Today on The Robot Beat: AMD makes an aggressive, full-stack push into physical AI, challenging NVIDIA's long-held dominance with a new line of embedded processors and an open developer ecosystem. This new competition at the silicon layer arrives alongside a confirmed $1.7 billion funding round for Travis Kalanick's industrial AI venture, Atoms, and continued momentum in the surgical robotics space following yesterday's landmark J&J approval.
AMD has launched a major strategic initiative to compete directly with NVIDIA in the physical AI and robotics market. At its Advancing AI 2026 event on Thursday, the company unveiled its new Ryzen AI Embedded X100 series processors, new Kria AI System-on-Modules (SOMs), and the AMD Robotics Partner Network. The X100 series integrates a Zen 5 CPU, RDNA 3.5 GPU, and an XDNA 2 NPU on a single chip, designed to provide deterministic, real-time control for robots. AMD is positioning its open software stack (ROCm) as a direct competitor to NVIDIA's CUDA ecosystem.
Why it matters
AMD's entry creates the first serious, full-stack competitor to NVIDIA's long-standing dominance in robotics AI hardware. For robotics entrepreneurs, this is a significant development. It introduces much-needed competition at the silicon layer, which could drive down prices, increase innovation, and reduce vendor lock-in. AMD's emphasis on an open-source software stack and partnerships with companies like Foundation Robotics and IEI signals a concerted effort to build a viable alternative ecosystem, offering you more choice and flexibility when architecting next-generation robotic systems.
SiliconANGLE highlighted AMD's strategy of providing a comprehensive solution of specialized hardware and an open ecosystem to rival NVIDIA. Unite.AI noted that humanoid developer Foundation Future Industries has already selected AMD's new chips for its Phantom robots, marking a significant early win. Fierce Electronics framed the move as an attempt to simplify development and accelerate market entry for robotics companies by offering an alternative to the dominant CUDA ecosystem.
Apptronik has opened 'Robot Park,' a nearly 90,000-square-foot facility in Austin, Texas, dedicated to training its Apollo humanoid robots. The facility is designed to collect real-world operational data through both teleoperation and autonomous learning. This initiative is a core part of its research partnership with Google DeepMind, aimed at advancing embodied AI capabilities using Google's Gemini Robotics AI models. The park will serve as a hub for developing, testing, and validating Apollo's skills before deployment in customer environments.
Why it matters
The creation of dedicated, large-scale training facilities like Robot Park signals the industry's maturation from building hardware prototypes to developing scalable, intelligent software. For a robotics entrepreneur, this underscores the critical importance of a robust data pipeline and real-world testing infrastructure for training foundation models. It shows that access to physical space and operational data is becoming a key competitive advantage in the race to build truly general-purpose robots, moving beyond simulated environments.
Web Wide Studios noted that the park is crucial for supporting the Google DeepMind partnership to advance Gemini Robotics models. Violons Delegende framed the facility as a necessary step for moving humanoids from controlled labs to practical, real-world applications. This follows a similar move by Agility Robotics, which recently opened a 60,000-square-foot facility in Fremont, CA.
Brooklyn-based third-party logistics (3PL) provider Highline Commerce announced on Thursday that its fleet of Operator OP1 robots from Ultra Robotics is now fulfilling 30% of its clients' orders. The OP1 units are stationary, wall-powered humanoids designed for 24/7 operation within a fixed work cell for tasks like picking and packing. This deployment model forgoes bipedal mobility in favor of continuous, reliable operation, tailored for the needs of mid-market e-commerce fulfillment centers.
Why it matters
This marks a significant and commercially verified milestone for a non-mobile humanoid deployment. By designing for a fixed work cell and eliminating the complexities and power constraints of bipedal locomotion, Ultra Robotics is demonstrating a pragmatic path to commercialization for humanoid form factors. This approach, focused on a specific, high-value task for independent 3PLs rather than large enterprise ecosystems, could provide a blueprint for faster, more scalable adoption of humanoid manipulators in logistics.
TechTimes highlighted this as a unique deployment model outside the major enterprise ecosystems, calling it a commercially verified task-share milestone for independent logistics providers. The focus on a stationary, wall-powered design is seen as a key enabler for its 24/7 operational success and commercial viability in the mid-market.
