Self-Adaptive Quantum Topology Transformation for Dynamic Adaptive Path Planning

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper presents a novel self-adaptive quantum topology transformation algorithm designed for dynamic path planning. Traditional path planning algorithms are often static, ill-suited to evolving environments. Our approach leverages quantum topology transformations to dynamically adjust the topology of the system, enabling intelligent path optimization. The core mechanism involves a dynamic shift in the underlying quantum structure, guided by system-specific properties, to generate optimal paths. This algorithm offers a significant advancement over conventional methods, addressing the limitations of static path planning by enabling adaptive and robust route exploration. The paper details the algorithm's architecture, the mathematical foundation of the transformation process, and its performance evaluation on a simulated environment. The key contribution lies in the self-adaptive nature of the topology adjustment, promoting optimal path finding in dynamic scenarios.

DOI: 10.5281/zenodo.22266390

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