Modern robotic platforms should be designed with security as a foundational principle, incorporating architectural controls such as least-privilege execution, strong isolation between system components, and robust fault containment.
Key Considerations for Robotics Manufacturers Ensure Secure Connected Systems
Q&A with Winston Leung, Senior Strategic Alliances Manager | QNX
Winston Leung is an innovation strategist and technology leader with over a decade of experience advancing robotics, autonomy, and intelligent systems across North America and Asia. He has worked at the intersection of emerging technologies, business strategy, and public policy helping drive adoption of autonomous, connected, and electric vehicles while shaping supportive ecosystems for innovation. Winston’s notable achievements include spearheading Canada’s first connected vehicle testbed and guiding go-to-market strategies for breakthrough technologies such as quantum computing and 5G.
In his current role as Senior Strategic Alliances Manager at QNX, Winston focuses on functional safety, real-time performance, and reliability for embedded systems across robotics, medical devices, and transportation sectors. He has collaborated with global stakeholders, advised on government policies, and supported startup growth, combining technical depth with strategic vision to shape the future of autonomous and robotic technologies.
Tell us about yourself, your role at QNX and how you got there?
From autonomous vehicles to surgical robots, my career has long been driven by an interest in how complex software enables intelligent machines to operate safely in the real world. For the past decade, I’ve worked on advancing autonomous and connected technologies, helped shape early connected vehicle testbeds and collaborated with partners to bring emerging technologies closer to real-world deployment. Today, I’m Senior Strategic Alliances Manager at QNX where I focus on building partnerships that help robotics and embedded systems companies bring their innovations to life on a foundation of real-time determinism, safety, security and reliability. QNX is trusted in safety-critical applications across industries from automotive and medical devices to industrial automation and robotics, and my role is centered around building our ecosystem so that we can better help our customers navigate the path from prototype to production with ease and confidence.
What is the role of QNX in robotics?
QNX serves as the real-time, IEC 61508 SIL 3 safety-certified foundation for modern robotic systems, enabling deterministic control, system reliability, and secure operation. It provides the operating system and hypervisor layers, as well as other open and proprietary middleware frameworks, that coordinates sensing, decision-making, and actuation with deterministic performance. The QNX microkernel architecture supports fault isolation, scalability, and long-term maintainability, ranking first overall as the RTOS for Robotics Functional Safety by ABI Research. QNX is the platform for robotic applications that must meet stringent safety, security, and reliability, while still integrating advanced workloads for autonomy, AI/ML, and high-performance perception.
By using QNX, what are the biggest advantages for robot innovators and manufacturers?
Robot innovators and manufacturers gain a trusted, real-time software foundation that reduces risk while accelerating development and deployment. QNX delivers deterministic performance, fault isolation, and proven safety and security capabilities essential for robots operating around humans and in real-world environments. This allows teams to focus on engineering effort on differentiation – such as autonomy, perception, and AI – rather than building a validating core system infrastructure from scratch.
QNX also enables long-term scalability and lifecycle efficiency. Its modular architecture supports hardware flexibility, mixed-criticality workloads, and software reuse across product generations helping reduce total cost of ownership and time to market. Combined with common tooling, certification support, open ecosystem and mature partner networks, QNX provides a stable platform that can evolve as robotics systems grow more autonomous and software defined.
Cybersecurity is a growing issue in robotics, what key considerations should robotics manufacturers and companies keep in mind to ensure secure connected systems?
As robotics systems become increasingly software-defined and connected – to cloud services, enterprise networks, and other devices – the cybersecurity risks expand significantly, making a strong security posture and formal certification an essential component to a robot’s design and software considerations. Modern robotic platforms should be designed with security as a foundational principle, incorporating architectural controls such as least-privilege execution, strong isolation between system components, and robust fault containment to limit the impact of vulnerabilities or malicious acts. However, technology alone is insufficient: robotics manufacturers must also demonstrate that both their organization’s processes, development practices, and products follow disciplined, auditable cybersecurity practices. Certification to standards such as IEC 62443 is critical in this context, as it provides a globally recognized framework for secure system design, development lifecycle governance, and operational security across industrial and robotic environments. This standard helps ensure that security is addressed end-to-end – from threat modelling and secure boot to access control, patch management, and incident response – rather than treated as an afterthought. As robots take on more autonomous and safety-critical roles, the potential consequences of cyberattacks increase, ranging from IP theft and operational disruption to physical harm, making certification, defense-in-depth, and continuous vulnerability management key considerations for any deploying their connected robotic systems. Against this backdrop, QNX enables manufacturers to move faster and with less risk delivering a security-first platform designed to support IEC 62443 certification and the realities of highly connected, safety-critical robotic systems.
What role does the operating system play in robots and mission-critical systems ensuring safety?
The operating system is one of the most critical components in robotic systems. It serves as the foundation that orchestrates the system that includes hardware and software and ensures they work in harmony. All sensing, control, decision-making, and actuation ultimately flow through the OS, meaning its performance directly impacts the behavior and reliability of the entire system. This is why a hard real-time OS is especially critical for these systems. It provides deterministic scheduling, low latency, and minimal jitter – ensuring tasks, especially critical ones, execute when they are supposed to, every time with no compromise. With QNX, this real-time behavior reduces timing variability, which allows for greater precision, more predictable control loops, and safer system responses. Lower jitter is particularly important for motion control, perception pipelines, and closed-loop feedback, where small timing deviations can lead to instability or unsafe behavior. The OS is responsible for interrupt handling and prioritization, ensuring that safety-critical events are serviced immediately, without delay, even under heavy system load. As a result, the OS is not just an enabling component but a safety-critical element itself, forming the backbone on which dependable, high-performance systems are built.
What are the biggest trends shaping robotics for the rest of 2026?
In a recent study we commissioned, 77% of global technology leaders said they already trust robotics for essential functions in the workplace. That level of confidence is expected to rise significantly as robotics moves from experimental or narrowly defined use cases into more central, day-to-day operational roles across industries. As we look toward the future, I expect several trends to shape the industry:
- First, robots are becoming core operational infrastructure, not just task-specific tools. We’re seeing a shift toward robots embedded directly into workflows across manufacturing, logistics, healthcare, and service environments.
- Second, software consolidation and platformization are accelerating. Developers want fewer fragmented systems and more unified software foundations that allow them to scale faster and reduce integration complexity.
- Third, there is a growing expectation of safety, security, and reliability by default, especially as robots operate more frequently in human-centric environments. This is pushing demand for deterministic, real-time systems that can guarantee predictable behavior under all conditions.
As robotics rapidly evolves, what skills will be critical for the next generation of developers?
As robotics continues to evolve rapidly, the next generation of developers will need a hybrid skill set that spans software, systems thinking and domain awareness. Strong fundamentals in real-time and embedded software remain critical, including an understanding of operating systems, concurrency, timing, and hardware interaction, because performance, determinism, and reliability are foundational to safe robotic behavior. At the same time, developers must be comfortable working across the full software stack – from low-level control and sensor integration to higher-level autonomy, AI/ ML and perception – while understanding how design decisions at one layer impact system behavior as a whole.
Equally important are skills in safety, security and lifecycle engineering. As robots become more connected and autonomous, developers must think beyond functionality to include cybersecurity, functional safety, and standards compliance as part of the design process. As robotics innovation increasingly becomes more complex, collaboration and working with the right partners will be essential for developing and deploying next generation robotic systems.
The content & opinions in this article are the author’s and do not necessarily represent the views of RoboticsTomorrow
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