanical principles. Inspired by and going beyond the existing biological systems, these designs include 1-D (dimensional), 2-D, and 3-D robotic locomotion patterns enabled by the simple actuation of continuous beams. We report herein over 20 locomotion modes achieving various locomotion functions, including crawling, rising, running, creeping, squirming, slithering, swimming, jumping, turning, turning over, helix rolling, wheeling, etc. Some are able to reach high speed, high efficiency, and overcome obstacles. All these locomotion strategies and functions can be integrated into a simple beam model. The proposed simple and robust models are adaptive for severe and complex environments. These elegant designs for diverse robotic locomotion patterns are expected to underpin future deployments of soft robots and to inspire a series of advanced designs.

Graphical abstract: Architectures of soft robotic locomotion enabled by simple mechanical principles

Back to tab navigation

Supplementary files

Publication details

The article was received on 29 Mar 2017, accepted on 01 Jun 2017 and first published on 02 Jun 2017


Article type: Paper
DOI: 10.1039/C7SM00636E
Citation: Soft Matter, 2017, Advance Article
  •   Request permissions

    Architectures of soft robotic locomotion enabled by simple mechanical principles

    L. Zhu, Y. Cao, Y. Liu, Z. Yang and X. Chen, Soft Matter, 2017, Advance Article , DOI: 10.1039/C7SM00636E

Search articles by author

Spotlight

Advertisements