Empowering Precision Robotics: AI Edge Computing for Real-Time Industrial Automation

Overview

Industries worldwide are increasingly relying on robotics to streamline operations, improve precision, and reduce manual labor. From automotive manufacturing to warehouse automation, robots are integral in performing complex, repetitive tasks with speed and accuracy. 

The Company

Founded as a forward-thinking AI robotics and software developer, the company focuses on streamlining access to industrial robots with a unified dataflow ecosystem and operating system. Their mission is to enhance industrial automation by making AI robots more intelligent, adaptable, and affordable. By simplifying robotics programming process, it allows industrial robots to autonomously learn and adapt to different tasks, reducing the need for manual reprogramming. 

In this case study, we’ll explore how this AI robotics company leverages Premio’s industrial computing solutions to further enhance the performance and reliability of their AI-enabled solutions. 

The Challenges

  • Traditional PLC-based robotics workflows only handle simple, repetitive tasks and lack the flexibility needed for complex AI-driven operations. 
  • PLCs struggle with the precision required for advanced object detection and pose estimation with diverse sensor and camera inputs. 
  • PLCs cannot support advanced motion planning, leading to potential collisions and inefficiencies. 
  • Real-time data analytics is crucial for adapting to dynamic environments. PLC systems often fail to handle real-time data analytics, causing delays and performance bottlenecks. 
  • PLC systems are typically brand dependent, making them less adaptable across different robotic platforms. 

The Solution

  • Premio’s VCO-6000-RPL Machine Vision Computer with latest Intel 13th Gen CPU and NVIDIA A5000 GPU, delivering up to 27.8 TFLOPS of performance.  
  • The VCO-6000-RPL is purpose-built to support a full-height, full-length GPU with PCIe Gen 4 performance. 
  • The robotics solution provider integrates AI-powered capabilities for perception, motion planning, and control, supporting complexity beyond PLC limitations. 
  • DDR5 RAM for enhanced optimization and efficiency, resulting in faster real-time data aggregation.  
  • The VCO-6000-RPL Machine Vision Computer provides essential automation-centric I/O such as DIO, CAN Bus, and COM ports, which are readily available on-board with a front-facing design for easy accessibility. 

The Benefits

  • Enhanced AI Performance: Premio’s VCO-6000-RPL supporting an NVIDIA A5000 GPU power resource-intensive AI-driven robotics. 
  • Real-Time Data Processing: Enables seamless real-time analytics for precise object detection and motion planning. 
  • Improved Efficiency: Streamlines complex workflows and reduces manual intervention. 
  • Rugged Reliability: Built for harsh factory floor environments with shock resistance and wide temperature tolerance. 
  • Minimized Downtime: Predictive maintenance reduces failures and ensures continuous operations. 

Background  

In the rapidly evolving field of robotics, precision and real-time decision-making are crucial. This AI robotics and software company, specializing in cutting-edge robotic automation systems, sought to enhance existing automation solutions by integrating AI-driven capabilities that allow robots to interact more intuitively with their environment. By leveraging artificial intelligence and machine learning, the company aims to develop systems that enable robots to learn, adapt, and execute complex tasks autonomously, reducing the need for manual reprogramming and improving overall efficiency. 

The company's focus extends to deploying robust, industrial-grade edge AI computing solutions capable of handling intense computational loads in challenging environments. With its cloud-based platform, it empowers manufacturers to implement scalable robotics solutions across a variety of sectors, from manufacturing to logistics. Through collaboration with key industry players and a commitment to advancing automation, the company continues to revolutionize how robotics interact with the physical world, driving smarter and more efficient industrial systems. 

Challenge 

 

The robotics solution provider required an infrastructure capable of handling real-time data processing for complex tasks like robotic manipulation, perception, and pathfinding. These tasks demand powerful edge AI computing performance, low latency, and high reliability, all while operating in challenging industrial environments with fluctuating power and harsh conditions. Traditional computing systems, particularly those based on legacy architectures, were not sufficient to meet these real-time demands. 

Traditional PLC-based robotics workflows present significant limitations when it comes to handling complex, AI-driven operations. While PLCs are well-suited for simple, repetitive tasks, they lack the flexibility required for advanced robotics applications. For instance, PLCs struggle with the precision needed for tasks like object detection and pose estimation, especially when integrating diverse sensor and camera inputs. Additionally, PLCs are incapable of supporting advanced motion planning, leading to potential inefficiencies, increased risk of collisions, and a lack of adaptability in dynamic environments. 

Moreover, real-time data analytics, crucial for quick adaptation to changing conditions, often exceeds the processing capabilities of PLC systems, causing delays and performance bottlenecks. These systems are typically brand-dependent, further limiting their interoperability across different robotic platforms. To enable faster decision-making and support time-sensitive applications such as autonomous manufacturing and industrial automation, the company needed to move beyond PLC-based architectures and adopt a robust, AI-driven edge computing solution that could meet the rigorous demands of modern robotics. 

Solution 

The company partnered with Premio, utilizing its high-performance industrial machine vision computer, VCO-6000-RPL Series, designed specifically for rugged environments. By integrating the VCO-6000-RPL, they were able to power their AI robotic solutions with the following key advantages: 

High-Performance AI Processing 

    Traditional PLCs or legacy PCs without high-performance CPUs will cause “throttling” in the process of robotics motion planning and perception, leading to significant operation failure for the robotics solution provider. Premio’s VCO-6000-RPL Machine Vision Computers, equipped with the powerful NVIDIA A5000 GPU supported by PCIe Gen 4 and 13th Gen Intel Core CPUs, address this issue with robust AI acceleration at the edge. This high-performance setup allows the company's robots to execute machine learning algorithms locally, eliminating reliance on cloud processing and drastically reducing latency for critical tasks. 

    Rugged Durability for Factory Floor Environment 

    With a wide operating temperature of –25 to 70°C, military standard 810G compliant shock & vibration resistance, and a secure GPU bracket design, Premio’s VCO-6000-RPL was built to withstand the extreme conditions of factory floor environments. This ensures reliable operation in high-temperature, high-vibration, and dust-heavy settings, aligning perfectly with the needs of robotic deployments in industrial settings. 

    Multi-Slot PCIe Expandability for Highspeed Network 

    The VCO-6000-RPL provides extensive expansion capabilities with up to four PCIe Gen 4 slots, making it ideal for the robotics AI company to boost connectivity and processing power. These slots allow seamless integration of SFP+ fiber cards and Intel-based chips that support the EtherCAT protocol, enabling real-time, low-latency control and precise automation.  

    Benefits 

    By integrating Premio’s advanced edge AI computing systems, the robotics company achieved significant improvements in the performance and reliability of its robotic solutions: 

    • Increased Uptime and Durability: With Premio’s rugged design, the robots experienced far fewer breakdowns, leading to increased uptime and higher operational efficiency. 
    • Enhanced AI Capabilities: The integration of edge AI technology allowed the robots to better perceive their surroundings, making them more adaptable in dynamic environments such as manufacturing floors and warehouses. 

    Through Premio’s rugged edge AI computing solutions, the company revolutionized their robotics offerings, bringing enhanced intelligence, durability, and real-time processing power to their systems. This collaboration has not only improved operational efficiency but has also positioned the company at the forefront of innovation in the robotics industry, empowering them to tackle more complex automation challenges with confidence.