电商物流中的光学与机器视觉应用逻辑、现实约束与发展路径研究

Research on the Application Logic, Practical Constraints and Development Path of Optical and Machine Vision in E-Commerce Logistics

摘要: 在履约提速、订单碎片化和逆向物流常态化背景下，电商物流对识别效率、流程稳定性和过程留痕提出了更高要求。本文通过文献梳理、案例分析和场景归纳，对光学与机器视觉在电商物流中的应用进行了分析。研究发现，这类技术不仅能够分担部分人工识别工作，还能提高物流环节的可视化和可追踪水平。当前，其已在货物识别、测量定位、动态跟踪、库存盘点、导航建图和退货筛查等方面得到应用，但实际落地仍面临场景复杂、系统对接困难、成本回收周期较长和人机边界不清等问题。未来应坚持问题导向，结合具体场景推进相关技术应用。

Abstract: Against the background of faster fulfillment, fragmented orders, and the normalization of reverse logistics, e-commerce logistics has placed higher demands on recognition efficiency, process stability, and traceability. This paper analyzes the application of optical and machine vision technologies in e-commerce logistics through literature review, case analysis, and scenario-based induction. The study finds that these technologies not only reduce part of the manual identification workload, but also improve the visibility and traceability of logistics processes. At present, they have been applied in cargo identification, measurement and positioning, dynamic tracking, inventory counting, navigation and mapping, and return inspection. However, their large-scale adoption still faces practical constraints, including complex operating scenarios, difficulties in system integration, long payback periods, and unclear boundaries between human and machine tasks. In the future, the application of optical and machine vision in e-commerce logistics should remain problem-oriented and be advanced step by step in line with specific business scenarios.