Quadrotor unmanned aerial vehicle trajectory planning method based on space-time joint optimization

Abstract

The invention discloses a quadrotor unmanned aerial vehicle trajectory planning method based on space-time joint optimization. The method comprises the following steps: searching a front-end path to obtain discrete path points, allocating a time interval to each section of path by adopting a trapezoidal time allocation method, and optimizing through an unconstrained polynomial coefficient to obtain an initial trajectory path; based on duration cost and energy consumption cost of the initial trajectory, carrying out proportional adjustment on the time interval under the condition that constraints are considered, solving an optimal adjustment proportion, and updating the time intervals of all trajectory segments; then, alternately carrying out two links of unconstrained polynomial coefficient optimization and proportional adjustment of a time interval, and when trajectory cost tends to converge, ending a circulation step; carrying out overall proportion adjustment on the whole trajectorypath, ensuring that the whole trajectory meets constraint conditions, and acquiring a final optimized trajectory; and enabling the unmanned aerial vehicle to follow the trajectory by using the path points obtained by time discretization of the polynomial trajectory. According to the invention, the space-time joint optimization of the trajectory is realized, and meanwhile, a calculation rate is greatly improved.

Description

technical field [0001] The invention belongs to the technical field of four-rotor unmanned aircraft navigation trajectory planning, and in particular relates to a four-rotor unmanned aircraft trajectory planning method for joint optimization of space and time. Background technique [0002] In the past ten years, with the development of various new technologies, such as integrated circuits, micro-electromechanical systems, and new control theories and methods, quadrotor UAVs have gained people's research interest. Quadrotor drones are small in size, flexible in movement, have vertical take-off and landing functions, and can hover in the air. They have irreplaceable advantages. In addition, the improvement of communication technology, control theory, SLAM algorithm, path planning algorithm, etc. has gradually improved the performance indicators and various capabilities of quadrotor drones. In addition to military applications, the application of quadrotor drones has been exten...

AI Technical Summary

Problems solved by technology

For the quadrotor rear-end trajectory planning problem, based on the segmented polynomial trajectory, the QP problem of minimizing the trajectory snap integral is modeled, and the closed-form solution of the optimal boundary condition of the polynomial trajectory is derived, and the focus is on the trajectory space optimization part. ; There is also a method of path search combined with back-end B-spline curve optimization under the front-end dynamic constraints, and by adjusting the node length of the non-uniform B-spline curve to ensure the dynamic constraints of the trajectory, the disadvantage is that the trajectory time is ignored segment optimization, the trajectory after node length adjustment can no longer guarantee optimality; and based on piecewise polynomials, the optimization of polynomial boundary conditions with constraints and the optimization of polynomial time intervals with constraints are proposed and proved for the first time. Spatial-temporal Joint Optimal Trajectory Generation Method

However, due to the complexity of solving two constrained optimization problems and the loop optimization structure of the method, the rate of trajectory generation is slowed down.

[0004] In summary, although there are many solutions in the field of trajectory planning, there is still a lack of real-time and fast space-time joint optimization trajectory generation methods.

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