Unmanned aerial vehicle path planning method and device, electronic equipment and readable storage medium

By initializing the population through chaotic mapping and combining fitness and occlusion coefficient partitioning, the number of individuals in the illuminated and shaded areas is adaptively adjusted. New and old sub-individuals are generated using Lévy distribution and gradient information, which solves the problem of imbalance between global search and local development in UAV path planning and enables the rapid generation of high-quality obstacle avoidance paths.

CN122192340APending Publication Date: 2026-06-12JILIN JIANZHU UNIVERSITY
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
JILIN JIANZHU UNIVERSITY
Filing Date
2026-05-18
Publication Date
2026-06-12

AI Technical Summary

Technical Problem

Existing UAV path planning methods suffer from an imbalance between global search and local development in dynamic and complex environments, leading to premature convergence and difficulty in generating high-quality feasible paths.

Method used

The population is initialized using chaotic mapping. The illuminated and shaded areas are divided by combining fitness and occlusion coefficients. The number of individuals is adaptively adjusted during the iteration process. New and old sub-individuals are generated using Lévy distribution and gradient information. The number of path points is adaptively adjusted by evaluating path complexity using the first indicator function.

Benefits of technology

It improves the path planning adaptability and search efficiency of UAVs in dynamic environments, enhances obstacle avoidance safety in complex environments and computational efficiency in simple environments, reduces invalid searches, and quickly generates globally optimal obstacle avoidance paths.

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Abstract

The application relates to the technical field of path optimization, in particular to a UAV path planning method and device, electronic equipment and a readable storage medium, which comprises the following steps: generating a population; determining the first light intensity and the second light intensity of each individual and partitioning the individuals, executing an iteration cycle based on the partitioning result; and adaptively adjusting the number of individuals in the light area and the shadow area; determining the first sub-individual and the second sub-individual of each individual in the light area; determining all individuals of the current generation based on gradient information and speed information; determining the complexity of the optimal individual of the current generation, adjusting the number of path points of all individuals of the next generation based on the complexity, and screening the initial individuals of the next iteration; when the iteration number is a preset number of rounds, determining the global optimal solution as the optimal obstacle avoidance path of the UAV, so that the adaptability and search efficiency in a dynamic environment are improved, and the problems that the algorithm in the prior art is unbalanced in global search and local development in a dynamic complex environment, slow in convergence speed and prone to premature convergence are solved.
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