Drones, Free Full-Text

Self-localization and state estimation are crucial capabilities for agile drone autonomous navigation. This article presents a lightweight and drift-free vision-IMU-GNSS tightly coupled multisensor fusion (LDMF) strategy for drones’ autonomous and safe navigation. The drone is carried out with a front-facing camera to create visual geometric constraints and generate a 3D environmental map. Ulteriorly, a GNSS receiver with multiple constellations support is used to continuously provide pseudo-range, Doppler frequency shift and UTC time pulse signals to the drone navigation system. The proposed multisensor fusion strategy leverages the Kanade–Lucas algorithm to track multiple visual features in each input image. The local graph solution is bounded in a restricted sliding window, which can immensely predigest the computational complexity in factor graph optimization procedures. The drone navigation system can achieve camera-rate performance on a small companion computer. We thoroughly experimented with the LDMF system in both simulated and real-world environments, and the results demonstrate dramatic advantages over the state-of-the-art sensor fusion strategies.

[Juniper, Adam] on . *FREE* shipping on qualifying offers. The Complete Guide to Drones, Extended and Fully Updated 2nd Edition: Choose,

The Complete Guide to Drones, Extended and Fully Updated 2nd Edition: Choose, Build, Photograph, Race

Drones Free Full-Text A Visual Aquaculture System Using A Cloud

What Is a Drone?

The complete beginner's guide to drone photography

Drones may have attacked humans fully autonomously for the first

MSU Team Developing Lightweight Anti-Icing System for Drones

Drones, Free Full-Text

Drone Prohibition District - Free Powerpoint Template

Drones Free Full-Text Flying Free: A Research Overview Of Deep

Drone Express teams up with Microsoft on navigation AI