Coherent movement of error-prone individuals through mechanical coupling.

Journal: Nature communications
PMID:

Abstract

We investigate how reliable movement can emerge in aggregates of highly error-prone individuals. The individuals-robotic modules-move stochastically using vibration motors. By coupling them via elastic links, soft-bodied aggregates can be created. We present distributed algorithms that enable the aggregates to move and deform reliably. The concept and algorithms are validated through formal analysis of the elastic couplings and experiments with aggregates comprising up to 49 physical modules-among the biggest soft-bodied aggregates to date made of autonomous modules. The experiments show that aggregates with elastic couplings can shrink and stretch their bodies, move with a precision that increases with the number of modules, and outperform aggregates with no, or rigid, couplings. Our findings demonstrate that mechanical couplings can play a vital role in reaching coherent motion among individuals with exceedingly limited and error-prone abilities, and may pave the way for low-power, stretchable robots for high-resolution monitoring and manipulation.

Authors

  • Federico Pratissoli
    Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Reggio Emilia, Italy.
  • Andreagiovanni Reina
    Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK.
  • Yuri Kaszubowski Lopes
    Department of Computer Science, Santa Catarina State University, Joinville, Brazil.
  • Carlo Pinciroli
    Department of Robotics Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.
  • Genki Miyauchi
    Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK.
  • Lorenzo Sabattini
    Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Reggio Emilia, Italy.
  • Roderich Groß
    Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK. r.gross@sheffield.ac.uk.