Unmanned aerial vehicle transportation route distribution method for logistics multi-point transportation

By standardizing the three-dimensional feature vectors and encoding the topological ring structure of UAV logistics path planning, and combining quantum annealing and federated learning, the problems of multi-constraint collaborative optimization, privacy protection and dynamic adaptability in UAV logistics path planning are solved, and efficient, safe and robust logistics network transportation is realized.

CN120975692APending Publication Date: 2025-11-18CHENGDU CHUQIAN TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202511111885.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-08-08
Publication Date
2025-11-18

AI Technical Summary

Technical Problem

Existing UAV logistics path planning methods have significant shortcomings in terms of multi-constraint collaborative optimization, privacy protection, and dynamic adaptability, making it difficult to meet the comprehensive requirements of modern logistics for efficiency, privacy, and robustness. In particular, path planning in multi-UAV collaborative transportation and dynamic environments suffers from wasted computational resources and response delays.

Method used

By performing coordinate-weight joint standardization on the delivery point set, a three-dimensional feature vector is generated, a topological complex is constructed and the key loop structure is extracted, which is encoded as the topological constraint term of the quantum model. Quantum annealing is used to solve the problem and federated learning is combined for privacy fine-tuning, thereby achieving efficient, secure and dynamically adaptable path planning.

Benefits of technology

It achieves efficient solutions for large-scale logistics networks, reduces computational complexity, optimizes transportation costs and capacity constraints, protects data privacy, enhances system robustness and responsiveness, and improves resource utilization.

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Abstract

The invention relates to the field of intelligent logistics optimization, and discloses an unmanned aerial vehicle transportation route distribution method for logistics multi-point transportation, which comprises the following steps: carrying out coordinate-weight joint standardization on a distribution point set to generate a three-dimensional feature vector; constructing a topological complex based on the standardized data, and extracting a key ring structure through continuous coherence; encoding the ring structure into a topological constraint term of a quantum model, and constructing Hamiltonian containing distance, load and topological constraint; dividing quantum sub-blocks according to the topological ring, and executing block annealing solution through chain coupling constraint; and carrying out topology-guided privacy fine tuning under a federated learning framework by using gradient information of a quantum solution. According to the method, a complex path optimization problem is decomposed into sub-problems capable of being processed in parallel through a quantum topological coding and block annealing strategy, quantum bit grouping is guided through a topological ring structure, the calculation complexity is reduced, efficient solving of a large-scale logistics network is achieved, and the calculation speed is increased compared with a traditional optimization method.
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