PlusAI says it has reached 93.4 percent “Safety Case Readiness” as the autonomous trucking company moves toward the planned commercial launch of factory-built driverless trucks in 2027. The company has published updated performance figures for the first half of 2026, showing improvements in safety validation, autonomous driving and the number of journeys completed without assistance […]

The British Antarctic Survey says autonomous vehicles are ‘transforming polar science’ A robot is cruising beneath Antarctic sea ice. Another is bolted to the face of a collapsing Greenland glacier. A third is silently counting penguins on a remote, windswept beach. None of them has a human operator nearby. Across the Arctic and Antarctic, autonomous […]

Dubai Future Foundation (DFF) and Oxa, a developer of autonomous vehicle technology, has announced the launch of SHIFFT, a joint venture that will establish Dubai as a global hub for autonomous logistics. SHIFFT will incorporate self-driving technology into a fully integrated autonomous logistics and worksite intelligence product, enabling end-to-end operational deployment. It will unlock productivity, […]

Atlas Energy Solutions has expanded its autonomous truck operations in the Permian Basin, advancing its commitment to unlocking energy by digitally transforming oilfield logistics. Working with Kodiak AI, a provider of physical AI-powered autonomous driving technology, Atlas is expanding its driverless proppant delivery program to a second simultaneous load-out point along its 42-mile Dune Express sand […]

Developers building 3D, design, simulation, robotics, and industrial digital twin applications need ways to bring physical AI capabilities into the tools and...

Developers building 3D, design, simulation, robotics, and industrial digital twin applications need ways to bring physical AI capabilities into the tools and services they already use. Many of these workflows already depend on OpenUSD scenes, simulation-ready (SimReady) assets, Blender-based workflows, CAD pipelines, or domain-specific app stacks. The challenge is how to provide applications and…

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NVIDIA Omniverse NuRec is a neural reconstruction pipeline for building high-fidelity 3D representations of real-world environments from multisensor data such...

NVIDIA Omniverse NuRec is a neural reconstruction pipeline for building high-fidelity 3D representations of real-world environments from multisensor data such as cameras and lidar. It is used to reconstruct dynamic scenes captured by autonomous vehicle (AV) and robotics platforms into simulation-ready digital environments that can be rendered, replayed, and analyzed inside NVIDIA Omniverse and…

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An increasingly common design pattern for autonomous vehicles (AVs), robotics, and spatial AI systems is bird's-eye-view (BEV) perception. BEV models project...

An increasingly common design pattern for autonomous vehicles (AVs), robotics, and spatial AI systems is bird’s-eye-view (BEV) perception. BEV models project multicamera image features into a shared top-down grid, providing downstream perception and planning modules with a common spatial layout for reasoning about lanes, vehicles, pedestrians, and free space. A key operation in this pipeline…

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Physical AI—robots working autonomously alongside people in factories, warehouses, hospitals, and homes—is arriving faster than most expected. Traditional...

Physical AI—robots working autonomously alongside people in factories, warehouses, hospitals, and homes—is arriving faster than most expected. Traditional safety which was built for structured environments can not work anymore as the spaces become more unstructured and robots move out of cages. AI-driven safety is the key. Marking a major milestone in the arrival of physical AI…

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Developing autonomous vehicle (AV) policies requires bridging an important gap between training and deployment. Vision-language-action (VLA) models that can...

Developing autonomous vehicle (AV) policies requires bridging an important gap between training and deployment. Vision-language-action (VLA) models that can reason over more complex driving scenes and produce richer intermediate reasoning are predominantly trained in open-loop, where model outputs are directly compared to ground-truth behaviors without considering their effect on the environment.

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