# Accurate IMU Preintegration Using Switched Linear Systems For Autonomous   Systems

**Authors:** John Henawy, Zhengguo Li, Wei Yun Yau, Gerald Seet, Kong Wah Wan

arXiv: 1907.08434 · 2019-12-03

## TL;DR

This paper introduces a novel IMU preintegration method using switched linear systems, improving accuracy for autonomous vehicle localization in GPS-denied environments by modeling constant acceleration and angular velocity between measurements.

## Contribution

A new IMU integration model based on switched linear systems that assumes constant acceleration and angular velocity between measurements, outperforming existing models.

## Key findings

- Outperforms state-of-the-art IMU integration models
- Enhances localization accuracy for high-speed autonomous vehicles
- Effective in GPS-denied environments

## Abstract

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.

## Full text

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## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/1907.08434/full.md

## References

32 references — full list in the complete paper: https://tomesphere.com/paper/1907.08434/full.md

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Source: https://tomesphere.com/paper/1907.08434