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The BangQi Goods-to-Person Picking Solution is a highly efficient picking approach developed using the BangQi AI small model and the Multi-Robot Collaborative Scheduling Algorithm (ADS). It’s perfectly suited for modern warehouse logistics environments that demand high efficiency in handling multi-SKU, high-frequency orders. At the heart of this system lies the "goods-to-person" principle, where ARM robots seamlessly transport items to picking stations, enabling a fully automated, intelligent, and standardized picking process.
This solution is perfectly tailored to handle complex business scenarios across multiple industries, including e-commerce retail, 3C electronics, pharmaceuticals, automotive parts, and cross-border warehousing—it serves as a critical component in enabling smart warehouses to operate with maximum efficiency.
Key Highlights
Efficiency doubled
Robots handle the entire process of scheduling and transporting goods, boosting picking efficiency by 80% to 120% while effortlessly managing the high-frequency demands of inbound and outbound logistics.
Workforce halved
People don’t need to walk around or carry items—by focusing solely on the picking operation, labor input for order fulfillment can be reduced by 50% to 70%.
Precision Assurance
The picking process is system-guided, supporting visual recognition and RFID-based positioning, achieving an accuracy rate of up to 99.9% and significantly reducing the risk of errors or omissions.
Elastic Deployment
The system can be flexibly deployed across various warehouse types and picking strategy scenarios, seamlessly meeting the demands of multi-category, multi-order, and multi-batch operations.
Smart Recommendations
Support AI-based small-model order prioritization and optimal path matching to enhance overall warehouse scheduling and picking efficiency.
Technological Advantages
Multi-Robot Cooperative Scheduling System (ADS)
Achieve unified planning for scheduling multiple undercover robots, bin-handling robots, and more, automatically assigning transport paths and task priorities while preventing path congestion and task conflicts.
Dynamic Warehouse Management System
Based on metrics such as outbound frequency and inventory popularity, we reorganize and optimize storage locations to improve shelf utilization and reduce the length of robot-based handling paths.
Visual Positioning and Intelligent Error Correction System
Equipped with visual recognition or sensor-based identification mechanisms, pickers follow system prompts during the picking process, and the system provides real-time alerts in case of incorrect selections, ensuring high-quality order fulfillment.
Seamlessly integrates with WMS/WCS
In coordination with Pound Flag's WMS and WCS systems, it enables integrated management—including task dispatching, inventory synchronization, and equipment control.
Standardized + Flexible Workstation Design
The picking station can be configured with various shelf/bin structures, enabling quick identification and retrieval of multiple SKUs and different types of materials, thereby enhancing human-machine interaction efficiency.
Industry Applications
E-commerce and Retail Industry
To handle peak volumes of orders, automatically deliver high-frequency SKU materials to workstations, reducing order-picking response time.
3C Electronics Industry
Handling complex materials and multi-batch small-item picking tasks, while enhancing operational standardization and traceability.
Pharmaceutical Distribution and Medical Devices
Achieve precise and efficient sorting of pharmaceuticals and reagents, meeting batch control and traceability requirements while ensuring medication safety.
Cross-border Warehousing and Overseas Warehouses
By implementing a flexible picking strategy, we optimize the handling of order characteristics and shipping rhythms across different countries, enabling seamless coordination among multiple warehouses.
Automotive and Parts Industry
Accurately pick and dispense components of various specifications in large quantities, enhancing line coordination and assembly efficiency.
Customer Case
A globally renowned e-commerce company's Southeast Asia warehouse project
Customer pain point: Significant delays in order picking during surge periods, making it impossible to fulfill same-day shipping.
Solution: An AI algorithm based on order priority dynamically schedules robots to move the highest-demand SKUs to workstations.
Results achieved: Daily order-picking capacity increased threefold, and on-time order fulfillment rate improved from 70% to over 98%.
A smart warehouse belonging to a well-known 3C electronics manufacturer
Customer pain point: A wide variety of SKUs and high order frequency lead to frequent errors in manual picking.
Solution: Deploy 100 stealth robots and equip them with 8 flexible workstations.
Results achieved: Picking efficiency increased by 100%, labor costs were reduced by 60%, and picking accuracy improved from the original 95% to 99.98%.
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