# Accurate IMU Preintegration Using Switched Linear Systems For Autonomous Systems

arXiv: https://arxiv.org/abs/1907.08434 · HTML: https://mlsanity.com/paper/1907.08434/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jul 2019.

## Built on by (most cited first, 2 of 2)

- [Probabilistic Spatial Distribution Prior Based Attentional Keypoints Matching Network](https://mlsanity.com/paper/2111.09006/) (2021)
- [Deep Inertial Odometry with Accurate IMU Preintegration](https://mlsanity.com/paper/2101.07061/) (2021)

## Abstract (arXiv)

Employing an inertial measurement unit (IMU) as an additional sensor can dramatically improve both reliability and accuracy of visual/Lidar odometry (VO/LO). Different IMU integration models are introduced using different assumptions on the linear acceleration from the IMU. In this paper, a novel IMU integration model is proposed by using switched linear systems. The proposed approach assumes that both the linear acceleration and the angular velocity in the body frame are constant between two consecutive IMU measurements. This is more realistic in real world situation compared to existing approaches which assume that linear acceleration is constant in the world frame while angular velocity is constant in the body frame between two successive IMU measurements. Experimental results show that the proposed approach outperforms the state-of-the-art IMU integration model. The proposed model is thus important for localization of high speed autonomous vehicles in GPS denied environments.