Optimization free control and ground force estimation with momentum observer for a multimodal legged aerial robot

TL;DR

This paper introduces an optimization-free control framework for a multimodal legged-aerial robot that estimates ground forces and maintains stability using a momentum observer and an explicit reference governor, reducing computational load.

Contribution

It presents a novel control approach combining an explicit reference governor with a momentum observer for ground force estimation, avoiding heavy optimization computations.

Findings

The ERG effectively filters velocity references to prevent slippage.

The momentum observer accurately estimates ground reaction forces in simulations.

The framework reduces computational complexity compared to traditional optimization-based methods.

Abstract

Legged-aerial multimodal robots can make the most of both legged and aerial systems. In this paper, we propose a control framework that bypasses heavy onboard computers by using an optimization-free Explicit Reference Governor that incorporates external thruster forces from an attitude controller. Ground reaction forces are maintained within friction cone constraints using costly optimization solvers, but the ERG framework filters applied velocity references that ensure no slippage at the foot end. We also propose a Conjugate momentum observer, that is widely used in Disturbance Observation to estimate ground reaction forces and compare its efficacy against a constrained model in estimating ground reaction forces in a reduced-order simulation of Husky.