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 Plus annual

Presents the access of premium content as premium feature

Premium Content

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 annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper discusses the design of computer vision and odometer integrated autonomous navigation algorithm based on RatSLAM system for land vehicles. The research aims at testing the effectiveness of a vision/odometer bio-inspired navigation approach for land vehicle applications. Images and odometer measurements are inputted into the RatSLAM system. Odometer data can be used to improve the robustness of RatSLAM system significantly. The proposed system has been verified on real vision/odometer data collected in land vehicle tests. Campus round road experiments illustrate that the algorithm is effective and robust.

Vision/Odometer Autonomous Navigation Based on RatSLAM for Land Vehicles