Robotics

The technology that could bring robot mowers to one in two American lawns

Robotic mowing is becoming more commercially viable because of vision and satellite guidance, AI planning, and autonomy. Source: Sunseeker Robotics For years, robotic lawn mowers have been perceived as a niche technology: an interesting solution, but one limited by complex installations, wired systems, and performance that was not always suitable for larger and more demanding lawns. Today, that phase is over. The evolution of artificial intelligence, satellite navigation, and autonomous systems

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Robotic lawn mowers are becoming commercially viable due to advances in artificial intelligence, satellite navigation, and autonomous systems that enable them to operate with minimal human intervention and wired installation. The global lawn mower market is projected to grow significantly, and analysts believe the U.S. robotic mower market could reach 50% household penetration within eight years as costs decrease and consumer awareness increases. The main barrier to widespread adoption is not technological but cultural, as many homeowners still associate robotic mowers with older models that required complex installation and frequent maintenance. Beyond residential use, the technology addresses labor shortages in the commercial landscaping industry while improving worker safety by automating repetitive and physically demanding tasks.

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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