Autonomous Landing of Micro Unmanned Aerial Vehicles with Landing-Assistive Platform and Robust Spherical Object Detection
Source abstract
Abstract
Autonomous unmanned aerial vehicle (UAV) landing can be useful in multiple applications. Precise landing is a difficult task because of the significant navigation errors of the global positioning system (GPS). To overcome these errors and to realize precise landing control, various sensors have been installed on UAVs. However, this approach can be challenging for micro UAVs (MAVs) because strong thrust forces are required to carry multiple sensors. In this study, a new autonomous MAV landing system is proposed, in which a landing platform actively assists vehicle landing. In addition to the vision system of the UAV, a camera was installed on the platform to precisely control the MAV near the landing area. The platform was also designed with various types of equipment to assist the MAV in searching, approaching, alignment, and landing. Furthermore, a novel algorithm was developed for robust spherical object detection under different illumination conditions. To validate the proposed landing system and detection algorithm, 80 flight experiments were conducted using a DJI TELLO drone, which successfully landed on the platform in every trial with a small landing position average error of 2.7 cm.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Robotics and Sensor-Based Localization · Robotic Path Planning Algorithms · UAV Applications and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechanical Engineering, Chung-Ang University, Seoul 06974, Korea
Funding
National Research Foundation of Korea · Korean government · Chung-Ang University
References (33)
Show source-provided references
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