Real-time IO-Link Sensor from IFM AL1122 to Isaac Sim | Hybrid Digital Twin

Описание: In this video, I demonstrate how to connect a physical IO-Link sensor to NVIDIA Isaac Sim using the IFM AL1122 IO-Link Master. Watch as physical sensor detection drives virtual object behavior in real-time — this is NOT a simulation, it's actual hardware-in-the-loop communication!

✨ Key Innovations:
• Auto-discovery algorithm (zero configuration!) - Automatically found Instance 100, Byte 0, Bit 1
• Real EtherNet/IP communication with connected=False parameter
• Hardware-in-the-loop digital twin demonstration
• Perfect synchronization between physical and virtual worlds
• Aggregated assembly data reading (Instance 100)

⏱️ Timestamps:
0:00 - Introduction & Setup Overview
0:25 - Hardware Connections (Sensor → Ethernet → Power)
1:00 - AL1122 Module Overview
1:10 - Physical Sensor Testing
1:30 - LR-Device Configuration
1:55 - Isaac Sim Setup
2:15 - Script Node & Auto-Discovery Algorithm (Technical Deep Dive)
4:00 - Ready for Testing
4:20 - Demo 1: Isaac Sim + LR-Device Synchronization
4:28 - Demo 2: Isaac Sim + Physical Module (Split Screen!)
4:55 - Conclusion & Resources


💻 Hardware Requirements:
• NVIDIA Isaac Sim
• IFM AL1122 IO-Link Master
• IO-Link compatible sensor (e.g., inductive proximity sensor)
• 24V DC power supply
• Network switch and Ethernet cables

🐍 Software Requirements:
• Python with pycomm3 library
• Isaac Sim Script Node API

🎓 What You'll Learn:
✓ EtherNet/IP communication with industrial devices
✓ Isaac Sim Script Node development
✓ Hardware-in-the-loop simulation techniques
✓ Auto-discovery algorithm implementation
✓ Digital twin concepts for industrial automation
✓ Why connected=False is critical for AL1122
✓ Assembly instance mapping (Instance 100 vs 101)

🔗 Useful Links:
• IFM AL1122 Product Page: https://www.ifm.com/
• Isaac Sim Documentation: https://docs.omniverse.nvidia.com/isa...

📧 Questions? Drop a comment below!

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This project demonstrates true hybrid digital twin technology — combining real physical sensors with virtual simulation for industrial automation, robotics training, and predictive maintenance applications.

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