Mechanical intelligence simplifies control in terrestrial limbless locomotion

Author:

Wang Tianyu123ORCID,Pierce Christopher24,Kojouharov Velin3,Chong Baxi2ORCID,Diaz Kelimar2ORCID,Lu Hang4ORCID,Goldman Daniel I.12ORCID

Affiliation:

1. Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, 801 Atlantic Dr NW, Atlanta, GA 30332, USA.

2. School of Physics, Georgia Institute of Technology, 837 State St NW, Atlanta, GA 30332, USA.

3. George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 801 Ferst Dr NW, Atlanta, GA 30318, USA.

4. School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, 311 Ferst Dr, Atlanta, GA 30332, USA.

Abstract

Limbless locomotors, from microscopic worms to macroscopic snakes, traverse complex, heterogeneous natural environments typically using undulatory body wave propagation. Theoretical and robophysical models typically emphasize body kinematics and active neural/electronic control. However, we contend that because such approaches often neglect the role of passive, mechanically controlled processes (those involving “mechanical intelligence”), they fail to reproduce the performance of even the simplest organisms. To uncover principles of how mechanical intelligence aids limbless locomotion in heterogeneous terradynamic regimes, here we conduct a comparative study of locomotion in a model of heterogeneous terrain (lattices of rigid posts). We used a model biological system, the highly studied nematode worm Caenorhabditis elegans , and a robophysical device whose bilateral actuator morphology models that of limbless organisms across scales. The robot’s kinematics quantitatively reproduced the performance of the nematodes with purely open-loop control; mechanical intelligence simplified control of obstacle navigation and exploitation by reducing the need for active sensing and feedback. An active behavior observed in C. elegans , undulatory wave reversal upon head collisions, robustified locomotion via exploitation of the systems’ mechanical intelligence. Our study provides insights into how neurally simple limbless organisms like nematodes can leverage mechanical intelligence via appropriately tuned bilateral actuation to locomote in complex environments. These principles likely apply to neurally more sophisticated organisms and also provide a design and control paradigm for limbless robots for applications like search and rescue and planetary exploration.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Mechanical Engineering

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