🤖 New Era in Industrial Robot Safety: More Capable, More Widespread, More Secure! 🚀

[Elif Özaksu]

As collaboration between robots and humans in industrial environments increasingly grows, robot safety is also gaining a new dimension. This situation offers great advantages for both employees and businesses. We discussed these exciting developments with NexCOBOT General Manager Jenny Shern.

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💡 Where is Robot Safety Evolving?​

According to Shern, the understanding of safety in the industrial field is transforming from a static requirement into an active and intelligent layer that keeps pace with the development of human-robot collaboration and AI-powered robots. She states that while robots work side-by-side with humans, AI alone is not sufficient for precision and real-time performance. Even if high-level AI perception is integrated, she emphasizes that motion control, safety-certified hardware, and software should be prioritized.

Furthermore, investments by large technology companies in the robotics sector are creating a critical ecosystem gap that requires protocol evolution and bridging. These companies often prefer proprietary, closed-loop systems, which conflicts with the fragmented manufacturing sector's reliance on established industrial standards like PLCs and EtherCAT, and new software frameworks like ROS 2. She states that widespread industrial deployment of robots will be challenging unless the robotics industry adopts standardized protocols similar to those in the PC or mobile sectors.

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⚙️ What is the Cutting Edge in Robotic Motion Control?​

At the forefront of robotic motion control is the ability of legged and humanoid robots to learn motion control. Shern states that this ability allows robots to learn on their own, rather than being programmed with functions. However, she points out the difficulty of this situation: when the AI model is integrated with motion control, the robot's "brain" (AI model) thinks much slower compared to its "body" (motors). If the body waits for the brain every time it needs to move, the result is jerky and stuttering movements.

She adds that even if the AI model is technically intelligent enough, an intermediary is needed to trigger specific motor commands at precisely the right microsecond.

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🤝 How to Integrate High-Performance Computing, Real-Time Control, and Functional Safety?​

Shern states that this process, which she calls "seamless integration of high-performance computing, real-time control, and functional safety," begins by acknowledging that each component serves a different purpose but must work together without competing for priority. While AI and high-performance computing provide the robot with sensing, planning, and decision-making capabilities, the real-time control layer ensures that these decisions translate into smooth and predictable motion.

Functional safety, on the other hand, operates independently, continuously monitoring the system and intervening when unsafe conditions arise. She states that as manufacturers use more AI-powered robots alongside human workers, successful integration will depend on architectures that tightly coordinate these layers, allowing robots to make intelligent decisions while maintaining the precision, reliability, and safety required in factory environments.

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🔮 What Will Next-Generation Robotic Solutions Look Like?​

Two fundamental shifts are shaping the future of robotic solutions: how robots are trained and how they are built. On the training side, Shern predicts that real change will come as the industry creates scalable, robust, and high-quality video datasets. Once this foundation is laid, AI will be able to train robots in a wide variety of complex tasks, such as automotive maintenance, aerospace, and healthcare, in a much shorter time than traditional programming would require.

Currently, engineers code robots for a single specific task. This shift will enable future robotic solutions to be multi-tasking and agile enough to be redeployed in response to changing needs. On the building side, the industry is shifting towards open, platform-based development.

Next-generation robots, whether humanoid, quadruped, or mobile platforms, will not be built by a single person. Open platforms will provide engineers with access to ready-made AI models, control layers, and safety technology, allowing them to focus human efforts on navigation, sensing, voice interaction, and task-specific workflows. These changes will contribute to faster development cycles, wider deployment across industries, and a collaborative robotics ecosystem.