AquaMILR: Mechanical intelligence simplifies control of undulatory robots in cluttered fluid environments

TL;DR

This paper introduces AquaMILR, an untethered limbless robot that uses passive body mechanics and real-time compliance tuning to navigate complex aquatic environments effectively, demonstrating the extension of mechanical intelligence principles to fluid regimes.

Contribution

The study presents a novel undulatory robot with programmable anisotropic body compliance and a real-time tension-based control system for obstacle navigation in cluttered water environments.

Findings

Passive body compliance facilitates emergent swimming in complex environments.

Optimal undulation frequency is crucial for effective locomotion.

Real-time compliance tuning improves robustness and speed.

Abstract

While undulatory swimming of elongate limbless robots has been extensively studied in open hydrodynamic environments, less research has been focused on limbless locomotion in complex, cluttered aquatic environments. Motivated by the concept of mechanical intelligence, where controls for obstacle navigation can be offloaded to passive body mechanics in terrestrial limbless locomotion, we hypothesize that principles of mechanical intelligence can be extended to cluttered hydrodynamic regimes. To test this, we developed an untethered limbless robot capable of undulatory swimming on water surfaces, utilizing a bilateral cable-driven mechanism inspired by organismal muscle actuation morphology to achieve programmable anisotropic body compliance. We demonstrated through robophysical experiments that, similar to terrestrial locomotion, an appropriate level of body compliance can facilitate emergent swim through complex hydrodynamic environments under pure open-loop control. Moreover, we found that swimming performance depends on undulation frequency, with effective locomotion achieved only within a specific frequency range. This contrasts with highly damped terrestrial regimes, where inertial effects can often be neglected. Further, to enhance performance and address the challenges posed by nondeterministic obstacle distributions, we incorporated computational intelligence by developing a real-time body compliance tuning controller based on cable tension feedback. This controller improves the robot's robustness and overall speed in heterogeneous hydrodynamic environments.