The financial models are banking on a massive acceleration in humanoid adoption over the next decade. Goldman Sachs now projects global shipments will multiply 70-fold by 2035, a staggering figure that shifts focus right back to the foundational tools required to hit that scale, starting with a new open-source integration between NVIDIA and Hugging Face.
Adding to the market projections we've been tracking—such as Morgan Stanley's near-term forecast of 28,000 global units by 2026—Goldman Sachs has issued a much longer-term outlook. A new report predicts global humanoid robot shipments will surge 70-fold over the next decade, reaching 1.4 million units annually by 2035. A separate analysis from MarketsandMarkets corroborates this trend, projecting the market will grow from $5.41 billion in 2026 to $50.27 billion by 2035.
Why it matters
These bullish forecasts from major financial institutions signal that humanoid robotics is transitioning from a speculative research field to a significant industrial and economic force. The projected scale suggests a paradigm shift where robots move beyond repetitive, caged tasks to become active participants in human-centric environments. For an entrepreneur, this validates the market opportunity and indicates a burgeoning ecosystem for components, software, and services. The key challenge will be moving from impressive demos to reliable, cost-effective deployment at scale, a gap that many startups are now racing to fill.
Goldman Sachs frames the growth as a solution to critical labor shortages and a key component of the broader "physical AI" wave. MarketsandMarkets attributes the expansion to a convergence of AI, advanced mobility, and sensing technologies, with bipedal platforms leading the charge. This market optimism is also attracting venture capital, though some investors remain skeptical, arguing that specialized robots often offer a more immediate and efficient return than general-purpose humanoids.
Paris-based startup UMA, co-founded by former Tesla research scientist Rémi Cadene, has emerged to develop a lightweight, AI-powered humanoid robot for the European market. The company, which also introduced a new learning architecture called 'Real-Time Learning', is targeting manufacturing, logistics, and eventually home applications with its 'Northstar' robot. UMA claims it is already in discussions with 50 potential customers.
Why it matters
UMA's entry signifies a growing European effort to compete in the global humanoid robotics market, which is currently dominated by US and Chinese firms. The focus on 'Real-Time Learning'—acquiring skills through demonstration rather than programming—points to a key industry trend aimed at simplifying robot deployment and reducing setup costs. This approach could be crucial for adoption in small and medium-sized enterprises, which are a major part of the European industrial landscape.
UMA's approach focuses on making robots adaptable and easy to deploy to address Europe's specific challenges with labor costs and demographics. The company's 'Real-Time Learning' is positioned as a significant advancement that allows robots to learn skills quickly in real-world settings. This development comes as other European nations, like Japan, are also launching large-scale national initiatives to deploy millions of robots to counter workforce shortages.
Building on the Isaac GR00T humanoid platform we tracked in June, NVIDIA is partnering with Hugging Face to deeply integrate its robotics tools into the LeRobot open-source library. Announced on Tuesday, the collaboration brings NVIDIA's GR00T 1.7 model, Isaac Teleop, and the forthcoming Cosmos 3 world model into the LeRobot ecosystem, creating a common workflow for collecting robot data and deploying models on physical hardware.
Why it matters
This collaboration is a pivotal moment for open-source robotics, creating a standardized, end-to-end pipeline that could significantly accelerate innovation. By combining NVIDIA's powerful simulation and AI models with Hugging Face's widely adopted platform, it lowers the barrier to entry for researchers, startups, and hobbyists. For an entrepreneur in the space, this provides a production-ready and increasingly standard toolkit, reducing the need to build foundational infrastructure from scratch and allowing a greater focus on application-specific development. The move mirrors the open-source revolution in software, suggesting a future of more rapid, collaborative progress in physical AI.
NVIDIA positions the partnership as a way to "democratize humanoid AI" by giving the community access to the same tools used by leading robotics labs. Hugging Face emphasizes the creation of a standardized "end-to-end open workflow for robot foundation models." This follows the recent v0.6.0 release of LeRobot, which introduced a framework for turning real-world robot failures into new training data, a process that will be enhanced by NVIDIA's simulation and teleoperation tools.
