Overview
As autonomous mobility continues to reshape the future of transportation, fleet operators are expanding beyond self driving technology to automate the supporting infrastructure that keeps vehicles on the road. A leading autonomous driving technology company partnered with Intrinsic to develop an autonomous robotic charging system capable of automatically recharging self driving vehicles at service depots without human intervention. To support reliable 24/7 outdoor operation, Premio's Rugged Edge AI Workstation provided the industrial computing performance, AI acceleration, and durability required to power the robotic charging platform.
Challenges
- Need for high performance AI computing to process robotic charging and automation workloads
- Continuous outdoor operation exposed computing hardware to harsh environmental conditions
- Reliable high bandwidth networking required for communication between robotic systems and charging infrastructure
- Flexible deployment within space constrained charging depot installations
- Long term industrial reliability required for around the clock autonomous fleet operations
Solution
- Premio's Rugged Edge AI Workstation (VCO-6000-RPL Series)
- Intel Core i9-13900E processor delivers high performance computing for robotic control and AI workloads
- NVIDIA RTX Pro 4000 Blackwell GPU accelerates AI vision and autonomous robotic decision making
- Multiple high speed Ethernet interfaces enable seamless communication across robotic and charging networks
- Rugged industrial design supports reliable 24/7 deployment in outdoor charging depot environments
Benefits
- Reliable autonomous charging operations around the clock
- Increased fleet efficiency through fully automated charging
- Industrial durability reduces maintenance and downtime
Company Overview
Founded to advance autonomous driving technology, the company develops fully autonomous vehicles that safely transport passengers without human drivers. Years of real world driving experience, advanced artificial intelligence, and continuous innovation have positioned the organization as a global leader in autonomous mobility. As autonomous transportation expands into more cities, the company continues investing in technologies that improve safety, operational efficiency, and accessibility for future mobility services.
The Challenges
High Performance Computing for Autonomous Robotics
Developing an autonomous robotic charging system requires significantly more computing capability than traditional industrial automation. The robotic platform must process AI models, coordinate robotic movements, and communicate with charging infrastructure in real time. Without sufficient processing performance, charging accuracy and operational efficiency could be compromised.
Harsh Outdoor Deployment
The robotic charging system is installed in an outdoor service depot where computing hardware is exposed to fluctuating temperatures and changing weather conditions. Unlike indoor installations, the platform must continue operating despite environmental stresses. A ruggedized edge computer was essential to maintain consistent performance in these demanding outdoor settings.
High Speed Network Connectivity
The autonomous charging platform depends on fast, reliable communication between robots, vehicles, and backend fleet management systems. Multiple network connections are required to support control systems, diagnostics, and data transfer simultaneously. Any interruption in communication could delay charging operations and reduce fleet availability.
Flexible Installation in Charging Depots
Charging depots require computing platforms that can be integrated into existing robotic systems without occupying unnecessary space. Industrial computers must fit within equipment enclosures while remaining accessible for maintenance and future expansion. Flexible deployment options simplify installation across multiple charging locations.
Continuous Industrial Reliability
The autonomous charging infrastructure operates around the clock with minimal human intervention. Any unexpected downtime could interrupt fleet charging schedules and reduce vehicle availability. The deployment required an industrial computing platform engineered for long term reliability and dependable 24/7 operation.
The Solution
Premio's Rugged Edge AI Workstation (VCO-6000-RPL-4)
The project selected Premio's VCO-6000-RPL Series Rugged Edge AI Workstation as the computing platform powering the autonomous robotic charging system. Designed specifically for demanding industrial AI applications, the system delivers the processing power, expandability, and rugged reliability needed for continuous autonomous operation. Its industrial architecture enables dependable deployment within outdoor fleet charging depots where uptime is critical.
Intel Core i9 Processing Power
Powered by the Intel Core i9-13900E processor and 64GB of ECC DDR5 memory, the workstation provides the computing performance required for robotic control, automation software, and real time decision making. Multiple workloads can execute simultaneously without impacting system responsiveness. The platform supports future software enhancements as robotic capabilities continue to evolve.
NVIDIA RTX Pro 4000 Blackwell AI Acceleration
The integrated NVIDIA RTX Pro 4000 Blackwell GPU delivers powerful AI acceleration for computer vision and autonomous robotic guidance. Vision models can accurately identify vehicle charging ports while enabling precise robotic positioning during charging operations. Hardware accelerated AI allows the robotic system to perform consistently under demanding real world operating conditions.
High Speed Industrial Networking
Multiple networking interfaces including dual Intel 2.5GbE ports, and an additional Realtek LAN interface provide extensive connectivity for industrial automation. The workstation communicates simultaneously with robotic controllers, charging equipment, backend servers, and fleet management platforms. This networking flexibility supports reliable coordination across the entire charging infrastructure.
Rugged Industrial Design for Continuous Operation
Purpose built for industrial environments, the workstation is engineered to withstand continuous 24/7 operation in outdoor charging depots. Wide temperature storage, industrial components, removable SSD storage, redundant power supplies, and rugged construction contribute to dependable long term performance. The result is a stable computing platform capable of supporting autonomous fleet charging with minimal maintenance requirements.
The Benefits
Higher Fleet Availability
Automated robotic charging minimizes manual intervention, allowing self driving vehicles to return to service more quickly and efficiently.
Reliable Autonomous Operations
Industrial grade computing provides dependable performance that supports continuous charging operations day and night with minimal downtime.
Scalable Future Deployment
As autonomous fleets continue expanding into new markets, the rugged edge computing platform provides a scalable foundation for deploying additional robotic charging systems. Premio's engineering support from its Los Angeles headquarters further helps accelerate deployment and long term system reliability.
Conclusion
As autonomous transportation continues evolving, automation extends far beyond the vehicle itself into every aspect of fleet operations. By combining autonomous robotic charging with Premio's VCO-6000-RPL Rugged Edge AI Workstation, the deployment delivers the computing performance, AI acceleration, and industrial reliability necessary to support continuous fleet operations. Together, the solution helps advance a safer, more efficient, and increasingly autonomous transportation ecosystem.