As Tesla dismantles legacy lines at its Fremont factory to make space for the Optimus Gen 3 mass production we've been tracking, the humanoid's external supply chain is solidifying. South Korean materials company ICH has successfully completed qualification tests for a high-performance polyurethane foam component used in the robot's structure, securing a mass production supply agreement. The material will support initial shipments anticipated in the second half of this year.
Why it matters
This is a concrete step in the operationalization of the Optimus supply chain, moving from ambition to execution. Securing qualified external suppliers for specialized materials is a critical and often-overlooked hurdle in scaling production, confirming that Tesla is making tangible progress on the manufacturing front alongside its factory retooling efforts.
The Asia Business Daily reported the successful qualification and mass production supply agreement for the polyurethane foam. Elon Musk commented during Tesla's Q2 earnings call on Wednesday that building Optimus is the 'hardest product to scale manufacturing' Tesla has ever faced, requiring an entirely new supply chain for its custom components. Interesting Engineering added that Tesla plans to train Optimus by having workers at its German Gigafactory wear cameras to record assembly tasks.
NASA and Rice University have launched the iMETRO Dynamic Simulation, the world's first open-source remote space robotics simulator. The platform is a digital twin of NASA's physical iMETRO facility, which is used for testing robotic systems in environments that mimic extraterrestrial surfaces. The simulator aims to democratize innovation in space robotics by providing researchers, students, and companies worldwide with a virtual environment to develop and test robotic systems for space exploration.
Why it matters
This initiative dramatically lowers the barrier to entry for space robotics R&D. By providing open access to a high-fidelity simulation environment, NASA is enabling a global community of developers, startups, and researchers to contribute to and innovate on the technologies needed for future space missions. For a robotics entrepreneur, this open-source platform represents a significant opportunity to develop, test, and validate robotic hardware and software for the burgeoning space economy without needing access to expensive physical testing facilities.
SENS Network called the platform a revolutionary tool for democratizing space robotics innovation. Convicts and Cops highlighted that the open-source digital twin will expand access to advanced space robotics research and accelerate innovation for future human space missions by enabling global collaboration.
Alibaba has introduced the Qwen-Robot Suite, a full-stack software offering for embodied intelligence that aims to become a foundational operating system for the robotics industry. The suite includes specialized foundation models for navigation (Qwen-RobotNav), manipulation (Qwen-RobotManip), and world understanding (Qwen-RobotWorld). The company is emphasizing a modular architecture, hardware-agnostic operation, and an open-source approach to its data, positioning the suite as the 'Android of robotics'.
Why it matters
Alibaba's ambition to create a universal OS for robots could have massive implications for the industry, similar to Android's impact on mobile phones. By providing a standardized, open-data software layer, the Qwen-Robot Suite could dramatically reduce development costs and complexity for robotics startups and researchers. This could foster a more vibrant and interoperable ecosystem, allowing developers to focus on building applications rather than re-inventing the entire stack, and accelerating the deployment of capable robots across various sectors.
Tempus Antiques reported the suite aims to be the 'Android of robotics' with a strong focus on physics-based simulation and open data. This follows an earlier announcement from Alibaba's Amap unit detailing its 'ABot' system, a 5-in-1 AI framework using specialized foundation models to unify robot functions like navigation and manipulation.
In a collaboration, mimic robotics and Black Forest Labs have introduced FLUX-mimic, a next-generation Video-Action Model (VAM) designed to teach robots complex manipulation tasks from just a few video demonstrations. This technology is already being deployed in production tests at Audi's manufacturing facilities. It enables robots to handle tasks involving flexible parts and fine manipulation, which are traditionally difficult to automate, by leveraging generative video models that understand physical dynamics, significantly reducing the amount of training data required. Black Forest Labs also announced FLUX 3, a unified multimodal architecture.
Why it matters
This is a significant breakthrough in applying generative AI to industrial robotics. By drastically lowering the data and time cost of training robots for complex, variable tasks, FLUX-mimic could fundamentally change the economics of automation. It bridges the gap between the rigid requirements of conventional industrial robots and the flexible demands of modern manufacturing. For a robotics entrepreneur, this demonstrates a commercially viable path to deploying advanced learning models on the factory floor, opening up a large market for automating tasks previously deemed too complex.
Unite.AI framed this as a technology that could change the economic landscape of automation by making robotics more accessible and adaptable for manufacturers. FinancialContent highlighted the collaboration with Black Forest Labs and the implementation at Audi for tasks involving flexible materials. explainx noted the simultaneous announcement of the FLUX 3 multimodal backbone, which an open-weight version will be released later this year.
