Altera Advances FPGA-Based Physical AI for Robotics and Edge Applications

Live demos at Embedded World highlight adaptable FPGA-based AI for sensor processing, industrial vision, and robotics control

SAN JOSE, Calif.–(BUSINESS WIRE)–#FPGA–At Embedded World, Altera, the world’s largest pure-play FPGA solutions provider, will showcase how its Agilex® FPGAs are engineered to meet the real-time demands of physical AI systems. Together with ecosystem partners, Altera is enabling a unified sensor-to-actuator architecture that delivers deterministic performance, safety, and adaptability for robotics, industrial vision, and autonomous edge applications.

Embedded World Image
Embedded World Image
altera logo tm alterablue 3000
altera logo tm alterablue 3000

Physical AI systems must sense, process, and act in real time while meeting strict requirements for deterministic latency, power efficiency, functional safety, security, and long product lifecycles. As adoption accelerates across robotics, industrial automation, smart infrastructure, and autonomous machines, Altera’s adaptable FPGA platforms provide scalable acceleration from multi-sensor ingestion and AI inference to real-time control.

At Embedded World, Altera will present live demonstrations illustrating how FPGAs power multi-sensor processing, AI-driven perception, and low-latency decision-making at the edge. Featured demos include:

  • An AI-enabled high-definition camera and sensor fusion pipeline supporting multi-camera ingest, synchronization, and stitching for industrial environments.
  • High-resolution imaging pre-processing and enhancement for advanced medical systems.
  • A robotics showcase demonstrating deterministic, low-latency control and closed-loop autonomous operation.

These demonstrations are built on Agilex 3 and Agilex 5 FPGAs and SoCs, optimized for deterministic, real-time edge deployments. Their reconfigurable architecture allows developers to adapt to evolving sensors, AI models, and workloads, while supporting flexible design partitioning, from bridging and aggregation to AI acceleration or standalone inference. Long product lifecycles further extend system longevity in industrial and safety-critical markets.

Agilex devices integrate distributed AI tensor blocks, ARM-based processors, advanced LPDDR5/DDR5 memory support, and high-performance I/O to accelerate sensor fusion, AI inference, and real-time control. This tightly integrated architecture enables efficient data movement and scalable compute for next-generation robotics and industrial systems.

“We are entering the era of physical AI, where machines must not only perceive the world, but act on it instantly, securely, and safely,” said Venkat Yadavalli, head of Altera’s Business Management Group. “With Agilex, Altera delivers purpose-built FPGA architectures that combine deterministic performance, adaptability, and long lifecycle support to power robotics, autonomous systems, and safety-critical edge applications.”

Altera’s physical AI portfolio spans hardware, software, optimized IP, and development tools, including Quartus® Prime and the FPGA AI Suite. By enabling AI inference directly within the FPGA fabric using integrated AI tensor blocks, Altera allows developers to deploy low-power, real-time AI acceleration within familiar FPGA workflows, which helps to reduce integration complexity and accelerate time to market.

Visit Altera in Hall 5, Booth 343 at Embedded World to learn more.

About Altera

Altera is a leading supplier of programmable hardware, software, and development tools that empower designers of electronic systems to innovate, differentiate, and succeed in their markets. With a broad portfolio of industry-leading FPGAs, SoCs, and design solutions, Altera enables customers to achieve faster time-to-market and unmatched performance in applications spanning industrial automation, audio/video, robotics, aerospace, defense, data centers, telecommunications, edge AI, and more. For more information, visit https://www.altera.com.

Contacts

Media Contact:
Stephen Gabriel

Altera Corporation

[email protected]

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