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Odyssey launches world model to control robots, humanoids, vehicles and drones
Robbyant and AFDE partner to expand embodied AI and robotics across Middle East
Stäubli Robotics to host automation summit following European sales restructuring
Sereact robots automate Zalando returns processing at logistics facilities in Germany and Poland
DataraAI develops robotic system to automate server cabling
Faraday Future plans US robot factory as it expands beyond electric vehicles
Interview with CEO of Minerva Humanoids: ‘Roger is engineered to be the best possible avatar’
Minerva Humanoids raises $10 million to develop robots for dangerous industrial jobs
How to Make a Cloud Read a Drone's Mind (and Cut Data Usage by 94%)
Two copies of one small AI model keep a remote machine in sync with the cloud, with no constant streaming. A beginner-friendly world model tutorial in PyTorch.
The post How to Make a Cloud Read a Drone's Mind (and Cut Data Usage by 94%) appeared first on Towards Data Science.
Aigen trains solar-powered farming robots for new crops in under a week
Agile Robots CEO: ‘Physical AI is going to be 10x bigger than automotive’
RobCo reaches $1 billion valuation as investors back US expansion
Japanese nursing home operator Charm Care invests in humanoid company Donut Robotics
Teradyne invests in Bright Machines to advance AI infrastructure manufacturing
SafeWorld emerges from stealth with $12.2 million to develop robot safety simulation technology
How to Use AI Agents to Prepare 3D Scenes for Simulation
Agentic AI workflows can be used to prepare and validate digital twins for physical AI systems. Agents can inspect 3D scenes, author simulation-relevant data in...
Agentic AI workflows can be used to prepare and validate digital twins for physical AI systems. Agents can inspect 3D scenes, author simulation-relevant data in OpenUSD, add physics properties, render preflight views, and validate the result against simulation-ready (SimReady) requirements. This workflow follows that process from a scene in Blender to a simulation-ready OpenUSD handoff for NVIDIA…
Frontier Reasoning Reaches the Edge: How to Deploy and Optimize Models on NVIDIA Jetson
Running reasoning and agentic AI at the edge has been harder than it needs to be. Until recently, models capable of multi-step reasoning were too large to run...
Running reasoning and agentic AI at the edge has been harder than it needs to be. Until recently, models capable of multi-step reasoning were too large to run locally on edge hardware. Developers building agents have had to route inference through a data center, adding network dependency, increasing costs, and exposing data that may need to stay on device. That constraint is lifting.
Scale AV Perception Across Vehicle Platforms with NVIDIA Omniverse NuRec
A perception stack is shaped by the vehicle that carries it. Move the same software to a new carline—for example, from an SUV to a sedan or another vehicle...
A perception stack is shaped by the vehicle that carries it. Move the same software to a new carline—for example, from an SUV to a sedan or another vehicle variant in the portfolio—and its perception of the world changes. The sensor placement, calibration, fields of view, occlusions, body geometry, timing, and coverage all shift. A traffic light may appear in a different part of the frame.
How to Train a Cross-Embodiment Robot Navigation Policy with AI Agents
Navigation enables a robot to turn perception and motion into purposeful autonomy. Unlike locomotion, which produces stable movement, navigation must be used to...
Navigation enables a robot to turn perception and motion into purposeful autonomy. Unlike locomotion, which produces stable movement, navigation must be used to continuously localize the robot, interpret changing surroundings, select a route, and avoid obstacles to reach a goal safely. Moving this capability to a new robot or scene can require new data, simulation assets, robot interfaces…