Inertial preintegration for VI‐SLAM by the screw motion theory

Author:

Bessaad Nassim1ORCID,Qilian Bao1,Jiankang Zhao1,Benoudina Nardjess2,Sun Shuodong3,Zhang Xuwei3

Affiliation:

1. Department of Instrument Science and Engineering Shanghai Jiao Tong University Shanghai China

2. Department of Mathematics and Computer Science Zhejiang Normal University Jinhua China

3. Shanghai Aerospace Control Technology Institute Shanghai China

Abstract

AbstractMost smoothing‐based visual‐inertial simultaneous localization and mapping algorithms (VI‐SLAM) rely on the Lie algebra processing of the inertial measurements. This approach is limited in its decoupled update of the attitude by using SO3 and velocity increments by SE3. In addition to limitations on only point transformation between frames. We present a novel approach to handling inertial measurement unit (IMU) measurements between two camera frames by the screw motion theory. Where rigid body dynamics are concisely represented by the compact unit dual quaternion. With this approach, the limitations of point transformation are mitigated by the superior Plücker line transformation and the states update is achieved by a single coupled operation. To harness this consistent framework for a smoothing‐based VI‐SLAM, the screw motion twist parameter is based on the raw IMU measurements. Then, a consistent residual cost function with the corresponding Jacobian and covariance updates is derived for graph‐optimization algorithm respecting the screw motion paradigm. A transition method is proposed to overcome the issues of over‐parametrization by the unit dual quaternion. solving all singularity threats while saving the advantages of adopting the twist operator. Finally, the loftier performance of the proposed algorithms is attested by simulation and real‐world experiments.

Publisher

Wiley

Subject

Computer Science Applications,Control and Systems Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A novel multi-sensor hybrid fusion framework;Measurement Science and Technology;2024-05-02

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