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A UAV path planning method based on control parameterization

A technology for controlling parameters and path planning, applied in control/regulating systems, non-electric variable control, two-dimensional position/channel control, etc., can solve problems such as underactuation, nonlinearity, and no consideration of UAV dynamics constraints, etc. To achieve the effect of small optimal path error, stable motor speed change, and stable and feasible motion trajectory

Active Publication Date: 2021-07-27
SICHUAN UNIV
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Problems solved by technology

The dynamic model of the quadrotor UAV has the characteristics of nonlinearity, underactuation, and strong coupling, and the above algorithms do not consider the dynamic constraints of the UAV itself, so the calculated path is not optimal.
For mathematical methods such as convex optimization and mixed integer programming, most of them need to linearize the kinematics model, and the optimal path obtained in this way is only an approximate solution, which is not accurate enough.

Method used

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  • A UAV path planning method based on control parameterization
  • A UAV path planning method based on control parameterization
  • A UAV path planning method based on control parameterization

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Embodiment

[0030] like Figure 1 to Figure 10 As shown, the UAV path planning method based on control parameterization mainly includes four steps: nonlinear programming modeling, control parameterization, constraint transcription processing and gradient formula solution.

[0031] (S1) Nonlinear programming modeling: Select the state variables and control variables according to the nonlinear dynamic equation of the UAV and rewrite them into the form of a state space model, using the UAV's own performance index constraints and obstacles in the environment Object constraints, modeled as UAV continuous state inequality constraints, take the UAV's initial state and target point as the boundary constraint conditions, take the UAV flight time as the optimized objective function, and transform the UAV path planning problem into The nonlinear optimal control problem for the minimization of flight time of the UAV is to solve the optimal control variable u(t) to minimize the flight time T and satis...

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Abstract

The invention discloses a path planning method for an unmanned aerial vehicle based on control parameterization, which mainly includes four steps of nonlinear programming modeling, control parameterization, constraint transcription processing and gradient formula solution. The invention comprehensively considers the obstacle constraints in the 3D environment and the dynamic constraints and performance index constraints of the drone itself, and uses two obstacle modeling methods to make the path planning of the drone meet the application of urban and mountain environments. By solving the optimal solution, the optimal time collision-free path of the UAV is obtained under the condition of satisfying the state constraints and control constraints. The optimal path of the UAV obtained by this method is compared with the existing conventional RRT method and The optimal path of the A* method is smoother, and the motor speed changes more stably during the motion of the UAV, and the motion trajectory is stable and feasible.

Description

technical field [0001] The invention relates to the technical field of quadrotor unmanned aerial vehicle control, in particular, relates to a UAV path planning method based on control parameterization. Background technique [0002] Quadrotor UAV has the characteristics of vertical lift, fast flight speed, lightness and flexibility, so it has been widely used in many fields. For example, with the continuous development of drone aerial photography technology, when natural disasters occur, we need to understand the disaster situation in time, which requires drones to enter the disaster area and analyze the disaster situation through images. In addition, UAVs are also used in the field of traffic monitoring, which can monitor urban road conditions in real time, realize regional control, and ensure smooth traffic. For sudden traffic accidents, information can be transmitted in time to facilitate emergency rescue. The complexity of drone missions continues to increase. In order ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/02G01C21/20
CPCG01C21/20G05D1/0221G05D1/0223
Inventor 李彬郭金龙吴昊李响刘鹭航毛新涛汤浩王振华张爱新马巍
Owner SICHUAN UNIV
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