The open-source AI research group OpenBMB has released the MiniCPM-Robot series, a family of compact, open-source embodied intelligence models designed for on-device processing in real-world robots. The series includes MiniCPM-RobotManip for manipulation and MiniCPM-RobotTrack for tracking. The models are optimized to run on local hardware with the group's PhyAI Inference Engine, providing real-time vision-language-action (VLA) capabilities without requiring massive cloud compute resources.
Why it matters
This release directly addresses one of the biggest challenges in deploying advanced AI in robotics: the need for low-latency, on-device inference. By providing capable, open-source models that are small enough to run locally, OpenBMB is lowering the barrier to entry for developers and startups looking to build autonomous robots. This is particularly crucial for applications in unstructured environments where cloud reliance is a liability for safety and reliability, pushing the ecosystem toward more practical and accessible robotics.
EmbodiedGlobal reported that the compact models aim to provide real-time VLA capabilities and make advanced robotics more accessible. The release focuses on offering specialized, efficient models that can outperform larger alternatives on specific tasks where low latency is critical.
Researchers at IIT Madras have developed a cost-effective hydraulic-electric hybrid actuation module for humanoid robots, named 'IIT-Hydro'. The design reportedly achieves a 40% weight reduction compared to similar systems while maintaining a high torque output. The team aims to lower the cost of building humanoid robots in India, targeting a unit cost of approximately ₹45,000 (around $540 USD) and relying on domestically sourced materials.
Why it matters
Actuators are a primary cost and weight driver in humanoid robots, making this development significant for democratizing access to robotics hardware. By dramatically lowering the cost and weight of a critical component, this research could make building capable humanoid robots more feasible for startups, researchers, and educational institutions, particularly within India's burgeoning robotics ecosystem. It represents a key step in building out a domestic supply chain for affordable, high-performance robotic components.
RobotWale News reported that the module, led by Dr. Aravind Kumar, offers a significant weight reduction and aims for a low unit cost to support local manufacturing in India. This follows a broader industry recognition, as noted by Rocking Robots, that actuators are a crucial bottleneck for the commercial viability of humanoid robots, accounting for over half their total weight.
Confirming reports from Wednesday, Travis Kalanick's industrial robotics and AI holding company, Atoms, announced on Thursday it has raised $1.7 billion in an equity investment round. The round was led by Andreessen Horowitz (a16z), whose co-founder Ben Horowitz will join the Atoms board. The funding consolidates Kalanick's various businesses—including City Storage Systems, CloudKitchens, and the newly acquired self-driving startup Pronto—under a single entity focused on 'physical AI' for industries like mining, construction, transport, and food production. Uber, Bain Capital, and JPMorgan also participated.
Why it matters
This is a massive capital injection into the 'atoms-not-bits' thesis, reinforcing a strategic divergence in the robotics industry away from general-purpose humanoids and towards specialized, industrial applications. For a robotics entrepreneur, Kalanick's success in raising this much capital validates the market for automating traditional, physical industries. The participation of a16z and the return of Uber as an investor signals strong belief from top-tier VCs and strategic partners in the potential for large-scale physical automation to transform core economic sectors. The acquisition of Pronto also indicates that a full-stack approach including autonomous mobility is seen as key.
TechCrunch noted this round debunks a previously unverified claim, confirming the significant investment. Startup Fortune emphasized Atoms' focus on specialized robots over humanoids, highlighting a key strategic split in the industry. Caproasia pointed out the deal brings all of Kalanick's ventures under a single Atoms equity structure, simplifying his push into physical automation.
Robotics foundation model startup Genesis AI is reportedly in talks with investors to raise approximately $500 million in a new funding round. According to reports on Thursday, the fundraising could value the company at around $3 billion before the new capital. Genesis AI, founded by Zhou Xian and Théophile Gervet, is focused on creating a universal software layer, GENE-26.5, that enables various robots to perform physical tasks without individual programming. The company has also developed its own general-purpose hardware, a robot named Eno.
Why it matters
This potential mega-round for Genesis AI highlights a significant strategic shift in venture capital, with investors increasingly betting on the 'brains'—the AI foundation models—rather than just the robotic 'bodies'. The massive valuation, just a year after a seed round, indicates strong belief that a universal OS for robots could unlock value across the entire hardware ecosystem, similar to how operating systems created platforms in computing. For robotics entrepreneurs, this trend validates a software-first or full-stack approach and suggests that the most defensible moats may be built with data and models, not just mechatronics.
