NXP and NVIDIA Team Up to Build the Nervous System of Humanoid Robots

NXP and NVIDIA Join Forces on Physical AI

NXP Semiconductors has announced a major collaboration with NVIDIA to deliver integrated robotics solutions designed specifically for humanoid robots and other physical AI applications. The partnership combines NXP's edge processing expertise with NVIDIA's advanced sensor bridge technology to tackle one of the biggest challenges in robotics: enabling fast, reliable communication between a robot's body and its brain.

What the Technology Does

The new solutions bring together NXP's i.MX 95 applications processor for machine vision, i.MX RT1180 microcontrollers for motor control, and the S32J TSN switch with NVIDIA's Holoscan Sensor Bridge. Together, these components enable low-latency sensor fusion and real-time communication, essentially creating a high-speed nervous system for robots. The motor control solution supports widely used industrial protocols including EtherCAT and TSN, and the integrated design reduces the number of discrete components needed, shrinking footprint, power consumption, and cost.

European Chipmakers Race for Position

The announcement came on the eve of NVIDIA's GTC twenty twenty-six conference in San Jose, where several other European chipmakers including Infineon, STMicroelectronics, Texas Instruments, and Analog Devices also revealed integrations with NVIDIA's physical AI platforms. While NVIDIA's Jetson Thor processors aim to serve as the central brain of humanoid robots, these European partners are positioning themselves to supply the rest of the body, from sensors and motion control to power management and high-speed internal communications.

Looking Ahead

NXP described the launch as the first in a planned series of foundational robotics solutions aimed at the emerging physical AI ecosystem. The solutions are expected to be available in the first half of twenty twenty-six, marking an important step toward making humanoid robots more practical, affordable, and scalable for real-world deployment.