Trends in Robotics Innovation

AI agents and physical AI are shifting industrial automation from equipment supply to autonomous, self-optimizing systems. The most mature vendors are moving from pilots to production, with robots navigating complex environments and digital twins optimizing the value chain. This CB Insights brief gives a good view of where the top 20 industrial automation companies stand on AI maturity. Three key trends. 1. Leaders like Siemens Industry and ABB are linking AI systems across design, logistics, manufacturing, and maintenance creating compounding benefits. 2. Optimization dominates near-term priorities, while digital twins are emerging as the backbone for connecting hardware and software. 3. Partnerships with tech companies like Microsoft, Google, and Nvidia are essential, but they create new dependencies that must be managed. Siemens at the top of the ranking, combining copilots, edge platforms, and digital twins. Its work with Microsoft and Nvidia expands capabilities but increases reliance on external tech. Honeywell takes a more focused approach, embedding AI into devices and workflows. Its Qualcomm partnership highlights product-level integration over broad system building. ABB advances through its OmniCore platform and acquisitions such as Sevensense and SensorFact, blending robotics, software, and energy management. Schneider Electric pushes AI in energy management, using digital twins and partnerships with Nvidia, Microsoft, and Itron to extend from factory optimization into grid intelligence. The path forward in industrial AI is moving beyond pilots or isolated tools. It will depend on how well vendors embed AI into their platforms, link technologies across domains, and balance the benefits of external partners with the need for strategic independence. Those that will get it right will turn AI from experimentation into durable advantage. Just as critical is how their customers adopt these technologies. Industrial firms must shift from isolated use cases to embedding AI in design, production, energy, and logistics. Success requires not only advanced tools, but also the data, skills, and processes to make AI scale in complex operations.

My biggest takeaways from ex-OpenAI, Apple, Meta roboticist Caitlin Kalinowski: 1. The AI frontier is shifting from digital to physical because labs see the ceiling of keyboard-bound AI. “What you can do behind a keyboard with AI is going to saturate.” Which is why labs, big tech, and startups are increasingly investing in hardware, and why enrollment at universities is rising while CS enrollment is trending down. 2. More change is coming to warfare than to consumer electronics in the next two years. Drones, robotics, and the hardware supply chain all converge on the battlefield, and Caitlin argues we have to be able to control adversarial threats to our hardware layer, not just our chatbots. 3. VR didn’t become a mainstream product, but it created the tech necessary for robotics (and war). SLAM (simultaneous localization and mapping), depth sensors, spatial computing, and understanding how humans perceive visual data in space is now powering robotics, autonomous vehicles, and drones. The technology needed to understand how a robot moves through space is essentially the same technology developed for VR headsets. 4. The hardware industry faces a looming memory crisis that could derail the robotics revolution. Memory prices are spiking—potentially doubling or more—driven by AI data center demand. Companies building consumer robotics can’t compete on price with data centers. Caitlin is advising startups to pre-buy memory and stockpile components if they can afford it, because “we are in trouble as an industry.” 5. Humanoid robots are overhyped. While humanoids are interesting for certain long-tail tasks, most manufacturing and real-world applications need dedicated robots designed for specific jobs. A robot screwing keyboards into laptop cases doesn’t need to be humanoid—it needs to be optimized for that exact task. The future will have robots for construction, electrical work, logistics, and low-volume assembly, and most won’t look humanoid. 6. Supply chain independence is a national security imperative. Over the past 25 years, essentially every layer of the hardware supply chain—from raw magnets to actuators to final assembly—has been outsourced to China, Japan, and Korea. The same actuator technology that makes a drone rotor spin also makes a robot arm move. Without an independent supply chain, the U.S. is vulnerable. As Caitlin warns, “We need to re-industrialize this country significantly in order to be safe in a military sense.” 7. Software builders don't understand how fundamentally different building hardware is. Software can compile code hourly, but in hardware, you may get only a handful of chances to “compile” before mass production, with each major build taking three to five months. Once you ship, you’re done—there are no over-the-air updates for physical components. Software intuition doesn’t transfer to hardware.