Researchers from NASA's Johnson Space Center and Rice University have launched iMETRO Dynamic Simulation, the world's first open-source dynamic simulation environment for space robotics. Debuted at the ICRA 2026 conference and announced on Tuesday, the platform is designed to help researchers develop and test robots for tasks inside space vehicles and habitats. It aims to democratize space robotics research, which has historically relied on expensive, proprietary tools.
Why it matters
This initiative significantly lowers the barrier to entry for developing robots capable of operating in the challenging low- and zero-gravity environments of space. By providing a common, accessible platform, NASA and Rice are fostering a global community of innovation. For a robotics entrepreneur, iMETRO offers a unique, cost-effective opportunity to develop and validate solutions for the growing space economy, potentially enabling robots to take over routine maintenance and logistics, thereby freeing up valuable astronaut time for scientific discovery.
The project's goal is to accelerate the development of autonomous systems for long-duration space missions. According to the research team, a key objective is to "maximize the human potential for discovery and exploration." The open-source nature of the platform is intended to foster global collaboration and bring new perspectives to solving the unique challenges of robotic operation in space.
Following up on the recent rollout of its RynnBrain perception model and Qwen3.7-Max, Alibaba's DAMO Academy has released its dedicated Qwen-Robot suite. Announced Tuesday, the suite includes three specialized models: Qwen-RobotNav for navigation, Qwen-RobotManip for object manipulation, and Qwen-RobotWorld, a world model that enables real-time decision-making. The models are designed to fuse language, reasoning, and physical interaction, allowing robots to understand and execute complex commands.
Why it matters
Alibaba's entry adds another major player to the increasingly competitive global race to develop foundational models for robotics. This move signifies China's strategic push to lead in embodied AI, moving beyond industrial automation to create robots that can operate autonomously in complex, dynamic settings. For the robotics ecosystem, this means more powerful, open-source tools could become available, but it also signals intensifying competition for talent and market share among the large tech companies investing heavily in physical AI.
Alibaba frames this as a step toward AI that acts as a partner in the physical world, not just a digital tool. The release follows Google DeepMind's recent showcase of its Gemini Robotics 1.5 model, which also emphasizes a multi-level thinking process of understanding, planning, and reasoning before acting. The parallel developments highlight a consensus in the AI community that advanced reasoning is the key to unlocking the next level of robotic capability.
Japan's Ministry of Economy, Trade and Industry has announced an ambitious national plan to deploy 10 million humanoid and other physical AI robots by 2040. The initiative is a direct response to the country's aging population and shrinking workforce. The robots are slated for integration into 18 different job sectors, with a heavy focus on eldercare, food manufacturing, and disaster response.
Why it matters
This large-scale, government-directed strategy represents one of the world's most significant commitments to deploying physical AI to solve pressing demographic and economic challenges. It signals a future where robots are deeply integrated into the fabric of society, not just the factory floor. For the robotics industry, this creates a massive, state-supported market for hardware, software, and services, likely accelerating development and driving down costs through economies of scale. We have been tracking similar, though less specific, national initiatives in China and South Korea.
Minister of Economy, Trade and Industry, Ryosei Akazawa, presented the plan as essential for Japan's future economic stability. The strategy mirrors efforts in other East Asian nations facing similar demographic pressures. The plan's success will hinge on public acceptance and the ability of the robots to perform reliably in complex, human-centric environments.
Norwegian physical AI startup HIVE has raised $15 million in a pre-Series A funding round led by SuperSeed. The company is developing a 'silicon brain'—a neural network platform that can be installed on existing industrial machines like forklifts and excavators to make them more intelligent. Unlike traditional automation, HIVE's system allows machines to learn and improve over time by observing human operators.
Why it matters
HIVE's approach represents a cost-effective and scalable path to industrial intelligence, focusing on upgrading the vast installed base of existing machinery rather than replacing it entirely. This is highly relevant for industries facing labor shortages but wary of the high capital expenditure of full robotic replacement. For an entrepreneur, this highlights a significant market opportunity in retrofitting and software-based upgrades, which can offer a faster and more flexible ROI than ground-up automation projects.
HIVE aims to create a network effect where machines learn from each other, becoming smarter collectively. This investment is part of a broader trend of venture capital flowing into 'real economy' tech. Omni Ventures, led by ex-Apple engineers, just closed a $33 million fund for manufacturing tech, and UK-based Worldmodeldata raised €8 million to turn video game data into training sets for physical AI, all pointing to a focus on practical, industrial applications of AI.
