Ultra-fast escape maneuver of an octopus-inspired robot

TL;DR

This paper presents a novel octopus-inspired robot that rapidly deflates to achieve ultra-fast escape maneuvers, demonstrating superior speed and energy recovery compared to traditional rigid bodies.

Contribution

The study introduces a flexible, inflatable robot that leverages rapid size change for enhanced escape performance, verifying fluid energy recovery in laboratory tests for the first time.

Findings

Robot reaches speeds over ten body lengths per second.

Peak thrust exceeds 2.6 times that of an optimal rigid body.

Over 53% of energy is converted into payload kinetic energy.

Abstract

We design and test an octopus-inspired flexible hull robot that demonstrates outstanding fast-starting performance. The robot is hyper-inflated with water, and then rapidly deflates to expel the fluid so as to power the escape maneuver. Using this robot we verify for the first time in laboratory testing that rapid size-change can substantially reduce separation in bluff bodies traveling several body lengths, and recover fluid energy which can be employed to improve the propulsive performance. The robot is found to experience speeds over ten body lengths per second, exceeding that of a similarly propelled optimally streamlined rigid rocket. The peak net thrust force on the robot is more than 2.6 times that on an optimal rigid body performing the same maneuver, experimentally demonstrating large energy recovery and enabling acceleration greater than 14 body lengths per second squared. Finally, over 53% of the available energy is converted into payload kinetic energy, a performance that exceeds the estimated energy conversion efficiency of fast-starting fish. The Reynolds number based on final speed and robot length is $Re \approx 700,000$. We use the experimental data to establish a fundamental deflation scaling parameter $\sigma^*$ which characterizes the mechanisms of flow control via shape change. Based on this scaling parameter, we find that the fast-starting performance improves with increasing size.