Physical AI is starting to look less like robotics - and more like the next cloud infrastructure race. This week, Mind Robotics raised another $400M to build AI-powered industrial robots, pushing its valuation past $3.4B. At the same time, a new wave of embodied AI companies - from Physical Intelligence to Skild AI - are attracting capital at infrastructure-scale valuations. The narrative is shifting fast: investors are no longer underwriting “robots.” They’re underwriting foundational control systems for the physical world. What most people are missing is that hardware is becoming the distribution layer, not the moat. The real asset is the data flywheel created by real-world interaction: motion, failure, correction, adaptation. Physical AI companies are converging on the same realization that defined cloud and autonomous driving - whoever owns the operational data layer compounds fastest. That’s why simulation, deployment infrastructure, and robotics middleware are suddenly strategic assets, not support tooling. The implication for founders is clear: vertical robotics companies may struggle unless they control proprietary environments or workflows. For investors, the bigger opportunity may sit one layer below - orchestration, simulation, embodied foundation models, and industrial data infrastructure. Physical AI won’t be won by the best robot demo. It’ll be won by the company that learns fastest in the real world. #PhysicalAI #Robotics #EmbodiedAI #VentureCapital #AIInfrastructure https://lnkd.in/gUY4-Zsx

The global economy has an impending problem. While AI is compounding its ability at a historic rate, an aging population and declining fertility rates are already causing labor shortages. These trends, combined with declining costs of robotics hardware, underpin a compelling case for humanoid robots and physical AI. According to Morgan Stanley, the humanoid robot market is set to exceed $5 trillion by 2050. Even in 2025, the larger robotics space saw $21 billion of VC capital invested. And with a steady increase in patent activity mentioning “humanoid” over the past few years, these machines are already walking onto factory floors. For most of human history, productive output was a function of human muscle. Agriculture, manufacturing, logistics, and construction were all built around the physical limits of the human body. Because humans did the work, the built world standardized around human form: doorways, staircases, countertops, and tools are all designed for two arms, two legs, and hands that grip. Redesigning every factory, warehouse, and home around task-specific machines would be unfeasible. A humanoid robot that fits into existing infrastructure doesn’t need the world to change around it. Near-term use cases focus on structured, predictable settings, enabling a robot to learn quickly, make mistakes cheaply, and improve rapidly. My research team at Social Capital concluded that humanoid Robots will have the highest impact in these 7 areas: 1. Domestic Assistance: Supporting mobility needs, handling household chores, and providing medication reminders. 2. Manufacturing: Assisting assembly tasks, moving tools and parts, inspecting finished products. 3. Security & Monitoring: Patrolling facilities, investigating alerts, and assisting in emergencies. 4. Customer Service & Reception: Greeting and directing visitors, answering questions, and managing check-ins or bookings. 5. Facility Maintenance: Conducting routine inspections, performing minor repairs, cleaning, and sanitizing spaces. 6. Healthcare: Assisting nurses, delivering supplies or meals, monitoring patients. 7. Warehouse and Logistics: Picking and packing items, loading and unloading goods, and moving inventory in warehouses. By 2050, Morgan Stanley estimates that more than 1 billion humanoid robots could be working globally, with a market size of over $5 trillion. This is one of the biggest opportunities in the AI era.

Reflections and Insights: 2024 and Beyond In 2024, I learned that the most impactful transitions are not departures but transformations. As I stepped back from operational roles, I observed a pivotal shift I had long anticipated: mobile robotics have moved beyond being tactical tools to becoming strategic necessities, especially in public safety and defense. This year underscored four critical insights into our industry’s evolution: 1) The integration of mobile robotics within the Tactical Bubble is no longer optional—it’s essential for modern operations. 2) Private mesh networks (MANET) are solidifying their role as the backbone of reliable tactical communications. 3) Bridging the gap between technical capabilities and tactical operations remains our greatest challenge—and our greatest opportunity. 4) It's not just hardware; proper software (from AI to TAK, to autonomy) are the key to fully leveraging the benefits of uncrewed systems in the air, on the ground, on water and sub water. Key Developments Shaping Our Industry in 2024: Deployment and training of advanced mobile robotics across multiple agencies. Seamless integration of air, ground, and maritime robotics into unified tactical operations. Transformation of the Tech/Tac Bubble concept into actionable, real-world implementations. Significant industry shifts in military drone and mobile robotics capabilities amidst growing competition. Looking Ahead to 2025 While I didn’t initially expect to see this new year, I’ve made it here—and my focus remains steadfast. As I continue to scale back operational roles, my efforts will center on advancing mobile robotics innovation through strategic advisory and knowledge sharing. Key projects I’ve nurtured for years are being transitioned to capable individuals and entities, ensuring they remain aligned with the industry's pressing needs: standardization, immersive training, connectivity, and user-friendly solutions. To the global public safety community, defense sector, and mobile robotics innovators and manufacturers: The technology is proven. The infrastructure is advancing. We have validated countless claims and use cases. Now, the focus must shift to proper implementation, selecting the right hardware and software, ensuring comprehensive tactical training, and maintaining data-driven validation of claims. Together, we are shaping the future of mobile robotics, ensuring they serve as a force multiplier for safety, security, and innovation. Wishing you all a safe start into 2025 and a year of health, success, passion and the ability to stay grounded. #UAVsForGood #MobileRobotics #PublicSafety #TacBubble #Drones #UAVs #Training #2024Review #2025Forecast Image courtesy of FLYMOTION

