An Autonomous Tracking and Landing Method for Unmanned Aerial Vehicles Based on Visual Navigation

Autor: Bingkun Wang, Ruitao Ma, Hang Zhu, Yongbai Sha, Tianye Yang
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Drones, Vol 7, Iss 12, p 703 (2023)
Druh dokumentu: article
ISSN: 2504-446X
DOI: 10.3390/drones7120703
Popis: In this paper, we examine potential methods for autonomously tracking and landing multi-rotor unmanned aerial vehicles (UAVs), a complex yet essential problem. Autonomous tracking and landing control technology utilizes visual navigation, relying solely on vision and landmarks to track targets and achieve autonomous landing. This technology improves the UAV’s environment perception and autonomous flight capabilities in GPS-free scenarios. In particular, we are researching tracking and landing as a cohesive unit, devising a switching plan for various UAV tracking and landing modes, and creating a flight controller that has an inner and outer loop structure based on relative position estimation. The inner and outer nested markers aid in the autonomous tracking and landing of UAVs. Optimal parameters are determined via optimized experiments on the measurements of the inner and outer markers. An indoor experimental platform for tracking and landing UAVs was established. Tracking performance was verified by tracking three trajectories of an unmanned ground vehicle (UGV) at varying speeds, and landing accuracy was confirmed through static and dynamic landing experiments. The experimental results show that the proposed scheme has good dynamic tracking and landing performance.
Databáze: Directory of Open Access Journals