Open AccessImproved Positioning of Delivery Quad copter Using GPS - Accelerometer Multimode Controller and Unscented Kalman Filter
Author(s) -
Ahmed Abdulmahdi Abdulkareem Alawsi,
Basil H. Jasim,
Safanah M. Raafat
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/745/1/012018
Subject(s) - global positioning system , quadcopter , kalman filter , gps signals , computer science , signal (programming language) , real time computing , assisted gps , accelerometer , control theory (sociology) , control engineering , simulation , engineering , control (management) , artificial intelligence , aerospace engineering , telecommunications , programming language , operating system
In last area of technology, the quadrotor helicopter became essential equipment of everyday man use. Delivery by quadcopter has increased significantly in the last few years in different private and military fields because of its indispensable features such as autonomous flight, vertical take-off and landing. Most quadcopters used for delivery service utilize GPS signal for its autonomous flight to control itself and follow the desired path to the destination. Despite the prevalence of autonomous flight, it produces many challenges. GPS signal denial is one of the most critical challenges that may occur. GPS signal denial problem leads to affect the quadcopter control and potentially get lost. Many studies have tried to provide a solution toward this issue, yet, most solutions focused on specific applications and terms rather than achieving a general solution. In this paper, a multimode control algorithm is proposed as a solution for GPS signal denied through the autonomous flight. The algorithm consists of two control modes: GPS and accelerometer modes with Unscented Kalman Filter (UKF). The results show that the proposed algorithm is reliable and suitable for various applications of the quadcopter in different environments. The proposed algorithm can keep the quadcopter under control during GPS signal denial period and continue moving toward the desired path.