计算机科学
人工智能
稳健性(进化)
基准标记
计算机视觉
恶劣天气
标准差
机器人学
日光
实时计算
模拟
机器人
生物化学
基因
统计
光学
物理
气象学
数学
化学
作者
Rafael Marques Claro,Diogo Brandão Silva,Andry Maykol Pinto
标识
DOI:10.1016/j.robot.2023.104398
摘要
For Vertical Take-Off and Landing Unmanned Aerial Vehicles (VTOL UAVs) to operate autonomously and effectively, it is mandatory to endow them with precise landing abilities. The UAV has to be able to detect the landing target and to perform the landing maneuver without compromising its own safety and the integrity of its surroundings. However, current UAVs do not present the required robustness and reliability for precise landing in highly demanding scenarios, particularly due to their inadequacy to perform accordingly under challenging lighting and weather conditions, including in day and night operations. This work proposes a multimodal fiducial marker, named ArTuga (Augmented Reality Tag for Unmanned vision-Guided Aircraft), capable of being detected by an heterogeneous perception system for accurate and precise landing in challenging environments and daylight conditions. This research combines photometric and radiometric information by proposing a real-time multimodal fusion technique that ensures a robust and reliable detection of the landing target in severe environments. Experimental results using a real multicopter UAV show that the system was able to detect the proposed marker in adverse conditions (such as at different heights, with intense sunlight and in dark environments). The obtained average accuracy for position estimation at 1 m height was of 0.0060 m with a standard deviation of 0.0003 m. Precise landing tests obtained an average deviation of 0.027 m from the proposed marker, with a standard deviation of 0.026 m. These results demonstrate the relevance of the proposed system for the precise landing in adverse conditions, such as in day and night operations with harsh weather conditions.
科研通智能强力驱动
Strongly Powered by AbleSci AI