Contextualizing the Ant Group investment in household robot startup Zeroth we tracked last week, new reports reveal Ant has made 12 distinct deals in the humanoid robotics space over the last 18 months. Zeroth itself has recently secured IP authorization for the 'Wall-E' character, utilizing the Ant-led capital infusion—which brings its total funding past the 1 billion yuan mark—to develop educational companion robots.
Why it matters
Ant Group's rapid-fire investment strategy signals a major push by a Chinese tech giant to build a broad portfolio in the emerging humanoid market. Unlike competitors focusing on a single hardware design, Ant appears to be betting on a diverse range of applications, from industrial automation to IP-driven consumer and educational robots. This aggressive capital deployment is accelerating the growth of the Chinese robotics ecosystem, creating both partnership and competitive pressure for startups globally. This follows our previous tracking of Ant's initial investment in Zeroth.
Zeroth Robotics plans to use the Wall-E IP for an educational companion robot. Ant's investment strategy appears to cover multiple facets of the humanoid value chain. This news comes as state-backed funding also flows into other major players, with Tsinghua University-affiliated Stardust AI (Xingdong Jiyuan) recently announcing another RMB 1 billion round, bringing its total for the year to RMB 3.5 billion.
A research team at Lehigh University has experimentally confirmed that millimeter-scale drug-delivery robots exhibit an unexpected motion reversal when swimming in non-Newtonian fluids that mimic blood or mucus. The study, published in Applied Physics Letters, found that as the frequency of the magnetic field used to actuate the helical robots increases, their sideways motion reverses—a phenomenon previously predicted numerically but never observed in practice.
Why it matters
This discovery is fundamental for the future of targeted drug delivery. It reveals that the physical properties of bodily fluids are not just a passive medium but an active participant in how microrobots move. Understanding this complex interaction provides a powerful new handle for controlling these tiny robots, which is essential for navigating them precisely to a target like a tumor while avoiding healthy tissue. It shifts the design focus from just the robot's shape to the interplay between the robot and its fluid environment.
Lead researcher Ebru Demir states this finding is "critical for the successful manipulation of these swimmers for targeted drug delivery applications." The experimental validation of this counterintuitive behavior provides a foundational principle for engineers designing the next generation of medical microrobots. This comes as other research teams are also exploring novel locomotion, such as UKRI-funded snail-inspired microbots that use a mucus-like trail for precise drug delivery in the gut.
Following up on the Tufts and Harvard research we noted yesterday, the team has formally published their work on 'neurobots' in Advanced Science. These living, mobile biological robots—made from frog embryo cells that grow their own functional neural networks—can self-organize, display spontaneous neural activity, and form connections, exhibiting more complex behaviors than previous biobots without neural tissue.
Why it matters
This research pushes the frontier of bio-robotics, creating a novel platform for studying how nervous systems develop and function outside of a natural organism. It opens the door to creating fully biological and biodegradable microrobots that could potentially be used for regenerative medicine, such as delivering therapies to specific sites in the body. For robotics, this explores the very definition of a machine, blurring the line between synthetic constructs and living organisms and providing a new model for understanding the origins of cognitive architecture. This story follows similar research from the same team that was reported on last week.
The researchers highlight this as a new tool to investigate neuroplasticity and the basic mechanisms of cognition. Unlike their previous 'Xenobots', these 'neurobots' incorporate neuronal precursor cells that develop into a functioning nervous system, allowing for more advanced behaviors. This represents a significant step toward creating autonomous biological agents that can perform useful work.
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AI is dramatically speeding up development in two critical and traditionally slow-moving areas for humanoid robotics: battery chemistry and joint actuators. According to a new analysis, machine learning is compressing materials discovery timelines for batteries from years to months. Simultaneously, AI-driven simulation and optimization are accelerating the design, testing, and mass production of the high-performance motors essential for robot joints.
Why it matters
This development is crucial because power density and mechanical components, not just software, have been major bottlenecks holding back commercially viable humanoids. By tackling these foundational hardware challenges, AI is enabling the entire field to move faster from prototype to production. For an entrepreneur, this suggests that the supply chain for essential robot components is maturing rapidly, potentially lowering costs and improving performance for new designs. It also highlights an investment opportunity in the "picks and shovels" of the robotics gold rush. LG Energy Solution is already emerging as a key battery supplier for top humanoid makers, underscoring this trend.
