Coordinated appendages accumulate more energy to self-right on the ground

TL;DR

This study models how coordinated appendage movements in animals and robots influence energy accumulation and improve self-righting ability after flipping, highlighting the importance of wing-leg phase coordination.

Contribution

The paper introduces a template model that explains how wing-leg coordination affects energy dynamics and self-righting success in cockroach-inspired robots.

Findings

Well-coordinated appendage motions increase mechanical energy accumulation.

Phase coordination significantly impacts the ability to overcome the energy barrier.

The template can predict control strategies to enhance self-righting performance.

Abstract

Animals and robots must right themselves after flipping over on the ground. The discoid cockroach pushes its wings against the ground in an attempt to dynamically self-right by a somersault. However, because this maneuver is strenuous, the animal often fails to overcome the potential energy barrier and makes continual attempts. In this process, the animal flails its legs, whose lateral perturbation eventually leads it to roll to the side to self-right. Our previous work developed a cockroach-inspired robot capable of leg-assisted, winged self-righting, and a robot simulation study revealed that the outcome of this strategy depends sensitively on wing-leg coordination (measured by the phase between their motions). Here, we further elucidate why this is the case by developing a template to model the complex hybrid dynamics resulting from discontinuous contact and actuation. We used the template to calculate the potential energy barrier that the body must overcome to self-right, mechanical energy contribution by wing pushing and leg flailing, and mechanical energy dissipation due to wing-ground collision. The template revealed that wing-leg coordination (phase) strongly affects self-righting outcome by changing mechanical energy budget. Well-coordinated appendage motions (good phase) accumulate more mechanical energy than poorly-coordinated motions (bad phase), thereby better overcoming the potential energy barrier to self-right more successfully. Finally, we demonstrated practical use of the template for predicting a new control strategy to further increase self-righting performance and informing robot design.