Project Overview
This video presents an autonomous mobile robot (AMR) logistics transport system based on SLAM (Simultaneous Localization and Mapping). It provides an optimal solution for logistics and precision repetitive tasks on production sites by implementing autonomous unmanned transport and loading. Key features include Laser Sensing-based self-mapping and optimal path securing with safety through 2D/3D cameras for object recognition and obstacle identification. The system can be equipped with various applications such as collaborative robots (Co-Bots), roller conveyors, and Jack-Up systems.
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
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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. |
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Haemil FA Collaborative Robot & AMR
- Implementing Company
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- Estimated Project Duration
- 0week
- Robot Model
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