HomeElectronics NewsAI Platform for Building and Deploying Robots

AI Platform for Building and Deploying Robots

A robotics platform combines CPU, GPU, NPU and FPGA computing to help developers build, test and deploy AI-powered robots.

An exploded view shows the AMD Kria AI Robotics Developer Platform, the first open, turnkey integrated platform for agentic robotics. It was introduced at Advancing AI 2026 as part of AMD Kria AI solutions. (Credit: AMD)
An exploded view shows the AMD Kria AI Robotics Developer Platform, the first open, turnkey integrated platform for agentic robotics. It was introduced at Advancing AI 2026 as part of AMD Kria AI solutions. (Credit: AMD)

AMD has introduced the Kria AI Solutions portfolio to help developers prototype, build and deploy autonomous robotics and physical AI systems. The portfolio includes Kria AI system-on-modules (SOMs), a robotics carrier card based on the Ryzen AI Embedded X100 Series processors, and the Kria AI Robotics Developer Platform. The platform combines CPU, GPU, NPU and FPGA computing on a single system to support AI perception, reasoning, decision-making and control while meeting power, thermal and latency requirements.

The platform is designed for developers building robots that require more than fixed automation. As robotics increasingly relies on AI for perception, reasoning and decision-making, developers need hardware and software that reduces design complexity and speeds deployment. The Kria AI SOMs feature Ryzen AI Embedded X100 Series processors with up to 16 Zen 5 CPU cores for control, an RDNA 3.5 integrated GPU for graphics processing, and an NPU for AI workloads. AMD also supports the platform with an open software ecosystem, allowing developers to build and deploy physical AI systems without being tied to a single vendor.

According to the company, the unified memory architecture reduces data movement between computing engines, allowing AI inference, robot control and other workloads to run simultaneously. The company says the platform can perform more than 8,000 control decisions per second while completing vision-language-action (VLA) AI reasoning in less than 100 milliseconds. AMD also claims up to 3.4 times better reliability, up to 1.6 times more available CPU cores, and support for up to 2.3 times more concurrent AI agents than the Nvidia Jetson T5000.

The Kria AI Robotics Developer Platform includes the Kria AI SOM, a robotics carrier card, an evaluation kit, the AMD Robotics Software Suite and reference designs. The software stack is based on AMD ROCm software and the ROS 2 robotics framework, providing a development environment for robotics applications.

The platform supports AI and robotics frameworks including PyTorch, ONNX, ROS 2 and MoveIt. It also supports CUDA-to-ROCm migration, allowing developers to reuse about 75% of their existing CUDA code, according to AMD. Hardware from ODM partners is intended to help developers transition from development to production.

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Nidhi Agarwal
Nidhi Agarwal
Nidhi Agarwal is a Senior Technology Journalist at Electronics For You, specialising in embedded systems, development boards, and IoT cloud solutions. With a Master’s degree in Signal Processing, she combines strong technical knowledge with hands-on industry experience to deliver clear, insightful, and application-focused content. Nidhi began her career in engineering roles, working as a Product Engineer at Makerdemy, where she gained practical exposure to IoT systems, development platforms, and real-world implementation challenges. She has also worked as an IoT intern and robotics developer, building a solid foundation in hardware-software integration and emerging technologies. Before transitioning fully into technology journalism, she spent several years in academia as an Assistant Professor and Lecturer, teaching electronics and related subjects. This background reflects in her writing, which is structured, easy to understand, and highly educational for both students and professionals. At Electronics For You, Nidhi covers a wide range of topics including embedded development, cloud-connected devices, and next-generation electronics platforms. Her work focuses on simplifying complex technologies while maintaining technical accuracy, helping engineers, developers, and learners stay updated in a rapidly evolving ecosystem.

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