Bloomberg first reported the funding talks, noting the potential $3 billion pre-money valuation. The Next Web framed the news as a sign of strong investor interest in the 'physical AI' sector. StartupFortune emphasized that the move signals a broader VC pivot from robotics hardware to the software and foundation models that power them.
Ropedia, a Singapore-based startup, has secured $30 million in pre-A funding to build out its data infrastructure platform for physical AI and robotics. The company is focused on solving the data bottleneck for training embodied AI. It uses a proprietary wearable system called 'HOMIE' to capture large-scale, multimodal human experience data (sights, sounds, motion) to create datasets for training robots to perform complex, real-world tasks. The new funding will be used to expand data collection efforts and grow its engineering team.
Why it matters
This funding round underscores the market's growing recognition that the primary constraint in robotics is no longer just hardware, but the availability of high-quality, diverse training data. Ropedia's approach of building a dedicated data infrastructure positions it as a crucial enabler for the entire embodied AI ecosystem. For robotics startups, the emergence of specialized data providers could significantly accelerate development by offering a path to acquire the vast datasets needed to train capable foundation models, without having to build the entire data collection pipeline in-house.
TechStartups reported the funding will support the deployment of HOMIE devices and team growth in the US. FinSMEs highlighted the company's focus on creating 'the data infrastructure powering physical AI'. DealStreetAsia noted the round size and the company's large multimodal datasets like Xperience-10M.
Following Johnson & Johnson's FDA De Novo authorization for its OTTAVA surgical robot—which we highlighted yesterday—the company is now officially outlining its U.S. market strategy. While the clearance covers several upper abdomen general surgery procedures, the primary differentiator J&J is pitching is the system's unique table-integrated design. The company claims this architecture reduces the operating room footprint by 30-50% compared to traditional cart-based models, addressing a key adoption barrier ahead of its controlled commercial launch.
Why it matters
As we noted yesterday, J&J's entry turns the surgical robotics market into a three-way race with Intuitive Surgical and Medtronic. The specific focus on a smaller footprint addresses a genuine pain point for hospitals with limited operating room space, potentially democratizing access to robotic surgery for facilities that couldn't accommodate bulkier legacy systems.
Fierce Biotech highlighted that the approval covers multiple soft-tissue surgeries, positioning J&J to compete broadly with incumbents. StartupFeed focused on the space-saving design, noting it could enable robotic surgery in smaller hospitals that previously lacked the physical space. Bariatric News emphasized the approval for bariatric procedures and the system's aim to improve OR efficiency.
Momentis Surgical announced on Thursday it has received 510(k) clearance from the FDA for the multiport configuration of its Anovo Surgical System. This expansion makes Anovo the first and only robotic platform capable of supporting natural orifice (transvaginal), single-port, and multiport surgical approaches on a single system. The clearance enhances the system's modularity and broadens its applicability to procedures like ventral hernia repair, in addition to its existing use in gynecology.
Why it matters
This clearance gives Momentis a unique competitive differentiator in the crowded surgical robotics market. By offering a single, flexible platform that can handle multiple surgical approaches, the Anovo system can reduce the need for hospitals to invest in multiple specialized and expensive robotic systems. Its smaller footprint and humanoid-inspired articulated instruments position it as a versatile and potentially lower-cost alternative to dominant players like Intuitive Surgical's da Vinci, which could increase access to robotic surgery, especially in smaller hospitals or outpatient centers.
In its press release, Momentis Surgical highlighted that Anovo is now the first platform to support all three access approaches. MassDevice noted the clearance expands the system's utility for ventral hernia repair and gynecologic surgeries. Unite.AI positioned the clearance as a direct challenge to Intuitive Surgical in high-volume procedures.
Wetour Robotics has introduced Orchestra, a portable AI hub and operating system designed to power a suite of wearable robotics. The system is built on the NVIDIA Jetson platform and functions as a centralized processing unit. It offloads intensive computation—such as real-time visual perception and gesture recognition—from individual wearable devices, allowing for more lightweight and power-efficient endpoints while enabling multi-device coordination.
