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

Song, Junlin, Richard, Antoine, Olivares-Mendez, Miguel

arXiv.org Artificial Intelligence 

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.

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