Empowering Intelligent Sorting Systems with ARM Controllers: Full-Chain Synergy from Recognition to Execution
In today's rapidly evolving landscape of smart manufacturing and logistics automation, automated sorting systems have become essential for boosting efficiency and reducing costs. At the core of these systems' control layer, ARM controllers—leveraging their high performance, low power consumption, and high integration— are reshaping the intelligent architecture of sorting operations. This article delves into the application value and technical implementation of ARM controllers in multi-target recognition, control logic processing, and robotic arm coordination.
Multi-Target Recognition: The Vanguard of Edge Intelligence
The first step in automated sorting is target identification—whether it's parcels, components, or agricultural products. Traditional approaches rely on cloud-based recognition, which suffers from latency and bandwidth constraints. In contrast, ARM controllers equipped with AI acceleration modules (such as the Cortex-A53 BL370 series integrated with 1Tops NPUs) enable on-edge image recognition tasks:
Support for lightweight models (e.g., YOLOv5, MobileNet) running locally for real-time identification;
Integration with diverse sensing devices, including industrial cameras, color sensors, and LiDAR;
Transmission of recognition results (category, position, size) via SPI, UART, or CAN bus to the control logic module.
This edge intelligence architecture not only accelerates response times but also enhances system stability and security.
Control Logic: The "Brain" for Real-Time Scheduling and Path Planning
Recognition is merely the starting point; the real challenge lies in executing the sort. ARM controllers, running embedded Linux or RTOS, handle scheduling and decision-making tasks:
Task allocation based on target priorities and sorting strategies (e.g., by destination, category, or size);
Real-time computation of optimal robotic arm paths to avoid obstacles and minimize redundant movements;
Support for multi-task concurrency, ensuring stable operation under high loads.
Additionally, ARM controllers can interface with upper-layer systems like MES and WMS to form closed-loop data flows and enable intelligent optimizations.
Robotic Arm Coordination: The "Arms" for Precise Execution
At the execution layer, ARM controllers manage servo motors via industrial protocols (e.g., Modbus, CANopen, EtherCAT) to deliver precise robotic arm movements:
Multi-axis coordination for complex action sequences, such as grasping, transporting, and placing;
Scalability for multi-arm collaborative operations, supporting master-slave control or synchronized execution;
Real-time feedback on position and status for closed-loop control and fault alerting.
This control architecture is suitable not only for standard sorting tasks but also for customized, high-flexibility production needs.
Typical Application Scenarios
Application DomainRecognition ObjectsSorting StrategyAction ExamplesSmart LogisticsParcels, Express PackagesBy Destination ClassificationGrasp → Place into CompartmentFood PackagingBiscuits, Bottled BeveragesBy Category/Weight SortingGrasp → Pack into Box → SealIndustrial ManufacturingScrews, WashersBy Model/Batch SortingGrasp → Place into TrayAgricultural ScreeningApples, OrangesBy Maturity/Defect ScreeningGrasp → Place into Channel
Technical Advantages and Future Outlook
The integration of ARM controllers into automated sorting systems not only highlights their robust control capabilities but also exemplifies the fusion of edge intelligence with industrial automation trends:
Modular design for easy expansion and maintenance;
On-device AI inference to reduce cloud dependency;
Compatibility with various industrial protocols for adaptation to different production lines;
Synergy with 5G, industrial gateways, and cloud platforms to achieve full-stack intelligent sorting.
Looking ahead, as ARM architectures continue to evolve, their role in automated sorting systems will become even more versatile—from standalone controllers to edge servers, and from single-point control to multi-node collaboration—propelling industrial intelligence to new heights.
