🤖 Industrial Robot Safety Control Architecture: A New Era in Human-Robot Collaboration 🚀

[Semih Asil]

Safety Solutions for Next-Generation Robotics from NEXCOM​

AI-powered and humanoid robots in industrial automation and logistics require reliable functional safety mechanisms to regulate human-robot interaction. NEXCOM introduced safety control frameworks and open architecture platforms addressing this need at NVIDIA GTC Berlin.

⚙️ Core Technology and System Architecture​

At the heart of the introduced architecture is the RCB400 humanoid robot controller, which integrates the NVIDIA IGX Thor edge AI platform, capable of simultaneously processing perception workloads requiring high computational power and real-time motion control commands. The system operates with NEXCOM's proprietary NexRTOS real-time operating system and NexECM EtherCAT motion control software, which manages multi-joint synchronization. Spatial data collection relies on a RealSense D555 depth camera that monitors human positioning parameters within the workspace. To provide hardware-level redundancy, an EBK Safety MCU expansion board monitors the status of the central controller. If an anomaly occurs, the safety microcontroller intervenes independently, executing the NVIDIA IGX Thor platform's native functional safety routines in accordance with IEC 61508 and ISO 13849 requirements.

🚀 Ease of Deployment and Application​

This solution is implemented as a pre-integrated modular framework through the RoboWIZ AI Robot Open Platform. Deployment involves connecting industrial-grade vision sensors like RealSense and StereoLabs, as well as Synapticon ACTILINK-JD08 high-dynamic joint modules communicating via EtherCAT protocols. While system integrators embed the hardware architecture directly into humanoid robot chassis, functional safety engineering frameworks provided by partners like Reynolds & Moore manage hazard assessment and safety validation workflows, reducing custom integration times.

🏭 Industrial Applications​

Target sectors include smart manufacturing, automated logistics, and commercial service environments where autonomous systems work alongside personnel. Specific use cases include dynamic speed reduction based on proximity calculations and hard stop intervention if operators exceed defined hazardous boundary thresholds. These mechanisms ensure process safety while preventing mechanical overload or uncontrolled trajectory deviations.

📈 Operational Impact and Performance Metrics​

The integration of edge AI processing and hardware-level safety monitoring reduces latency in human detection feedback loops. The dual-core architecture separates standard operating system functions from deterministic safety routines, ensuring that safety-rated interruptions are executed without bus congestion. The inclusion of hardware safety microcontrollers and pre-validated open platform components minimizes custom validation steps, shortening compliance times with international machinery directives.