Advanced vision systems in logistics

Imagine a huge warehouse filled with rows of tall racks, where every package must be inspected before shipment. Mistakes are inevitable - damaged packaging, wrong products reaching customers or simple oversights. This not only wastes time, but also money.

It is problems like these that drive companies to look for solutions, that streamline logistics processes. Advanced vision technology - industrial cameras, sensors and software - allows for real-time quality control, eliminating errors and improving efficiency. This allows companies to quickly detect nonconformities and take appropriate action.

Learn, how vision systems support daily work in logistics, what benefits they offer and how they are used in practice. Discover, how technology is changing the face of modern logistics.

• What are vision systems
  • What are the components of vision systems
  • How a vision system works
• Examples of how systems are used in logistics
• Challenges of vision systems
• What to consider, when planning an implementation
• Examples of successful implementations
• Impact of vision systems on the logistics industry
• The future of vision systems

What are vision systems?

Vision systems are integrated technological solutions for automatic analysis of images in real time. Their main task is to perform quality control, identification of objects, and thus support logistics and production processes.

Thanks to the use of advanced algorithms, these systems can execute commands on the basis of collected visual data, eliminating human errors and speeding up operational processes.

Key components of vision systems

To fully understand the operation of vision systems, it is useful to look at their key components. Each of them plays an important role in ensuring the accuracy and efficiency of logistics processes.

• Industrial cameras
  Vision cameras are an essential tool for capturing high-resolution images. Depending on the application, they can be line cameras (for scanning narrow objects), matrix (for analyzing wide areas), thermal (for detecting temperature changes) or multispectral (for analyzing features not visible in visible light). They are designed to work in demanding environments - they must be resistant to shock, dust and changing lighting conditions.
• Sensors
  Depth sensors, such as LIDAR (Light Detection and Ranging) or ToF (Time of Flight) sensors, enable precise measurements of the distance and shape of objects. They enable systems to create three-dimensional maps of goods, which is crucial in automatic sorting or load stacking processes. Vision sensors also detect texture differences and micro-damage invisible to traditional cameras.
• Controlled Lighting
  An integral component of vision systems is dedicated lighting. Even and properly selected light minimizes the impact of shadows or reflections, which increases the precision of image analysis. Typical technologies used include LED lighting, infrared and ultraviolet light, tailored to the specific application.
• Analytics software
  Software based on artificial intelligence and machine learning algorithms processes images captured by cameras and sensors. Analysis includes shape identification, defect detection, label recognition or verification of barcodes and QR codes. Advanced systems use OCR (Optical Character Recognition) technology to read text on labels and packaging.

How do vision systems work?

Vision systems work by combining image analysis and precision logistics operations. The process begins with the capture of an image by a camera, which is then processed by software that analyzes the visual data. After comparing the image with predefined patterns, the system identifies potential deviations or errors. In such cases, it can automatically report the problem, direct the product for further inspection or take other defined actions.

Importantly, vision systems do not function in isolation. Their efficiency is increased through integration with other logistics tools, such as warehouse management systems (WMS). This makes it possible not only to monitor the status of goods in real time, but also full synchronization of picking processes, packing and shipping. Such integration ensures the smooth operation of the entire logistics chain, minimizing the risk of errors and optimizing operational efficiency.

Learning about the mechanisms of vision systems and their integration allows you to better understand, why they have become a key tool in modern logistics. To fully appreciate their potential, it is worth looking at real applications, that show, how technology is changing everyday operations.

Examples of vision system applications in logistics

Vision systems are widely used in various areas of logistics, streamlining daily operations and increasing process efficiency. Here are the most important examples of their use.

Automatic quality inspection
Vision systems enable fast and precise inspection of product quality. For example,, during goods receipt, cameras can detect damage to packaging, deformation of cartons or dirt, that affect further logistics processes. This allows you to quickly isolate defective goods, avoid costly complaints and delivery downtime.

Recognition and classification of goods
Thanks to advanced AI algorithms, vision systems are able to recognize different types of goods and automatically classify them based on shape, color or label. For example, in courier sorting facilities, cameras can identify packages based on bar codes or unique markings, directing them to the appropriate shipping zones. This allows to significantly speed up operations in distribution centers.

For the food industry, vision systems can additionally identify goods for freshness or mechanical damage, which is crucial in ensuring high quality deliveries.

Optimizing Packing Processes
Vision systems check the correctness of packing goods, checking e.g. whether all order elements have been placed in the package. On packing lines in large warehouses, systems can automatically identify missing products, verify compliance with the order and monitor the quality of packaging seals.

