Vision Based Autonomous Landing of Multirotor UAV on Moving Platform

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• 作者：Oualid Araar ; Nabil Aouf ; Ivan Vitanov
• 关键词：Autonomous landing ; Multirotor UAVs ; Visual ; inertial data fusion ; Ground vehcile tracking
• 刊名：Journal of Intelligent & Robotic Systems
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：85
• 期：2
• 页码：369-384
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Control, Robotics, Mechatronics; Electrical Engineering; Artificial Intelligence (incl. Robotics); Mechanical Engineering;
• 出版者：Springer Netherlands
• ISSN：1573-0409
• 卷排序：85

文摘

This paper investigates solutions for the fundamental yet challenging problem of autonomous landing of multirotor Unammaned Aerial Vehicles UAVs. In addition to landing on static targets, tracking and landing on a moving platform is addressed, as a solution to facilitate the deployment of the UAV. The paper presents the design of a new landing pad and its relative pose estimation. The fusion of inertial measurement with the estimated pose is considered to ensure a high sampling rate, and to increase the manoeuvrability of the vehicle. Two filters are designed to conduct the fusion, an Extended Kalman Filter (EKF) and an Extended H_∞ (EH_∞). The extensive simulation and practical tests permitted identification of the challenges of the landing task. Adequate solutions to these challenges are proposed to lessen their impact on landing precision.