基于量子自组织网络的路径规划

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper presents a novel path planning algorithm based on quantum self-organization networks. Traditional path planning methods often rely on static optimization, struggling with complex systems. We propose a framework leveraging the inherent dynamism of quantum self-organization networks to achieve optimized path planning. This approach utilizes the network's self-organizing properties to dynamically adjust parameters, leading to improved efficiency compared to conventional methods. The core mechanism involves constructing a path planning framework that adapts to the network's state through quantum fluctuations. This enhances the algorithm's robustness and adaptability to dynamic environments, offering a significant advancement in path planning for complex systems. This work demonstrates the potential for quantum-enhanced path planning to address challenges associated with traditional optimization techniques.

DOI: 10.5281/zenodo.22296002

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