English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

In this paper, we present a novel stereo visual inertial pose estimationmethod. Compared to the widely used filter-based or optimization-basedapproaches, the pose estimation process is modeled as a control system.Designed feedback or feedforward loops are introduced to achieve the stablecontrol of the system, which include a gradient decreased feedback loop, aroll-pitch feed forward loop and a bias estimation feedback loop. This system,named FLVIS (Feedforward-feedback Loop-based Visual Inertial System), isevaluated on the popular EuRoc MAV dataset. FLVIS achieves high accuracy androbustness with respect to other state-of-the-art visual SLAM approaches. Thesystem has also been implemented and tested on a UAV platform. The source codeof this research is public to the research community.

Stereo Visual Inertial Pose Estimation Based on Feedforward-Feedback Loops