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Lattice Semiconductor, the low power programmable leader, announced that the company is collaborating with Texas Instruments (TI) to simplify sensor integration and to scale real-time edge AI systems. The combination of TI’s sensing technologies and the Lattice Holoscan Sensor Bridge solution, based on Lattice low power FPGA technology, will provide developers with a flexible hardware foundation for synchronized, low-latency sensor data pipelines in advanced robotics and industrial applications.
The collaboration demonstrates a real-time AI sensor fusion architecture that integrates TI mmWave radar and camera sensors using NVIDIA Holoscan Sensor Bridge running on Lattice’s low power FPGA. The FPGA acts as a companion chip delivering synchronized sensor data directly into GPU-accessible memory to enable low-latency and robust perception for robotics and industrial edge AI applications.
“As edge AI systems scale, developers need flexible platforms that simplify sensor integration while delivering predictable real-time performance,” said Raemin Wang, Vice President, Segment Marketing, Lattice Semiconductor. “By integrating NVIDIA Holoscan Sensor Bridge solutions and pairing Lattice FPGAs with TI’s radar sensor expertise, we are creating powerful technology that helps developers efficiently connect real-world sensors to NVIDIA platforms, enabling real-time AI sensor fusion and accelerating the transition from evaluation to production.”
“Real-time sensor fusion is essential for enabling safe and reliable physical AI systems,” said Giovanni Campanella, General Manager of Industrial Automation and Robotics at Texas Instruments. “By combining TI’s mmWave radar technology with Lattice’s Holoscan Sensor Bridge solutions, developers can build low-latency perception pipelines that scale from development to real-world deployment.”
The ecosystem of Lattice Holoscan solutions is growing through collaboration with industry-leading sensor, compute, and software partners, enabling deterministic data movement, low-latency performance, flexible sensor connectivity, and low power operation. This expanding ecosystem provides developers with a strong foundation to build scalable, production-ready edge AI systems for robotics, industrial automation, and emerging physical AI applications.
