The CE approval opens Europe for Cornerstone Robotics as the company expands its global surgical robotics business
Updated
May 29, 2026 4:20 AM
A tray of surgical tools. PHOTO: UNSPLASH
As surgical robotics companies expand beyond domestic markets, regulatory approvals are becoming a critical part of global growth. Companies are no longer competing only on hardware and clinical performance. They are also competing on their ability to enter tightly regulated healthcare systems and build long-term hospital partnerships.
Hong Kong-based Cornerstone Robotics is now moving further into that phase of expansion after its Sentire Endoscopic Surgical System received CE Mark certification under the European Union’s Medical Device Regulation framework.
The approval allows the company to commercialize the system across European markets for minimally invasive procedures in general surgery, gynecology, thoracic surgery and urology. For surgical robotics companies, regulatory approvals often represent more than product validation. They also determine market access, hospital adoption opportunities and long-term commercial scale.
Cornerstone Robotics has already been building clinical operations in the UK ahead of the approval. Since 2025, the company has worked with Portsmouth Hospitals University NHS Trust on clinical investigations involving the Sentire Surgical System. According to the company, the system has been used across procedures involving urology, gynecology and gastrointestinal surgery. The company says the clinical investigation helped generate real-world data to support physician training, research and future adoption efforts.
Alongside the regulatory approval, Cornerstone Robotics is also expanding its local operations in Europe. The company established a UK subsidiary in 2025 and has been developing training, clinical support and after-sales service capabilities for hospitals using the system.
That operational buildout reflects a larger challenge inside surgical robotics. Hospitals adopting robotic systems often require ongoing clinical training, technical support and workflow integration alongside the hardware itself.
Cornerstone Robotics says its strategy centers around vertically integrated development across engineering, software, imaging and robotics systems. The company argues that this structure gives it greater control over product development, supply chain management and long-term operational stability.
Professor Samuel Au, Founder and CEO of Cornerstone Robotics, said: "Receiving CE Certification marks a major milestone in Cornerstone Robotics' evolution from a technology innovator to a global clinical solutions provider. From our first clinical investigation in Portsmouth, UK, to achieving European regulatory approval, each step of the journey reflects our commitment to proprietary innovation, product excellence, and clinical value. Looking ahead, we will continue expanding into key global markets and partnering with leading medical institutions to bring high-quality surgical robotic solutions to more physicians and patients worldwide."
The CE approval also comes several months after the company completed an oversubscribed financing round of approximately US$200 million in November 2025.
The funding and regulatory expansion together signal how surgical robotics companies are increasingly entering a more commercially focused stage of growth. Beyond research and development, companies are now investing more heavily in regulatory approvals, hospital partnerships, physician training and international operational infrastructure as competition expands across global healthcare markets.
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Robots that learn on the job: AgiBot tests reinforcement learning in real-world manufacturing.
Updated
January 8, 2026 6:34 PM
A humanoid robot works on a factory line, showcasing advanced automation in real-world production. PHOTO: AGIBOT
Shanghai-based robotics firm AgiBot has taken a major step toward bringing artificial intelligence into real manufacturing. The company announced that its Real-World Reinforcement Learning (RW-RL) system has been successfully deployed on a pilot production line run in partnership with Longcheer Technology. It marks one of the first real applications of reinforcement learning in industrial robotics.
The project represents a key shift in factory automation. For years, precision manufacturing has relied on rigid setups: robots that need custom fixtures, intricate programming and long calibration cycles. Even newer systems combining vision and force control often struggle with slow deployment and complex maintenance. AgiBot’s system aims to change that by letting robots learn and adapt on the job, reducing the need for extensive tuning or manual reconfiguration.
The RW-RL setup allows a robot to pick up new tasks within minutes rather than weeks. Once trained, the system can automatically adjust to variations, such as changes in part placement or size tolerance, maintaining steady performance throughout long operations. When production lines switch models or products, only minor hardware tweaks are needed. This flexibility could significantly cut downtime and setup costs in industries where rapid product turnover is common.
The system’s main strengths lie in faster deployment, high adaptability and easier reconfiguration. In practice, robots can be retrained quickly for new tasks without needing new fixtures or tools — a long-standing obstacle in consumer electronics production. The platform also works reliably across different factory layouts, showing potential for broader use in complex or varied manufacturing environments.
Beyond its technical claims, the milestone demonstrates a deeper convergence between algorithmic intelligence and mechanical motion.Instead of being tested only in the lab, AgiBot’s system was tried in real factory settings, showing it can perform reliably outside research conditions.
This progress builds on years of reinforcement learning research, which has gradually pushed AI toward greater stability and real-world usability. AgiBot’s Chief Scientist Dr. Jianlan Luo and his team have been at the forefront of that effort, refining algorithms capable of reliable performance on physical machines. Their work now underpins a production-ready platform that blends adaptive learning with precision motion control — turning what was once a research goal into a working industrial solution.
Looking forward, the two companies plan to extend the approach to other manufacturing areas, including consumer electronics and automotive components. They also aim to develop modular robot systems that can integrate smoothly with existing production setups.