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

The technology of unmanned aerial vehicles (UAVs) has increasingly become part of many civil and research applications in recent years. UAVs offer high-quality aerial imaging and the ability to perform quick, flexible and in-depth data acquisition over an area of interest. While navigating in remote environments, UAVs need to be capable of autonomously landing on complex terrains for security, safety and delivery reasons. This is extremely challenging as the structure of these terrains is often unknown, and no prior knowledge can be leveraged. In this study, we present a vision-based autonomous landing system for rotor wing UAVs equipped with a stereo camera and an inertial measurement unit (IMU). The landing site detection algorithm introduces and evaluates several factors including terrain’s flatness, inclination and steepness. Considering these features we compute map metrics that are used to obtain a landing-score map, based on which we detect candidate landing sites. The 3D reconstruction of the scene is acquired by stereo processing and the pose of the UAV at any given time is estimated by fusing raw data from the inertial sensors with the pose obtained from stereo ORB-SLAM2. Real-world trials demonstrate successful landing in unknown and complex terrains such as suburban and forest areas.

Landing Site Detection for Autonomous Rotor Wing UAVs Using Visual and Structural Information