This large-scale application case features an automated picking and replenishment system utilizing 120 Geek+ P500 mobile robots. By integrating a massive fleet into a unified fulfillment center, the system uses self-learning algorithms to optimize storage layouts based on order frequency. This solution maximizes space utilization and effectively addresses challenges such as labor shortages and rising personnel costs.
Components
| Robot |
|
|---|
Workflow
| STEP 1. | [Picking Process] |
|---|---|
| STEP 2. | Order Entry: Online orders are received and processed by the system. |
| STEP 3. | Targeting: Robots navigate to the specific racks containing the required items. |
| STEP 4. | GTP Transport: Robots lift the racks and move them to the picking station. |
| STEP 5. | Item Picking: Workers pick items from the racks brought by the robots. |
| STEP 6. | Return: Robots return the racks to their optimized storage positions. [Replenishment Process] |
| STEP 7. | Restock Request: A replenishment order is initiated for stock. |
| STEP 8. | Rack Retrieval: Robots move to the corresponding storage racks. |
| STEP 9. | Inbound Flow: Robots carry the racks to the replenishment station. |
| STEP 10. | Loading: New stock is loaded onto the racks by workers. |
| STEP 11. | Final Placement: Robots transport the replenished racks back to the storage area. |
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E-commerce Fulfillment using 120 units of Geek+ P500
- Implementing Company
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- Estimated Project Duration
- 0week
- Robot Model
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