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Research on UAV Online Trajectory Planning Algorithm Based on C/FD-GMRES Method

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In order to ensure that the UAV online route planning results meet the terminal constraints of the task, a rolling optimization algorithm based on C/FD-GMRES for UAV online route planning is designed. The C/FD-GMRES is a real-time nonlinear receding horizon control approach; combining the homotopy continuation method differential approximation generalized minimum residual method instead of solving complex Riccati differential equations. At each sampling time, the C/FD-GMRES calculate a residual vector linear equation once and the product of Jacobi matrix and vector product is approximated to the forward difference, the GMRES fast algorithm is used to solve large scale linear equations in the end. The C/FD-GMRES method has a good real-time performance, not sensitive to the selection of initial estimates, and can meet the need of UAV terminal state constraints. Simulation results show that the algorithm can effectively avoid barriers of space and the planned trajectory can converge to a stable terminal state, meeting the real-time requirements.
Title: Research on UAV Online Trajectory Planning Algorithm Based on C/FD-GMRES Method
Description:
In order to ensure that the UAV online route planning results meet the terminal constraints of the task, a rolling optimization algorithm based on C/FD-GMRES for UAV online route planning is designed.
The C/FD-GMRES is a real-time nonlinear receding horizon control approach; combining the homotopy continuation method differential approximation generalized minimum residual method instead of solving complex Riccati differential equations.
At each sampling time, the C/FD-GMRES calculate a residual vector linear equation once and the product of Jacobi matrix and vector product is approximated to the forward difference, the GMRES fast algorithm is used to solve large scale linear equations in the end.
The C/FD-GMRES method has a good real-time performance, not sensitive to the selection of initial estimates, and can meet the need of UAV terminal state constraints.
Simulation results show that the algorithm can effectively avoid barriers of space and the planned trajectory can converge to a stable terminal state, meeting the real-time requirements.

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