Overview
In the fast-moving world of robotics, engineering teams are under constant pressure to transform advanced autonomy concepts into machines that can operate reliably beyond the lab. A robotics OEM developing agile autonomous systems needed rugged, high-performance compute that could support real time control, AI perception, and scalable I O inside compact robot platforms. By adopting Premio’s rugged AI edge industrial computer, the team gained a durable and configurable foundation for moving robotic systems from prototype testing to field ready deployment.
Challenges
- CPU performance headroom for dense real time control and perception pipelines
- Limited PCIe and I O expansion for motion controllers, sensors, and safety interfaces
- Thermal, shock, and vibration stress from test rigs and pilot deployments causing premature hardware failures
- Inconsistent mounting footprints across prototypes leading to redesign and rewiring work
- Need for UL and CE ready compute to shorten time to market in safety sensitive environments
Solution
- Premio’s rugged AI edge industrial computer (RCO-6000-RPL-2)
- Intel Core processor support with hybrid P core and E core architecture
- EDGEBoost expansion for GPUs, AI modules, storage, 5G, Ethernet, USB, and remote management
- Fanless rugged design with wide temperature, shock, vibration, and wide voltage support
- Wall mounting and front accessible I O for repeatable integration across robot platforms
Benefits
- Faster prototype to deployment cycles
- Higher uptime in demanding test environments
- Scalable compute foundation for future robots
Company Overview
A robotics OEM designs agile autonomous systems for industrial, research, and advanced automation customers. The engineering team excels at combining whole body control, intelligent autonomy, and highly integrated mechatronics into compact robotic platforms. Its future direction is focused on moving more robots from lab validation into dependable deployments across manufacturing, logistics, and research environments.
The Challenges
Real Time Compute for Whole Body Control
Agile robots rely on fast control loops, sensor fusion, perception, and safety monitoring working together without interruption. Early compute platforms struggled to provide enough CPU headroom as engineers added more autonomy features and higher data rates. The team needed industrial computing performance that could keep pace with dense robotics workloads while preserving room for future algorithm growth.
Fragmented I O and Expansion Across Platforms
Each robot generation introduced new servo drives, cameras, lidar sensors, networking requirements, and safety interfaces. Without a flexible expansion architecture, the engineering team risked redesigning compute, cabling, and carrier hardware each time the robot platform evolved. A more modular approach was needed to support different configurations while maintaining a common compute foundation.
Environmental Stress in Labs and Pilot Deployments
Although much of the work began in controlled lab spaces, robots still experienced shock, vibration, heat, transport stress, and unpredictable test conditions. Consumer style computers and fan based systems created reliability concerns when installed near batteries, drives, actuators, and moving assemblies. The team needed rugged fanless hardware that could operate in harsh edge environments without becoming a point of failure.
Mechanical Integration and Mounting Churn
Mechanical designers needed a repeatable compute footprint that could fit into multiple robot platforms. When each prototype used a different PC form factor, brackets, cable routing, and service access had to be redesigned. This slowed down design freezes and made it harder to create a clean path from prototype builds to manufacturable robot systems.
Certification Pressure from Industrial Customers
As robotic systems moved closer to customer facing pilots, buyers began asking for documentation around safety, emissions, and reliability. Using ad hoc computing hardware would have increased the burden on the robotics OEM during qualification and certification planning. The team needed a compute platform designed with UL, CE, FCC Class A, and industrial compliance requirements in mind.
The Solution
Standardizing on a Rugged Edge Compute Platform
The engineering team selected the RCO-6000-RPL-2 as the baseline compute platform for next generation robotic systems. Its support for Intel Core Series 2, 14th, 13th, and 12th Gen processors gave the team scalable performance options for different autonomy workloads. By standardizing on one rugged industrial platform, software, electrical, and mechanical teams reduced the number of compute variants they needed to validate and support.
Supporting Real Time Workloads with Hybrid Core Processing
The RCO-6000-RPL-2 supports Intel hybrid architecture with Performance cores and Efficient cores, allowing demanding workloads to be distributed across high performance and background processing tasks. In robotics applications, this helps separate compute intensive perception and control functions from supporting processes such as logging, communication, and system monitoring. The result is a more balanced compute environment for robots that need fast, responsive decision making at the edge.
Expanding Robot I O with EDGEBoost Modularity
The team used EDGEBoost expansion to support changing robotics requirements without replacing the core computer. GPU acceleration, AI modules, additional Ethernet, 10GbE, M12 LAN, USB, 5G, NVMe storage, and remote management options gave engineers flexibility as sensor and actuator architectures evolved. This allowed new robot configurations to be tested and refined while preserving a consistent compute architecture across platforms.
Deploying Rugged Fanless Hardware Inside Mobile Robots
The RCO-6000-RPL-2’s fanless design, wide temperature support, 9 to 48VDC power input, and rugged shock and vibration resistance made it suitable for installation directly inside compact robot chassis. The system could operate near power electronics, motors, and battery systems where heat, vibration, and power fluctuations are common. This reduced the risk of compute instability during long test cycles, pilot deployments, and transport between validation sites.
Simplifying Integration with Mounting and Service Access
Wall mounting and front accessible I O helped the mechanical team design a repeatable compute bay for multiple robot families. Engineers could route cables, define service procedures, and maintain consistent installation practices across prototypes and production intent builds. This simplified manufacturing planning while reducing the amount of rework required when new robot models were introduced.
The Benefits
Faster Path from Prototype to Deployment
By reducing repeated compute redesigns, the robotics OEM accelerated the transition from simulation to prototype testing and field trials. Engineering time shifted away from hardware workarounds and back toward autonomy, control, and customer specific functionality.
Higher Reliability in Demanding Environments
Rugged fanless computing helped reduce downtime caused by vibration, heat, and mechanical stress. With a more dependable compute foundation, engineers could troubleshoot robotics behavior with greater confidence and fewer hardware related distractions.
Scalable Platform for Future Product Lines
The modular architecture gave the company a reusable compute strategy for future robot platforms. Premio’s Los Angeles area support and industrial product lifecycle focus also provided a stronger foundation for long term deployment planning.
Conclusion
For a robotics OEM building agile autonomous machines, compute reliability became just as important as control algorithms and mechanical design. The RCO-6000-RPL-2 provided a rugged, expandable, and certification friendly platform that helped the team standardize compute across evolving robotic systems. With a stable edge compute foundation in place, the company can continue scaling its robots from the lab into real world industrial environments.