Title
Micro Air Vehicle'S 3D Trajectory Planning And Parametric Estimation
Abstract
Obstacle avoidance and optimal trajectory planning in 3D urban environments is one of the challenging tasks in micro air vehicle's research. This paper studies a rapid optimal trajectory finding and tracking control method for MAVs with uncertain parameters to navigate in an obstacle-laden 3D urban space. A varying subspace (or manifold) based method in a receding horizon framework is used to rapidly solve the constrained trajectory planning problem based on the nominal micro aerial vehicle model. In each horizon, a linear quadratic regulator is designed to track the generated nominal path, and an extended Kalman filter is applied to update the unknown aerodynamic coefficients, which will then be used in the trajectory planning and control in the next horizon. The capabilities of the proposed method are demonstrated through simulation.
Publication Date
9-16-2013
Publication Title
AIAA Guidance, Navigation, and Control (GNC) Conference
Number of Pages
-
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
84883700426 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84883700426
STARS Citation
Li, Ni; Xu, Yun Jun; and Pham, Khanh D., "Micro Air Vehicle'S 3D Trajectory Planning And Parametric Estimation" (2013). Scopus Export 2010-2014. 6253.
https://stars.library.ucf.edu/scopus2010/6253