Self-adaptive three-dimensional space path planning method based on particle swarm algorithm

Abstract

The invention provides a self-adaptive three-dimensional space path planning method based on a particle swarm algorithm and direct at a submarine topography elevation model. The method comprises firstly initializing space position and displacement of particles, conducting dimensional reconstruction while space position is initialized, initializing the best position where a first generation of particles pass and the best position found by a group currently, then updating the next generation displacement and the space position of particles, introducing an attraction operator and an exclusion operator during the updating, updating the best position where the next generation of particles pass and the best position found by the group by calculating the adaptability of the particles, and updating the displacement and the space positions of the particles repeatedly until the required number of iterations is fulfilled. The method has no special requirements on a pathing environment, the convergence rate, the convergence accuracy and the self-adaptability are all improved in the path planning process, the free movement of particle nodes in the space becomes possible, the success rate of pathing is increased, and the calculated amount of path planning is reduced.

Description

technical field [0001] The invention belongs to the technical field of computational intelligence, and relates to a three-dimensional space path planning method designed through an intelligent optimization mode of a simulation group. Background technique [0002] With the development of sea and air business, people pay more and more attention to 3D path planning, which plays a vital role in the effective use of resources and time. However, most of the existing path planning methods are proposed for two-dimensional space, and most of the existing three-dimensional space path planning methods are the promotion of two-dimensional methods to three-dimensional methods. Many problems will inevitably be brought about in the process, such as the artificial potential field method, the A * Search method, case-based reasoning method and genetic algorithm, among which the potential field method will inevitably fall into the local minimum, and when complex optimization criteria are used...

AI Technical Summary

Problems solved by technology

[0003] Based on the basic particle swarm algorithm and combined with the specific situation of three-dimensional space path planning, the present invention proposes an adaptive three-dimensional space path planning method based on particle swarm algorithm, which overcomes the improvement of the existing three-dimensional space path planning method due to the dimension , so that the amount of calculation increases sharply, it is difficult or impossible to complete the path planning task, and the problem of finding the optimal path is not smooth

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