An Accurate Filter-based Visual Inertial External Force Estimator via Instantaneous Accelerometer Update

TL;DR

This paper introduces a high-frequency accelerometer update method for visual inertial external force estimation, improving disturbance accuracy in robotic interactions without relying on force sensors.

Contribution

It presents a novel filter-based estimator that overcomes low-frequency preintegration issues using instantaneous accelerometer updates.

Findings

Enhanced disturbance estimation accuracy

Effective in low-cost, sensorless robotic systems

Improved robustness in physical interaction tasks

Abstract

Accurate disturbance estimation is crucial for reliable robotic physical interaction. To estimate environmental interference in a low-cost and sensorless way (without force sensor), a variety of tightly-coupled visual inertial external force estimators are proposed in the literature. However, existing solutions may suffer from relatively low-frequency preintegration. In this paper, a novel estimator is designed to overcome this issue via high-frequency instantaneous accelerometer update.