
HII signs up to $900M agreement with Path Robotics, GrayMatter Robotics
Rove pairs Path Robotics’ Obsidian physical AI model with legged robot for autonomous welding beyond fixed cells. | Source: Path Robotics Huntington Ingalls Industries, or HII, today announced long-term performance-based production agreements with GrayMatter Robotics and Path Robotics. Under the agreements, HII intends to award up to $900 million in total shipbuilding work to Path Robotics and GrayMatter across seven years. Path Robotics provides robotic welding technology, while GrayMatte
Huntington Ingalls Industries has signed long-term agreements with two robotics companies to provide up to $900 million in shipbuilding work over seven years, with one company supplying robotic welding technology and the other providing robotic sanding systems. Both companies are part of a program launched to accelerate advanced adaptive automation in naval shipbuilding for aircraft carriers, submarines, destroyers, and other vessels. The agreements include a development stage where the companies will work with Huntington Ingalls to create and validate production techniques, followed by a delivery stage where the robotics companies will perform actual shipbuilding work if they meet cost, schedule, and quality performance standards. This represents an expansion of Huntington Ingalls' strategy to outsource shipbuilding work, with plans to outsource more than 2.5 million hours of work in 2026, a 30 percent increase from the previous year.
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Browse AI courses on MavenGoogle DeepMind releases new advanced robotics AI model and next-generation gene prediction model
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Can AI agents program industrial robots without training data? Berkeley says yes
The new RoboSimStudio is an open-source project that enables agentic AI coding of robotic simulation environments. | Credit: UC Berkeley UC Berkeley and NVIDIA have released open-source tools for a new approach: enabling teams of AI coding agents to write, simulate, and refine readable robot programs. Since the early days of industrial robots, programming, tuning, and troubleshooting robotic workcells has taken weeks to months. New research coming out of UC Berkeley has demonstrated that new age

Boston Dynamics adds wheels to Atlas humanoid to test whole-body control
Bridging the divide between deterministic physics-based control and policy-driven adaptation, Boston Dynamics has deployed a hybrid locomotion architecture on a wheeled variant of its Atlas humanoid. The “experiment” combined classical model-based motor control with whole-body reinforcement learning to maintain dynamic stability across unstructured, real-world terrain. In the video, Andy Wu, controls engineer for Atlas at Boston Dynamics, highlights some recent experiments that he

Practice Makes Precise: At CoRL, NVIDIA and Partners Reveal How Robots Rehearse Delicate Work in Simulation
Simulation, which has long been the proving ground for robots learning to walk, roll and hop, is now helping researchers teach robots tasks that require a finer touch: aligning gears, connecting cables and assembling small components. The shift from locomotion to manipulation is taking center stage at this week’s Conference on Robot Learning (CoRL) in Austin, Texas, alongside the rise of agentic robotics — a new paradigm that integrates frontier agents to create interpretable code for physical

Memories.ai builds standardized egocentric video pipeline
Memories.ai models label every clip: Memories-H0 for hand pose, EgoAction for action segments. | Credit: Memories.ai Memories.ai is building a data pipeline for robotics companies that combines standardized video collection with AI-powered annotation to turn everyday egocentric footage into training data for robots. The San Francisco-based company is developing software and AI to help robots understand the physical world. It builds video-understanding models and data infrastructure, and it colle