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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The vision of unmanned aerial vehicles is very significant for UAV-relatedapplications such as search and rescue, landing on a moving platform, etc. Inthis work, we have developed an integrated system for the UAV landing on themoving platform, and the UAV object detection with tracking in the complicatedenvironment. Firstly, we have proposed a robust LoG-based deep neural networkfor object detection and tracking, which has great advantages in robustness toobject scale and illuminations compared with typical deep network-basedapproaches. Then, we have also improved based on the original Kalman filter anddesigned an iterative multi-model-based filter to tackle the problem of unknowndynamics in real circumstances of motion estimations. Next, we implemented thewhole system and do ROS Gazebo-based testing in two complicated circumstancesto verify the effectiveness of our design. Finally, we have deployed theproposed detection, tracking, and motion estimation strategies into realapplications to do UAV tracking of a pillar and obstacle avoidance. It isdemonstrated that our system shows great accuracy and robustness in realapplications.

An Integrated Visual System for Unmanned Aerial Vehicles Tracking and Landing on the Ground Vehicles