Smart E-commerce Logistics using 15 units of Geek+ P800 (AMR)

This application case features an automated picking and replenishment system utilizing 15 Geek+ P800 mobile robots within an e-commerce fulfillment center. By integrating specialized picking and replenishment stations, the system uses self-learning algorithms to optimize warehouse layouts based on SKU movement frequency, maximizing storage density and operational efficiency in a compact space.

Components

Robot	Robot: Geek+ P800 (15 Units) Max Payload: 1,000kg Speed: 2.0m/s (Empty) / 1.6m/s (Full load) Navigation: Inertial Sensor + QR Code Dimensions: L1090 x W830 x H275 mm / Weight: 195kg Lifting Height: 60mm / Stop Accuracy: ±10mm Efficiency: 2–3 hours of operation with a 10-minute charge. Operating Temp: -20°C to 50°C.

Workflow

STEP 1.	[Picking Process]
STEP 2.	Order Entry: Online orders are received and entered into the system.
STEP 3.	Targeting: Robots navigate to the specific racks containing the ordered items.
STEP 4.	Transport: Robots lift the racks and move them to the designated picking station.
STEP 5.	Item Picking: Workers pick the required items from the delivered rack.
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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Key Features

Exceptional Performance & Maximized Space Utilization

Compact Efficiency: Build a high-performance logistics center even within limited footprints by utilizing space-saving mobile robot technology.
Intelligent Storage Optimization: Automatically reconfigures storage layouts based on SKU movement frequency to minimize travel time for both picking and replenishment.
Heavy-Duty Handling: Robustly transports heavy loads up to 1,000kg.
Operational Versatility: Supports a hybrid mix of pallet and rack-based workflows.
Flexible Picking Strategies: Adaptable to multiple methods, including discrete order picking and total (batch) picking.
High Throughput: Achieves a picking rate of 300 to 600 pieces per hour per worker.

Minimized Investment & Operational Excellence

RaaS (Robots-as-a-Service) Model: Minimizes initial CAPEX while maximizing uptime through professional maintenance and service-based operation.
Massive Fleet Management: Advanced technology capable of coordinating and optimizing fleets of over 100 units simultaneously.
24/7 Productivity: Automated self-charging ensures non-stop, day-and-night operation.

High Stability and Global Reliability

Proven Track Record: Reliability is guaranteed by a global installation base of over 10,000 units operating worldwide.

Implementation Results

ROI Period	24 months
Key Metrics	Storage Efficiency: Significant increase in inventory density within the existing footprint. Time Optimization: Drastic reduction in lead times for both restocking and picking processes.
Client Feedback	By implementing the Geek+ solution, we reduced our storage footprint by 30% and successfully gained the capacity to rapidly process approximately 300,000 orders per day.

※ The content provided by Marosol is protected under U.S. and Canadian copyright and intellectual property laws. Unauthorized reproduction, distribution, or use of this content is strictly prohibited.

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The content provided by Marosol is protected under U.S. and Canadian copyright and intellectual property laws. Unauthorized reproduction, distribution, or use of this content is strictly prohibited.

※ The content provided by Marosol is protected under U.S. and Canadian copyright and intellectual property laws. Unauthorized reproduction, distribution, or use of this content is strictly prohibited.

Components

Workflow

Key Features

Implementation Results

Smart E-commerce Logistics using 15 units of Geek+ P800 (AMR)

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