If an error is detected, the system can report the problem, allowing a correction to be made quickly and preventing the shipment of an incomplete order. In the pharmaceutical sector, vision technology allows to control the compliance of drug packaging with safety requirements, which eliminates the risk of mistakes.

Monitoring of warehouses and robot navigation
In automated warehouses, vision systems support robot navigation, enabling precise location and transport of goods. For example, AGV (Automated Guided Vehicles) robots use vision cameras to track paths and avoid obstacles, which increases safety in the warehouse. In addition, these systems help monitor inventory levels on shelves, automatically reporting missing products to the warehouse management system (WMS).

In large logistics centers, vision cameras are used to optimize robot movement, minimizing the time required for order picking.

Compliance verification of labels and barcodes
In logistics centers, vision systems can also be used to verify that labels on packages are correct. Vision software analyzes barcodes and QR codes, verifying their compliance with the order and documentation. This eliminates the risk of delivery errors, which is particularly important in the e-commerce, where the number of packages to be processed is growing exponentially.

Practical applications of vision systems show, how many benefits they can bring to logistics. However, every new technology also comes with challenges, that must be considered before implementation.

Challenges in implementing vision systems

Despite the enormous potential, that vision systems carry, their implementation is not without its difficulties. Below are the key challenges, that may arise at the implementation stage.

Investment costs
Advanced vision technologies, including cameras, sensors and dedicated software, require significant financial outlays. For many companies, the initial purchase and installation costs can be a barrier, especially for smaller companies.

Technology requirements
Vision systems require the right infrastructure, such as stable power sources, advanced computer networks, and an appropriate operating environment (e.g. controlled lighting). Lack of these elements can reduce the effectiveness of the systems.

Integration with existing systems
Combining vision systems with existing logistics solutions, such as WMS or ERP, can be time-consuming and require technological adjustments. Improperly performed integration can lead to process errors.

Personnel training
Operation and maintenance of advanced vision systems requires staff training. Lack of proper competence among staff can affect the effectiveness of technology use and generate additional costs for team education.

Data problems
Vision systems generate huge amounts of visual data, which must be stored, analyzed and properly secured. Data management challenges can strain IT infrastructure and increase the risk of security breaches.

Understanding the challenges of implementing vision systems is key to successful implementation. Once technological and organizational barriers have been overcome, it makes sense to focus on the factors, that will ensure the success of the process.

Key success factors for implementing vision systems

For a successful implementation of vision systems to be successful, several key elements must be taken into account:

• A thorough analysis of the company's needs. The selection of appropriate technologies must be tailored to the specifics of the company's operations, including the type of goods stored and the scale of operations.
• Personnel training. Even the most advanced technology will fail without properly trained users. Regular training helps teams get the most out of vision systems.
• Providing the right infrastructure. Stable communication networks, optimal lighting in warehouses and compatibility with existing systems, such as WMS or ERP, are crucial to the operation of vision systems.
• Monitoring performance and optimization. Continuous monitoring of deployed systems allows you to identify areas for improvement and adapt technology to meet changing business needs.

Successful implementation of vision systems not only improves operational efficiency, but also increases the company's competitiveness in the market. A well-thought-out implementation strategy and continuous process improvement are key to achieving the full benefits offered by this technology.

Examples of successful implementations of vision systems

The implementation of vision systems brings tangible benefits, as evidenced by the experience of companies in various sectors.

TME
The first example operating in production at TME is a vision system supporting robotic drop stations. The system, by detecting the position of product bags and locating their 3D position, enables the robot to perform a bin picking type task. Product detection is made possible by using a trained machine learning model and 2D and 3D data from the RGB camera-D. The products moved by the robot reach the sorter and participate in the further logistics process. In addition, products are identified at the time of transfer by reading barcodes and QR codes by code scanners.Another system based on the analysis of data from 2D cameras makes it possible to verify the correctness of throw-ins into specific trays of the sorter. This applies to both throws made by robots, as well as warehouse employees at manual drop-in stations.Another example of a vision system at TME is the goods parameterization station. In this case, not an image, but a 3D point cloud derived from profilometers, makes it possible to accurately size the products being tested.Another example of a system based on RGB data-D is the real volume measurement system. It analyzes the volume of bags of products riding on sorter trays, and then this data is used in the process of selecting a carton for shipment.

DB Schenker
The deployment of Picavi smart glasses in this company's warehouses has helped increase the efficiency of order picking. Warehouse employees can thus see information about the location of products, which minimizes the time needed to find them. The system also reduces errors, because the data displayed on the glasses indicates the exact number of products to be picked and their location.

Bosch
Bosch has used vision systems in factories to inspect component quality. Cameras equipped with advanced software analyze part geometry and structure in real time, eliminating defective components even before they are assembled. This approach reduces claim costs and improves the overall quality of final products.

