Process layout
This video information presents an autonomous logistics transport Forklift system based on SLAM (Simultaneous Localization and Mapping). It provides an autonomous unmanned method for logistics transport and stacking tasks, ensuring safety through Navigation Scan Lidar for positioning, Multi-Lidar for object and obstacle recognition, and 2D/3D cameras for pallet and cage loading.
What is SLAM (Simultaneous Localization and Mapping)? It is a core technology for autonomous driving where a robot creates an accurate map of its work environment using only its onboard autonomous sensors while navigating the workspace.
Project Background & Objectives
Accurate and repetitive logistics tasks using autonomous robots.
Components
| Robot |
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Workflow
| STEP 1. | Scenario Configuration: Configure transport and loading scenarios according to the work environment. |
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| STEP 2. | System Integration: Install and connect the system to the site. |
| STEP 3. | SLAM Mapping: Create a work map using the AMR’s built-in SLAM function. |
| STEP 4. | Site Application: Implement the system for operational use. |
Features
Operational Efficiency and Safety
Market Proven AMR: Secured stability with the world's No. 1 global market share in autonomous mobile robots.
Efficient Space Utilization & Optimal Logistics Routing: Implementation of SLAM-based 3D mapping and Digital Twin CCTV monitoring.
Max 12–18 Months ROI
Expected ROI within 12–18 months for standard sales.
Labor costs (including incidental expenses) X 2 Shifts = 90–100 million KRW per year (Forklift purchase cost excluded).
Results
| Key Benefits | Reduced operational losses + reduced accidents = increased opportunity cost.
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| Client Feedback | "Thanks to the outstanding performance of the unmanned forklift, we were able to configure stable and accurate logistics scenarios."
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