An obstacle avoidance system-based trajectory planning method for fire-fighting drones

Abstract

The invention relates to a fire-fighting UAV flight path planning method based an obstacle avoiding system. Ultrasonic distance-measurement sensors are arranged before, behind, on the left side and onthe right side of an UAV. When the measured distance is not less than a safety distance, an original control signal is output and the UAV will fly normally as planned. When an obstacle is found in one direction of the UAV, it is judged that collision is about to occur. A flying control system will take actions such as throttling back and tilting and flying towards the direction opposite to the obstacle according to the measured distance to avoid the obstacle. According to the invention, the obstacle avoidance algorithm designed in the invention has the advantages of good compatibility and high implementation efficiency compared with the traditional local obstacle avoidance planning algorithms (the artificial potential field method and the grid method). Based on the ultrasonic obstacle avoidance system, the adopted A* search algorithm can effectively reduce the computational load of an airborne controller, and can ensure that the UAV can quickly avoid obstacles in emergencies and planout new flight paths in time.

Description

Technical field [0001] The invention belongs to the field of fire-fighting drones, and relates to a method for trajectory planning of a fire-fighting drone based on an obstacle avoidance system. Background technique [0002] UAVs have strong advantages in the fire detection and rescue missions of urban high-rise buildings. In order to reach the fire scene quickly and accurately, it is necessary to ensure that the firefighting UAV can fly to the destination with minimum time, fuel consumption, and environmental threats. It can ensure that the drone has a rapid response capability to sudden obstacles. [0003] Conventional UAV planning algorithms mostly use dynamic planning, A* search, Voronoi diagram algorithm, artificial potential energy method, ant colony algorithm, genetic algorithm, etc. They have their own advantages and disadvantages. Under certain conditions, UAV trajectory planning can be realized. However, due to the complex flight environment, the objective function of UA...

AI Technical Summary

Problems solved by technology

They have their own advantages and disadvantages. Under certain conditions, UAV trajectory planning can be realized. However, due to the complex flight environment, the objective function of UAV trajectory planning is too complicated, and the onboard controller needs to deal with it. A large amount of information, in the face of emergencies, it is difficult to meet the rapid response requirements of the UAV obstacle avoidance system

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