The past 10 years have seen the United States move from a laggard to a leader as it pertains to the adoption of industrial robots (HS code 84.7950.000). With 2023’s trade data finalized, I thought it would be interesting to show both the trends in terms of unit imports of robots as well as the price per robot. Two charts below. Thoughts: •Top chart shows the number of industrial robots imported from the USA from all over the world. Prior to 2011, that number never crossed 10,000. However, it took off starting in 2015 (where it almost reached 50,000). 2023 is the second highest year ever, with ~128,000 industrial robots brought into the USA. This slightly outpaces what we saw in 2020 and 2022 (note, I’m guessing 2021 was lower due more to supply side issues [e,g., shortfall of semiconductors and other components] as opposed to less demand). •Bottom chart shows the average price per unit. Fun pattern here: note that price per unit is much lower in 2017, 2020, 2022, and 2023 (corresponding the years for the most imports). This does suggest the highest years are being driven by unobserved differences in the types of robots being brought into the US. •Given the labor market remains quite tight, I don’t see this trend reversing anytime soon. This points to the need for developing more workers with the skills to not only work with industrial robots, but also to be able to repair them. •As technology continues to become more flexible, I expect we will continue to see industrial robots find applications outside of traditional key sectors for their use like motor vehicle production, chemical manufacturing, fabricated metal product manufacturing, plastics manufacturing, and both basic metals and fabricated metal product manufacturing (see https://lnkd.in/dDmuan3P). Implication: I expect industrial robots will continue to become an increasingly common sight in American factories. It will be critical for firms to adapt their workforces to best leverage these technologies. #supplychain #supplychainmanagement #manufacturing #economics 

For years, robotics in India was treated as a futuristic category. Interesting, but not urgent. Technically impressive, but commercially early. The assumption was that India had enough low-cost labour, too much operational complexity, and too little depth in hardware components for robotics to become a growth market. That assumption is breaking down. Across warehouses, factories, hospitals, construction sites, farms, mines, and public infrastructure, the economics are changing in plain sight. Same-day delivery cannot scale on manual sortation alone. Export-grade manufacturing cannot run on inconsistent precision. Hospital systems cannot absorb growing demand with chronic staff shortages. The inflection point is this: in sector after sector, the cost of inaction is now exceeding the cost of automation. Physical AI is the call to action. That is why at 3one4 Capital, we have published our recent thesis: Scaling Robotics for India: Why Now, Where to Build, and How to Win. What makes this moment especially important is that India is not looking at one robotics market. It is looking at several, all opening at once. - Warehouse automation is being pulled forward by e-commerce, 3PL expansion, and rising throughput requirements. - Manufacturing is reaching the point where cobots, inspection systems, and programmable automation become essential to quality and export competitiveness. - In healthcare, robotics is moving from aspiration to necessity across surgery, rehabilitation, assistive care, and hospital operations. - In agriculture, construction, mining, sanitation, and infrastructure inspection, India’s hardest operating environments are starting to look less like barriers and more like the exact conditions that can produce globally relevant robotics companies. India’s biggest advantage in robotics may not be engineering talent alone. It may be the fact that we are forced to build for constraints. If a robotic system can work within India’s space constraints, scope variability, evolving workflows, multilingual operators, high-variance inputs, and extreme price sensitivity, it is not just India-ready. It is ready for much of the world. That is how global champions are built. We are already seeing early evidence of this potential. Our investment in Unbox Robotics came from exactly this conviction. The company is solving a globally relevant challenge: high-density, high-throughput, space-efficient automation built for operational reality rather than lab conditions. We believe robotics and physical AI can define India’s next productivity leap in the same way DPIs defined the last one. If you are building in robotics, industrial automation, physical AI, autonomous systems, machine vision, or any adjacent layer of this stack, I would love to hear from you. Especially if you are solving a high-friction, real-world problem with a product customers are willing to adopt, integrate, and pay for.

