Erkan Teskancan
Corporate
- Thread Author
- #1
The world of robotics is rapidly evolving! Systems are becoming more software-centric, AI-powered, and ready to work alongside humans. So, what are the fundamental dynamics behind this transformation? QNX's (part of BlackBerry Limited) "Inside the Robot: Architecture Benchmark Report" sheds light on these questions.
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π Key Findings from Global Developers
A survey of 1,000 developers worldwide revealed striking results about the future of the robotics sector. The research indicates an increasing focus on software foundations to overcome critical challenges such as performance, security, and scalability.
[]Approximately 89% of participants state that physical AI is vital for their future plans.
[]Deterministic and real-time behavior is indispensable for 95% of robotics developers.
[]Despite increasing demands for safety and security, 91% still rely on general-purpose operating systems (GPOS) to run real-time or safety-critical workloads.
[]86% of participants using GPOS express openness to changing their operating systems, highlighting concerns about the suitability of existing solutions.
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βοΈ Software Architecture and Integration: The Biggest Obstacle?
The research reveals that 27% of developers view software architecture and integration as the biggest performance bottleneck. Only 16% point to hardware. This indicates that future progress is less about new hardware and more about building systems that are predictable, secure, and capable of managing different criticality levels.
As robots expand from controlled environments (like operating rooms and factory floors) to real-world settings, developers realize that software foundations are the decisive factor in the success of innovation.
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π Future Robotics Investments: AI and Cybersecurity
85% of developers expect software to play an even larger role in robotics in the next 3-5 years. The largest investments are predicted to be in AI-powered decision-making and cybersecurity, at 51%. Operating systems and real-time control software follow with 37%. These data prove that as robotic systems become more complex, interconnected, and distributed, software foundations are transforming into strategic assets.
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π€ Human-Robot Collaboration and Security Concerns
Robotics teams are already feeling the effects of this change; 83% of participants state that their systems now work alongside humans. Of those not yet deployed with humans, 67% expect to transition to this state within 3-5 years. This expanding presence in uncontrolled environments increases expectations for reliability, safety, and predictable behavior. 95% of participants emphasize that deterministic, real-time execution is important for the systems they develop.
However, most development teams still rely on software not designed for real-time or safety-critical uses. The research shows that 91% of participants run these workloads at least partially on GPOS. This persists despite safety-certified commercial solutions being rated as most suitable for their needs. Consequently, 86% of these GPOS users state they are open to changing their operating systems. This contradiction encapsulates the increasing tension between flexibility and the need for predictable, guaranteed behavior as robotic deployments scale.
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βοΈ Regulatory Hurdles and Regional Differences
Regulatory and compliance demands further exacerbate these challenges. 66% of participants report experiencing project delays due to certification processes. This rate rises to 70% in the UK and Germany, while remaining at only 56% in China due to less stringent regulatory requirements. These delays directly impact development costs, delivery times, and commercial risk. Cybersecurity and functional safety standards are among the most difficult areas to comply with, at 51% and 49% respectively.
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π Optimism for the Future and Solutions
Despite all these pressures, ambition and optimism in the sector remain high. Physical AI is definitely on the roadmap; 89% of participants state that AI-powered robots capable of perceiving, reasoning, and moving autonomously in the physical world will be critical to their organization's strategy within the next 3-5 years. China is taking global leadership in this area. While confidence in the long-term potential of physical AI is strong, readiness is still uneven. Only 29% of participants express "high confidence" in their ability to make safe and predictable decisions in real-world environments.
Jim Hirsch, QNX's VP of global sales for general embedded markets, says, "Robotics teams are clearly moving towards smarter, autonomous systems, but the data shows they are hitting the real limits of architectures never designed for this level of complexity or accountability." Hirsch adds that developers consistently mention four core challenges: integration complexity, certification delays, functional safety risks in human-machine interaction, and ensuring predictable behavior when it's most needed. The good news is that these are all solvable problems, and by focusing on stronger software foundations, developers can accelerate innovation and pave the way for the next generation of safe, reliable, and highly autonomous robots.
