Robotics

Swarmer to acquire Ukrainian UGV maker Ratel Robotics for up to $224M

Ratel Robotics makes uncrewed ground vehicles for Ukrainian defense. Credit: Viktor Kharyton, Swarmer Ukrainian companies have demonstrated their ability to develop and field autonomous systems at a fraction of the price of Western defense contractors, according to Swarmer Inc. The company today said it has signed an agreement to acquire Ratel Robotics, a leading manufacturer of uncrewed ground vehicles or UGVs. “Ratel is a major provider of UGVs for Ukraine,” stated Alex Fink, co-founder, presi

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A U.S. robotics company specializing in autonomous swarm coordination software is acquiring a Ukrainian manufacturer of uncrewed ground vehicles, with the deal valued at up to $224 million if certain milestones are met. The acquisition combines the Ukrainian company's battle-tested ground vehicles with the U.S. company's software that allows one operator to control hundreds of autonomous platforms in real time. Ukrainian defense companies have demonstrated the ability to develop autonomous systems at lower cost than Western defense contractors, and the Ukrainian manufacturer's products have been widely adopted by Ukrainian Defense Forces for logistics, reconnaissance, de-mining, and other missions. The U.S. company stated that the acquisition aligns with its objective to build a platform for products proven effective under demanding battlefield conditions.

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Google DeepMind releases new advanced robotics AI model and next-generation gene prediction model

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Gemini Robotics 2.5 accelerates real-world general dexterity

Our most capable vision-language-action model enhances robot dexterity, reliability, and safety

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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

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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

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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

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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