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Machine vision technology is a foundational element in the development of automated and intelligent logistics, with its applications spanning all critical aspects of the logistics process. Intelligent logistics leverages integrated intelligent technologies and devices to mimic human intelligence, enabling the logistics system to think, perceive, learn, reason, judge, and independently resolve certain issues within logistics—this is the domain where machine vision truly excels.
Machine vision simulates the human eye's visual function, extracting information from images or image sequences, processing and understanding it for inspection, measurement, and control. It serves as the "eyes" of robots, equipping them with a visual simulation system for judgment. While human vision excels at qualitative interpretation of complex, unstructured scenes, machine vision, with its speed, precision, and repeatability, is adept at quantitative measurement of structured scenes.
For instance, on production lines, machine vision systems can inspect hundreds or even thousands of components per minute without fatigue. With appropriate resolution cameras and optical components, these systems can easily inspect minute details of items that are invisible to the human eye, analyzing across multiple dimensions and spectral ranges, including infrared or ultraviolet spectra that are imperceptible to humans.
The inspection results from machine vision systems are based on rigorous algorithms and programs, unaffected by subjective factors, ensuring the stability and repeatability of the results. This significantly enhances the flexibility and level of automation in industrial production.
The current domestic market for machine vision is primarily focused on 2D technology. With the rapid development of AI vision concepts, driven by market demand growth and national policy support, China has emerged with several manufacturers with considerable experience in the field of machine vision, such as Hikvision, Mia Optics, and Lingyun Optics. From the perspective of industry application, China's machine vision market still has significant development potential in industries such as electronics manufacturing, automotive, machinery manufacturing, logistics, and more.
Machine vision applications in logistics offer a broad range of scenarios. With intelligent recognition technology as a strong support, various high-efficiency and high-performance automated logistics equipment are widely applied. Machine vision can replace manual labor for precise recognition of barcodes, characters, images, and accurate measurement of cargo volumes, quickly and efficiently extracting product information, including deformed shelves due to compression.
In the field of warehousing logistics, machine vision technology is driving innovation and upgrading in a unique way, taking on key tasks such as control, positioning, and monitoring. By closely integrating software and hardware, image perception, and control theory, it enables efficient robot control or real-time operation of various devices, thereby improving the slow response, low efficiency, and weak precision of current warehousing logistics.
Currently, the main innovations in machine vision include three major directions: "goods-to-person" picking, efficient sorting and grasping, and unmanned warehousing transportation.
"Goods-to-person" order picking involves increasingly diverse item locations, orientations, types, shapes, and sizes. By equipping robots with vision recognition technology, "shelf-to-person" order picking is achieved.
Due to the continuous and large-scale sorting nature of logistics automatic sorting systems, equipment must operate unaffected by climate, time, or labor constraints. Machine vision processes packages efficiently, and modern sorting machines, which are fast and have small package intervals, can read damaged codes on all surfaces of packages at extreme angles, requiring vision recognition technology. This enables logistics centers to increase processing volume without compromising sorting accuracy and precision.
Machine vision navigation systems allow unmanned forklifts, AGVs, and other warehousing automation handling equipment to operate automatically and safely. By enhancing traditional AGVs with machine vision capabilities, they exhibit stronger target recognition abilities, adjust paths autonomously through computational control, and take on the core of independent operation, ensuring the system's real-time and accurate operation, thus enhancing the efficiency of intelligent warehousing mobile logistics.
As logistics centers face a significant increase in workload and complexity, machine vision equips various intelligent logistics devices with "vision."
With the continuous development of technology, machine vision is increasingly applied in the logistics industry, aggressively capturing the logistics market.
China's logistics turnover costs still account for a relatively high proportion of the entire GDP, and efforts will be made in the future to further improve logistics efficiency and reduce logistics turnover costs. Therefore, machine vision technology is bound to迎来 even broader development prospects.
As artificial intelligence and high-performance image processing technologies advance, the integration of machine vision and AI will become a future trend. With AI technology, machine vision can "think independently" and make judgments more rapidly.
The deep integration of machine vision and AI, with deep learning algorithms at its core, enables rapid classification of different types of items and, when paired with 3D vision devices, precise grasping of products. This effectively addresses the complexities of the logistics industry, solving issues of diversified logistics scenario applications, complex item types, and environmental variability, making information acquisition and linkage in logistics more intelligent.
Machine vision systems can also continuously learn and optimize to improve their detection accuracy and recognition rates. AI-driven machine vision offers multiple advantages in internal logistics management, from improving accuracy and efficiency to reducing costs and enhancing safety. These advanced technologies bring revolutionary changes to the modern logistics field, warranting further research and application by more businesses and industries.
Utilizing "vision AI" technology to endow systems with the ability to think, reason, judge, and independently resolve complex logistics issues is the next trend in intelligent logistics development.
Logistics scenarios are characterized by their "boundlessness and multi-variety," with increasing personalization and fragmentation of orders. The demand for intelligent recognition technology in many large distribution centers will continue to rise, presenting challenges in logistics scenario recognition due to the unordered sorting of a vast number of SKU items, which has always been a technical difficulty.
To address the complexity of logistics scenario recognition, the core technology lies in enhancing the performance of 3D stereo vision products, which mainly includes the following aspects: high light resistance, adaptability to multiple materials, high-speed detection, anti-interference capabilities, and broad applicability.
The successful application of deep learning neural networks in the field of machine vision is still limited. Technological advancements in related disciplines provide more possibilities for the future development of machine vision in logistics applications.
FALenses Technology specializes in providing machine vision core hardware. You can go to the official website of FALenses Technology at https://www.falenses.com/ for more information.