NXP Semiconductors has announced a series of robotics solutions designed for real-time data processing, sensor fusion and motor control. Developed in collaboration with Nvidia, these ready-to-deploy systems implement the Nvidia Holoscan Sensor Bridge with NXP’s system-on-chip (SoC) technology to reduce component count, power consumption and costs in robotic development.

The solutions focus on Physical AI, which requires low-latency data transport to synchronise motion and sensor data. By integrating the Holoscan Sensor Bridge into NXP's software, developers can establish a direct transport route between a robot's body and its central processing unit.

The architecture incorporates several NXP technologies:

• i.MX 95 Applications Processor: A machine vision solution designed to deliver high-bandwidth data to the robot brain.
• i.MX RT1180 Crossover MCUs: A motor control solution based on a kinematic chain.
• S32J TSN Switch: Aggregates motor control data and provides direct connectivity to the brain using Time-Sensitive Networking (TSN) and EtherCAT protocols.
• Asymmetric Data Transport: Technology acquired through Aviva Links to manage high-throughput data across the robot body.

The unified architecture is designed to support humanoid form factors, which require complex motor synchronisation and real-time perception. NXP’s automotive-grade networking and functional safety expertise are used to ensure the reliability of these systems in physical environments.

Charles Dachs, Executive Vice-President and General Manager, Secure Connected Edge at NXP Semiconductors, said, “Physical AI is redefining what machines can do in the real world, and humanoid robots represent the most complex expression of that revolution. By combining NXP’s deep expertise in edge processing, secure networking, functional safety and real-time control with Nvidia robotics platforms, we are greatly simplifying physical AI development, enabling seamless connectivity between the physical AI edge and the central brain. This is just the beginning of what NXP will deliver to accelerate the ecosystem for physical AI.”

Deepu Talla, Vice-President of Robotics and Edge AI, Nvidia, commented, “The development of autonomous machines requires a high-performance computing architecture that can synchronize complex motor controls with real-time perception. By integrating Nvidia Holoscan Sensor Bridge into its edge portfolio, NXP is providing developers with a scalable foundation to accelerate the deployment of physical AI.”

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Horse Powertrain, a leading supplier of powertrain solutions, has launched the V20 engine through its Aurobay Technologies division with production already underway at its Skovde, Sweden, manufacturing facility.

The V20 engine aims to assist automakers in meeting emission regulations for 2026 and 2027 with units destined for customers in Europe, the US and Asia. The 2.0-litre, 4-cylinder engine features a single architecture offered in two variants: a 400-volt plug-in hybrid and a 48-volt mild hybrid. The plug-in version provides a reduction in fuel consumption of seven per cent compared to the predecessor.

The platform design intends to reduce material costs. Hardware for the plug-in variant includes a crankshaft-mounted starter-generator, a mechanical water pump, and a re-routed cooling system. Additional updates include a multi-injection fuel system, an engine management system, and an air induction system.

Ingo Scholten, Managing Director, Aurobay Technologies Sweden and Deputy CTO of Horse Powertrain, said, “Designing one engine to meet three different regulatory regimes is harder than designing three separate engines. As the regulatory map is fragmenting, one engine that meets all three sets of rules delivers greater value to our customers, ensuring we can offer greater economies of scale. Pulling that off requires serious engineering. Further, the Skovde team also successfully changed production lines while keeping current production running.”

The Skovde plant integrated a final assembly line with the base assembly line to improve material flow. This transition occurred during ongoing operations. Output is scheduled to increase through 2026 and 2027 to meet demand.

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AEye, Inc. and MoveAWheeL have signed a Memorandum of Understanding to explore the integration of their sensing technologies for use in Advanced Driver Assistance Systems (ADAS) and autonomous driving applications.

The partnership aims to combine AEye’s lidar perception with MoveAWheeL’s road-surface sensing to assist vehicles in interpreting surroundings and road conditions.

The collaboration will evaluate the pairing of AEye’s Apollo LiDAR sensor with MoveAWheeL’s friction-coefficient prediction technology. Apollo is a 1550-nanometer LiDAR sensor capable of detecting objects at distances of up to one kilometre. MoveAWheeL’s sensor uses acoustic sensing to estimate the friction of road surfaces, providing data to inform decisions regarding acceleration, braking and stability control.

