With the increasing edge capabilities of artificial intelligence (AI) processing platforms, robots are quickly becoming a norm in heavy industrial and logistics-dependent settings. From autonomous mobile robots (AMRs) for stock management and delivery, to collaborative robots (cobots) working directly alongside human-driven assembly lines, physical AI-directed platforms increase operational efficiency while lowering manual labor costs.
Engineering teams targeting such applications may first establish a proof of concept (PoC) where hard evidence of conceptual viability is established, thus mitigating risk via early identification of technical or logistical hurdles. A PoC and eventual prototype enable AMR and cobot development teams to validate a platform’s perceptual and navigational frameworks while developing the application that will ultimately evolve into the final robotics solution, with an elevated level of confidence before moving toward production.
However, many robotics concepts fail to ever reach the factory or warehouse floor. This is not due to poor conceptualization. Rather, there’s a fundamental mismatch between standard prototyping platforms and long-term requirements in real-world deployment, where application-specific hardware, long-term availability, lifecycle support and industrial-grade reliability become essential.
A dead end for robotics prototypes
When building robotics prototypes, designers see commercial-off-the-shelf (COTS) development platforms as an effective solution, minimizing risk and initial cost while accelerating design timelines. The Arduino® VENTUNO™ Q board, for example, offers a powerful heterogeneous processing platform based on the Qualcomm Dragonwing™ IQ8 Series and a dedicated microcontroller for deterministic tasks with physical ports for connecting essential robotics peripherals such as cameras, Ethernet, and CAN-FD systems. It ships with 16 GB RAM and 64 GB expandable storage, and pre-loaded Ubuntu and a complimentary Ubuntu Pro license. All housed within a compact board, it enables easy edge intelligence experimentation and integration, allowing engineering teams to rapidly develop and validate robotics applications using the familiar Arduino software environment.
Understandably, such a platform is attractive for modern robotics teams. VENTUNO Q contains hardware fundamentals for supporting versatile builds, and when paired with the familiar Arduino software ecosystem, development is streamlined versus starting from zero. This enables teams to focus their engineering effort on developing application functionality rather than platform bring-up. Nevertheless, the difference between prototype and production is typically vast after post-prototype design optimization. This is not a matter solely contingent on AI processing hardware. In real-world industrial settings, robots require specific interface combinations; for example, CAN-FD, industrial Ethernet, sensor and functional safety interfaces, and motor-control networks. Development boards may have enough to validate a concept. However, to address application-specific requirements and efficiency, production-ready designs end up purpose-built, requiring hardware specifically engineered for the target application and deployment environment.
Industrial robots also require well-defined software lifecycle processes and security frameworks to meet key regulatory requirements, such as those dictated by the European Union’s (EU’s) Cyber Resilience Act (CRA). Prototype software stacks may require significant additional infrastructure to support secure updates, device lifecycle management, and software traceability.
Equally important, engineering teams need a migration path that allows them to move from rapid prototyping to production without disrupting the software workflows established during the development phase.
In short, a single AMR or cobot based on VENTUNO Q, or a similar platform, may fully prove an embedded AI concept. But device provisioning, long-term management, and updating mechanisms at scale to a fleet of fifty robots, for example, are often late to be considered. At deployment, these quickly become operational requirements, so many prototypes fail to scale, creating a wall to production rather than a clear path.
Robotics teams must realize that every prototyping decision, in both hardware and software, can directly affect production and eventual deployment. However, selecting production platforms that maintain continuity with the development environment used during prototyping can significantly reduce redesign effort, accelerate time-to-market, and help preserve the engineering work already invested in the application.
How to ease the transition from robotics PoC to production model
For robotics teams developing applications with VENTUNO Q, the challenge is no longer proving the concept, it is transforming that application into a production-ready robotics product. This is where the SECO SOM-SMARC-Dragonwing-IQ8 aims to bridge the gap between rapid prototyping and industrial deployment. The System-on-module (SOM) is based on the same Dragonwing™ IQ-8275 processor in a compact, production-aligned form factor. Based on the SMARC (Smart Mobility Architecture) open standard, SECO’s SOM does not feature physical connectors typical of a prototyping platform. Instead, a carrier board supports application integration, which robotics teams can design to meet the specific requirements of a given robotics platform, in contrast to the initial prototype. This modular approach gives developers the freedom to design application-specific hardware while preserving continuity with the software environment established during prototyping.