In my last post, we explored Soft-body Dexterity and how robots touch the world with nuance. Today, we will explore how they might understand it: World Models Grounded in Human Narrative: From Physics to Semantics. To thrive in human spaces, robots need more than physics. They need to understand why things matter, from how an object falls to why it matters to you. Embodied AI Agents will need two layers of understanding: 🌍 Physical World Model: Simulates physics, motion, gravity, and materials...enabling robots to interact with the physical world. 🗣️ Semantic and Narrative World Model: Interprets meaning, intention, and emotion. These are some examples: 🤖 A Humanoid Robot in an Office: It sees more than a desk, laptop, and spilled coffee; it understands the urgency. It lifts the laptop and grabs towels, not from a script, but by inferring consequences from context. 🤖 A Domestic Robot at Home: It knows slippers by the door mean someone’s home. A breeze could scatter papers. It navigates not just with geometry but with semantic awareness. 🤖 An Elder Care Robot: It detects tremors, slower gait, and a shift in tone, not as data points, but signs of risk. It clears a path and offers help because it sees the story behind the signal. Recent research: 🔬 NVIDIA Cosmos A platform for training world models that simulate rich physical environments, enabling autonomous systems to reason about space, dynamics, and interactions. https://lnkd.in/g3zJwDmb 🔬 World Labs (Fei-Fei Li) Building "Large World Models" that convert 2D inputs into 3D environments with semantic layers. https://lnkd.in/gwQ2FwzV 🔬 Dreamer Algorithm Equips AI agents with an internal model of the world, allowing them to imagine futures and plan actions without trial-and-error. https://lnkd.in/gnPZeRy5 🔬 WHAM (World and Human Action Model) A generative model that simulates human behavior and physical environments simultaneously, enabling realistic, ethical AI interaction. https://lnkd.in/gt5NJ8az These are some relevant startups, leading the way: 🚀 Figure AI (Helix): Multimodal robot reasoning across vision, language, and control. Grounded in real-time world modeling for dynamic, human-aligned decision-making. https://lnkd.in/gj6_N3MN 🚀 World Labs: Converts 2D images into fully explorable 3D spaces, allowing AI agents to “step inside” a visual world and reason spatially and semantically. https://lnkd.in/grMS9sjs What's the time horizon? 2–4 years: Context-aware agents in homes, apps, and services; reasoning spatially and emotionally. 5–7 years: Robots in real-world settings, guided by meaning, story, and human context. World models transform a robot from a tool into a cognitive partner. Robots that understand space are helpful. Robots that understand stories — are transformative. It’s the difference between executing commands... and aligning with purpose. Next up: Silent Voice — Subvocal Agents & Bone-Conduction Interfaces.

Collaborative robots are moving automation from isolated cells into daily production activities beside human operators. Factories adopting cobots are reorganizing safety procedures and line management to gain steadier execution with less physical strain on teams. A few operational consequences are becoming visible: - Repetitive assembly tasks are shifting toward robotic support while operators focus on supervision - Flexible production lines can adapt faster to product changes through rapid robot reprogramming - Safety management is evolving with sensors and motion control integrated into daily workflows - Workforce development now requires technical skills linked to monitoring and process optimization - Stable robot movements help reduce variability and improve consistency across production cycles Long-term adoption depends on human-machine coordination and production models designed around collaboration rather than replacement. #Cobots #Industry40

