Neural-network-based navigation and control of unmanned aerial vehicles for detecting unintended emissions

Author(s):  
H. Zargarzadeh ◽  
David Nodland ◽  
V. Thotla ◽  
S. Jagannathan ◽  
S. Agarwal
2016 ◽  
Vol 2 (45) ◽  
pp. 26 ◽  
Author(s):  
Vladimir Alexandrovich Knyaz ◽  
Boris Vaisovich Vishnyakov ◽  
Yuri Valentinovich Vizilter ◽  
Vladimir Sergeevich Gorbatsevich ◽  
Oleg Vjacheslavovich Vygolov

2006 ◽  
Vol 3 (5) ◽  
pp. 187-213 ◽  
Author(s):  
Henrik B. Christophersen ◽  
R. Wayne Pickell ◽  
James C. Neidhoefer ◽  
Adrian A. Koller ◽  
Suresh K. Kannan ◽  
...  

2020 ◽  
Vol 71 (7) ◽  
pp. 828-839
Author(s):  
Thinh Hoang Dinh ◽  
Hieu Le Thi Hong

Autonomous landing of rotary wing type unmanned aerial vehicles is a challenging problem and key to autonomous aerial fleet operation. We propose a method for localizing the UAV around the helipad, that is to estimate the relative position of the helipad with respect to the UAV. This data is highly desirable to design controllers that have robust and consistent control characteristics and can find applications in search – rescue operations. AI-based neural network is set up for helipad detection, followed by optimization by the localization algorithm. The performance of this approach is compared against fiducial marker approach, demonstrating good consensus between two estimations


Author(s):  
Hongbo Xin ◽  
Yujie Wang ◽  
Xianzhong Gao ◽  
Qingyang Chen ◽  
Bingjie Zhu ◽  
...  

The tail-sitter unmanned aerial vehicles have the advantages of multi-rotors and fixed-wing aircrafts, such as vertical takeoff and landing, long endurance and high-speed cruise. These make the tail-sitter unmanned aerial vehicle capable for special tasks in complex environments. In this article, we present the modeling and the control system design for a quadrotor tail-sitter unmanned aerial vehicle whose main structure consists of a traditional quadrotor with four wings fixed on the four rotor arms. The key point of the control system is the transition process between hover flight mode and level flight mode. However, the normal Euler angle representation cannot tackle both of the hover and level flight modes because of the singularity when pitch angle tends to [Formula: see text]. The dual-Euler method using two Euler-angle representations in two body-fixed coordinate frames is presented to couple with this problem, which gives continuous attitude representation throughout the whole flight envelope. The control system is divided into hover and level controllers to adapt to the two different flight modes. The nonlinear dynamic inverse method is employed to realize fuselage rotation and attitude stabilization. In guidance control, the vector field method is used in level flight guidance logic, and the quadrotor guidance method is used in hover flight mode. The framework of the whole system is established by MATLAB and Simulink, and the effectiveness of the guidance and control algorithms are verified by simulation. Finally, the flight test of the prototype shows the feasibility of the whole system.


Author(s):  
Magesh T. Rajan ◽  
Hao Xu ◽  
Clyde Avalos ◽  
Anthony Matheson ◽  
Eric Swinny

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