Matt Fisch, Chairman and CEO of AEye, said, “Physical AI depends on giving machines the ability to accurately perceive and understand the real world. Apollo was designed to deliver long-range, real-time 3D perception that helps systems see farther and react earlier in complex environments. By exploring the integration of Apollo with MoveAWheeL’s road-surface intelligence, we have the opportunity to create an even deeper understanding of the driving environment, particularly in the adverse conditions where advanced safety systems are needed most.”

Dr. Min-Hyun Kim, Founder and CEO, MoveAWheeL, said, “While LiDAR provides the ‘eyes’ for a vehicle to see obstacles, MoveAWheeL provides the ‘tactile sense’ to feel the road. By integrating our Physical AI with AEye’s long-range perception, we are creating a complete safety stack that remains robust even in the most treacherous weather conditions.”

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L&T Technology Services (LTTS), a leading ER&D sevices company, has inaugurated its first Engineering Intelligence Centre of Excellence (EI CoE) in Munich, Germany. The facility marks a step in the company's Engineering Intelligence (EI) strategy, which focuses on embedding AI across the engineering lifecycle to support intelligent products, autonomous operations and manufacturing systems.

The centre aims to assist global enterprises in transitioning from AI experimentation to industrial transformation by combining domain engineering expertise with technologies such as GenAI, Agentic AI, multimodal AI, Physical AI and edge intelligence. LTTS states that it has filed over 237 patents in AI and GenAI during FY2026.

Located within a technology ecosystem, the Munich EI CoE will function as a collaborative hub for clients in the mobility, industrial products, sustainability and technology sectors. Its work will focus on: Applied AI solutions, Intelligent manufacturing, Software-defined products, Predictive operations and Connected engineering ecosystems.

At present, LTTS serves more than 60 clients in Europe with a team of over 4,500 engineers. The new centre is intended to improve local collaboration with clients, partners and academic institutions, facilitating outcome-driven innovation.

Amit Chadha, Chief Executive Officer & Managing Director, L&T Technology Services, said, “LTTS’ first EI Centre of Excellence in our Munich design centre is a milestone as it brings our deep-tech and EI-based solutions closer to the clients’ R&D hubs across the region. The centre will act as a focal point for innovation, R&D and new product development, redefining how products, platforms and manufacturing are engineered and optimised in the AI era.”

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European automaker Stellantis has announced a strategic initiative with Accenture to deploy artificial intelligence (AI)-enabled digital twin capabilities across its global manufacturing network using Nvidia technologies. The project focuses on creating virtual manufacturing environments powered by real-time data and physical AI.

The collaboration integrates Stellantis's automotive infrastructure, Accenture’s digital manufacturing engineering and Nvidia’s accelerated computing platforms and Omniverse libraries.

The system uses virtual factory replicas to validate manufacturing processes prior to physical installation, track metrics for quality control and conduct predictive monitoring.

Initial testing and deployment of the digital twin infrastructure are scheduled to begin with pilot programmes in North America in 2026. The long-term objective is to evaluate scalability across the carmaker's international plant footprint to establish a predictive manufacturing model.

Francesco Ciancia, Head of Manufacturing, Stellantis, said, “We are laying the foundation for the next generation of manufacturing at Stellantis. By combining digital twins, AI and advanced simulation, we are rethinking how we design, operate and continuously improve our production systems. This initiative is designed to work hand in hand with our teams, enhancing their ability to anticipate issues, enabling faster decisions and continuous improvement. Together with Accenture and NVIDIA, we are exploring new ways to drive more scalable and intelligent operations.”

Tracey Countryman, Supply Chain and Engineering Global Lead, Accenture, added, “The opportunity in manufacturing today is to scale AI across complex industrial operations in ways that deliver measurable business value. By partnering with Accenture and harnessing Nvidia’s compute and simulation technologies, Stellantis is positioned to accelerate manufacturing reinvention and lead the industry into a new era of intelligent, high-performance operations.”

The computational framework is built to enable closed-loop optimisation, a process where physical assembly lines and virtual systems continuously exchange data to improve performance. The architecture supports automated throughput adjustment, maintenance scheduling and software-defined factory operations.

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