On the SOM-SMARC-Dragonwing-IQ8, that processor family delivers up to 40 TOPS of on-device AI performance for perception and sensor fusion, support for up to 12 concurrent camera inputs, and a SIL3-compliant safety island for functional-safety-relevant control tasks, on a SMARC® Rel. 2.1.1 module built for industrial operating conditions. Teams that want to validate the module before committing to a custom carrier board can start with SECO’s DEV-KIT-SMARC, a development and carrier board designed to host the SOM-SMARC-Dragonwing-IQ8 for early bring-up and testing.
The transition is not limited to replacing a development board with a production-ready module; it is about evolving a prototype into a complete industrial product. Compatibility with Arduino software frameworks provides engineering teams with a more continuous software path, allowing applications and development work created during the prototyping phase to be carried forward and adapted for an industrial SECO hardware platform. This helps reduce duplicated engineering effort while enabling teams to focus on designing the application-specific hardware and integrating the security, connectivity and lifecycle capabilities required of the final robot solution.
SOM-based design also has lifecycle advantages for long-term robotics deployments. The established, open-standard nature of SMARC mitigates vendor lock-in and reduces carrier redesign efforts when migrating between compatible SMARC modules, as AI processing platforms advance. Designers can also reuse much of the same carrier-board architecture across related robotics platforms, streamlining development efforts across entire product families. This enables robotics manufacturers to accelerate future product generations while protecting both hardware and software development efforts over the long term.
Long-term lifecycle management for industrial robot fleets
Industrial robotics deployments also require a software layer beyond the hardware transition, to support device lifecycle, fleet management, secure updates, and more. To address these requirements, SECO provides software infrastructure for long-term management of industrial edge devices, including robotics fleets.
SECO is also developing a version of Clea OS designed to provide full support for the Arduino software stack, helping teams industrialize applications developed within the Arduino software ecosystem through a production-ready operating system and software infrastructure designed for embedded robotics. Planned usability features, including package-based software management and a desktop-style graphical interface, are intended to lower the entry barrier for developers who are less familiar with embedded operating systems, while retaining the security, manageability, and customization required for industrial deployments.
Built as a highly modular Linux framework based on the Yocto Project, Clea OS is engineered to allow developers to utilize the heterogeneous architecture of the Dragonwing™ IQ-8275 processor while also providing robust security measures, such as secure boot and secure over-the-air (OTA) updates with A/B partitioning, minimizing downtime and promoting operational continuity.
Clea OS’ basis in Yocto is intended to add great flexibility to robotics stacks by helping enable full OS customization and removing unnecessary, resource-draining packages typical of general-purpose Linux distributions. Yocto also supports reproducible builds, automated software bill-of-materials (SBOM) generation, and high traceability in its software components, making it well-aligned with CRA mandates. The broader Clea software framework further supports CRA-aligned robotics deployments by enabling secure and timely OTA updates, device telemetry monitoring, and fleet management at scale. Together, these capabilities should allow robotics manufacturers to deploy, monitor, maintain and continuously evolve their products throughout their operational lifetime, helping to reduce maintenance costs while supporting long-term compliance with evolving cybersecurity requirements.
Conclusion
Development boards such as VENTUNO Q provide an accessible environment for validating AMRs and cobots. Moving those concepts into production, however, requires more than equivalent compute performance. It requires production-ready hardware, a compatible path for application software, and an infrastructure for securely managing devices throughout their operational lifecycle.
SECO addresses this transition through a combination of production-ready embedded hardware and software infrastructure. While the SOM-SMARC-Dragonwing-IQ8 provides the industrial hardware foundation for application-specific robotics platforms, Clea helps enable teams to industrialize applications developed within the Arduino software ecosystem, providing the security, lifecycle management, software maintainability and deployment capabilities required for commercial robotics products.
Stay updated on SECO’s SOM-SMARC-Dragonwing-IQ8, now open for pre-order ahead of its planned Q3 2026 availability, and the path from Arduino-based robotics prototypes to industrial deployment.
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