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Project Background
A South China automated warehouse deployed multiple AGVs to optimize the goods handling process. However, during the daily operations of the warehouse, manual handling of goods is inevitable, leading to delayed updates of storage location occupancy status information in the system. This information lag may cause AGVs to receive incorrect operation instructions, not only reducing operational efficiency but also potentially causing safety risks.
To address this issue, the project plans to introduce an advanced storage location status recognition system to comprehensively monitor storage location status and provide real-time updates to the WMS system. In this way, digital management of storage locations can be achieved, ensuring that AGVs perform goods picking and placing tasks more efficiently, stably, and safely.
Selection of Storage Location Status Recognition Sensors
- Single-point LiDAR: Single-point LiDar can only emit one laser beam at a time to form a point on the object surface. This ranging method is prone to ignoring gaps between cartons or pallets, leading to the misidentification of the current storage location as lacking goods or being empty, which can cause stacking accidents.
- RGB Camera: When detecting target areas through deep learning, if objects not included in the training set enter the storage location, misdetection may occur, providing incorrect storage location status information. Additionally, for storage locations requiring goods stacking, the RGB camera lacks height information, making it difficult to arrange stacking tasks.
- MRDVS RGB-D Camera: Provides three-dimensional data and color information of storage locations, with built-in computing power, eliminating the need for an external industrial computer.
Meanwhile,MRDVS offers an integrated hardware and software solution for storage location status recognition, along with professional model training and deployment guidance services. Considering the high cost-effectiveness and convenient deployment of the entire solution, the warehouse ultimately deployed hundreds of sensors, enabling comprehensive and real-time monitoring of storage location status across the entire warehouse.
Detailed Solution Introduction
MRDVS's 3D visual storage location status recognition solution, developed based on the RGB-D camera, achieves accurate storage location recognition by collecting 3D point cloud data and RGB data of storage locations. It monitors the occupancy status and goods height information of each storage location in real time, providing precise data support for AMR （Autonomous Mobile Robot）, enabling digital management of storage locations, and ensuring accurate goods picking and placing operations. The location recognition algorithm is built into the camera, eliminating the need for external computing units, reducing deployment complexity, and lowering project costs.
- Comprehensive Monitoring: Collect three-dimensional data and color information of storage locations, combined with AI technology, to accurately identify the status of storage locations.
- Easy Deployment: The location status recognition algorithm is integrated into the camera, reducing deployment and maintenance costs.
- Flexible Communication: Supports TCP/IP, UDP, HTTP, and other communication methods, reporting data to the control system in real-time via JSON format.
- Efficiency Improvement: Real-time transmission of location information assists the scheduling system in quickly and accurately allocating tasks.
On-site installation photo
As an expert in AMR （Autonomous Mobile Robot） and logistics warehouse automation visual solutions, MRDVS not only provides integrated hardware and software visual technology solutions but also offers comprehensive service support, committed to helping partners enhance logistics automation levels and achieve more stable, safer, and smarter warehouse management.
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