A simplified approach to motion estimation in a UAV using two filters

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• 作者：Gabriel Schmitz^* ; ^{gschmitz@ece.ufrgs.br} ; Tiago Alves^* ; ^{talves@ece.ufrgs.br} ; Renato Henriques^* ; ^{rventura@ece.ufrgs.br} ; Edison Freitas^* ; ^{epfreitas@inf.ufrgs.br} ; Ebrahim El'Youssef^** ; ^{ebrahim.el.youssef@ufsc.br}
• 关键词：Pose Estimation ; Kalman Filter ; Sensor Fusion ; Complementary Filter ; Unmanned Aerial Vehicle
• 刊名：IFAC-PapersOnLine
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：49
• 期：30
• 页码：325-330
• 全文大小：601 K
• 卷排序：49

文摘

Considering the requirement of precision positioning of Unmanned Aerial Vehicles in applications like in flights formations and flights with collision avoidance, this paper presents the proposal of a composition of a Complementary Filter used in orientation estimation and a Linear Kalman Filter (KF) in position estimation of the UAVs. The data evaluated in the experiments were acquired post flight from the flight controller embedded in a UAV. An Inertial Measurement Unit is used to provide the essentials datasets to the implementation of the Complementary Filter, which is modelled by Euler Angles referenced in a North-East-Down (NED) Coordinate System. The position estimation is obtained using the data from Global Positioning System (GPS) allied to a barometer applied in a Position-Velocity-Acceleration (PVA) model with Linear Kalman Filter. The acquired results provide evidence of the suitability and soundness of the proposed approach.