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Anatomy-based organization of morphology and control in self-reconfigurable modular robots

  • Technical University of Denmark
    ,
  • Intel
    ,
  • University of Southern Denmark
Research Output:
Journal Article or Conference Article in Journal
Journal article
Research

Open access

Abstract

In this paper, we address the challenge of realizing full-body behaviors in scalable modular robots. We present an experimental study of a biologically inspired approach to organize the morphology and control of modular robots. The approach introduces a nested hierarchy that decomposes the complexity of assembling and commanding a functional robot made of numerous simple modules. The purpose is to support versatility, scalability, and provide design abstraction. The robots we describe incorporate anatomy-inspired parts such as muscles, bones, and joints, and these parts in turn are assembled from modules. Each of those parts encapsulates one or more functions, e.g., a muscle can contract. Control of the robot can then be cast as a problem of controlling its anatomical parts rather than each discrete module. To validate this approach, we perform experiments with micron-scale spherical catom modules in simulation. The robots we simulate are increasingly complex and include snake, crawler, quadruped, cilia surface, arm-joint-muscle, and grasping robots. We conclude that this is a promising approach for future microscopic many-modules systems, but also that it is not applicable to relatively weak and slow homogeneous systems such as the centimeter-scale ATRON.

Publication Information

Output type

Research Output:
Journal Article or Conference Article in Journal
Journal article
Research

Original language

Undefined/Unknown

Pages from-to (Number of pages)

Pages 787-805 (19 pages)

Journal (Volume, Issue Number)

Neural Computing and Applications (Volume 19, Issue 6)

Publication milestones

  • Published - 2010

Publication status

Published - 2010

ISSN

0941-0643

Publication IDs

  • Scopus: 77955711989

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Citation count
25
Captures
18