Why it matters
This 'hub-and-spoke' architecture offers a clever solution to the power and processing constraints that have limited the complexity of wearable robotics. By centralizing the 'brain' into a portable AI hub, Orchestra could enable a new class of sophisticated, coordinated assistive devices without sacrificing wearability. For an entrepreneur in consumer or assistive robotics, this platform approach presents a new paradigm for designing systems that are both powerful and practical for everyday use.
GlobeNewswire, in a press release, described Orchestra as an AI hub that enables real-time visual perception, gesture recognition, and multi-device coordination for wearable robotics. StockTitan added that the system is powered by NVIDIA Jetson, centralizing AI processing to create a more capable and efficient ecosystem of wearable devices.
Singaporean startup Acrab has unveiled its first-generation edge AI System-on-Chip (SoC), the GΞLIX 1, and the 'Agent Box,' a personal edge AI system built around it. The GΞLIX 1 is a 5nm processor designed to run 100-billion-parameter AI models locally, without constant cloud connectivity. The SoC integrates a CPU, GPU, and NPU on a single die, aiming to provide faster, more private, and more cost-effective AI processing for on-device applications.
Why it matters
Acrab's technology represents a significant step toward liberating powerful AI from the data center. The ability to run large-scale models directly on an edge device could be a game-changer for robotics, enabling more complex, responsive, and autonomous behaviors without the latency and privacy concerns of cloud-based processing. For an entrepreneur developing robotic systems, this type of hardware could unlock new capabilities for real-time decision-making in dynamic environments.
In a press release, Acrab emphasized that the GΞLIX 1 chip significantly accelerates edge AI capabilities while reducing reliance on cloud infrastructure. Unite.AI highlighted that the offering challenges the prevailing cloud-based AI model by providing a local and private alternative for running large language models, potentially accelerating on-device inference for a wide range of AI applications.
Samsung has provided more detail on the official launch of its 'Robotics eXperience' (RX) division we tracked earlier this week. Led directly by CEO TM Roh, the division will consolidate the company's robotics efforts to develop humanoids and transform its global manufacturing facilities into 'AI autonomous factories' by 2030. Samsung also revealed its 'Shallow-π' Vision-Language-Action (VLA) model has already been proven in factory settings, and it plans to establish a 'Robot Data Factory' at its Gumi plant to create a proprietary AI training pipeline.
Why it matters
Samsung's explicit goal of creating autonomous factories expands on the strategic shift we've been tracking, representing a massive commitment from a global manufacturing giant. Its plan to build a 'Robot Data Factory' also signals that, much like Tesla, large-scale manufacturers increasingly view a proprietary data flywheel as a core competitive advantage for deploying physical AI.
TechTimes detailed the plan to establish a 'Robot Data Factory' and leverage the 'Shallow-π' VLA model. Kekinianku.com emphasized the goal of transforming manufacturing into 'AI autonomous factories' by 2030, driven by the new RX division. The move follows Samsung's prior investment in robotics firm Rainbow Robotics.
Engineers at Harvard's Wyss Institute and School of Engineering and Applied Sciences have developed a novel 3D printing method called rotational multimaterial 3D printing (MM-R3D). This technique allows for the creation of soft robots that can bend, twist, and change shape in predictable ways when inflated. The process prints long, flexible filaments with precisely positioned hollow channels that act as actuators when pressurized, embedding the shape-morphing behavior directly into the material's structure.
Why it matters
This innovation significantly simplifies the fabrication of complex soft robots, which previously required painstaking multi-step processes and custom molds. By integrating the actuating mechanism directly into the printed material, this technique enables the rapid prototyping and customization of soft robotic components. This could accelerate development in fields like surgical robotics, assistive devices, and delicate grippers, making soft robotics more accessible and adaptable for a wider range of applications.
danburymethodist.org highlighted that the method allows for predictable bending and twisting upon inflation, integrating motion directly into the printed structure. The technique holds promise for creating customized soft robots for medical and human-machine interface applications.
A team of European scientists has developed a new tactile system for robots using a stretchable, soft mechanochromic material that changes its structural color in response to physical deformation. This allows a robot to 'see' touch and pressure in real-time as a detailed color map, without the need for complex electronics or wiring embedded in the material. The approach bypasses the typical trade-off between detail and speed in conventional tactile sensors.
Why it matters
This is a significant advance in robotic perception, offering a path to a more human-like sense of touch that is both high-resolution and fast. For applications like surgical robotics, prosthetics, and delicate micromanufacturing, the ability to precisely sense and differentiate pressure signatures is critical. By shifting the sensing mechanism to the material itself, this technology simplifies the design of soft robotic hands and grippers, potentially enabling more intuitive and safer human-robot interaction.