The analysis argues that AI's impact on these "unglamorous" but essential fields is what's making humanoid robots an investable category. While foundation models for control get most of the attention, these hardware advancements enabled by AI are equally important for practical deployment. LG Energy Solution's recent success in securing supply deals confirms the growing demand for specialized, high-performance power sources tailored for robotic hardware.
The high-end robot vacuum market is seeing new AI-powered entrants. Dyson has released the Spot+Scrub Ai, a wet-and-dry model that uses an HD camera and AI to detect, identify, and verify the cleaning of stains. Meanwhile, Dreame Technology has launched its more affordable L50 Plus and L50 models in India, featuring powerful suction and smart navigation to target a broader consumer base.
Why it matters
These launches demonstrate two key trends in the consumer robotics market: the push for more sophisticated, autonomous cleaning capabilities at the high end, and increasing accessibility of advanced features in mid-range models. Dyson's focus on AI-driven stain recognition and adaptive cleaning represents a step toward more intelligent and less supervised home automation. Dreame's entry into the Indian market highlights the growing global demand for these devices, suggesting a large untapped market for home robotics beyond early adopters in the US and Europe.
Dyson's system is trained to recognize nearly 200 common household objects to adapt its strategy, showcasing the increasing role of machine vision in consumer products. Dreame's pricing strategy in India (starting around $335) makes features like dual-rotary mops and smart navigation available to a new demographic. The market continues to evolve, with ongoing deals like a recent discount on the Worx Landroid Vision making AI-powered outdoor robots more affordable as well.
The market for autonomous commercial and high-end residential lawn mowers is heating up with several new launches. Kress has introduced its EyePilot line, which uses Vision AI and V-SLAM to operate without boundary wires. Mammotion's new Luba 3 AWD is designed for rugged terrain, capable of tackling slopes up to 45 degrees. Similarly, the Mova Viax 300 is built to handle slopes and narrow passages, using GPS and RTK for wire-free navigation.
Why it matters
These new models represent a significant step forward in outdoor consumer robotics, directly addressing the key limitations of previous generations: complex terrains, steep slopes, and the hassle of boundary wires. By leveraging advanced navigation technologies like Vision AI, V-SLAM, and high-precision RTK GPS, these mowers make autonomous lawn care a viable solution for a much wider range of properties, including large, sloped, or complex commercial landscapes. This expands the addressable market and pushes the category closer to true 'set it and forget it' autonomy.
Kress's EyePilot focuses on multi-zone maintenance and automatic property mapping for commercial use. Mammotion's Luba 3 AWD is positioned for its raw power and all-terrain capability, even offering a modular snowplow attachment. The Mova Viax 300 targets homeowners with complex yards who want premium, wire-free performance. Together, they show a market segmenting to solve specific user pain points beyond basic flat-lawn mowing.
Researchers at the Istituto Italiano di Tecnologia (IIT) have developed a soft robotic arm inspired by an octopus that integrates perception and action directly into its structure. Unveiled on Monday, the arm uses soft silicone suction cups with embedded optical sensors to feel force and direction in real-time. This decentralized sensing allows the arm to autonomously adapt its grasp and manipulate objects in complex, unstructured environments without central processing.
Why it matters
This represents a significant step away from rigid, centrally controlled robots toward more flexible, biologically-inspired systems. By distributing intelligence throughout the arm's body, the robot can react and adapt much faster and more naturally, similar to a real octopus. This design is inherently safer for human collaboration and is particularly well-suited for delicate tasks in unpredictable settings, such as subsea infrastructure maintenance, handling fragile biological samples in a lab, or navigating cluttered disaster sites.
The IIT team's design philosophy is a shift "from a brain-centric to a body-centric approach," where the physical structure itself contributes to the robot's intelligence. This work aligns with other recent breakthroughs in soft robotics, including a new artificial muscle from Seoul National University that integrates sensing and actuation, further blurring the lines between material and machine.
Expanding on the pea-sized liquid-metal pump we covered from the University of Bristol last month, researchers there—along with North Carolina State University—have developed a method to make soft robots more than three times more powerful without increasing size. Detailed on Monday, the breakthrough uses an Electrocapillary-enhanced Magnetohydrodynamic Pump (EMP) that leverages the surface tension of a tiny, electrically-charged liquid metal droplet to amplify force.
