Method and device for quickly planning flight path of intelligent aircraft under multiple constraint conditions

Abstract

The invention provides a method and a device for quickly planning a flight path of an intelligent aircraft under multiple constraint conditions. The method comprises the following steps: controlling the intelligent aircraft to fly out from a starting point; setting constraint conditions of the intelligent aircraft; constructing a cost function according to the constraint condition; updating boundary conditions, and determining a search range according to the boundary conditions; searching an optimal node according to the search range and the cost function; controlling the intelligent aircraftto fly to the optimal node; judging whether the Euclidean distance between the optimal node and the terminal point is smaller than the constraint distance or not; if so, taking the current optimal node as an end point, and controlling the intelligent aircraft to fly to the end point; otherwise, returning to the step of constructing the cost function according to the constraint condition. Therefore, the method has the advantages that the searching is more targeted and planned, the time complexity caused by continuously and blindly iteratively searching the optimal node is further saved, the searching is higher in effectiveness and lower in complexity, and the correction times can be sought as few as possible while the minimum track length is sought.

Description

technical field [0001] The invention relates to the technical field of aircraft, in particular to a method for quickly planning flight paths of intelligent aircraft under multi-constraint conditions and a device for rapidly planning flight paths of intelligent aircraft under multi-constraint conditions. Background technique [0002] Rapid trajectory planning in complex environments is an important topic of intelligent aircraft control. Due to the limitations of the system structure, the positioning system of this type of aircraft cannot accurately position itself. Once the positioning error accumulates to a certain extent, the mission may fail. Therefore, correcting positioning errors during flight is an important task in trajectory planning of intelligent aircraft. [0003] Among the currently researched track planning algorithms, the A* search algorithm is a grid-based intelligent search algorithm. Compared with the linear programming method and genetic algorithm, the alg...

AI Technical Summary

Problems solved by technology

[0004] The A* algorithm determines the search range by constructing a cost function, which will lead to a larger search range. If the search process finds that the cost of a path to a node is lower than the cost of the existing path, the pointer to the node must be redirected, which is already closed The redirection of the descendants of nodes in the array saves the subsequent search results, but may require exponential calculation costs, reducing the effectiveness of the search tool and increasing the complexity of the search

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