KCWIlliamsFanClub.com noted that this innovation allows robots to perceive touch with unprecedented precision and speed, with implications for prosthetics and surgical robotics. ThisHere.org added that the material-based sensing simplifies design and could lead to more adaptable machines.
A study from Lehigh University has found that the movement of drug-delivering microrobots is governed more by the properties of the bodily fluids they travel through than by their own shape. Researchers led by Ebru Demir discovered that in non-Newtonian fluids, which mimic biological fluids, increasing the robots' rotation speed unexpectedly caused them to reverse direction. This suggests the complex fluid environment plays an active, rather than passive, role in their locomotion.
Why it matters
This finding could fundamentally change how medical microrobots are designed. Instead of focusing primarily on optimizing the robot's shape for propulsion, engineers may need to adopt a 'fluid-first' approach, designing systems that actively leverage the complex dynamics of the biological environment. This paradigm shift could lead to entirely new and more effective strategies for targeted drug delivery and other in-body medical procedures.
yexpund.com framed the research as a potential revolution for treating diseases like cancer, where fluids can be seen as active partners in treatment delivery. dtours.org emphasized that this challenges traditional engineering by highlighting the environment's active role, shifting the focus from robot shape to fluid dynamics.
AMD Enters the Robotics Chip Arena, Challenging NVIDIA AMD has launched a full-stack offensive into the robotics and physical AI market with its new Ryzen AI Embedded X100 series processors, Kria AI modules, and a dedicated Robotics Partner Network. This move directly challenges NVIDIA's Jetson platform, with AMD emphasizing an open ecosystem and integrated compute, sensing, and control. Multiple partners, including Foundation Robotics, are already adopting AMD's new hardware, signaling a significant shift in the competitive landscape for the silicon that powers next-generation robots.
Venture Capital Flows into Robotics Software and Infrastructure A clear trend is emerging in venture capital, with massive funding rounds prioritizing the software and data layers of robotics over pure hardware plays. Travis Kalanick's industrial AI firm Atoms secured a blockbuster $1.7 billion, while robotics foundation model startup Genesis AI is in talks for $500 million. At the same time, companies like Ropedia, focused on data infrastructure for physical AI, are closing significant pre-A rounds, indicating that investors believe the key to unlocking robotics is in the AI 'brains' and the data that trains them.
Humanoid Robot Companies Invest in Dedicated Training Facilities As the focus shifts from hardware prototypes to scalable software, major humanoid robotics companies are establishing large-scale, dedicated facilities for real-world robot training. Apptronik has opened a 90,000-square-foot 'Robot Park' in Austin to gather operational data for its Apollo humanoids in partnership with Google DeepMind. This follows Agility Robotics' new 60,000-square-foot engineering hub in Fremont, creating a 'Robot Row' near Tesla. These 'robot gyms' are becoming critical infrastructure for developing and validating embodied AI models before deployment.
Surgical Robotics Market Heats Up with New FDA Clearances The surgical robotics field is experiencing a surge of competition. Johnson & Johnson's Ottava system received FDA authorization, introducing a major new player to challenge Intuitive Surgical's long-held dominance with an innovative, space-saving table-integrated design. Simultaneously, Momentis Surgical's Anovo system gained clearance for multiport surgery, making it the first platform to support three different surgical approaches. These approvals promise to increase options for hospitals, drive innovation, and potentially expand access to robotic-assisted procedures.
Soft Robotics Advances Through Material Science and Fabrication Breakthroughs A wave of innovations in materials science and fabrication is pushing the boundaries of soft robotics. Researchers have unveiled a new 3D printing technique for creating complex shape-morphing robots, a color-changing material that gives robots a visual 'sense of touch,' and a self-healing underwater e-skin. Other breakthroughs include using liquid metal droplets to boost power output and developing elastomers that are flexible, self-healing, and photoluminescent, all pointing toward more durable, adaptable, and capable soft robots for a variety of applications.
What to Expect
2026-07-26—Roborock plans to launch its 'Q Revo 2 Pro' robot vacuum cleaner in South Korea.
2026-09-16—Michael Shorrosh, an Amazon site leader, will speak on operational excellence and robotics at IntraLogisteX Dallas.
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