Conference
Ship, Guide My Landing! A Binocular Extended Kalman Filter for Maritime UAV Landing Operations
OCEANS 2024 - Halifax
2024 — IEEE
—Key information
Authors:
Published in
11/25/2024
Abstract
Unmanned Aerial Vehicles (UAVs) are continuously being explored as important means of decreasing human intervention and improving system reliability. The more challenging tasks when operating with UAVs are take-off and landing. Most low-size UAVs can have their take-off performed by hand, but the capacity to perform autonomous landing is essential. The autonomous landing environment is usually challenging since we are considering a moving platform, and the system must be able to deal with Global Position System (GPS)-denied environments. The proposed system is based on a ground-based stereoscopic vision system with temporal filtering based on an Extended Kalman Filter (EKF) to track the position of a rotary-wing UAV during landing. The obtained position detects and guides the rotary-wing UAV during landing. The initial results indicate that this setup has the potential to track with low error, demonstrating its suitability for exploration and further improvements.
Publication details
Authors in the community:
Bruno Duarte Damas
ist45387
Publication version
VoR - Version of Record
Publisher
IEEE
Link to the publisher's version
https://ieeexplore.ieee.org/document/10753980
Title of the publication container
OCEANS 2024 - Halifax
Fields of Science and Technology (FOS)
electrical-engineering-electronic-engineering-information-engineering - Electrical engineering, electronic engineering, information engineering
Keywords
- Unmanned Aerial Vehicles
- Computer Vision
- Motion Estimation
- Kalman Filters
- Landing Maneuver
- Maritime Robotics
- Three-dimensional displays
- Stereo image processing
Publication language (ISO code)
eng - English
Rights type:
Open access