Four-rotor unmanned aerial vehicle flight path planning method and system in unknown environment

Abstract

The invention discloses a four-rotor unmanned aerial vehicle flight path planning method and system in an unknown environment. The method comprises the following steps: obtaining a global flight path by using polynomial optimization based on minimum snap; in the flight process, triggering to update the global flight path, and realizing the re-planning of the global flight path by introducing a new global safety point; selecting a point as a target point of local planning by a planning distance Rp, performing optimization solution of a local track based on a constraint condition to generate a feasible local track, if the solution is successful, executing a safe flight track of the unmanned aerial vehicle obtained by planning, and sending the position of the generated track point and yaw angle information to a controller for execution to complete track planning; and updating and solving the local track needing to be replanned to obtain a safe and feasible unmanned aerial vehicle track, and executing the obtained track. The method effectively breaks through the inherent visual angle limitation of a visual sensor, and greatly improves the flight safety and success rate of the unmanned aerial vehicle in an unknown environment while guaranteeing the real-time performance.

Description

technical field [0001] The invention belongs to the technical field of trajectory planning for autonomous navigation of a quadrotor unmanned aerial vehicle, and in particular relates to a method and system for trajectory planning of a quadrotor unmanned aerial vehicle in an unknown environment. Background technique [0002] In recent years, the development and production costs of UAVs have been continuously reduced, and the application scope has become increasingly extensive. Among them, the quadrotor UAV is deeply loved by the public because of its simple structure, good maneuverability and convenient use. People gradually began to use quadrotor UAVs to carry various load equipment to complete tasks such as power inspection, material distribution, and assistance in disaster rescue. However, the complexity of the flight environment has put forward higher requirements for the trajectory planning capabilities of UAV systems. At present, there are many solutions for UAV trajec...

AI Technical Summary

Problems solved by technology

However, in large and complex obstacle environments, such as indoor environments of buildings or long corridors, the above methods are almost ineffective, and the success rate is very low.

The reason is that the field of view of the UAV is obviously limited, and the initially generated global track cannot guarantee to provide correct direction guidance information

In particular, when the global track gives inappropriate guidance, the UAV will optimize with the wrong local target point. Even if the local re-planning is carried out continuously, it is difficult to solve the feasible track. The success rate of the track planning of the drone and Flight safety is greatly reduced, and serious accidents such as drone crashing into walls and crashes may even occur

[0005] To sum up, although the global planning and local re-planning methods can realize UAV navigation in unknown environments to a certain extent, the applicability is not enough, and the vision of UAVs in the environment is required to be wide enough

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