DHL
In DHL warehouses, vision systems are integrated into parcel sorting processes. The cameras work with WMS systems, automatically reading labels and assigning parcels to appropriate shipping zones. This makes the sorting process faster, more precise and less prone to errors, even with large shipment volumes.

ABB and Sevensense Robotics
ABB in 2024 acquired Swiss startup Sevensense Robotics, which has developed Visual Simultaneous Localization and Mapping (Visual SLAM) technology. The technology enables autonomous mobile robots (AMR) to navigate in dynamically changing environments, which is particularly useful in warehouse logistics. This enables ABB to introduce more advanced solutions to support automation and optimization of warehouse processes.

These examples show, that properly implemented vision systems can significantly improve operational efficiency, reduce costs and increase service quality, which translates into customer satisfaction and competitive advantage in the marketplace.

The impact of vision systems on the transformation of the logistics industry

For years, the logistics industry has been struggling with key challenges: limited process efficiency, high error rates and difficulty in adapting operations to rapidly changing market conditions. Vision systems have emerged as an answer to these problems, to improve existing standards of operation.

One of the most onerous challenges was the manual monitoring of warehouse processes, which generated delays and increased operating costs. With the use of cameras working with advanced image analysis algorithms, it became possible to automate these tasks. Vision systems are able to locate goods in real time, detect errors in markings and dynamically optimize logistics processes, eliminating the need for manual intervention.

Seasonal spikes in demand, such as those observed during the holiday season, presented another challenge. Logistics companies often struggled with a lack of resources or overloaded infrastructure. Vision systems, by analyzing visual data and predicting order patterns, enable more precise resource planning and avoid downtime. Automation also makes it possible to quickly adjust warehouse configurations to meet changing needs.

Another major concern was the quality of customer service, especially in the context of order processing errors. Vision systems allow for real-time monitoring of order status, which significantly reduces the number of complaints and improves the timeliness of deliveries. Customers receive precise information about the status of shipments, which builds trust and loyalty to the brand.

Vision systems also influence supply chain collaboration. Thanks to integration with IoT technologies and WMS systems, it is possible to seamlessly exchange data between suppliers, distribution centers and end customers. This leads to a more integrated and efficient logistics ecosystem.

The future of vision systems in logistics

Vision systems are playing an increasingly important role in logistics, and their development is already opening up new opportunities to improve operational processes. Many technologies, such as integration with IoT or data analysis using artificial intelligence, are already available and are finding applications in advanced warehouse operations.

IoT, or Internet of Things, enables a constant flow of data between devices, which allows real-time monitoring of parameters such as temperature or location of goods. AI algorithms, on the other hand, analyze visual data in real time, identifying potential problems, such as improperly packaged products or labeling errors.

However, the future of these technologies promises even more. The development of IoT will allow even more advanced monitoring of logistics processes in real time, creating fully integrated data-driven networks. AI algorithms, which already analyze visual data, will be developed to predict potential problems, such as equipment failures or warehouse congestion. This will make predictive analytics the standard, minimizing waste and increasing operational efficiency.

Augmented reality (AR) technologies are another direction, that is developing gradually. An example of their application is the Picavi smart glasses, which have been implemented by DB Schenker to support order picking. Thanks to this technology, warehouse workers can receive real-time information about the location of goods and quantities to be picked. However, the future will bring more advanced solutions, such as real-time display of product information or automatic warehouse navigation, which will streamline processes and make them more precise.

Technological advances, including miniaturization of components and decreasing implementation costs, are already making it possible to deploy vision systems in smaller companies. This is an important step toward the democratization of these technologies.

The sustainability aspect cannot be overlooked either. Vision systems already support environmentally friendly activities, such as precise process monitoring or waste minimization. In the future, even more advanced solutions can be expected to support resource management and reduce energy consumption.

The future of vision systems in logistics, although partially available today, promises further innovations. These technologies will play a central role in shaping modern logistics processes, adapted to the challenges of the future, combining precision, efficiency and environmental concerns.

Transfer Multisort Elektronik (TME) is one of the world’s largest global distributors of electronic components, electrotechnical parts, workshop equipment, and industrial automation. The catalog includes over 1,500,000 products from 1,300 leading manufacturers. TME’s modern logistics centers in Łódź and Rzgów (Poland), with a combined area of over 40,000 m², ship nearly 6,000 packages daily to customers in more than 150 countries.

TME also invests in the development of knowledge and skills of young engineers and electronics enthusiasts through the TME Education project, and supports the tech community by organizing the TechMasterEvent series, promoting innovation and experience exchange.