Why it matters
Power and strength have long been major limitations for soft, compliant robots. This innovation provides a way to create more capable, compact, and lightweight systems. The potential applications are broad, ranging from more effective wearable assistive devices for rehabilitation to more powerful miniature biomedical tools for drug delivery and diagnostics. This fundamental research, which follows a similar announcement about liquid-metal pumps from Bristol University last month, could significantly accelerate the practical use of soft robotics.
The research team highlights that this method avoids the need for larger, heavier, or more complex components, which is a key advantage for wearable and medical applications. The technology is described as a "tiny, but mighty, artificial heart" for soft robots, enabling a new class of powerful yet flexible devices.
California-based startup Queue has launched what it calls the world's first fully autonomous robotic pharmacy, backed by $12.6 million in new seed funding (bringing its total to $18.6 million). The system uses a combination of robotics, AI, and computer vision to manage the entire prescription process, from receiving sealed medication bottles to verifying and dispensing them into patient-ready vials, with minimal human intervention.
Why it matters
This technology directly addresses several critical pain points in the U.S. pharmacy industry, including chronic staff shortages, rising operational costs, and dispensing errors. By automating the most repetitive and time-consuming tasks, Queue's system could significantly lower costs, improve accuracy, and free up pharmacists for patient consultation. For a robotics entrepreneur, this is a prime example of identifying a high-value, regulated process and applying a full-stack automation solution to create a compelling business case.
Queue's system is designed to support the 250 most commonly prescribed medications in the U.S. The company claims it can reduce prescription processing costs by up to 90%. The funding and launch come as automation in healthcare is accelerating, with Finnish startup CurifyLabs also raising €12 million this week to automate personalized medicine manufacturing using 3D printing.
NVIDIA is offering significant discounts on its lineup of Jetson developer kits, including the AGX Thor, AGX Orin, and Orin Nano Super. The price reductions are aimed at making powerful edge AI hardware more accessible to developers, researchers, and startups working on robotics and other autonomous systems. The company highlights that these platforms are already being used in a wide range of applications, from humanoid robots and autonomous delivery vehicles to underwater monitoring systems.
Why it matters
This move lowers the financial barrier to entry for developing sophisticated, real-world robotic applications. For entrepreneurs and developers, more affordable access to high-performance computing hardware like the Jetson series means the ability to prototype, test, and deploy advanced embodied AI systems more extensively and at a lower cost. It's a strategic effort by NVIDIA to solidify its platform's position as the standard for edge AI, fostering a larger ecosystem of developers building on its hardware and software stack, which includes the Isaac Sim and Isaac ROS tools.
This pricing strategy is part of a broader push by chipmakers to capture the burgeoning physical AI market. Intel is promoting its new Core Ultra Series 3 processors for robotics through distributors like Rutronik, emphasizing integrated CPU, GPU, and NPU capabilities. Meanwhile, Advantech is rolling out industrial platforms based on Qualcomm's Dragonwing IQ9 architecture. The competition to provide the 'brain' for robots is intensifying, with a clear focus on enabling powerful, real-time inference directly on the device.
Starship Technologies is strategically winding down its extensive U.S. university campus operations and redeploying more than 1,200 of its delivery robots to focus on grocery and hot food delivery in cities across the U.S. and Europe. The company, which has seen significant expansion in the UK with partners like Co-op, expects tenfold growth in its grocery segment over the next two years, claiming its robots can deliver at a lower cost than human couriers.
Why it matters
This major pivot signals a critical maturation phase for the autonomous delivery industry, moving from controlled, semi-private environments to the complexities and larger scale of public urban streets. It's a bet on the superior unit economics of urban logistics over campus services. However, this expansion into public spaces is already generating pushback. In the UK, walking charities and campaigners are raising safety concerns, arguing the robots create hazards for pedestrians, particularly for elderly and disabled individuals. This highlights the central challenge for the industry: balancing commercial scalability with public acceptance and safety regulations.