𝐓𝐡𝐞 𝐦𝐨𝐦𝐞𝐧𝐭 𝐦𝐚𝐜𝐡𝐢𝐧𝐞𝐬 𝐥𝐞𝐚𝐫𝐧 𝐭𝐨 𝐦𝐨𝐯𝐞 – 𝐧𝐨𝐭 𝐣𝐮𝐬𝐭 𝐭𝐨 𝐭𝐡𝐢𝐧𝐤 – 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠 𝐬𝐡𝐢𝐟𝐭𝐬. In a recent client workshop, we analysed China’s rise of 𝐝𝐚𝐫𝐤 𝐟𝐚𝐜𝐭𝐨𝐫𝐢𝐞𝐬 – fully autonomous plants running with almost 𝐧𝐨 𝐡𝐮𝐦𝐚𝐧 𝐩𝐫𝐞𝐬𝐞𝐧𝐜𝐞. What struck everyone in the room was not the robotics itself, but the 𝐬𝐩𝐞𝐞𝐝. Some sites run 24/7 with 𝟕𝟎–𝟖𝟎 𝐩𝐞𝐫𝐜𝐞𝐧𝐭 𝐟𝐞𝐰𝐞𝐫 𝐰𝐨𝐫𝐤𝐞𝐫𝐬, guided by fleets of autonomous mobile robots and vision-driven quality systems. And then we looked west. ✔️ Amazon already operates more than 𝟕𝟓𝟎,𝟎𝟎𝟎 𝐫𝐨𝐛𝐨𝐭𝐬 across its fulfilment network. ✔️ Manufacturing costs for humanoid robots dropped 𝟒𝟎 𝐩𝐞𝐫𝐜𝐞𝐧𝐭 𝐢𝐧 𝐨𝐧𝐞 𝐲𝐞𝐚𝐫. ✔️ The global robotics market is projected to hit 𝐔𝐒𝐃 𝟑𝟗𝟐 𝐛𝐢𝐥𝐥𝐢𝐨𝐧 by 2033. The message is simple: 𝐭𝐡𝐢𝐬 𝐢𝐬 𝐧𝐨 𝐥𝐨𝐧𝐠𝐞𝐫 “𝐟𝐮𝐭𝐮𝐫𝐞 𝐰𝐨𝐫𝐤”. 𝐈𝐭 𝐢𝐬 𝐜𝐨𝐦𝐩𝐞𝐭𝐢𝐭𝐢𝐯𝐞 𝐫𝐞𝐚𝐥𝐢𝐭𝐲. But the deeper shift is something else entirely. For the first time, intelligence isn’t staying behind screens. It is entering the physical world – perceiving, reasoning, deciding and acting 𝐢𝐧 𝐫𝐞𝐚𝐥 𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭𝐬. What #Deloitte calls 𝐩𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞. And with it, leadership must change at its core. In our latest work, Deloitte introduced the 𝟔𝐏𝐬 for leaders navigating this shift: 𝐏𝐫𝐞𝐩𝐚𝐫𝐞, 𝐏𝐞𝐫𝐜𝐞𝐢𝐯𝐞, 𝐏𝐫𝐨𝐜𝐞𝐬𝐬, 𝐏𝐞𝐫𝐟𝐨𝐫𝐦, 𝐏𝐫𝐨𝐜𝐞𝐞𝐝, 𝐏𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥 – a roadmap stretching from data foundations to workforce design and long-term societal impact. Every executive said the same thing afterwards: “𝐈 𝐝𝐢𝐝𝐧’𝐭 𝐫𝐞𝐚𝐥𝐢𝐬𝐞 𝐡𝐨𝐰 𝐛𝐢𝐠 𝐭𝐡𝐞 𝐨𝐫𝐠𝐚𝐧𝐢𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐬𝐡𝐢𝐟𝐭 𝐦𝐮𝐬𝐭 𝐛𝐞.” Because this isn’t just automation. It is 𝐦𝐚𝐜𝐡𝐢𝐧𝐞𝐬 𝐛𝐞𝐜𝐨𝐦𝐢𝐧𝐠 𝐩𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐦𝐚𝐤𝐞𝐫𝐬. And that forces new questions: ❓𝐖𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐭𝐫𝐮𝐬𝐭 𝐦𝐞𝐚𝐧 𝐰𝐡𝐞𝐧 𝐚𝐮𝐭𝐨𝐧𝐨𝐦𝐲 𝐡𝐚𝐬 𝐚 𝐛𝐨𝐝𝐲? ❓𝐇𝐨𝐰 𝐝𝐨 𝐰𝐞 𝐛𝐮𝐢𝐥𝐝 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 𝐰𝐡𝐞𝐫𝐞 𝐡𝐮𝐦𝐚𝐧𝐬 𝐚𝐧𝐝 𝐦𝐚𝐜𝐡𝐢𝐧𝐞𝐬 𝐜𝐨-𝐨𝐰𝐧 𝐨𝐮𝐭𝐜𝐨𝐦𝐞𝐬? ❓𝐖𝐡𝐞𝐫𝐞 𝐝𝐨 𝐰𝐞 𝐫𝐞𝐝𝐫𝐚𝐰 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲? The next decade won’t reward the fastest adopters. It will reward the 𝐛𝐫𝐚𝐯𝐞𝐬𝐭 𝐫𝐞𝐝𝐞𝐬𝐢𝐠𝐧𝐞𝐫𝐬. Curious where you stand: 𝐈𝐟 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐜𝐚𝐧 𝐧𝐨𝐰 𝐰𝐚𝐥𝐤 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐫𝐨𝐨𝐦 𝐰𝐢𝐭𝐡 𝐮𝐬 – 𝐡𝐨𝐰 𝐝𝐨 𝐲𝐨𝐮 𝐰𝐚𝐧𝐭 𝐲𝐨𝐮𝐫 𝐨𝐫𝐠𝐚𝐧𝐢𝐬𝐚𝐭𝐢𝐨𝐧 𝐭𝐨 𝐞𝐯𝐨𝐥𝐯𝐞? #PhysicalIntelligence #FutureOfWork #LeadershipTransformation #RoboticsReimagined #HumanAndMachine