Inverse Statics Optimization for Compound Tensegrity Robots

TL;DR

This paper introduces a novel inverse statics optimization method for compound tensegrity robots with arbitrary rigid bodies, enabling improved design and control through a quadratic optimization approach validated by simulations and hardware experiments.

Contribution

It reformulates the static equilibrium model for compound tensegrity robots and proposes a quadratic optimization solution for tension calculation, advancing tensegrity robot modeling and control.

Findings

The method accurately computes cable tensions in compound tensegrity robots.

Simulations demonstrate effectiveness in spine and quadruped robots.

Hardware experiments confirm low-error open-loop control feasibility.

Abstract

Robots built from cable-driven tensegrity (`tension-integrity') structures have many of the advantages of soft robots, such as flexibility and robustness, while still obeying simple statics and dynamics models. However, existing tensegrity modeling approaches cannot natively describe robots with arbitrary rigid bodies in their tension network. This work presents a method to calculate the cable tensions in static equilibrium for such tensegrity robots, here defined as compound tensegrity. First, a static equilibrium model for compound tensegrity robots is reformulated from the standard force density method used with other tensegrity structures. Next, we pose the problem of calculating tension forces in the robot's cables under our proposed model. A solution is proposed as a quadratic optimization problem with practical constraints. Simulations illustrate how this inverse statics optimization problem can be used for both the design and control of two different compound tensegrity applications: a spine robot and a quadruped robot built from that spine. Finally, we verify the accuracy of the inverse statics model through a hardware experiment, demonstrating the feasibility of low-error open-loop control using our proposed methodology.