Robotics

Top 10 robotics stories of August 2026

In August 2026, large funding rounds, humanoid robot developments, and stories about the latest AI models for robotics got our readers’ attention. Here are the 10 most popular articles on The Robot Report in the past month. Subscribe to The Robot Report newsletter and listen to The Robot Report Podcast to stay up to date on the latest robotics news. 10. XPeng humanoid robot unit Dogotix picks up $900M in August 2026 Like other global automakers, XPeng Motors is branching into humanoid rob

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In August 2026, The Robot Report compiled its ten most popular robotics stories, which were driven by reader interest in large funding rounds, humanoid robot developments, and new AI models for robotics. The top stories covered topics including humanoid robot fundraising and public offerings, autonomous vehicle production readiness, construction robotics investment, robotic lawn mowers, and advances in AI control systems for robots. These stories reflect major developments across multiple robotics sectors, including autonomous vehicles, manufacturing, construction, and consumer applications. The compilation provides a snapshot of which robotics innovations and business developments captured mainstream attention during that month.

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

Alphabet Inc.’s artificial intelligence research lab, Google DeepMind, Tuesday debuted the next generation of Gemini Robotics, the company’s most capable vision-language-action model to date for creating an “AI brain” for robotics. Separately, DeepMind announced AlphaGenome 2 today, a next-generation AI model that can predict how DNA sequences and their variations affect human cell types, creating […] The post Google DeepMind releases new advanced robotics AI model and next-generation gene

Also reported by MarkTechPost

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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

Also reported by Ars Technica

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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