  The inertial measurement unit (IMU) preintegration approach nowadays is
widely used in various robotic applications. In this article, we revisit the
preintegration theory and propose a novel interpretation to understand it from
a nonlinear observer perspective, specifically the parameter estimation-based
observer (PEBO). We demonstrate that the preintegration approach can be viewed
as recursive implementation of PEBO in moving horizons, and that the two
approaches are equivalent in the case of perfect measurements. We then discuss
how these findings can be used to tackle practical challenges in estimation
problems. As byproducts, our results lead to a novel hybrid sampled-data
observer design and an approach to address statistical optimality for PEBO in
presence of noise.