Starship sees a massive opportunity in last-mile grocery delivery, a segment with high demand and costs. However, advocacy groups like Living Streets in the UK are calling for stricter regulations, warning of 'pavement overload' and accessibility issues. This tension between innovation and public good will be a defining factor in whether autonomous delivery can achieve mainstream success.
Fleshing out the advanced bipedal project from IIT Madras we recently tracked, the institute's Robotics Lab has officially introduced 'Astra-1'. The 1.7-meter-tall humanoid is designed for industrial automation tasks like assembly line work and warehouse logistics, equipped with a dual-core NPU. The team aims to produce the robot at a cost significantly lower than international competitors to democratize automation for Indian industries.
Why it matters
This development is a key milestone for India's 'Make in India' initiative, aiming to build a domestic ecosystem for advanced robotics and reduce reliance on expensive imports. By targeting a lower price point, Astra-1 could democratize automation for the country's small and medium-sized enterprises (SMEs), boosting productivity and creating a local talent pool. This follows a trend of new Indian robotics startups like Astha Robotics, which recently raised $10M, signaling a vibrant and growing domestic market.
The IIT Madras team emphasizes the goal of providing an affordable and resilient solution tailored to the needs of Indian industry. The project is seen as a crucial step towards technological self-reliance. The emergence of Astra-1 adds to a competitive landscape of Indian humanoid startups, all aiming to drive automation in one of the world's fastest-growing economies.
Despite Waymo's massive scale—which we recently noted had crossed 500,000 paid rides per week—Amazon's Zoox is gaining significant ground in the U.S. robotaxi market. According to a new market analysis, Zoox's share of monthly active users grew from 15% to 25% in the first half of 2026, while Waymo's dominant share fell from 79% to 69%. Zoox benefited from service expansions into Austin and Miami, though Waymo has shown strong appeal among younger users aged 17-25.
Why it matters
This shift in market dynamics indicates that the robotaxi race is far from settled. Zoox's ability to quickly capture a quarter of the market demonstrates that a strong challenger can emerge, influencing investment and expansion strategies across the sector. The demographic data is also key; Waymo's traction with young riders—a crucial future customer base—could be a significant long-term advantage. For the industry, this underscores the importance of both geographic expansion and building brand loyalty with the next generation of users. This comes as Waymo continues its international push, recently registering a subsidiary in France.
The market share data suggests Zoox's expansion into new cities is paying off in user acquisition. Meanwhile, Tesla officially launched its unsupervised robotaxi service in Miami on Tuesday, adding another major competitor with a radically different, vision-only technology stack and business model, which will further reshape the competitive landscape.
Open-Source Robotics Gains a Standardized Toolkit The collaboration between NVIDIA and Hugging Face to integrate Isaac GR00T into the LeRobot library marks a significant step toward a common, open workflow for physical AI. This, along with new open simulators from NASA and Rice University, is lowering the barrier to entry and aims to accelerate innovation across the robotics community.
Humanoid Market Forecasts Signal Massive Industrial Shift A wave of new market reports, including a notable forecast from Goldman Sachs, are projecting explosive growth for the humanoid robot market. These analyses predict a 70-fold increase in shipments by 2035, driven by persistent labor shortages and advancements in embodied AI, pointing to a large-scale industrial transformation.
Venture Capital Continues to Pour into Specialized Robotics Funding rounds for startups like Norwegian HIVE, UK's Worldmodeldata, and California's Queue highlight investor confidence in specialized robotics and physical AI. Capital is flowing not just to humanoid developers, but to the entire ecosystem, including AI training data providers, industrial machine intelligence, and automated healthcare logistics.
Microrobotics Research Unlocks New Control Methods New academic research is revealing fundamental principles for controlling microrobots in complex biological environments. Studies on how non-Newtonian fluids affect locomotion and the development of snail-inspired bots for targeted drug delivery are paving the way for more precise and effective medical interventions.
AI Hardware for the Edge Becomes More Specialized and Accessible The market for edge AI silicon is diversifying and becoming more accessible. NVIDIA is discounting its popular Jetson developer kits, while companies like Intel and Advantech are releasing new processors specifically for robotics. This trend enables more powerful on-device inference, crucial for autonomous systems operating in the real world.
What to Expect
2026-07-10—International Conference on Robotics and Mechatronics (ICRM) begins in New York.
2026-09-XX—UBTECH expects to begin deliveries of its U1 companion robot in China.
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