Unmanned aerial vehicle trajectory generation method based on flight corridor and Bezier curve

Abstract

The invention discloses an unmanned aerial vehicle trajectory generation method based on a flight corridor and a Bezier curve, and belongs to the field of robot motion planning. According to the trajectory generation method, a robot can meet the motion constraint of continuous acceleration on the premise that obstacle avoidance is guaranteed, and the average speed is high. The method comprises thefollowing specific steps: obtaining surrounding map point cloud information through a depth camera sensor / laser radar sensor or global known information; constructing a rasterized obstacle map; planning a collision-free and optimal path by using an A* algorithm; generating a collision-free flight corridor capable of moving by a robot based on the A* planned path; and finally, generating a Beziercurve in the flight corridor for the robot to move. A series of nodes on a safety path are converted into a series of convex geometries (corridor blocks) in a mode of generating a safety corridor, sothat the information amount is greatly increased, and the modeling accuracy is ensured.

Description

technical field [0001] The invention belongs to the field of robot motion planning, in particular to a trajectory generation method for an unmanned aerial vehicle based on flight corridors and Bezier curves. Background technique [0002] The application of robots in today's society is becoming more and more widespread, such as sweeping robots, industrial robotic arms, logistics transportation robots, aerial photography drones, etc., which have brought many experiences to people's lives. No matter what kind of robot it is, as long as it involves movement, it is necessary to consider the problem of obstacle avoidance and smoothness of movement during the movement. [0003] When the robot performs a task, it must first plan the path. The planned path is enough to avoid all obstacles, and then do trajectory planning on the basis of this known path, and plan the speed at which the robot will pass through every obstacle on the path. points. This problem is transformed into traje...

AI Technical Summary

Problems solved by technology

Minimum-snap requires a given movement time. If the given time is too short, it will be difficult to solve. If the given time is too long, the curve will bend or even circle, which is not good for the robot's movement;

[0006] (2) Strictly abide by the constraint condition of the intermediate point obtained through path planning, which will limit the degree of freedom of the trajectory;

[0007] (3) The path obtained in path planning is not smooth, and there are often corners, and the existence of a large number of corners will cause the length difference between the two trajectories to be too large, which will lead to poor numerical stability when solving the optimization problem;

[0008] (4) There is no guarantee that the generated trajectory must not touch obstacles, and there is no guarantee that the trajectory acceleration is continuous, which is fatal to the control of drone-like robots, because discontinuous acceleration will cause frequent changes in the attitude of the drone, resulting in motion Unstable or even crashed

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